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The prediction of dropout in an entry level trades training program MacNeill, Rodney M. 1989

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The Prediction of Dropout in an Entry Level Trades Training Program by Rodney M. MacNeill B.Ed., The University of Alberta, 1975 H.Ed., The University of Alberta, 1980 A DISSERTATION SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF EDUCATION in THE FACULTY OF GRADUATE STUDIES (Department of Administrative, Adult and Higher Education) We accept this thesis as conforming to the required standard THE UNIVERSITY OF BRITISH COLUMBIA December 1989 ©Rodney M. MacNeill , 1989 In presenting this thesis in partial fulfilment of the requirements for an advanced degree at the University of British Columbia, I agree that the Library shall make it freely available for reference and study. I further agree that permission for extensive copying of this thesis for scholarly purposes may be granted by the head of my department or by his or her representatives. It is understood that copying or publication of this thesis for financial gain shall not be allowed without my written permission. Department of Administrative, Adult and Higher Education The University of British Columbia Vancouver, Canada Date May 18, 1990  DE-6 (2/88) ABSTRACT Withdrawal from a program of studies can have negative consequences that extend beyond those that d i r e c t l y a f f e c t the dropouts. Beyond the lack of employment r e l a t e d s k i l l s and the impact that dropping out may have on students' confidence i n t h e i r a b i l i t y as learners, a t t r i t i o n also has an e f f e c t on the educational i n s t i t u t e and sponsoring agencies. For example, program a t t r i t i o n leaves the t r a i n i n g provider with empty seats but no corresponding reduction i n t r a i n i n g costs and the sponsoring agencies with a l i m i t e d return on t h e i r t r a i n i n g investments. This study examined a t t r i t i o n i n short-term vocational programs to determine i f factors from research on other postsecondary populations are applicable to these kinds of students. A formula was also developed to pr e d i c t , e a r l y i n the program, which students are most l i k e l y to withdraw. A review of the research confirmed that what i s known about factors r e l a t e d to a t t r i t i o n f or students i n short-term vocational programs i s l i m i t e d . This necessitated a "borrowing" of factors from research directed at high school students and those i n adult and higher education programs. By means of a mailed questionnaire, and using i n s t i t u t e records, data were c o l l e c t e d f o r those factors relevant to the population and program under study. These factors were divided into those students brought with them and those they experienced a f t e r they i i i began their training. Of the 36 pre-entry factors studied, 12 produced statistically significant relationships when compared to persistence/withdrawal. The significant factors included high school graduation; test scores on reading vocabulary, reading comprehension, reference skills, math computation, math concepts and applications, and combined reading and combined math scores; mean differences in age; the student's socioeconomic status; certainty of program choice; and locus of control as related to high school persistence/withdrawal. Of those categorized as postentry, 10 of the 28 factors produced statistically significant relationships when compared to the indicator variable. These factors were enough study time, study time compared to others, hours per week at PVI, tests passed per attempt, tests exceeded per attempt, feeling that friends had gained from the program, estimation of program success, financial concern, agency sponsorship, and the use of Training Consultants. Combining the statistically significant factors using multiple regression analysis produced a prediction formula which included tests passed per attempt, combined math scores, study time compared, age, and feeling that friends had gained from the program. Conclusions based upon the results of the study centered around the application of attrition factors from the study of other populations and the utilize/ of prediction for practitioners. In essence, the researcher believes i t is inappropriate to make assumptions regarding attrition by iv short-term vocational students based upon research findings from other populations. In addition, even though the findings which characterized persisters as "good students" indicate that attrition rates may be reduced by either restricting admission by students who do not f i t the profile or by providing these students with additional support, the amount of variance accounted for (16 percent) based upon the results of the multiple regression analysis suggest caution be used in making any decision. The researcher concludes by recommending that future studies examine attrition by using a variety of research methods in an attempt to clarify which factors are related to student attrition. V TABLE OF CONTENTS ABSTRACT i i LIST OF TABLES ix ACKNOWLEDGEMENT xvii CHAPTER I: BACKGROUND TO THE PROBLEM 1 The Dimensions of Postsecondary Attrition 3 The State of Attrition Research 7 Studying Attrition in Entry Level Vocational Programs 14 Design of the Study 15 CHAPTER II: REVIEW OF THE LITERATURE 18 The Study of Attrition in Entry Level Vocational Programs 19 Adult Education and the Study of Attrition 22 The Melding of Participation and Persistence 22 Persistence in Adult Education Research 24 Conclusions from Adult Education Attrition Research 38 Higher Education and the Study of Attrition 40 Persistence, Dropout, Stopout and Attainers 42 Pre-Entry and Postentry Attrition Factors 43 Pre-Entry Attrition Factors 45 Previous Educational Experience . 45 Demographic Factors 46 Motivational Factors 47 Personality Factors 48 Pre-Entry Factors Relevant to Entry Level Vocational Programs 49 Postentry Attrition Factors 50 Academic Factors 50 v i Motivational Factors 51 Financial Factors 52 Institutional Factors 52 Postentry Factors Relevant to Entry Level Vocational Programs 54 Conclusions from Higher Education Attrition Research 54 Secondary Sources of Research on the Study of Attrition 58 Adult Vocational Education 58 The High School Dropout 60 The High School Vocational Student 63 Learner Self -Conf idence 64 Conclusion 68 CHAPTER III: RESEARCH DESIGN AND PROCEDURES 70 Research Environment 70 Site Selection 73 Setting and Subjects 75 Population and Sample 77 Data Collection from Institute Sources 83 Student*s Records 86 Canadian Achievement Tests (CAT) 87 The Rotter Internal/External Control Scale 92 Survey Development and Implementation 95 Questionnaire Pilot Testing 97 Questionnaire Administration 100 Data Analysis ..., 102 Summary 105 CHAPTER IV: RESEARCH FINDINGS: PRE-ENTRY FACTORS. .106 v i i Response to the Questionnaire 108 Pre-Entry Factors Related to Attrition 112 Previous Educational Experience 113 Academic Achievement 131 Demographic Factors 136 Motivational Factors. 148 Learner Self-Confidence 164 Conclusion 168 CHAPTER V: RESEARCH FINDINGS: POSTENTRY FACTORS 171 Postentry Factors Related to Attrition 172 Academic Factors 172 Motivational Factors 184 Financial Factors 195 Institutional Factors ...203 Attainers, Dropouts, and Persisters 218 Conclus ion 224 CHAPTER VI: THE PREDICTION OF DROPOUT 226 The Development of a Prediction Formula 229 The Relationship Between Pre-Entry Factors and Persistence/ Withdrawal '. 233 The Relationship Between Postentry Factors and Persistence/ Withdrawal 236 The Relationship Between Pre- and Postentry Factors and Persistence/Withdrawal 237 The Dropout Prediction Formula 239 Conclus ion 242 CHAPTER VII: SUMMARY AND DISCUSSION.. 244 The Design of the Study 245 Site Selection 246 v i i i Population and Sample Selection 247 Data Collection 248 Data Analysis 249 Research Findings 250 Response Rate 251 Pre-entry and Postentry Factors in Relation to Persistence/ Withdrawal 252 Dropout Prediction 258 Conclus ions 261 Validation of Borrowed Factors 261 The Prediction of Dropout 265 The Study's Contribution to the Knowledge Base 267 Limitations and Implications for Further Study 269 REFERENCES 275 APPENDIX A: LETTER OF CONSENT 281 APPENDIX B: QUESTIONNAIRE 283 LETTER OF TRANSMITTAL 291 REMINDER LETTER 292 FOLLOW-UP LETTER 293 APPENDIX C: DROPOUT FOLLOW-UP LETTER 294 i x LIST OF TABLES 1: Ages of Presample, Sample, and Postsample Students: A Multiple Comparison (Scheffe) of the Means of the Three Groups 80 2: CAT Results of the Sample and Nonsample Groups: A Comparison of the Means for the Two Groups 81 3: Dropout Prediction: Previous Research Results for Selected Variables and Sources of Data for these Variables 85 4: Raw Score Means (X), Standard Deviations (SD), Standard Errors of Measurement (SE), and KR 20s (KR) for CAT Level 18 (Normed Results) Tests 91 5: Means, Standard Deviations (SD), and Kuder-Richardson Formula 20 (KR 20) of the Category Objectives for Selected CAT Level 18 92 6: Responding (R) and Nonresponding (NR) Persisters: A Comparison of Their Mean Scores on Selected Variables 110 7: Responding (R) and Nonresponding (NR) Dropouts: A Comparison of Their Mean Scores on Selected Variables I l l 8: Persisters and Dropouts Compared by Failing/Not Failing a Grade in Elementary School 116 9: Persisters and Dropouts Compared by Skipping/Not Skipping a Grade in Elementary School 117 10: Persisters and Dropouts Compared by Self-reported High School Marks 120 X 11: Persisters and Dropouts Compared by Behavior in Public School ..121 12: Persisters and Dropouts Compared by Feelings Towards School Experience 122 13: Persisters and Dropouts Compared by High School Program Taken 124 14: Persisters and Dropouts Compared by Last Grade Completed 125 15: Persisters and Dropouts Compared by High School Graduation 126 16: Persisters and Dropouts Compared by Postsecondary Program Taken 127 17: Persisters and Dropouts Compared by Postsecondary Graduation 128 18: Persisters and Dropouts Compared by Number of Years Since Previous Educational Experience 129 19: Summary of the Statistical Analyses of Factors Related to Previous Educational Experience vs. Persistence/Withdrawal 130 20: Persisters and Dropouts Compared by Scores on the Canadian Achievement Tests 133 21: Persisters and Dropouts Compared by Scores on the Canadian Achievement Tests Combined Reading Scores 134 22: Persisters and Dropoucb* Compared.by Scores on the Canadian Achievement Tests Combined Math Scores... 134 xi 23: Summary of the Statistical Analyses of Achievement Persistence/Withdrawal 135 24: Persisters and Dropouts Compared by Variance in Age 138 25: Persisters and Dropouts Compared by Socioeconomic Status (Based Upon Their Previous Full-time Occupations) 140 26: Persisters and Dropouts Compared by Socioeconomic Status of Highest Ranked Parent 141 27: Persisters and Dropouts Compared by Social Mobility, (i.e., the Socioeconomic Status of the Student, Based Upon Previous Full-Time Employment, Versus the Student's Anticipated Posttraining Occupation) 143 28: Persisters and Dropouts compared by Social Mobility, (i.e., the Socioeconomic Status of the Highest Ranked Parent Versus the Student's Anticipated Posttraining Occupation) 144 29: Persisters and Dropouts Compared by the Number of Job Changes in the Twelve Months Previous to Beginning TRAC 145 30: Persisters and Dropouts Compared by Rate of Pay in the Last Job 146 31: Summary of the Statistical Analyses of Demographic Factors vs. Persistence/Withdrawal 148 32: Persisters and Dropouts Compareu by Intentions Regarding TRAC Program Completion 150 x i i 33: Persisters and Dropouts Compared by Selection of a TRAC Specialty Before Beginning the Program 151 34: Persisters and Dropouts Compared by Certainty of TRAC Specialty Selection 153 35: Persisters and Dropouts Compared by Changing Specialty While in the Program 154 36: Persisters and Dropouts Compared by Reason for Choice of Specialty 155 37: Persisters and Dropouts Compared by Choice Indicating Commitment 156 38: Persisters and Dropouts Compared by Perception of Family Support for the Decision to Return to School 158 39: Persisters and Dropouts Compared by Extent that Family Support, Regarding Return to School, is Valued 158 40: Persisters and Dropouts Compared by Varying Perceptions of Family Support and Valuing of their Opinion . 160 41: Persisters and Dropouts Compared by Perception of Friends' Support for the Decision to Return to School 160 42: Persisters and Dropouts Compared by Extent Friends' Support, Regarding Return to School, is Valued 161 43: Persisters and Dropouts Compared by Inception of Friends' Support and Valuing of their Opinion 162 x i i i 44: Persisters and Dropouts Compared by Planned Participation in Further Education Related to a Long Term Career Goal 163 45: Summary of the Statistical Analyses of Motivational Factors vs. Persistence/Withdrawal 163 46: TRAC Persisters and Dropouts Compared by Score on Rotter's IE Scale 165 47: High School Graduates and Nongraduates Compared by Score on Rotter's IE Scale 166 48: Summary of the Statistical Analyses of Learner Self-Confidence Factors vs. Persistence/Withdrawal 167 49: Persisters and Dropouts Compared by Perception of Spending Enough or Not Enough Time Studying Prior to Writing a Theory Test 175 50: Persisters and Dropouts Compared by Perceptions of Amount of Time Spent in Pretest Study Compared to Other TRAC Students 176 51: Persisters and Dropouts Compared by Number of Study Skills Used 177 52: Persisters and Dropouts Compared by Percentage of Each Group Who Used Selected Study Techniques 177 53: Persisters and Dropouts Compared by Hours per Week Spent at PVI 179 54: Persisters and Dropouts Compared by Majority of Study Time At/Away from PVI 180 xiv 55: Persisters and Dropouts Compared by the Proportion of Tests Passed to Tests Written During the First Six Weeks in the TRAC Program 183 56: Persisters and Dropouts Compared by the Proportion of Tests Exceeded to Tests Written During the First Six Weeks in the TRAC Program 183 57: Summary of the Statistical Analyses of Academic Factors vs. Persistence/Withdrawal 183 58: Persisters and Dropouts Compared by Belief that they were Gaining Something from the Program During Common Core 185 59: Persisters and Dropouts Compared by Belief that his Friends were Gaining Something from the Program During Common Core. . . . . . 186 60: Persisters and Dropouts Compared by Combined Beliefs that he and/or his Friends were Gaining Something from Common Core 188 61: Persisters and Dropouts Compared by Willingness to Recommend TRAC 189 62: Persisters and Dropouts Compared by Willingness to Recommend PVI 190 63: Persisters and Dropouts Compared by Willingness to Recommend TRAC and/or PVI 191 64: Persisters and Dropouts Compared by Their Estimation of the Completion Rate for TRAC Students..... 193 65: Summary of the Statistical Analyses of Motivational Factors vs. Persistence/Withdrawal. 194 X V 66: P e r s i s t e r s and Dropouts Compared by Concern Regarding the Adequacy of Personal F i n a n c i a l Resources 196 67: P e r s i s t e r s and Dropouts Compared by the Amount Borrowed on a Student Loan 198 68: P e r s i s t e r s and Dropouts Compared by Agency Sponsorship 199 69: The Re la t ionsh ip Between the Number of Hours Worked Per Week and Persistence/Withdrawal 200 70: A Comparison of the Mean Number of Hours Worked per Week by P e r s i s t e r s and Dropouts 201 71: Summary of the S t a t i s t i c a l Analyses of F i n a n c i a l Factors v s . Persistence/Withdrawal 202 72: P e r s i s t e r s and Dropouts Compared by Changing/Not Changing t h e i r Place of Residence to Attend PVI 204 73: P e r s i s t e r s and Dropouts Compared by Where they Lived During Common Core . . . . 2 0 5 74: P e r s i s t e r s and Dropouts Compared by Use of S p e c i f i c Student Services 207 75: P e r s i s t e r s and Dropouts Compared by Use of Ins t ruc tor Ass i s tance 209 76: Comparison of P e r s i s t e r s and Dropouts on Factors Used to Define F i t 212 77: P e r s i s t e r s and Dropouts Compared by Number of TRAC Friends they S o c i a l i z e d With 213 78s P e r s i s t e r s and Dropouts Compared by Having/Not Having Friends Taking the Same Occupational Core 214 xv i 79: Persisters and Dropouts Compared by Having/Not Having Friends Taking the Same Specialization 215 80: Persisters and Dropouts Compared by Having/Not Having Friends Starting on the Same Day 216 81: Summary of the Statistical Analyses of Institutional Factors vs. Persistence/Withdrawal 218 82: Statistically Significant Results from Previous Calculations 220 83: Comparison of Persisters and Dropouts to Being More/Less Like Attainers 222 84: Statistically Significant Factors and Results from Previous Calculations (Pre-entry Factors) 234 85: Statistically Significant Factors and Results from Previous Calculations (Postentry Factors) 236 86: A Comparison of Persisters 1 and Dropouts' Scores Using the Dropout Prediction Formula 241 xvii ACKNOWLE DGMENT The completion of this research project was facilitated through the efforts and support of a number of people. To my research supervisor Dr. W. Griffith, and my research committee members Dr. W. Borgan and Dr. H. Ratzlaff I am indebted for their guidance and counsel. I am also indebted to Michelle Carter for her careful reading of the many drafts. To my colleagues at the British Columbia Institute of Technology, Janice, Bruce, Debbie, Judy, Joyce, Shiela, and Henry for their assistance and support. Finally, to my family, I am thankful for their patience and understanding. 1 CHAPTER I BACKGROUND TO THE PROBLEM Educators delivering entry level trades training, as part of the postsecondary education system, have a mandate to offer short duration training programs designed to provide graduates with marketable skills. Training programs which articulate with subsequent training, such as apprenticeship, are selected by educators to provide graduates with a career path leading to employment as qualified tradespersons. Because the entrance requirements for these programs are minimal, they also provide access to individuals not served by other college, technical institute, and university programs. Consequently, entry level trades programs tend to attract less academically able students seeking solutions to their unemployment or underemployment problems. Because they lead to occupations which have some form of certification, short duration training programs are popular with sponsoring agencies, such as Employment and Immigration Canada, who see them as the shortest route between irregular employment and more stable, long-term jobs for their clients. These agencies believe the benefits of this training include increased wages and earnings (Abt Associates of Canada, 1985) as the result of moving from an unskilled to a skilled occupation. Sponsorship of these kinds of programs is seen as an investment and, as with any investment, an adequate return requires that the investment come to term. Coming to term applies particularly well to entry level vocational training. By leaving an entry level program prior to 2 completion, the early leaver may f a i l to obtain skills considered by employers as prerequisites to employment. Because employment for graduates is the primary objective of vocational training, the investment by the student, and the provincial and federal governments, is not realized i f the student fails to find a job. In apprenticable trades academic credit is given for the fi r s t year of institutional training i f the apprentice has completed an entry level program. Employers find this arrangement attractive because the entry level graduate does not have to attend school during his* f i r s t year of employment, thereby saving the employer the need to replace him during the four to six week training period. In this case, completing an entry level program also benefits the apprentice who does not suffer any loss of wages by returning to school during his fi r s t year of employment. The benefits of program completion are in turn passed on to the provincial and federal governments who fund both entry level and apprentice training. Ultimately, by completing entry level training, the student spares the taxpayer the double expense of paying for the dropout's i n i t i a l training and, subsequently, for his f i r s t year apprenticeship training i f he manages to obtain apprenticable employment. Even with the substantial benefits accrued by completing the program, not a l l those who enroll manage to complete. Just as completion has its positive outcomes, dropping out has its * Note: A generally accepted and gender free replacement for the masculine pronoun "he" has yet to be established. While acknowledging the inequity of its use, the author will continue to use the traditional masculine form. 3 negative implications. Prior to obtaining employment and becoming an apprentice, dropping out can adversely affect the early leaver's ability to get a job. In most cases, given the choice between hiring a graduate and nongraduate, an employer would likely see i t in the company's best interest to hire the "qualified" individual. In addition, for those students whose educational backgrounds do not qualify them for entrance to other postsecondary programs, failure to complete an entry level trades program could result in limiting their occupational options. At minimum, withdrawing early would result in the necessity to repeat training to develop skills that had already been learned when, as an apprentice, the dropout must return to complete the fi r s t year of institutional training. Perhaps more serious is the effect of the stigma of "yet another failure" on those who had previously failed to graduate from high school. A history of educational failure may subsequently discourage these individuals from considering further education as a means of improving their employment opportunities—a serious mistake considering the projected need for continuous upgrading throughout one's working l i f e . Even a positive withdrawal, which may provide students with a better understanding of their career goals, results in a loss of time and money for the dropout, the training institution, and, in certain cases, the agency paying for the training. The Dimensions of PostSiacondary Attrition Attrition figures for the United States predict that of the 2.8 million students who began their postsecondary education in 1986, 1.6 million will leave their f i r s t college or university 4 prior to graduation, and 1.2 million will withdraw altogether without obtaining a degree, diploma, or certificate (Tinto, 1987: 1). Attrition rates vary depending upon whether the institution offers two-year or four-year programs. Withdrawal from four-year institutions is 39 percent, whereas for two-year colleges 54 percent of those who enroll will never complete their program (Tinto, 1987: 17, 19). As stated by Tinto, these statistics do not indicate that attrition is a growing problem as they have remained relatively stable for the past 100 years. In Canada the largest sponsor of entry level training is Employment and Immigration Canada (EIC). Its mandate, under the National Training Act (1982), is "to establish a national program to provide occupational training for the labour force and . . . to increase the earning and employment potential of individual workers" (Employment Manual, EA 18-04). Seats in provincial training programs are purchased for sponsored trainees through the National Institutional Training Program (NITP). Expenditures for full-time training and living allowances amounted to $570,629,000 in 1983-84 (Abt Associates of Canada, 1985). Of this amount $308,876,000 was spent on Skill Training: the program through which purchases are made in entry level training programs. This expenditure provided training for 61,108 full-time students. However, this sum does not include part of an additional $20,829,254 for part-time programs, $40,373,706 for Provincial administration and related costs, and $221 million for Unemployment Insurance benefits paid to certain trainees, which was also paid out to support entry level training. Based only on the amount spent on full-time training and allowances, the average expenditure per trainee amounted to $5054.59 in 1983-84. In 1983-84 attrition from the Skill Training program ranged from a high of 28.7 percent in Ontario to a low of 9.6 percent in Prince Edward Island (Abt Associates of Canada, 1985). The average attrition rate across the provinces was 20 percent. Although low compared to attrition rates for postsecondary programs in general, attrition from the Sk i l l Training program cost the Canadian taxpayer more than 61 million dollars. While about one third of the noncompleters left to take jobs, a direct relationship between "employability gain [and] . . . the proportion of the training course completed" (Abt Associates of Canada, 1985: 11) was observed. In other words, the total number of months of employment in a year (i.e., employability, as defined by EIC) was directly related to the proportion of training completed. In the short-term, those who left to take a job would have cost taxpayers less in i n i t i a l training costs but this saving would be lost should they have to return to complete their f i r s t year apprenticeship training. In British Columbia since 1983 the majority of entry level trades training, both for fee paying and sponsored students, conducted in the colleges and institutes has been done through a program called Training Access (TRAC). TRAC consists of twenty-two different trade areas with each institute and college offering a variety of trade specialties. In an evaluation of TRAC commissioned by the Ministry of Education in 1985, the attrition rate was indicated to be 43 percent in 1983 and 1984, and 57 percent during 1985 (Province of British Columbia, 1985).: 6 A l t h o u g h l e a v i n g TRAC f o r r e l a t e d employment was c o n s i d e r e d a p o s i t i v e outcome, i t s t i l l r e q u i r e d t h e e a r l y l e a v e r t o r e t u r n and t a k e f i r s t y e a r a p p r e n t i c e s c h o o l i n g i f t h e p o s i t i o n he l e f t f o r was an a p p r e n t i c e s h i p . Of t h e 14 c o l l e g e s and i n s t i t u t e s o f f e r i n g TRAC i n B r i t i s h C o l u m b i a , t h e one w i t h t h e l a r g e s t e n r o l l m e n t and v a r i e t y o f s p e c i a l t y o f f e r i n g s was t h e P a c i f i c V o c a t i o n a l I n s t i t u t e (PVI) i n B u m a b y (now p a r t o f t h e B r i t i s h Co lumbia I n s t i t u t e o f T e c h n o l o g y ) . A t PVI t h e p e r c e n t a g e o f s t u d e n t s who withdrew p r i o r t o c o m p l e t i o n was 64 .5 p e r c e n t between September 19, 1984 and A p r i l 17, 1985; 59.4 p e r c e n t between A p r i l 24, 1985 and O c t o b e r 23, 1985; and 54 .0 p e r c e n t between O c t o b e r 30, 1985 and May 6, 1986. Comparable f i g u r e s a r e n o t a v a i l a b l e f o r t h e p e r i o d from when TRAC began, i n J a n u a r y o f 1983, t o September 19, 1984. The TRAC system o f t r a i n i n g p e r m i t t e d s t u d e n t s t o move o u t t o t a k e employment a t v a r i o u s e x i t p o i n t s , and h e l d employment r a t h e r t h a n c e r t i f i c a t i o n t o be t h e p r i m a r y g o a l . However, because a TRAC c e r t i f i c a t e was r e q u i r e d as a c o n d i t i o n o f employment f o r c e r t a i n u n i o n i z e d t r a d e s , and because o f the a t t r a c t i v e n e s s t o employers o f h i r i n g a TRAC g r a d u a t e who was n o t r e q u i r e d t o r e t u r n t o s c h o o l d u r i n g y e a r one o f h i s a p p r e n t i c e s h i p , w i t h d r a w a l p r i o r t o c o m p l e t i o n s t i l l l i m i t e d t h e b e n e f i t s o f program c o m p l e t i o n f o r t h o s e who wi thdrew. Of the 5990 s t u d e n t s e n r o l l e d i n TRAC a t PVI between i t s i n c e p t i o n and May o f 1986, more t h a n 3000 f a i l e d . t o c o m p l e t e , t h e r e b y f a i l i n g t o a c c r u e t h e s e b e n e f i t s . I n t i m e s o f f i s c a l r e s t r a i n t , a c c o u n t a b i l i t y and t h e c o s t / b e n e f i t r a t i o o f t h i s k i n d o f t r a i n i n g comes under the 7 constant scrutiny of those paying the b i l l . Pressure towards strict accountability has a direct impact on those institutions providing the training because their governing bodies are pressured by those who purchase their services, as well as by the Ministry of Education. For this reason, the educational value of a program is measured by outcomes that meet the goals of both the sponsoring agencies and the educational consumer. How to retain students in the program is of primary concern to educational providers. The corollary to this concern for both the Ministry and sponsoring agencies is to reduce the discrepancy between the number of seats paid for and the number of successful graduates. The State of Attrition Research Attrition affects a l l levels of education; therefore, the research domain includes studies from public, adult, and higher education. Although spoken of in different terms, dropout from high school, withdrawal from an adult education course, or attrition, as applied to higher education, are a l l parts of a similar phenomenon. There seems to be a misconception that each event must be distinct from the other because they occur at different times in an individual's l i f e . But, in reality, the similarities appear greater than the differences. The majority of research reviews dealing with factors related to withdrawal from postsecondary or adult programs stress the relationship between one's high school experience and success in subsequent educational activities. In withdrawal from high school the cri t i c a l elements are believed to be sociocultural and academic. From a sociocultural perspective 8 Howard and Anderson (1978) state that, dropping out is a complex action encompassing such factors as socioeconomic status, parents* level of education, siblings' level of education, parents' value of education, parents' occupational status, student's motivation, social contacts, mental and physical health, and material possessions (226). But even before reaching high school, patterns have begun to emerge which warn of future behavior. By the time children enter grade one they have already had five or six years of education as a participant in their home environment. Although not readily apparent before beginning school, academic problems such as poor marks, being held back a grade, and poor math and reading skills may have their roots in the experiences of the child from birth to when he f i r s t enters formal schooling. An understanding of the factors which influence withdrawal from secondary school is important because of the possible similarity between these factors and those influencing withdrawal from adult and higher education programs. For example, a recurring theme in attrition research is the idea of incompatibility between the student and the educational environment. A dislike of school, low participation in extracurricular activities, and high absenteeism (Self, 1983) parallel Boshier's (1973) concept of "incongruence." In both cases the student feels at odds with his fellow students, teachers, and the institution's goals. Just as with Self's (1983) review of public school dropout and Boshier's (1973) theory of persistence/withdrawal for adult students, Lenning et al. (1980) also see student " f i t " as an important factor in attrition from postsecondary education. The fact that entry 9 level programs attract students who may themselves have been high school dropouts strengthens the need to search studies of high school dropout for antecedent conditions related to subsequent withdrawal from postsecondary programs. As stated by Verner and Davis (1964), concern about adult students withdrawing from programs was evident as far back as 1814 when Thomas Pole emphasized the need for teachers to visi t their students to urge them to attend. Although disciplined research is a relatively new approach to discovering methods of retaining students, i t has evolved through a number of stages throughout its history in adult education. In their review of thirty-five years of attrition studies, Verner and Davis (1964) categorized them as either comparative, where individuals or groups of students are compared as persisters or dropouts in relation to some independent variable; or reactional, where dropouts are surveyed for the reason(s) for their leaving. The Verner and Davis (1964) review traces earlier research attempts "marked by simplicity bordering on oversimplification in design and analysis" (158) to the point when a growing sophistication in design, data gathering, and statistical analysis resulted in greater validity in the research findings. These changes influence the way in which the phenomenon of persistence/withdrawal is described. As stated by Boshier (1973), existing research was simply an "attempt to foist single variable esrgrlanations on a phenomenon which clearly has multivariate origins" (255). McClosky (1968) concurred, believing that decisions to persist or withdraw from a social or; educational activity were complex—mediated by many variables,'* 10 each exerting a different degree of influence. With the realization that dropout was a multifaceted problem, and because research efforts had failed to draw together this complex of variables and relationships, theory building began to be looked upon as a necessary next step (Mezirow, 1971; Boshier, 1973; Darkenwald, 1981). In adult education, the evolution of attrition research began with the identification of withdrawal as a problem, moved to the description of the extent of the problem, sought to define and quantify factors which influenced withdrawal, and moved towards the building of explanatory frameworks from which to describe the relationships between variables. The final step will be to use these theories to explain the phenomenon and identify cr i t i c a l events where intervention strategies would have a maximum effect in reducing the number of students who withdraw. Although attrition research in higher education followed a similar evolutionary path, development of theory building and the application of theory to retention programming surpasses that done in adult education. In his review of theories of attrition, Bean (1982) identifies six theoretical models (Spady, 1970; Rootman, 1972; Fishbein and Ajzen, 1975; Tinto, 1975; Pascarella, 1980; and Bean, 1983). In his conclusion he makes recommendations regarding the circumstances in which each theory proves most useful as a tool in explaining attrition and states that, although no model yet devised has u t i l i t y in a l l situations, the theoretical (as opposed to atheoretical model) has broader u t i l i t y because i t explains the "why" of dropping 11 out as opposed to the "who." In the l a t e s t summary and synthesis of the research on higher education a t t r i t i o n T i n t o (1987) discusses the need f o r , a theory of student departure which not only explains the l o n g i t u d i n a l process of student l eav ing from i n s t i t u t i o n s of higher education, but a l so leads to the formulation of successful re tent ion programs. I t must be p o l i c y re levant , not merely of academic i n t e r e s t (4). Contrad ic t ing Bean's (1982) emphasis on the value of a t h e o r e t i c a l approach to theory b u i l d i n g , T in to (1987) be l ieves t h i s to be an unaffordable luxury given the recent dec l ine i n postsecondary enrol lments . F ind ing that recruitment campaigns f a i l to produce the increases i n enrollment necessary to compensate for demographic dec l ines , co l l ege and u n i v e r s i t y adminis trators are now looking to re tent ion as a means of maintaining student numbers. In t h e i r search, adminis trators are turn ing to a t t r i t i o n researchers for s p e c i f i c so lu t ions to dropout problems—solutions yet to be advanced by a l e s s than pragmatic approach to theory b u i l d i n g . What i s obvious from an examination of a t t r i t i o n research, i n each of the three domains, i s the s i m i l a r i t y i n the factors be l i eved to inf luence withdrawal, and the way i n which the research fol lows s i m i l a r evolut ionary pathways towards the r e s o l u t i o n of s i m i l a r problems. Although the s i m i l a r i t i e s are usefu l i n prov id ing a broad perspect ive from which to examine the dropout phenomenon, a danger ex i s t s i f one f a i l s to recognize that important d i f ferences a lso e x i s t between the various populat ions . Higher education a t t r i t i o n research focuses p r i m a r i l y on f indings from four-year i n s t i t u t i o n s , and 12 assumptions based upon findings for this particular population may not apply to students in two-year programs. Differences between the populations involved in different levels of postsecondary schooling overlie many of the factors found related to persistence or dropout. These differences result in research findings that appear to contradict or f a i l to substantiate previous findings because these differences are not recognized. As part of the postsecondary education system, i t would seem logical for attrition research dealing specifically with entry level vocational programs to be included in the literature on higher education. But, as mentioned by Gates and Creamer (1984), even though they constitute a sizeable population in two-year colleges, vocational students have been virtually ignored by attrition researchers. This criticism is further substantiated by Dennison and Gallagher (1986) who, in their study of community colleges in Canada, state that research of any kind is not considered as a priority activity by these institutions. This lack of research creates problems for those attempting to deal specifically with attrition from short-term, entry level programs. As indicated previously, even though a broad perspective can be gained from examining attrition studies from different levels of education, assumptions about the applicability of the findings across different populations may not be valid. Because research directed at entry level vocational students is limited, the application of factors found related to withdrawal for other populations is a necessary first step in the evolution of attrition research for this group. 13 Studies of this kind are often criticized as redundant by writers in adult and higher education, but the search for factors related to persistence/withdrawal is a legitimate research activity in seeking solutions to attrition in entry level vocational programs. Entry level vocational programs differ from those typically examined in postsecondary attrition research studies in terms of entrance requirements, length, and employment goals. As factors influencing decisions by students to withdraw, each of these could produce results which are different for various populations. For example, in terms of academic achievement, students entering degree programs are more homogeneous than entry level vocational students. The "open access" philosophy of many vocational programs attracts students who vary greatly in their academic backgrounds. In addition, much can happen to influence what a student does over a period of four years. Four years of sustained effort requires a greater and perhaps different degree of individual commitment from the six to eight months required to complete an entry level vocational program. The reasons for enrolling in a postsecondary program also differ greatly among these population subgroups. Quoting from a study by Astin, et al. (1982), Tinto (1987) mentions the likelihood that the majority of students entering a four year degree program are uncertain of their long-term educational and employment goals. Unlike these stu.der.t2, those enrolling in short-term vocational programs have not only chosen a career field (e.g. mechanics), but a specific occupation within that field (e.g. motorcycle mechanic). Because of the direct; 14 connection between the educational program and the employment goal, and the short time span between these two, motivation is a factor which may have a different meaning for entry level vocational students. Studying Attrition in Entry Level Vocational Programs The primary purpose of this research was to identify factors related to withdrawal from entry level vocational programs. As a fi r s t step, variables found related to students' decisions to withdraw from postsecondary programs in general were identified in the literature. These variables were then developed into research hypotheses applicable to the program, the research site, and the research population. The data collected were analyzed and the hypotheses tested. Having identified those variables related to persistence or withdrawal, the final step was to use these in the development of a prediction "formula" by which those students most likely to dropout can be identified. Once identification is possible, educational decision makers can then choose to either limit access only to those with the best chance for success, or, to design strategies which would be effective in retaining potential dropouts until they have successfully completed the program. Through the process of selecting and validating the relevance of variables to withdrawal decisions, a secondary purpose is realized. Because of the limited amount of attrition research directed towards students in short-term vocational programs, this study narrowed the range of factors to be applied in future studies by eliminating those which appeared to have l i t t l e relevance for students in these programs. The lack of 15 research in this field necessitated somewhat of a "shotgun" approach in the selection of variables for this study. Although factors, such as concern about the adequacy of one's financial resources, were found related to dropout for university and college students, their application to students in entry level vocational programs was unknown. Therefore, what may appear as a redundant activity to adult and higher education researchers is necessary to f i l l a gap apparent in postsecondary attrition research. Design of the Study In Chapter II the literature on attrition is surveyed. This review includes studies from secondary, postsecondary, and adult education settings. In addition, the concept of- learner self-confidence is developed as a factor which may be related to students' decisions to persist or withdraw. The intention in this chapter is to provide a broad overview of the factors researchers have found which influence students' decisions to withdraw in a l l levels of educational programs. The outcome of this overview is the selection, in Chapters IV and V, of factors related to persistence/withdrawal which have application in entry level vocational programs. In Chapter III the entry level vocational program and site selected for the study are described, and the reasons for the selection of a particular program and institution are stated. Following this, the population is defined and the research sample is described in relation to the population. The sources and methods of gathering the data needed to answer the research questions are then outlined. This outline includes a detailed 16 description of the design of the survey instrument, its testing, and administration. The chapter concludes with an explanation of the methods used in the statistical analysis of the data. Chapter IV and V describe the results of the data collection and analyses. In Chapter IV factors considered as "pre-entry11 i.e., occurring before students begin their postsecondary program, are examined. Chapter V concentrates on factors which occur after the student begins the program, i.e., "postentry" factors. Chapter IV begins by describing the mailed questionnaire response rate and the impact that a response of less than 100 percent has on the research findings. In both chapters the research hypotheses are stated together with the rationale for their selection and the anticipated outcomes according to previous research findings. The results of each analysis are then explained in relation to the acceptance or rejection of each hypothesis. Alternative explanations are considered in cases where null hypotheses are accepted and the meaning of the rejection of a hypothesis is examined in cases where this is the outcome of the statistical analysis. Each chapter concludes with a summary of what the findings have to contribute to our understanding of students• decisions to persist or withdraw. In Chapter VI those variables found to be related to persistence or withdrawal are used in the development of a means tq identify students most likely to dropout. The resultiH^ prediction formula is then tested on the research sample to determine its effectiveness in differentiating between persisters and dropouts. In conclusion, the ways in which this 17 information can be used by practitioners is discussed. In Chapter VII the purpose of the study is reviewed. The results of the statistical analyses are discussed in relation to how they served to answer the questions asked. This is followed by suggestions for changes in the research design which may benefit researchers examining similar populations and programs in the future. Implications of the results and recommendations for further research conclude this final chapter. 18 CHAPTER II REVIEW OF THE LITERATURE The extent of the research on attrition in educational programs is dependent upon the population that one happens to examine. If one is interested in why students drop out of short-term postsecondary vocational programs, the literature on adult vocational education would be the most logical source. On finding a limited amount of research directed towards these kinds of programs, the researcher's next source would be the adult education literature. Even though i t provides a richer source of information, this research deals primarily with why adults withdraw from part-time continuing education classes. In addition, in much of the research persistence is combined with participation, making i t difficult to separate factors related to why adults withdraw from why they decide to participate in the fi r s t place. Because most adult vocational programs take place in colleges and vocational institutes, another source of attrition research would be the literature of higher education. This proves to be the major source of studies on why adult students drop out of educational programs. Although hundreds of studies have been reported, short-term vocational programs have rarely been chosen for examination. In addition to the sources already identified, and because a student's previous educational experience is believed to have an impact on subsequent attempts at : training, the literature on high school dropout also provides relevant information. In this regard both high school dropouts and high school vocational 19 program completers are of interest. The selection of factors related to attrition from short-term postsecondary vocational programs necessitates the review of the literature from a variety of sources. In this chapter the need for a broad perspective is examined in the f i r s t section. This is followed by the review of attrition studies done by adult education researchers including a discussion of the "melding" of participation and persistence and concluding with a review of what the literature contributes to the study of the research population. The higher education research is then reviewed, by clarifying the definitions surrounding student enrollment status, followed by a review of attrition factors. The review of these factors is divided into those students bring with them to their postsecondary experience and those they encounter after they have enrolled. From this review factors relevant to entry level vocational students are identified for inclusion in the present study. A review of the attrition research done by those studying adult vocational students and high school populations follows the survey of the primary sources of attrition research. The concept of "learner self-confidence" and its hypothesized relation to persistence/ withdrawal is introduced and discussed. The chapter concludes with a section which places the results of the literature review in context with the present study. The Study of Attrition in Entry Level Vocational Programs Entry level vocational training serves a heterogeneous clientele. Because of its "open access" philosophy i t is the1 only option available to those who left high school prior to graduating and who lack the academic qualifications to get into other career related postsecondary programs. Lacking a high school diploma, these students would be similar to students who participate in Adult Basic Education (ABE) programs. Also included among the participants in entry level vocational programs are those students who graduated from high school programs which were heavily shop based but not highly academic. These students would also have limited options regarding choice of postsecondary training. Found also in entry level vocational programs are students who graduated from high school and who are qualified to enter either two-year college programs or university. These students would be similar to those participating in higher education programs. Therefore, due to its minimal entrance requirements and because i t is an entry point to a career as a tradesperson, entry level vocational training serves students with a variety of educational backgrounds. In addition to an already varied clientele, entry level trades courses attract mature students seeking to change their employment options. Members of this group could f i t into any of the above categories based upon their previous education, but have the added differences that age (i.e., maturity, responsibilities, work experience) brings with i t . In other words, these participants, unlike recent high school graduates, have assumed the role of "adult." Even though community colleges serve students having diverse educational backgrounds, only entry level vocational programs include this diversity without crossing program boundaries. Therefore, the advantage of examining entry level trades students in attrition research is that "program" becomes one less source of variance. For example, when studying attrition at the college level one has to determine whether students taking fir s t and second year university courses are different from ABE students or from those taking a two-year technology program. To reduce the impact of "variation in program" as a confounding variable i t must either be controlled for, or the study narrowed to include only students from a specific program. But narrowing the study by including students from a particular program, such as ABE or two-year technology programs, reduces the likelihood of discovering a relationship between factors such as "previous educational experience" and persistence/withdrawal. Such a relationship, should i t exist, is made more apparent by studying students with a broad range of educational attainment rather than the homogeneous mix that would be found in a single program. A disadvantage of studying attrition within entry level vocational programs is that l i t t l e research has been done in this area. As stated by Gates and Creamer "not only is most retention research directed at four- rather than two-year college students, but most a l l of i t ignores the vocational students, a sizeable population for two-year colleges" (1984: 45). This means that the factors related to persistence/withdrawal selected for examination must be "borrowed" from adult education where ABE is studied, from higher education where two-year college programs and university populations are studied, and, i f available, from adult vocational education. In addition, because high school dropouts are included in entry level vocational program populations, the literature on high school dropout must also be examined for factors which could be related to subsequent withdrawal from postsecondary training. Adult Education and the Study of Attrition The failure of adult students to persist to the completion of educational programs has long been of concern to adult educators. As stated by Verner and Davis (1964) " i t was perceived as a major problem in adult education as early as 1814 when Thomas Pole urged adult teachers to v i s i t those students who were absent in order to exhort them to attend regularly" (157). Although recognized as a problem, the scientific study of this phenomenon was not initiated until early in the twentieth century and even then the research was characterized by Verner and Davis (1964) as unsystematic, fragmented, unsubstantiated, and incomparable. This is partially due to the emphasis placed by adult educators upon increasing participation and is also the result of a lack of the theory based framework necessary to give form and meaning to the variety of attrition studies. The Melding of Participation and Persistence Participation and persistence, though different in meaning, are frequently combined as related concepts in adult education research. As stated by Boshier (1973) " . . . dropout is in some ways an extension of non-participation; variables associated with one are associated with the other . . . " (256). Although not stated in such direct terms, the melding of the concepts of participation and persistence is obvious both in reviews of the participation literature (Cross, 1982) and in theory based participation research (Miller, 1967; Boshier, 1973; Rubenson, 1977; Cross, 1982). The rationale for this melding has yet to be clearly explained. Because the factors that lead to participation and those that result in persistence or withdrawal could be as different as the two concepts themselves, one has to question the soundness of this approach. For example, i t is generally agreed that adult education participation is directly related to educational attainment: those with a high level of education have a high level of participation. These participants see education as a means of meeting their needs, and have a history of successful educational experiences from which to extrapolate continuing success. These expectations lead to participation, but upon actual participation students are confronted by the rush of pressures "from head colds to changing goals" which diminish their staying power and increase their tendency to withdraw. Therefore, although related to both participation and persistence, the influence of educational attainment varies in strength and form dependent upon whether one is planning to participate, or is already in attendance and contemplating withdrawal. The melding of the two concepts makes i t difficult to segregate and examine those variables exclusively related to student dropout. The point is raised because awareness of this melding, at the outset, is necessary to better interpret the adult education literature. This tendency to combine participation and persistence research is a major reason for a: reliance on the literature from higher education, where 24 persistence has been dealt with as a separate concept. As stated previously, vocational training can improve the employment potential of individuals only i f they remain with the program long enough to gain marketable skills. Obviously, these skills can only be gained after the individual has made the decision to participate. Therefore, from a pragmatic point of view, the logical approach is to concentrate research efforts on the retention of those individuals who have already made the decision to participate. This concentration becomes even more important when dealing with populations which exhibit both low participation and high attrition rates (e.g. ill i t e r a t e and low educational attainment adults). Persistence in Adult Education Research The f i r s t review of attrition research in adult education was completed by Verner and Davis in 1964. In their review they examined thirty studies, the fir s t of which was published in 1928. While no factors were found which clearly differentiated between those who persisted and those who chose to withdraw, the two reviewers directed their criticism for this lack of concrete conclusions not at the factors selected for examination, but at the research methods chosen to explore the relationships. As stated by Verner and Davis, "a comparative analysis of the research procedures points up many deficiencies with respect to sampling procedures, sample sizes, data gathering processes and timing, and analytic procedures" . (158). A primary target of their criticism was the reliance on ex post facto research designs which they believed to be unsuited to detecting changes in attitudes or conditions during participation which may have 25 resulted in withdrawal. In considering adult educators' contributions to the increase of knowledge regarding attrition, Verner and Davis state that the " . . . lack of awareness of previous research has led to an unsystematic approach to the problem, to fragmentation, and to unsubstantiated or incomparable results" (157). They conclude their review with a challenge to future researchers: "virtually every aspect of adult education revolves around participation and persistence of attendance, yet the quantity of substantial research related to this particular aspect of the field is astonishingly small and inadequate. No other aspect of adult education so badly needs systematic and creative basic research" (173). In a subsequent study (National Survey of University Adult Education Students), 4562 respondents who attended university adult education classes in 1961-62 at one of seven selected institutions were surveyed in an attempt to describe university adult education participants, educational achievement variables related to adult learning outcomes, and characteristics which differentiated persisters from dropouts (Knox and Sjogren, 1965). Using attrition factors identified in the Verner and Davis (1964) study, Knox and Sjogren predicted that: 1. Completions, as with participation, will be positively related to measures of academic ability, such as verbal ability, level of education, and the selection process that is associated with age, but the degree of association will be small. 2. Completion will have a low negative association with measures of the passage of time such as age and years since leaving school. 3. Completion will have a low negative association with level of anxiety (1965: 83). Their predictions were translated into eight independent variables: level of education, verbal ability, age, years since last attending school, worker/homemaker satisfaction, occupational status, sense of political efficacy, and manifest anxiety. The correlations between these independent variables and dropout were combined using a multiple biserial correlation technique as a means of performing a discriminate analysis. Of the five institutions supplying data on the eight independent variables, statistically significant correlations were found to exist in the data supplied by only three of the institutions. As indicated by the authors, "even though statistically significant the use of these variables to predict completion or drop[out] has l i t t l e practical significance" (Knox and Sjogren, 1965: 84). Even though this study deals with part-time rather than full-time programs, and a population quite different from students in entry level vocational programs, its importance lies in the conclusion by the researchers which stresses that dropout is influenced by a broad range of factors, each having a small impact on dropout decisions and, therefore, calls for a broad range of solutions. Their failure to discover a few factors which account for the major portion of the dropout variance is a finding which is repeated over and over regardless of the research population under study. A similar study was conducted by Verner and Dickinson (1967) on 2075 students enrolled in academic, vocational, or general interest courses in an adult night school program. In addition to examining selected characteristics of participants (i.e., sex, age, marital status, number of children, years of schooling, previous adult education participation and occupation), Verner and Dickinson also examined the program variables of course length and subject matter in relation to persistence and dropout. They found that course length and subject matter do have a statistically significant effect on persistence. The holding power of programs was inversely related to length and attrition rates were higher for academic than vocational courses which, in turn, were higher than that for general interest courses. The researchers do indicate, however, that course length is not a significant factor when examined across the boundaries of subject areas. Similar results were found when age and marital status were compared with course length and subject matter. In other words, when compared across a l l subject areas, being younger and single was related to dropout, but this was not necessarily the case when individual subject area or course length was examined. The relationship of number of children to persistence or dropout was also found to be statistically significant: having more children was positively related to persistence, and was independent of course length and subject area. Although years of schooling in this study did not differentiate persisters from dropouts, having previously participated in an adult education course was positively related to persistence and was also independent of e©wrse length and subject area. When examined by occupation, there were statistically significant differences between persisters and dropouts, a relationship which was made more complex when considered with course length and content. 28 In summary, Verner and Dickinson indicated that, "the persistent attenders were older, married housewives who had children, while the dropouts were younger and usually single" (1964: 33). Even though their study dealt with part-time evening courses and not full-time postsecondary vocational programs, their results reinforce previous findings which emphasize a broad, multifactor explanation of attrition. The decision to withdraw is influenced by many different factors rather than simply educational attainment or socio-demographic characteristics. In 1971 Sainty attempted to combine factors, indicated by previous research to have predictive value in identifying dropouts, into a prediction formula. Rather than using the formula to restrict entry into the program, Sainty's objective was to identify and assist participants in jeopardy of withdrawing. After collecting data on students' intelligence, reading ability, personality traits and selected biographical information, Sainty, through a combination of Pearson product moment correlations and multiple linear regression, identified seventeen factors positively related to dropout at a statistically significant level. Compared to the persisters, the dropouts identified by Sainty were characterized as: being less intelligent, having lower reading speed, accuracy, vocabulary, and comprehension scores (Gates Reading Purvey), being younger and from a lower social position and occupational class, having a father from a lower occupational class, being downwardly mobile in both occupational class and social position, completing fewer and repeating more grades in school, having not attended high school or attending but taking a nonacademic program, likely to have failed past attempts at further education, having changed jobs more often in the previous twelve months, having had a lower wage in their last steady job, and being unilingual. By combining the above factors in a multiple regression calculation 63.88 per cent of the variance was accounted for. By using stepwise multiple regression Sainty identified three predictors: age, number of grades repeated, and number of job changes in the previous twelve months, which were positively related to dropout and which, when combined, accounted for 43.03 percent of the dropout variance. Through the use of beta weights, Sainty was able to establish a cutoff score which identified 90 percent of the dropouts while misclassifying only 23 percent of the dropouts. Although clearly significant in its ability to successfully identify dropouts, Sainty's prediction formula produced results which were considerably higher than those from the studies originally used in the selection of his variables. Boshier (1973) took exception to Sainty's results stating: "these findings are suspect (and unable to be generalized)..." (267). Although Boshier's (1973) concerns stemmed from Sainty's failure to adequately define who he considered a dropout, the strength of the prediction formula may have i n i t i a l l y alerted him to look for flaws in the research design. In view of the inability of numerous other studies (Verner and Davis 1964; Knox and Sjogren 1965; Verner and Dickinson 1967; Boshier, 1972; Londoner 1975; Wilson 1980, and Anderson and Darkenwald 1981) to 30 select a mix of variables with as strong a predictive value, caution is advisable, at least until Sainty's results are confirmed through replication. Even though Sainty's results are suspect, his research has value for the present study through his population, selection of variables, and statistical method. Although the students in Sainty's study were not enrolled in a vocational program, they would have had an educational attainment level similar to those students in the research population who failed to graduate from high school. In addition, the objective of Sainty's study—to predict persistence/ withdrawal—was similar to one of the goals of the present study, and his methods serve as an example of how that goal may be attained. A different means of predicting dropout from adult education programs was developed by Boshier (1972). The instrument he designed measured the attitude of students towards dropout at the beginning of a course and how that attitude differed between course persisters and course dropouts. His findings indicated that course persisters tend to evaluate persistence more positively than dropping out. Course dropouts, on the other hand, evaluate dropout either more positively, or no differently from persistence. Drawing from his i n i t i a l study, Boshier (1973) went on to develop a model to explain the persistence/withdrawal phenomenon in adult education. His model recognised the "interaction of internal psychological and external environmental variables" (256) and emphasized "that 'congruence' both within the participant and between the participant and his educational environment determine . . . dropout/persistence" (256). Simply put, intra/self congruence would be characterized by an adult who looks at education as a growth experience, the goal of which is this growth. Intra/self incongruence, on the other hand, would be characterized by the adult who sees education as a means to an end such as job promotion or woodworking skills. Boshier's belief is that the learner who has personal growth as his/her goal is less likely to be deterred by external factors such as child care problems or feelings of unease with the educational environment. The significance of Boshier's model rests upon his contention that single variables such as age, educational attainment, and socioeconomic status, typically examined in previous dropout research, simply mediate rather than cause decisions to drop out. Boshier's belief that single factors act only in a mediating role was strengthened by his testing of the relationship between these kinds of variables (separately and combined via stepwise linear regression) and dropout. The highest R produced using combinations of "single factors" was .39, accounting for only 9.6 per cent of the variance. In contrast, correlations between scores achieved on the instrument developed by Boshier to measure congruence/incongruence, and persistence/withdrawal accounted for more than thirty per cent of the variance. Boshier's conclusion was that intraself and self/other incongruence are antecedent conditions projected onto the educational situation and these conditions result in incongruence between the student and his lecturer, his fellow students, and his environment, which leads to the decision to 32 withdraw. By definition, students in vocational programs would be considered by Boshier to be intraself and self/other incongruent. Rather than having as their primary objective self-growth they would, by virtue of their enrollment in a vocational program, be seeking employment as the end product of their training. This would make them more susceptible to the external pressures mediating the decision to withdraw. However, according to the result of Verner and Dickinson's (1967) and Gates and Creamer's (1984) studies, vocational students are less likely to dropout than students in programs which may be more likely to nurture self-growth (i.e., academic programs). A major difference between the populations studied by adult education researchers and the research population is that adult education tends to deal more with part-time programs. In these programs the adult's role is not primarily that of student. Entry level vocational programs, on the other hand, are full-time and necessitate a greater commitment of resources and energies by the student. This would also make external pressures, such as child care and financial concerns, greater. Therefore, according to Boshier's predictions, a combination of the student's focus on the end result and the increased pressures accompanying full-time attendance would result in a high attrition rate for entry level vocational programs. But there are also forces common to fulx-iime enrollment which favour persistence rather than withdrawal. Unable to align itself with the designs, populations, or outcomes of either adult or higher education, and having a limited research base on which to draw, postsecondary vocational programs present the researcher with a unique set of problems. The answer to the question of what factors are related to students' decisions to withdraw is not to be found in existing research. At best what is provided is a variety of factors relevant to the question for other populations which provide the researcher with some direction. Even though of limited practical use in the present study, Boshier's research represents a trend towards a theory based approach to the study of attrition. It broke away from the exercise of trying to identify single or multiple factors which caused withdrawal by attempting to identify internal psychological predispositions which would tip students' decisions towards persistence or withdrawal as these factors were loaded on. In addition, Boshier's label of "congruence/incongruence" is similar to the idea of " f i t " referred to by higher education researchers (Pantages & Creedon, 1978; Tinto, 1987) in regards to whether a student feels himself to be a part of the social system of the school, college or university. In a similar vein, Londoner's (1972) view regarding intraself congruence is almost the opposite of Boshier's. More specifically, Londoner believes that perseverers "participate in adult education to achieve future tangible goals which strengthen .-Sheir external orientations to the work and social environments" (181), and that nonperseverers "enroll in adult education to satisfy personal inner directed needs which would result in a more integrated, stable, and self-assured person in 34 the vocational and social environments" (181). He collected data using an instrument he developed on which reasons for participation were listed and classified as indicating an external or internal orientation. In addition to the responses regarding educational goals, the age, sex, marital status, employment status, and annual income of each respondent were gathered and compared for perseverers and nonperseverers. Londoner's hypothesis that, "proportionally," more perseverers would rate the externally oriented educational goals higher in importance was proved marginally correct: for only one educational goal, "to obtain a high school diploma," did the relationship between i t and perserverence approach statistical significance. The association between perseverance and the other five goals was weak with one proving opposite to Londoner's prediction. Similar results were found with nonperseverers' ratings of the internally oriented educational goals. An i n i t i a l analysis of the participants' personal information indicated that the two groups were not significantly different on any factor. From Londoner's perspective vocational students would be expected to have relatively small attrition levels, however, for the population under study, attrition ran as high as 65 percent. Although creative in his hypothesized reason for dropout among adult student, Londoner's research design lacked the number of cases needed for more sophisticated statistical analyses. Using a different approach from Boshier (1973) and Londoner (1972) in studying psychological determinants of attrition, Wilson (1980) examined the relationship of personality characteristics between persisters and dropouts. Students, upon 35 enrolling in a General Education Diploma program, were assessed using the Adjective Check List (ACL) which provided scores on 24 standardized personality attributes. After categorizing students as either persisters or dropouts, the investigation compared the ACL scores for both groups. Persisters scored significantly higher on Self-control, Endurance, and Deference than did dropouts who scored higher on Number of Unfavorable Adjectives Checked, Autonomy, Change, and Succorance. Using the ACL Manual, Wilson provided a profile of dropouts and persisters based upon the ACL results: Dropouts described themselves as more rebellious and hostile. They were seen as less socialized, while being more impulsive, headstrong, irresponsible. They are less able to give prolonged effort, being more impatient and comfortable with disorder and change than the persisters. Dropouts were seen as indifferent to the feelings and needs of others and as assertive, less willing to subordinate self and more desirous of attention and authority. They seek succorance. While being inattentive to the needs of others they may desire more supportive and dependent relationships than persisters. Persisters were seen as more obliging, tactful, diligent, practical, and compliant than the dropout. They were more interested in stability and reducing risk. In relationships they were more concerned about the needs of others, more supportive, more persevering, more able to yield to the reasonable requests of others (1980: 183). Although Wilson's profile of individuals in each of the two groups clearly differentiates between them, the description of the groups as either dropouts or persisters seems conjectural. A persister is defined as a student who completes ten weeks of instruction and/or passes the GED exam. A dropout is defined as a student who formally withdraws or is involuntarily withdrawn due to lack of attendance. In addition, those who attend for the ten week period, but f a i l to pass the GED exam are similarly 36 c l a s s i f i e d as dropouts. Even though i t i s indicated that "29 students dropped out while 133 remained" (178), no mention i s made of those who remained but d i d not complete the GED exam. Possibly, f a i l u r e s are included with the dropouts, and the study i s a c t u a l l y measuring the a t t r i b u t e s of three groups: dropouts, p e r s i s t e r s , and students who f a i l . Consideration of t h i s p o s s i b i l i t y i s necessary i n evaluating the r e s u l t s of Wilson's study. Wilson's study can also be c r i t i c a l l y viewed f o r h i s use of a psychological measure of personality without f i r s t developing a l i n k between personality and decisions to withdraw from t r a i n i n g . In terms of b u i l d i n g on e x i s t i n g research Wilson may have hypothesized that personality was r e l a t e d to Boshier's (1973) concept of "congruence," h i s r e s u l t s thus describing the differences between congruent (persister) and incongruent (dropout) p e r s o n a l i t i e s . The danger that a s u p e r f i c i a l reading of h i s research presents i s the image that dropouts/dropout i s negative and persisters/persistence i s p o s i t i v e . This perception f a i l s to recognize the p o s i t i v e p o t e n t i a l that dropping out of a program which one i s t o t a l l y unsuited f o r or unhappy i n could have on a dropout's personal development. In 1979 Anderson and Darkenwald reported on the r e s u l t s of t h e i r study of p a r t i c i p a t i o n and persistence i n adult education. Based upon a national sample of several thousand p a r t i c i p a n t s , the r e s u l t s were used by Darkenwald (1981) 1-M a subsequent review of the l i t e r a t u r e to attempt to reduce the ambiguity surrounding the r e s u l t s of previous research. As mentioned i n studies by other researchers, "sociodemographic f a c t o r s " such as 37 sex, occupational status, age, residence, race, and educational attainment were seen as related to persistence/withdrawal. By controlling for extraneous factors, Anderson and Darkenwald (1979) found that, of these variables, only age and educational attainment were significant predictors of persistence. Although statistically significant, the amount of variance accounted for by age and educational attainment was too small to have any practical significance. In referring to "psychological factors" [i.e., those "relatively enduring individual characteristics such as intelligence and personality" (4)], Darkenwald (1981) states that existing research has produced " l i t t l e in the way of firm generalizations or conclusions" (5). He believes that any effect these factors may have on persistence is most likely to be an interaction between, for example, an individual's cognitive ability, or personality traits and the specific learning situation. Similar results were indicated for factors described by him as "external situational" which are those that affect the participants' ability to physically attend class. He views these factors such as illness or unexpected family problems as contributing to, rather than causing, withdrawal. Darkenwald also believes that these factors, because of the randomness of their occurrence in a participant's l i f e , are beyond the control of adult educators. Program context factors, described as "administrative or organizational properties of educational programs, such as frequency and length of class meetings, class size, provision of support services, and the like . . ." (6), were found by 38 Anderson and Darkenwald (1979) t o be r e l a t e d t o a t t r i t i o n . Number o f c l a s s s e s s i o n s and t h e f requency o f t h e meet ings were found t o be d i r e c t l y r e l a t e d t o d r o p o u t . A f t e r r e v i e w i n g p r e v i o u s s t u d i e s , Darkenwald (1981) i n d i c a t e s t h a t d u r i n g these c l a s s s e s s i o n s t h e s i t u a t i o n s t h a t a r i s e from t h e i n t e r a c t i o n between t h e a d u l t s t u d e n t and the t e a c h e r a n d / o r t h e l e a r n i n g environment a r e t h e most i m p o r t a n t f a c t o r s i n a c c o u n t i n g f o r a t t r i t i o n . F o r example , t h e e x t e n t t o which t h e l e a r n i n g a c t i v i t y i s p e r c e i v e d by the a d u l t l e a r n e r as m e e t i n g f e l t needs " i s p r o b a b l y t h e major d e t e r m i n a n t o f p e r s i s t e n c e " ( 7 ) . A r e l a t e d f a c t o r i s " s a t i s f a c t i o n " : a g l o b a l v a l u a t i o n encompass ing e v e r y t h i n g from meet ing s t u d e n t needs t o h a v i n g c o n v e n i e n t c o u r s e h o u r s . D i s s a t i s f a c t i o n , a c c o r d i n g t o Darkenwald (1981) , i s t h e b e s t p r e d i c t o r o f d r o p o u t , b u t , l i k e o t h e r s i n g l e v a r i a b l e e x p l a n a t i o n s , i t a c c o u n t s f o r o n l y a s m a l l p o r t i o n o f t h e v a r i a n c e . C o n c l u s i o n s From A d u l t E d u c a t i o n A t t r i t i o n R e s e a r c h A r e v i e w o f a d u l t e d u c a t i o n r e s e a r c h on p e r s i s t e n c e / w i t h d r a w a l c o n f i r m s o n l y t h a t t h e causes o f a d u l t d r o p o u t a r e i n a d e q u a t e l y u n d e r s t o o d . A f r e q u e n t l y sugges ted r e a s o n f o r t h i s l a c k o f c o n c l u s i v e f i n d i n g s i s t h e way i n which r e s e a r c h has been c o n d u c t e d . The c r i t i c i s m g e n e r a l l y e x p r e s s e d by a d u l t e d u c a t o r s r e g a r d i n g t h e s t a t e o f a t t r i t i o n r e s e a r c h i s b e s t summarized by Darkenwald (1981): A major p r o b l e m i s t h a t few s t u d i e s have been guiMed by any c o h e r e n t c o n c e p t u a l scheme o r t h e o r y . Thus t h e r e s e a r c h t e n d s t o l a c k f o c u s . In a d d i t i o n , t h e c u m u l a t i v e development and r e f i n e m e n t o f knowledge t h a t t h e o r y b u i l d i n g f o s t e r s has been r e t a r d e d . A second p r o b l e m i s t h a t most r e s e a r c h s t i l l employs s m a l l , u n r e p r e s e n t a t i v e samples , t h e r e b y l i m i t i n g t h e g e n e r a l i z a b i l i t y o f f i n d i n g s . Another s h o r t c o m i n g i s 39 that relatively few studies have employed rigorous statistical controls and, therefore, misleading findings are sometimes reported. . . . Finally, research on dropout behavior has failed to address the topic from the perspective of the adult student by taking into account the student's definition of the situation and the processes leading to the decision to continue or discontinue participation. Dropout behavior results from complex, interacting factors, yet the research designs commonly used to study the phenomenon are i l l suited to capturing this complexity (3). This criticism suggests two possibilities: factors exist that exert a major influence on dropout decisions which, through inadequate or inappropriate research methods, have yet to be discovered, or, the reasons for dropping out are as diverse as the individuals and situations that characterize adult education. An examination of the evolution of research methods since the review by Verner and Davis in 1964 indicates that major influencing factors most likely have not been overlooked. What remains is a complexity of reasons and interrelationships that f a i l to conform to the orderly processes thus far suggested by theorists and researchers. As stated previously, although failing to answer the questions asked in this research, the adult education literature does present factors for examination which may be relevant to the study of attrition from entry level vocational programs. It also provides some insight into the potential pitfalls to be encountered through the use of certain research designs and statistical techniques. However, because they are made in regard to a population of lean^rs different from those examined in the present study, Darkenwald's criticisms do not necessarily apply to the study of attrition in entry level vocational programs. Similar to the study of attrition in higher education, research by adult educators benefits from a long history and considerable research effort. With this in mind, Darkenwald1s criticisms seem appropriate in that with time and effort the study of a phenomenon should evolve from empirical exploration towards theoretical explanation. Lacking the history and effort expended on other educational populations, the study of attrition in vocational programs necessitates i n i t i a l l y a broad, empirical approach to lay the foundation upon which theoretical explanations can be built. In general, the trend in adult education has been to place more emphasis on attracting individuals to programs than on ensuring they persist to completion. This emphasis on participation may be due to the marketplace orientation of adult education, or to the belief in education as a means to social equality, but both rationales have an output as well as an input dimension. As accountability becomes more important with the tightening of educational spending, emphasis may shift to retaining those who have already decided to participate. This shift will necessitate a parallel move in research emphasis. Higher Education and the Study of Attrition Although drawn together through a sharing of client groups, programs, and facilities, higher education and adult education differ to some extent in the concern shown for attracting and retaining participants. For years colleges and universities have not been concerned with attracting students because they ea*tered to an established and select clientele. On the other hand, adult education, because of its diversity of offerings and client groups, and its social movement concerns, has been acutely aware 41 of underrepresentation by certain segments of society. These differences have carried over to influence the concerns of both fields regarding dropout and how to deal with i t . As stated by Lenning, Beal, and Sauer (1980) "attrition and retention or persistence have long been familiar terms in higher education. But until recently, most administrators have been content to acknowledge that the phenomena exist and to accept them" (1). Now, due to declining enrollments, attrition is assuming more importance as a major cause of the increasing costs of instruction. Also, administrators realize that "improved retention and effective recruiting enhance one another" (1). This realization has increased the emphasis placed upon retention research in higher education. Differences in attrition research between adult and higher education settings also reflect other differences between these two fields. Higher education, due to its long formal history, "size," public recognition, and sustained financial support is recognized as a societal institution. In comparison, adult education has existed as a marginal educational activity in terms of public recognition and the resulting level and consistency of financial support. The influence of size (the number of researchers and studies completed), can be realized by comparing the Verner and Davis (1964) review of adult education research in which thirty studies were examined (1928 to 1963), to the review done by Sex%on (1965) in which 168 higher education articles were reviewed (1933 to 1958). The sum of these differences has resulted in an organized and comprehensive approach to the study of persistence and withdrawal in the higher education literature. Because of this approach, an examination of the literature is facilitated by a number of reviews of higher education research such as those by Sexton, 1965; Tinto, 1975; Pantages and Creedon, 1978; Lenning, et al., 1980; and Tinto, 1987. Persistence, Dropout. Stopout. and Attainers The increasing interest in retention and attrition has resulted in an expansion of meaning for these concepts, and the addition of a new approach to interpreting the behaviour involved. Persistence is connected to the idea of "on time graduation"; stopout to "late graduation"; and dropout to "withdrawal at a particular time," a designation which may later change to stopout upon resumption of studies. In addition, an attainer is defined from the vantage point of the learner rather than of the institution, and is ". . . a student who drops out prior to graduation, but after attaining a personal goal such as a limited course of study, s k i l l acquisition, or employment. In contrast to persisters, stopouts, and dropouts, attainers are defined, not with respect to the perspective of the college or university, but with respect to their own personal goals" (Lenning, et al., 1980: 10). However, what the above authors f a i l to do is describe the attainer in relation to the definition given for persister, stopout, or dropout. Whether attainers are considered as persisters when they "graduate on time3' with respect to their own personal goals and schedule; or, whether they are considered as stopouts, returning to education as their personal goals change over time, is unclear. By formal definition, most likely, attainers are considered within educational institutions as dropouts. This failure of educational providers to account for attainers as something other than dropouts could, in itself, inflate attrition figures, thereby affecting funding and program image. Pre-Entry and Postentry Attrition Factors Some consistency exists in the findings indicated by researchers and theorists looking at participation/persistence from the adult education perspective, and those in higher education examining attrition/retention. Both groups agree that dropping out is a complex phenomenon, and only minimal understanding can come from looking at the individual or the institution in isolation. Lenning, Beal and Sauer (1980) have categorized attrition research into that which applies to students, institutions, interactions between the two, and external forces. These applications are further divided into the following factors: academic, demographic, and financial, which apply to the student; the objective environment, student involvement, and administrative policies and procedures which concern the institution; interactions between these groups, and, finally, factors such as economic cycles and social forces which are considered as external variables. Tinto (1987) also recognizes the idiosyncratic nature of each student's decision to persist or withdraw but recognizes that there also ". . . emerge [s] among the diversity of behaviors reported in the research. on this question a number of common themes as to the primary causes of individual withdrawal from institutions of higher education" (39). He goes on to state that these are divided into factors which "pertain on one hand to the dispositions of individuals who enter higher education and, on the other, to the character of their interactional experiences within the institution following entry" (39). Regarding the individual, he uses the terms "intention" and "commitment" to describe what the research seems to indicate as the primary influencers, with "adjustment", "difficulty", "incongruence", and "isolation" describing those factors related to the individual's experience within the institution. Although different in the way they categorize factors related to withdrawal, Tinto (1987) and Lenning, Beal, and Sauer (1980) differentiate between those factors which are determined prior to institutional entry but only become apparent upon enrollment, and those which are a part of the student's postsecondary experience. Because i t presents a logical method of organization, factors gleaned from the research will be classified as either "pre-entry" or "postentry." Pre-entry factors, i.e., those that the students bring with them to their postsecondary experience, include previous educational experience, academic factors, demographic factors, motivational factors, and personality factors. Postentry factors, i.e., those that students encounter only after enrolling, include academic factors, motivational factors, financial factors, and institutional factors. Academic factors are included in both categories because some, such as s k i l l i#7els in basic math and reading, are determined before students begin college or university, whereas early program performance is a product of their postentry experience. Similarly, because that which motivates students to enroll and that which motivates them to persist is apparent both before and after beginning training, motivation is included as both a pre-entry and a postentry factor. Pre-Entry Attrition Factors Prior to beginning postsecondary training, each student has been exposed to the public school system for a considerable number of years. During this period, skills are developed and attitudes regarding the educational process are formed. Because entry level vocational programs serve students having a wide variety of educational backgrounds, the s k i l l levels and attitudes of its population also vary greatly. This diversity may be beneficial in teasing out factors not previously found by researchers studying more homogeneous groups. Previous Educational Experience. As already indicated, educational attainment has been identified as a factor influencing persistence in adult education activities. This finding is consistent with higher education research done over the past five decades (Sexton, 1965; Pantages & Creedon, 1978; Lenning, et al., 1980). However, in referring to a student's academic record, including high school Grade Point Average (GPA), class rank, and scholastic aptitude, Pantages & Creedon (1978) state that, while providing the strongest single-variable predictive power, academic variables are stronger in predicting college achievement than attrition. They go on to say that academic variables account for only «. 3mall proportion of that which causes students to withdraw. Although small, the extent of its contribution to the total dropout variance does not exclude previous educational experience as a variable in the study of 46 factors influencing attrition in entry level vocational programs. Demographic Factors. Demographic factors include age and socioeconomic status (SES). Although the age of the student has been included as a variable in a number of studies, Pantages and Creedon (1978) indicate that i t has not been shown to be a crucial factor in determining dropout. More relevant may be the number of years since the student last attended school. Because this would apply more to adult students who attend colleges and universities primarily on a part-time basis, i t may be that this variable has been overlooked by higher education researchers who tend to concentrate on full-time students. Both age and the length of time since last schooling are relevant factors for the research population. Minimal prerequisites and a popularity among sponsoring agencies results in a population which tends to be heterogeneous with regard to both age and educational background. Because college and university populations are more homogeneous with regard to age and the length of time since last attending school, the influence that these two variables have on students' decisions to withdraw has not been made clear from the higher education research. No definite conclusions regarding socioeconomic status are evident in the higher education research, however, as stated by Lenning, Bial & Sauer (1980), "the best conclusion may be that students of distinctly disadvantaged status are more prone to attrition but the operating variables may be level of familial aspiration, educational level of parents, personal educational aspirations, and involvement with the college" (16). Again, the examination of this factor is limited by a concentration on the traditional higher education participant. In his study of adult students, Sainty (1971) expands the definition of socioeconomic status by examining job changes, rate of pay, the SES of the student and his parents i f he was living at home, and the student's social mobility. While not conclusive, these findings justify the inclusion of a variety of socioeconomic indicators to suit the population diversity of entry level vocational programs. Motivational Factors. Although not yet fully investigated, motivational factors are indicated as " . . .by far the most prominent reasons given by dropouts as prime factors in their decision to drop out . . . ." (Pantages & Creedon, 1978: 65). A student's expectation of success, the clarity of and reasons for specific educational and career goals, interest related to the chosen program of study, and the influence exerted by family and friends may a l l contribute to the effort the student is willing to expend to achieve completion. Motivation to remain in school has been found to be influenced by long term educational aspirations (Pantages & Creedon, 1978). Plans to go on to more advanced levels of education following completion of a program are positively related to persistence. This relationship emphasizes the importance of having a clear set of goals or objectives when considering participation in an educational program, and ensuring that those goals can be met through that participation (Darkenwald, 1981). 48 Research has also indicated the influence of parents and peers as a motivational factor related to persistence or withdrawal. Parental aspirations regarding the student's education, together with the quality of the relationship between student and parent, is believed to be directly related to persistence (Pantages & Creedon, 1978). Therefore, the students who feel that their parents support the decision to return to school will be more likely to complete the program, especially i f they perceive the relationship between themselves and their parents as a positive one. This is also indicated to be true for the support students feel from their peers. A major difference between studies which concentrate on college or university students and entry level vocational students is the time commitment required by each group to complete the program. Motivational factors may be more important for students in a two- or four-year program than for students taking short-term vocational training. Because the relation between program length and persistence in programs other than part-time adult education courses (Dickinson & Verner, 1967) is not obvious, i t is important to include motivational factors in the study of attrition in entry level vocational programs. Personality Factors. Personality factors relating to attrition have also been extensively studied, but have provided l i t t l e in the way of concrete predictors of persistence or withdrawal. Most studies decking with personality factors are able to typify dropouts as possessing a variety of characteristics—most of them negative. As stated by Pantages and Creedon (1978), most of these studies are done using students who are forced to drop out 49 for disciplinary or academic reasons and, because of this, the results may be different from those obtained involving voluntary dropouts. These investigators point out methodological problems associated with the measuring techniques used with personality tests, and argue that more powerful tests able to discriminate finer differences are necessary before the predictive value of tests of personality factors can be established. Even though the extent to which these factors are related to attrition is questioned, Pantages and Creedon (1978) recognize the potential value of such tests as useful tools for identifying potential dropouts and reducing attrition through intervention programs. Pre-Entry Factors Relevant to Entry Level Vocational Programs. Due to a lack of research directed specifically towards the study of attrition in entry level vocational programs, variables relevant to the research population were selected from adult education and higher education sources. From these sources answers were sought to the following questions: Are previous educational experiences, such as graduation from high school, high school grades, time since previous schooling, kind of previous school program, last grade completed, failing a grade, and/or agreeing with negative comments about previous educational experiences, related to vocational students' decisions to persist or withdraw? Are academic skills and abilities related to vocational students' decisions to persist or withdraw? Are demographic and socioeconomic factors, such as age, job changes, rate of pay, SES of the student or his parents i f he lived at home, and social mobility related to vocational students' decisions to persist or withdraw? Are motivational factors, such as level of commitment, support from family and friends, and long term educational aspirations, related to vocational students' decisions to persist or withdraw? 50 Are personality factors related to vocational students1 decisions to persist or withdraw? Postentry Attrition Factors Postentry factors refer to those students encounter only after they begin their training. Upon entering a postsecondary institution a student is confronted by situations which are considerably different from those experienced in high school or, in the case of the returning adult, from those of work or even unemployment. Because they occur after enrollment these factors are under the influence of the educational institution and tend to be those concentrated on by individuals attempting to reduce attrition. Academic Factors. Study habits and fir s t semester grades are included as postentry academic factors. Dropouts more often indicate their study habits as poor, whereas persisters indicate that they spend more time studying than the average student (Pantages & Creedon, 1978). Good grades early in the semester are indicated to be extremely effective in reinforcing, maintaining, and strengthening academic performance, and in reducing dropout potential. : Not a l l entry level vocational students graduate from high school. Their failure to obtain their high school diploma may be due in part to a lack of study skills. While the prerequisites for entry into college or university would guarantee a certain minimal level of study skills in higher education populations, the same, cannot be said for students in the research population. In addition, due to the practical nature of the training, the study skills required by vocational students may be different or 51 not as important as those required by more academic students. The existing research on higher education populations fails to consider these differences. Motivational Factors. The "quality" of the company one keeps while a student is believed to be a motivational factor related to decisions to remain in school or withdraw (Pantages & Creedon, 1978). Having a group of friends within the institution and gaining satisfaction from these relationships, plus the attitude of that group towards the institution and the value of education, can influence student decisions. Satisfaction or dissatisfaction is also believed to be influential in decisions to persist or withdraw. As pointed out by Lenning, et al. (1980), the decision to persist may be related more to a willingness to endure dissatisfactions, but satisfaction itself is probably more closely related to persistence. Darkenwald (1981), in his discussion of the goals and objectives of adult education participants, indicates that satisfaction probably depends primarily upon the students' perceptions that the program is delivering the anticipated benefits which led to their i n i t i a l decisions to participate. Having school friends would likely add to students' general feelings of satisfaction with their participation in training. In addition, being satisfied and having friends would be part of a l l the factors which determine whether the student feels a part of the social environment of the campus. This idea y£ "fitting in" is mentioned by a number of researchers (Boshier, 1973; Pantages & Creedon, 1978; Tinto, 1987) as related to decisions to persist or withdraw. Again, as stated previously, the length 52 of the program may influence how strongly motivated a student needs to be to persist to completion. Because entry level vocational programs are shorter than the programs from which the research on motivational factors was gathered, i t would be of value to include these factors in the present study to see i f the results differ. Financial Factors. Financial factors also play an important part in decisions to persist or withdraw. The relation between money and persistence is obvious: students drop out i f they no longer have and cannot obtain the financial resources required to remain in school. Research on the subject indicates that concern regarding finances increases withdrawal potential (Lenning et al., 1980). Loans, especially large loans, contribute to attrition, whereas scholarships and grants increase persistence. Employment while in school, i f less that 25 hours per week, is also indicated to be related to persistence, whereas full-time work contributes to dropout (Sexton, 1965; Pantages & Creedon, 1978). Work, especially i f i t is on campus, is helpful in promoting persistence. Vocational students have a mix of financially related characteristics. Some are sponsored while attending and others incur debts from large student loans. Some work a forty hour week while s t i l l being classified as a full-time student. Because of this variety, together with the lack of research aimed specifically at tii'i-s kind of program, i t is important to include financial factors when examining attrition in entry level vocational programs. Institutional Factors. Whether a student decides to complete a program, or to withdraw prior to completion, is influenced to a major extent by the institution itself. As stated by Pantages and Creedon (1978), i t has been only in the last 15 to 20 years that the student/institution relationship has been considered important enough to warrant examination. The concept of f i t between student and institution is rapidly becoming a major area of investigation. Institutional factors include such things as accommodation and student services. Research indicates that, similar to working on campus, living on campus is related in a positive way to persistence. Residence living is believed by Pantages and Creedon (1978) to increase persistence due to the socialization process in which participants more readily adopt the role of student. A similar socialization process is not as evident in students who leave the campus every day to return to a world which does not revolve around the school and the related l i f e style. Student services such as counselling services, academic advising, and learning assistance centers have also been shown to be positively related to persistence (Lenning et al., 1980). The important factor is whether students make use of these services. Usage depends upon i f and how the students are made aware of available services. In addition, the quantity and quality of student/faculty, student/staff relations is related to persistence (Pantages & Creedon, 1978). Research also indicates that students are more likely to persist i f they feel they are more alike than different from their fellow students. The social background of fellow students including such factors 54 as size of home town, religion, and race, are considered important components of this feeling (Lenning et al., 1980). Postsecondary institutions delivering vocational programs are not unlike those in which the research on f i t , accommodation, student/faculty or student/staff relations, and student services were studied in relation to attrition. Any differences would be the result of the length and nature of the program offerings. This does not, however, limit the possible impact that the Institute has on influencing the persistence or withdrawal of vocational students. Postentry Factors Relevant to Entry Level Vocational Programs. As a result of the review of the literature on attrition from higher and adult education, examined in the context of short-term vocational programs, the following questions remain to be answered: Are academic factors, such as entrance examination scores, study habits and early program performance, related to vocational students' decisions to persist or withdraw? Are motivational factors, such as evaluations of the benefit received from the program, willingness to recommend the program and/or Institute to others, and evaluation of the success of the program, related to vocational students' decisions to persist or withdraw? Are financial factors, such as concern regarding the adequacy of finances, amount of student loan, sponsorship, and hours worked while taking training, related to vocational students• decisions to persist or withdraw? Are institutional factors, such as accommodation, student services, student/instructor relations, " f i t " , and having friends in the program, related to vocational students' decisions to persist or withdraw? Conclusions From Higher Education Attrition Research Even though more attrition/retention research has been done 55 in higher education than in adult education, some of the criticisms directed towards the latter could also apply to the former. Although studies such as Astin's (1975) are addressing the need for large representative samples, sophisticated research designs and data analysis, the identification of potential dropouts s t i l l lacks the accuracy and reliability necessary to make i t a useful tool for retention programmers. In Tinto's latest book, Leaving College—Rethinking the Causes and  Cures of Student Attrition (1987), he departs from what has been written on the subject of attrition. His approach differs in the way in which he examines similar studies and uses their sometimes conflicting results to uncover basic flaws in the way in which researchers have viewed the phenomenon of withdrawal. In examining the definitions used by researchers in the study of similar factors he points out how assumptions about the commonality of these definitions have resulted in conflicting findings. For example, in studying the relationship between ability and dropout, there is obviously going to be a stronger relationship when examining students who were withdrawn for academic failure than there would be when studying those who withdrew on a voluntary basis. Students who choose to withdraw are often found to have ability levels more than adequate for success in college. By combining these two groups, studies which f a i l to define withdrawal in terms of voluntary and involuntary OEfi-y serve to conceal the relationship found between ability variables and withdrawal. Tinto's case for clarifying definitions is further advanced in discussing the difference between institutional departure 56 (i.e., transferring to another institution) and system departure (i.e., leaving the postsecondary system altogether): The two are frequently treated as i f they are the same. It is not uncommon, for instance, for researchers to employ one definition of departure in attempting to study what are two different types of behavior. . . . Though their data and definitions do not focus on institutional departure, they argue, by implication, that analyses of aggregate patterns of system departures [from multi-institutional studies] can illuminate the character of institutional departure. Regrettably, this is not the case. Results of the former type of leaving cannot be used to study the latter. While i t is true that such multi-institutional studies can be quite revealing of the aggregate patterns of departure from the enterprise as a whole and of the manner in which individuals and institutional attributes may be associated with those patterns, they are of l i t t l e use to either researchers or policy planners concerned with the character and roots of student departure from specific institutions of higher education (37-38). Tinto (1987) also addresses another of the criticisms common to attrition research in both the adult and higher education literature: the lack of unifying theory. In his book he further develops the conceptual model fi r s t discussed by him in 1975, Described as a longitudinal model he states that i t ". . . seeks to explain how interactions among different individuals within the academic and social systems of the institution lead individuals of different characteristics to withdraw from tha-tj institution prior to degree completion" (113). Using Van Gennep's (1960) study of the rites of passage in tribal societies and Durkheim's (1951) theory of suicide, Tinto's model represents th$ educational institution as a separate society and successful participation as the transition from membership in the former society (family, high school, community) to membership in the intellectual and social society of the college. Withdrawal, on 57 the other hand, is seen as similar to suicide in that both are forms of voluntary social withdrawal. Although he states that what goes on inside the society (e.g. postentry factors) has a greater influence on persistence or withdrawal, he acknowledges that what the individual brings into i t (e.g. pre-entry factors), to a great extent, determines how he will react to the stress associated with this transitional process. Tinto's contribution to the knowledge about why people leave college or university programs is significant to the present study. The idea of failing to make the transition to the role of student because that role is seen to be foreign to the perception of one's present membership (family, culture, profession) draws together and gives form to similar concepts from other research (i.e., "congruence", " f i t " , "participation"). Because, for example, high school dropouts do not appear to assimilate well as members of the of the high school's social environment (Self, 1985), they may have similar problems accepting and feeling part of the norms, purposes and philosophy of the postsecondary institution. However, by examining the attrition phenomenon from a wide perspective, differences which may apply to particular subgroup, such as vocational students, are lost in the breadth of his approach. Similar to that found in the review of attrition research from adult education, higher education research was also evolutionary in its development. From an awareness of the phenomenon, to its description, to the search for related factors and the development of theories to explain their relationships, and then, to the application of theory in the development of 58 retention p r a c t i c e s , a t t r i t i o n research slowly developed into i t s present form. The ultimate evaluation of t h i s research w i l l be the impact that i t has on solving a t t r i t i o n problems. In the f i n a l analysis, the extent to which higher education research provides answers to the questions asked i n t h i s study i s s i m i l a r to that found by reviewing the adult education l i t e r a t u r e . Because of the differences i n the populations and programs i t i s not possible to apply without question the findings from one to the other. The contribution that the findings from adult and higher education make i s one of d i r e c t i o n . Rather that approaching the s e l e c t i o n of a t t r i t i o n factors f o r a p p l i c a t i o n to vocational populations i n a random fashion, an i n i t i a l survey of the related research enabled a more focused approach. In addition, these findings provided some insi g h t to the methods available for the design of the study and analysis of the data. Secondary Sources of Research on the Study of A t t r i t i o n In addition to adult and higher education research, which includes the major portion of a t t r i t i o n studies, there are other sources of research relevant to entry l e v e l vocational programs, These include studies on adults i n vocational programs, studies from high school, and the research on adults' self-confidence as learners. This research i s examined i n the following sections with the intent of i d e n t i f y i n g additional a t t r i t i o n factors for i n c l u s i o n i n t h i s study. Adult Vocational Education Adult vocational education, as described here, ref e r s to postsecondary programs of l e s s than one year duration, serving adults and out-of-school youth, and designed to provide entry level skills in a skilled or semiskilled occupation. As indicated previously by Gates and Creamer (1984), although a part of higher education, adult vocational education has been virtually ignored in studies of student attrition. A number of possible reasons explain this lack of research. Most attrition studies done at the college level do not use "program1' as an independent variable and, therefore, include rather than separate vocational students from the rest of the student population. For example, when vocational students were examined separately i t was found that as a group their attrition rate was lower than that of the academic students (Gates and Creamer, 1984). The source of much of the college-based research can also explain this lack of research, Vocational instructors, especially at the college level, are selected for their vocational expertise rather than for their academic qualifications as educators. This lack of university training results in fewer studies being undertaken as part of graduate programs by this group of educators. In addition, research in the field of vocational education leans heavily towards curriculum development (e.g., Competency-Based Vocational Education), rather than towards administrative studies, which further excludes attrition as a research topic. In Canada, the lack of attrition research is compounded by the perception common among community colleges that research is an activity pursued at universities and has no role to play ii> the day-to-day operations of the college. Fortunately, this attitude is changing as is pointed out by Dennison and Gallagher (1986). When they asked college personnel from across Canada to 60 respond to the question "What are the aspects of your college (or college system) for which research studies are most needed at this time?" (268) the respondents identified 103 questions categorized under twenty separate topics. From this research agenda i t is interesting to note that attrition was addressed. The research priorities, however, were primarily concerned with the prediction of success in postsecondary education, the prediction of success in various college programs, the development of valid student selection criteria, and the identification of precollege experiences which are related to college success. Dennison and Gallagher's findings seem to indicate that a means of predicting persistence or withdrawal from college programs would be used primarily to screen out those students lacking certain characteristics, and not as a means of identifying students in need of extra assistance. The High School Dropout Low educational attainment is synonymous with high school dropout. Because entry level trades training provides an opportunity for high school dropouts to enter postsecondary programs, a logical step in the examination of attrition is determining whether characteristics which identify high school dropouts subsequently identify them as postsecondary dropouts. In other words, do high school dropouts possess certain characteristics which perpetuate an inability to complete educational programs? A multitude of studies have been conducted on what characterizes potential or actual high school dropouts. Results from this research consistently identify sets of student 61 characteristics related to dropout. As outlined in Self's (1985) review of the literature published between 1975 and 1983, potential dropouts are identified by the following characteristics: — Poor academics — Poor reading ability — Dislikes school — Participates less often or none in extracurricular activities — Parents pose low educational achievement (Many are dropouts themselves) — High grade retention — Discipline problems — Low family socioeconomic level — Broken homes (Physical and emotional) — Poor self-concept — Inadequate goals and low aspirations — High absenteeism (13) An indication of the effect previous educational experience has on subsequent attempts is evident in the Youth in Transition project (Bachman, Green & Wirtanen, 1967). This study followed a group of young men from the end of ninth grade to five years after their graduation from high school. In describing the relationship between an individual's high school and post high school educational experience the authors state that "past educational success or failure proved to be a most important predictor of future educational attainment . . . " (74), adding that, "self-concept of school ability, self-rating of hard work in school, stated interest in course work, and other attitudes toward school" (74) are similarly related to one's post high school educational experience. In other words: When i t comes to school performance, i t appears that nothing succeeds like success—and nothing predicts to future success better than past success. The negative side of the equation holds equally well—the boy who has been held back a grade, who brings home poor report cards, and who holds a low opinion of his scholastic 62 ability is the one most likely to drop out of school (58) . Differences in attitudes towards school are also indicated by this study with "the lowest rate of college entrance and the highest dropout rate occur[ing] among those who agreed with negative statements about school 'Pretty much' or 'Very much1" (67) . This description gives form to a profile of the low educational attainment individual. A reasonable hypothesis is that high, school dropouts' last contact with education produced a negative perception of school and of their ability as learners. The distinction drawn here between the terms "student" and "learner" is important. Whereas society's definition states that as a high school dropout one was unsuccessful as a high school student, this may be interpreted by the low educational attainment individual as a statement regarding his or her failure as a learner. This researcher believes that this has a negative impact upon subsequent educational participation and persistence. In summary, a profile of low educational attainment individuals, based upon characteristics of high school dropouts, gives credence to the belief that they lack self-confidence in their ability as learners. A reasonable hypothesis is that this lack of learner self-confidence negatively influences participation and persistence in further education. This hypothesis is supported by Prefontaine's (1980) study in which he examined the behavioral manifestations of self-confidence. His findings indicated a direct relationship between lack of 63 self-confidence and low educational attainment. The High School Vocational Student Even though they graduate from high school, vocational students differ from those in academic programs. As stated by Weber and Silvani-Lacey, "frequently, potential dropouts are culled from academic programs and placed in vocational programs based on the assumption that students who are unsuccessful in academic pursuits will find vocational subjects more relevant and more manageable than academic subjects" (1983: 1). Vocational programs at the high school level also provide an alternative to academic programs for students not planning to attend college or university. As a separate population, high school vocational students f a l l between the thirty-fifth and fortieth percentiles on standardized tests of basic skil l s . This places their basic skills at a level significantly lower than that of students in academic programs. Weber and Silvani-Lacey (1983) go on to report that preliminary studies comparing basic s k i l l scores of vocational and nonvocational high school students indicate that academic dropouts are similar to vocational persisters and that vocational dropouts have scores which are considerably lower. These results indicate that even though high school vocational students are graduates, they exhibit academic achievement characteristics similar to academic dropouts. This may provide a m^ ans of separating academic achievement from other factors associated with dropout. Comparing factors other than academic achievement for vocational persisters and academic dropouts may help isolate the part these factors play in 64 postsecondary attrition. Learner Self-Confidence Although mentioned as a factor related to attrition in adult education research (Darkenwald, 1981; Londoner, 1972; Fisher, 1969), self-confidence, as i t relates to the returning adult's belief in his ability to succeed, has never been adequately defined. Undefined i t remains unmeasured and, therefore, its inclusion as a factor related to attrition is dependent first upon its definition, followed by the selection of a way to measure its effect. Self-confidence, as i t relates to learning, can be defined by applying a general definition of the term within an educational context. As stated by Burke (1983), " self-confidence indicates the degree to which the individual's progress toward a goal was attributed to a combination of personal ability or power (i.e., can) and effort (i.e., trying)" (84). In referring to work done by Heider (1958), Burke (1983) goes on to explain that, the construct 'can* refers to an interaction between the individual and the environment. That is, different types and degrees are necessary to overcome the restraining environmental force(s) in any given situation. Thus, self-confidence, as herein used, is not a unidimensional construct. Rather, i t reflects these two subordinal constructs of 'can' (i.e., ability versus environmental restraints) and 'trying' (i.e., stable and unstable patterns of effort) (84). If, in considering the adult learner, the successful completion of the educational activity is seen as the |roal, then learner self-confidence can be described as the degree to which the learner attributes success to a combination of personal ability, or power and the effort expended. Conversely, i t would 65 be logical to deduce that the individual who attributes the outcomes of the educational activity to external factors (i.e., factors other than power or ability) would be convinced that effort would have l i t t l e to do with his success or failure. For the low educational attainment individual, because of previously demonstrated experience of inability as a learner (i.e., as a high school dropout), effort would assume limited importance in the above can/try relationship. This concept of self-confidence was examined by Coleman in 1966. He found that a feeling of control over one's destiny was correlated with school achievement. His findings were "confirmed and extended" by the Youth in Transition study in which i t is stated that: a feeling of personal control is one of the factors that predicts to later educational attainment. Long before the events actually occurred, those destined to drop out indicated below average feelings of personal efficacy, while those bound for college were above the average (Bachman, et al. 1967, 78). Similar results were mentioned by Rolfe (1979) with regard to adult students taking a high school completion course. Using the Adjective Check List he found that the self-description of dropouts indicated a "general tone of malaise and resignation to l i f e , " stating that "their lives are disorderly and that they have a limited repertoire of resources and responses to bring to situations" (10). This general feeling of "powerlessness" was not evident in the self-descriptions given by persisters. In summary, what this description of self-confidence indicates, with regard to learners, is that individuals having confidence in their ability as learners attribute success or 66 failure in educational activities to internal characteristics (i.e., a belief in their power to influence the outcome of the activity through a combination of ability and effort). Conversely, those who lack confidence in their ability as learners attribute their success or failure to external environmental factors, therefore, seeing l i t t l e relationship between effort and success. Determining the relationship between learner self-confidence and the persistence of low educational attainment students requires some method of measuring this construct. Because i t closely parallels Burke's conceptualization of self-confidence, locus of control, as operationalized using Rotter's I-E Scale, is believed to provide such a measure. The concept of locus of control or internal/external control is an integral part of Rotter's Social Learning Theory which is defined by him as a "molar theory of personality" (1966, 267), and which "in its most basic form . . . [states] the potential for a behavior to occur in any specific psychological situation [is] a function of the expectancy that the behavior will lead to a particular reinforcement in that situation and the value of that reinforcement" (267). The part that internal/external control plays in this theory pertains to the expectancy for reinforcement, and the way an individual perceives influence over i t . Rotter (1966) explains the relationship as follows: When a reinforcement is perceived by the subject -as following from some action of his own but not being entirely contingent upon his action, then, in our culture, i t is typically perceived as a result of luck, chance, fate, as under the control of powerful others, or as unpredictable because of the great complexity of the forces surrounding him. When the event is interpreted in this way by an individual, we have 67 labeled this a belief in external control. If the person perceives that the event is contingent upon his own behavior or his own relatively permanent characteristics, we have termed this a belief in internal control (1). Expectancies are determined by experience in a particular situation, as well as in situations perceived by the individual to be similar. Obviously, also of importance in determining behavior is the nature of the reinforcement and its perceived value. The significance of social learning theory as a means of explaining and predicting human behavior is perhaps best indicated by the extent to which the concept of locus of control has been used since the early 1960's. Published articles alone amounted to more than 600 by 1975, a figure which does not include a l l the unpublished articles, theses, and dissertations which have, in some way, also dealt with locus of control (Rotter, 1982). Even with this mass of data, however, conflicting results remain with regard to those variables to which locus of control has been compared. In this study, the concept of locus of control is of primary concern because i t relates to those factors which influence persistence in entry level trades training. Factors such as academic achievement, educational level, and those conditions antecedent to individual differences in locus of control are of interest due to the possible influence they have on secondary and postsecondary school performance. For example, as stated by Phares (1976), the majority of research supports the relationship between internality and higher levels of academic achievement even though the relationship is stronger for 68 children than for young adults. Phares' statement is supported by a nationwide study by Ekstrom, et al. (1986) in which an externalized locus of control is identified as a causal factor of potential dropout for high school sophomores. Persistence in educational activities has also been examined using locus of control as a predictor variable. In a study of students drawn from a population and program similar to that used in this study, Altmann & Arambasich (1982) indicated a correlation (contingency coefficient = .23, p = .05) between locus of control and attrition, with those indicated as externals being more likely to drop out. Even though locus of control accounted for only five percent of the variance in attrition, this may have been due to a mixing of male and female subjects in the research sample. Because women in achievement situations tend to lack self-confidence in their ability (Lenney, 1977), and as internality tends to be a factor in achievement settings for males and not females (Feather, 1968; Feather & Simon, 1971), these results may indicate a possible less than true correlation due to the moderating effect of the mixed sex sample (Phares, 1976). A similar conclusion was suggested by Levitz (1981) when his predominately female sample of students failed to support the hypothesized relationship between locus of control and persistence. Using an a l l male sample may result in the percentage of variance attributed to locus of control being higher than that found in mixeS sex studies. Conclusion Unlike higher, secondary, or even adult education, adult 69 vocational education has a limited base of attrition research on which to draw. This is not a major handicap, but necessitates the borrowing of factors found related to attrition from sources other than adult vocational education. This also means that until more research is done and confirms, for example, that single factors do not account for major portions of the variance, or, that particular research designs or statistical techniques have limited value in the study of attrition, that a certain amount of flexibility in the choice of variables and methods is appropriate. For example, attempting to s i f t through, select, and determine how a multitude of factors relate to an individual's decision to withdraw, or trying to use these functions to predict dropout, in a way that is generalized across institutions, may not be practical. This practical consideration is perhaps a major reason why few attempts have been made to apply prediction "formulas" to more than one institution at a time. To add institutional differences to an already complex set of predictor variables, for the sole purpose of being better able to generalize results across institutions, would have l i t t l e value for the practitioner seeking only to identify students in jeopardy of dropping out. Only after the research establishes that in the study of attrition the similarities between adult vocational education and other fields of education are greater than the differences, can the refingsBnt of theory and technique, and the application of prediction across institutional boundaries begin. CHAPTER III RESEARCH DESIGN AND PROCEDURES This chapter provides the blueprint by which the study was conducted. It includes a description of the selection of the research site, describes how the research sample was selected from the population, what Institute data were selected and how they were gathered, outlines the design, testing, and administration of the survey instrument, and describes the data analysis methods. First, the evolution of the provincial Training Access (TRAC) program is described and a rationale is developed for the selection of Pacific Vocational Institute (PVI) as the research site. PVI is then examined from a historical perspective and TRAC, as i t operates at PVI, is described. This is followed by a description of the population and the rationale and justification for the selection of the research sample. Following the description of the study site and sample selection, the reasons for the selection of the research design are examined. This is followed by an explanation of the methods used for collecting data from students1 Institute records. Finally, the design and testing of the survey instrument are described and the administration of the instrument and collection and analysis of data are explained. Research Environment In British Columbia, entry level trades training is offered primarily through the Training Access (TRAC) program. TRAC is a relatively new program which began in January of 1983. Prior to its inception, this kind of training was delivered through two 71 programs: Preapprenticeship and Pre-employment. The development and introduction of TRAC was a province-wide response to the proposed cancellation of the Preapprentice program by the provincial government. Funding for development of the new program was provided through the Cabinet Committee on Employment Development, which mandated that the new program provide "greater access to training; ability to vary employment goals; assured quality of graduates; individualized, self-paced curriculum; year-round entry; transferability; articulation; decreased costs; [and] increased number of students" (Kava, 1983: 2). To better attain these goals, the new program was designed to incorporate a competency-based approach. Similar to that which i t replaced, TRAC had a mandate to provide entry level training to people interested in a career in the trades. The major difference between TRAC and the Preapprentice program was in the means of delivery: the Preapprentice program utilized a traditional, instructor-driven approach in which sixteen students were taught theory and shop as a group. On the other hand, TRAC was developed utilizing a modularized, competency-based approach designed to be student driven. TRAC provided continuous intake and exit, allowing students to stop out for employment or other reasons, and was self-paced to permit people to move through the course requirements at a rate which best suited their particular needs. It was also modularized to provide bite sized pieces of knowledge within. a framework consisting of three major divisions: Common Core, Occupational Core, and Specialty. Being competency-based i t was structured around a format having 72 learning objectives, a criterion for competence, and credit for previous training or work experience. Segments of Common Core were completed by a l l students (except those in Horticulture), and provided basic knowledge and skills common to a l l trade areas. Modules on safety, math and science, drafting, communications, measurement and layout, basic hand and power tools, rigging and work platforms, gas welding, basic electricity, common fastening methods, materials, business methods, and job search techniques were included. The Occupational Cores: Mechanical, Carpentry/Joinery, Millwright/Machinist, Horticulture, Piping, Autobody, Metal Fabrication, and Electrical provided knowledge and skills common to the trades included in each occupational family. For example, the Metal Fabrication Occupational Core included the welding skills required by ironworkers, boilermakers, sheet metal workers, and steel fabricators. The Specialty was the final part of the program and provided the specific competencies required for i n i t i a l entry into one of twenty-two trade areas. TRAC's course content was organized into modules containing a variety of "competencies" representing the knowledge or skills necessary to master a specific task. Learning Guides provided the information and/or direction needed for the acquisition of knowledge, and demonstrations and practice sessions aided in the development of practical ski l l s . After familiarizing themselves with the information in a Learning Guide, viewing a demonstration, and practicing a particular s k i l l , or, i f students felt they had previously acquired that knowledge or s k i l l , they attempted the theory or practical "challenge" (i.e., 73 test). A performance criterion was set for each challenge, and "competence" (i.e., mastery) was attained only i f i t was met or exceeded. Failure to meet the performance criterion indicated to the student that more study or practice was necessary to attain competence. Attempts were made by the student until competence was achieved. Site Selection TRAC is offered at fourteen community colleges and institutes throughout British Columbia. In selecting one or a number of these institutions as a study site certain factors were considered. One option was to limit the study to an examination of factors which are related to persistence/withdrawal in one Specialty. This approach, however, would restrict the size of the population and thus the sample would be similarly small. This lack of student numbers would limit the options available in the choice of statistical methods. In addition, unless "program" as a variable could be controlled for, some of the findings may be confounded by the selection of, for instance, Automotive students as opposed to Carpentry students. Therefore, one of the selection criteria needed to be the inclusion of both a large variety of Specialty offerings and a large student enrollment. Another consideration was the different entrance requirements at the various institutions for students applying to begin the TRAC program. Because the skills that the students brought to the program were believed to be related to persistence or withdrawal, i t was felt that a sample of students having a wide range of s k i l l levels would better illustrate the strength of this relationship. Because some colleges and institutes required prospective TRAC students to write and pass a pre-entry test in reading and math skills, i t was deemed important to select a site which subscribed instead to an open access philosophy under which testing was not used to screen out students. The final criterion in the selection of a research site was the need to be granted access to confidential student records. Even though the intent of the study was to examine group as opposed to individual data, public institutions are obviously concerned about having an outsider examine their fi l e s . Because a l l of the data necessary to complete the research were of a confidential nature, i t was necessary to choose a site where the researcher would be granted permission to move freely within the student information system. Of a l l the sites considered, the one which most precisely f i t the selection criteria was Pacific Vocational Institute. Because i t offered a l l of the twenty-two possible Specialties and had a large enrollment (1330 students, 1984-1985), i t satisfied both the need for a variety of programs and a large enrollment. In addition, although PVI also tested students, i t did so only for diagnostic purposes after they had been accepted and had started the program. The results of these tests illustrated that PVI's TRAC students were indeed a heterogeneous group. Finally, the researcher had b e e n employed by PVI as a Training Consultant for the TRAC program since October 1, 1984. This enabled him to solicit support for the proposed research and therefore gain permission to have access to students1 75 records. Permission to conduct research was applied for and granted by the acting Institute president (see Appendix A). Over and above the extent to which PVI f i t the site profile, the convenience of conducting research at an institute where one is employed is an obvious factor in site selection. It reduces the costs inherent in such research and opens doors not usually open to those not employed at that site. But there was an additional consideration which perhaps overshadows a l l other rationalizations: attrition was a problem in the TRAC program at PVI. It was a problem which required facts as opposed to assumptions to bring about a solution. Because educational problems are directly affected by limited educational spending, answers need to be based on facts which will most effectively target the use of limited resources, whether i t would be more effective in reducing attrition to restrict entry to the TRAC program or, alternatively, to identify and help TRAC students most in need of extra assistance was that kind of question. Setting and Subjects PVI, situated in Burnaby, British Columbia, Canada, began in I960 as the B.C. Vocational School (Burnaby), one of a number of similar postsecondary vocational schools throughout the province. In 1977 its name was changed to the Pacific Vocational Institute and on April 1, 1986, PVI was amalgamated with the British Columbia Institute of Technology (BCIT) with which i t had shared the same Burnaby location since 1964. The name, "British Columbia Institute of Technology", was retained following the melding of the two institutes. Since its ' 76 inception, PVI's mandate had been the delivery of vocational programs at the entry, apprentice, and postapprentice levels. At PVI, students were admitted to the TRAC program every Wednesday. By means of a two-day orientation period, students were familiarized with the program, gradually establishing a schedule and rate of progress that suited their rate of learning, their work, and their family obligations. Tuition covered a year of training which, considering the anticipated time necessary to complete the program (ten months for the longest specialty), provided considerable flexibility in the way the program was completed. Although the program was, to a considerable extent, self-paced within the period covered by the tuition, certain expectations regarding performance were stated to the students. A computerized monitoring system calculated weekly what each student had accomplished. If expectations were not met, a series of steps were taken to assist students in meeting these requirements. These steps may include visits to a Training Consultant for counselling, referral to the Developmental Studies Center for remediation, or referral to other departments or agencies for specialized assistance. Unsatisfactory performance could lead to dismissal i f a student failed to cooperate in meeting performance requirements. Other colleges which offered the TRAC program throughout the province required students to complete an entrance exam, the results of which determine acceptance into their program. PVI's approach to student selection was significantly different from this: grade ten was set as a recommended prerequisite, but entry was not barred to those having lesser educational qualifications. This open door policy, together with PVI's TRAC program being the largest in the province, resulted in a student population having a wide variety of educational backgrounds. Educational qualifications ranged from grade eight up to completion of university degrees. Between the time TRAC began at PVI (January, 1983) and when the last TRAC student was admitted prior to the implementation of a major reorganization of the program beginning in May, 1986, 5990 students had enrolled. Population and Sample Because this study focused only on student variables as potential predictors of persistence/withdrawal, the program itself was purposely not included as a related factor. As a new and innovative program, TRAC experienced a number of modifications and changes when i t first began. Attrition in any educational or training program is due partly to the program itself. Consequently, the timing of an attrition study is crucial: program variables could overshadow students' decisions to persist or withdraw, thereby concealing subtle, individual differences influencing attrition. When the decision was made to cancel the Preapprentice program, the target date for the implementation of its replacement (TRAC) was set as January 3, 1983. The TRAC implementation project began on June 1, 1982 leaving only seven months for development prior to start-up. A direct result of the time constraint imposed upon the development project was a subsequent break-in period after which the program evolved into its final form. To describe a l l students who began PVI's TRAC program between January, 1983, and 7 8 May, 1986, as members of a single population would, due to the i n i t i a l state of the program, ignore the influence that differences within the program had had on students' decisions to persist or withdraw from training. On September 19, 1984, two significant events occurred which, together with the ongoing improvement of the learning materials, had a major effect on reducing "the program" as a primary attrition factor. These changes included the implementation of a computerized system to monitor student progress (so that needed assistance could be provided to those falling behind) and, the appointment of a new Director. Although s t i l l evolving as a program, these changes ushered in a period of stability which lasted from September 19, 1984, until the last students entered TRAC on May 6, 1986. This period was characterized by a slowly but steadily declining attrition rate which dropped from 64.5 percent to 54.0 percent during this 19 month period. Because of the program changes experienced by students prior to September 19, 1984, the research population was defined by this date rather than the January, 1983 date when TRAC began at PVI. Therefore, the research population included the 1473 male students who enrolled in PVI's TRAC program (Bumaby Campus) between September 19, 1984, and May 30, 1986. Students who enrolled in Horticulture were excluded from this study because this particular specialty does not include the COiiuaon Core, a bench mark in the measurement of student performance. Female students were also excluded from the research population. Because locus of control, used to measure learner self-confidence, was found to be sensitive to sex differences (Feather, 1968; Feather & Simon, 1971; Phares, 1976; Lenney, 1977) women were excluded from this study to prevent any possible weakening of this variable's predictive power. Because women accounted for less than two percent of the total student population, their exclusion had l i t t l e effect on the practical value of the outcomes of the research. From the defined population, a research sample (N=634) was selected which included a l l male students who entered the program between April 24, 1985, and October 23, 1985. The sample was selected to coincide with the fi r s t six months of assessment testing when sections of the Canadian Achievement Tests (CAT) were administered as part of the i n i t i a l student orientation process. Students included in the research sample were not selected randomly from the population, but were selected as members of a six-month cohort from the 19 months of student intakes which made up the research population. Because important data such as CAT test results and locus of control (I/E Scale) scores were not available for a l l members of the population, and because sample members had to be given enough time to complete or at least attempt Common Core, random selection would have resulted in the inclusion of students lacking CAT test scores and I/E Scale scores as well as student who had just started the program and who had not hau time to complete any of the Common Core. Because random selection was not used, tests were conducted to determine i f sample students differed significantly from members of the research population. 80 The similarity between the sample and population groups was demonstrated by searching for information available on those students who began the program before or after the sample students, and by comparing these data with similar data gathered for the sample. For the 504 students who began the TRAC program between September 19, 1984, and April 17, 1985 (before the sample group), the only readily available data were their ages on the date they started the program. In addition to this information, for those students who began between October 30, 1985, and April 30, 1986 (after the sample group), CAT scores were also available. Table 1 compares ages of the sample students, and those entering the TRAC program either before or after the sample students. Selecting p < .05 as the probability level, a significant statistical difference was found to exist between the mean ages of those students entering the program between September 19, 1984, and April 17, 1985, and those entering between October 30, 1985 and May 6, 1986. In other words, even though the mean ages of the sample students did not differ from those who came before or after them, the before and Table 1 Ages of Presample, Sample, and Postsample Students: A Multiple Comparison (Scheffe) of the Means of the Three Groups  Groups n Mean S.D. Before Sample Sample After Sample Before Sample 458 21.71 5.42 — — — Sample 568 22.35 6.10 — — — After 332 22.99 2.02 * — — Sample •Denotes pairs of groups significantly different at .05 level after sample groups were different from each other. Over the 19 month period the entry age of students increased. 81 Table 2 compares the CAT scores for Reading Vocabulary, Reading Comprehension, Reference Skills, Math Computation, and Math Concepts and Applications between the sample group and those who entered the program after them. These results indicate that no significant statistical difference existed between the two groups when comparing their mean scores on the Reading Vocabulary, Reading Comprehension, and Reference Skills tests. Both groups were drawn from the same population. Differences, however, between the mean scores of the two groups on the Math Computation and Math Concepts and Applications tests were statistically significant. Taken in isolation, this appears to Table 2 CAT Results of the Sample and Nonsample Groups: A Comparison of the Means for the Two Groups  n Mean S.D. t df P Reading Vocabulary Sample 592 24.45 5.23 -0.32 903 .75 After Sample 313 24.56 5.16 Reading Comprehension Sample 591 29.27 6.73 0.84 902 .40 After Sample 313 28.87 6.61 Reference Skills Sample 591 18.75 3.56 -0.14 901 .89 After Sample 312 18.79 3.92 Math Computation Sample 598 27.62 8.42 2.94 931 .01* After Sample 335 25.90 9.01 Math Concepts and Applications Sample 598 33.23 8.35 2.29 932 .02* After Sample 336 31.89 9.02 *p < .05 82 indicate that the two groups were drawn from different populations: one having a higher level of math skills than the other. These differences in the mean scores amount to 4.3 percent on Math Computation and 3.0 percent on Math Concepts and Applications in favour of the sample group. Those students who started TRAC after October 23, 1985 had poorer math scores. Following the last intake of students included in the sample, the researcher no longer administered testing. Because the I/E Scale was not administered to nonsample students, the testing schedule changed. The most significant change was the combining of both reading and math testing on the same day. Rather than completing the math tests on the following morning, "after sample" students wrote them in the afternoon following the reading tests. Because this made for a rather rigorous schedule, the difference in the test score means was more likely the result of fatigue than a population difference. Taken in total, the results of these analyses seem to justify the belief that the research sample was representative of the population. This, in turn, justifies drawing conclusions based upon sample data and generalizing to the population. From a strictly statistical point of view, because i t was not possible to select sample members at random, i t may be argued that the 634 TRAC students who entered the program between April 24, 1985 and October 23, 1985 are more correctly defined as simply a group of students believed representative of a larger group. In consideration of this, the use of inferential statistics to draw conclusions about the "population" may be open to question. However, in this research, the terms 83 "population" and "sample" were used in their traditional sense which explains the choice of statistical methods. It is useful to consider this in examining the research results. Data Collection from Institute Sources As stated previously, one of the purposes of this study was to identify factors related to persistence and withdrawal which can be used to predict which students entering the TRAC program are likely to withdraw before completion. In times of limited funding, interventions to reduce attrition must not only clearly define the target group but must also highlight those factors which are most closely related to decisions to drop out. It would make l i t t l e sense to concentrate limited resources on the upgrading of weak mathematics skills i f the lack of reading and comprehension skills were more closely related to decisions by students to drop out. The lack of research directed specifically at the research population suggested that the selection of variables for study be broader than would normally be the case when the research questions were more well defined by previous research. To sort through the large number of variables suggested by attrition research in public, adult and higher education, an empirical study utilizing hypotheses and tests for statistical significance, seemed the best method for making sense from the data. The "correlational method" most closely describes the way in which this study was structured. The emphasis was on prediction as well as the extent to which variables were related. As stated by Borg and Gall (1979), this research design is well suited to studies where previous research is limited or 84 nonexistent. It is, however, acknowledged that i f certain variables were found to be useful in predicting withdrawal, only tentative statements of a causal nature could be made regarding the relationship between the predictive variables and withdrawal. These statements could be clarified by subsequent studies utilizing an experimental design. Basically two research questions guided the design of this study: "In which ways do male students who complete TRAC differ from those who dropout?" and "Can these differences be used to predict, early in the program, which students are in jeopardy of failing to complete?" To answer these questions the adult and higher education literature was searched for variables indicated in previous studies to be related to attrition. Data on these variables were gathered from students' records and from a mailed questionnaire as students in the sample were tracked through the program to completion or withdrawal. Table 3 provides a summary of the variables selected, divided into seven categories: previous educational experience, academic, demographic, motivational, financial, and institutional factors, and locus of control. The source of the data (i.e., survey instrument or Institute records) and how the variable is related to dropout is listed beside each variable, as is the reference for each statistic cited. For example, under Financial Factors, employment is listed as a variable. In this study data on the numi>"©r of hours worked per week was collected using the questionnaire. Finally, in the right-hand column, the previous research (i.e., Lenning et al., 1980) is cited. 85 Table 3 Dropout Prediction: Previous Research Results for Selected Variables and Sources of Data for these Variables  Variable Source: Survey Inst. Rec. Relation to Dropout A.Previous Educational Experience 1.program of study * 2. educational attainment 3. failing a grade (a) 4. grades (b) 5. self-concept of school 6. ability (c) 7. school attitudes (d) 8. rebellious behavior (e) B. Academic Factors 1. academic ability 2. study habits 3. early performance C. Demographic Factors 1. age group 2. j ob changes/year 3. rate of pay 4. social position 5.occupational class 6.social mobility D. Motivational Factors 1. commitment 2. family support 3. peer support 4. educational aspiration 5. satisfaction E. Financial Factors 1. financial concern 2. agency sponsorship 3.employment (5) F. Institutional Factors 1. accommodation 2. student service use 3.instructor contact 4.social similarity G. Locus of Control l.I/E Scale * *(CAT) DOR for non-academic student is 20-25% higher(2) r=. 13 (l) R=.45 (3) (a+b+c)r=.51 (2) (d+e) r=.04 (2) r=.01 (2) <5hrs./wk.=33% DOR i . r . DOR (4) * * * * * * * * * * * * * * R=.51 R=.41 r=. 27 R=. 27 R=. 46 R=. 27 (3) (3) (3) (3) (3) (3) i . r . DOR (4) i . r . DOR (4) i . r . DOR (4) i . r . DOR (4) i . r . DOR (1) d.r. DOR (5) i . r . DOR (6) <2 5hrs./wk.=<D0R on campus=<DOR (4) use = <D0R (5) i . r . DOR (5) i . r . DOR (5) r=. 22 121 Note: Q.= Questionnaire; I.R.= Institute Records; D0R= dropout rate; i.r.= inversely related (to). (1) Anderson and Darkenwald (1979); (2) Bachman et al. (1967); (3) Sainty (1971); (4) Pantages and Creedon (1978); (5) Lenning et al. (1980); (6) Astin (1975); (7) Altmann and Arambasich (1982). 86 Student's Records The tracking of students in PVI1s TRAC program was accomplished through the use of a National Computer Systems Sentry 80 hardware/software package. This system marked and/or recorded the results of both theory and practical tests. For each student, the module number, description, grade, date(s) tested, and number of attempts to achieve mastery were recorded for each competency. In addition to performing this marking and fili n g function, the system also compared each student's progress to the program standard and indicated whether a student was falling behind. Basic personal information such as name, address, phone number, date of birth, start date, enrollment status, and program status were also available as a system option. This system served as the primary source of Institute records, providing data both for the examination of relationships between variables and persistence/withdrawal, and for the classification of students as persisters or dropouts. Age, as a variable, refered to the student's age in years on the date that he began the TRAC program. In other words, i f in comparing the year of birth and the year in which he began the program the difference between the two figures is twenty this will be recorded as the student's age i f the date of birth is before the start date. If the date of birth is after the start date then, in this example, age would be recorded as 19. As I< measure of early program performance, the number of theory and practical challenges (i.e., tests) attempted, and the number that met or exceeded the criteria set for mastery during the f i r s t six weeks of the program were counted and recorded for 87 each student i n the research sample. These data were then converted i n t o proport ions comparing tes t s passed to tes ts attempted, and tes t s on which the c r i t e r i a for mastery was exceeded to t e s t s attempted. Based upon t h e i r enrollment s tatus , as defined by the computer software, each student was placed in to one of two categor ies : pers i s tence or withdrawal. Status 7 i n d i c a t i n g "completed" was recorded as pers i s tence , and Status 5 or 6 i n d i c a t i n g "withdrawal-work" or "withdrawal-other" was recorded as withdrawal. Students whose enrollment status ind ica ted they were s t i l l e n r o l l e d , (therefore ne i ther a p e r s i s t e r nor a dropout) were p laced , by the researcher, in to one of the above categor ies . Th i s dec i s ion was based upon whether the students would complete before the expiry date set when he began the program ( i . e . , 1 year from h i s s t a r t date) and whether the student had cons is tent and recent attendance. Fac tors , such as when he completed h i s l a s t wr i t t en or p r a c t i c a l t e s t , and h i s record of attendance i n the shop, were assessed i n determining h i s s ta tus . For example, given the average time required to complete each of the three sect ions of the program, i t was pos s ib l e to t e l l i f the student would complete before h i s time ran out. I t was a l so pos s ib l e to t e l l i f the student had stopped attending and i f he planned on re turning to complete the program. Canadian Achievement Tests (CAT) On A p r i l 24, 1985 PVI i n i t i a t e d a process of assessment t e s t i n g and remediation for a l l students enter ing the TRAC program. During o r i e n t a t i o n , students were required to wri te the 88 Reading Vocabulary, Reading Comprehension, Reference Skills, Math Computation, and Math Concepts and Applications sections of the CAT (Level 18). Administration of the tests followed directions stated in the Examiner's Manual, Levels 14 - 19, Form A (Canadian Test Center/ McGraw-Hill Ryerson Ltd., 1981), and test supervision was done by the researcher for a l l research sample students. The Canadian Achievement Tests battery was developed and published by the Canadian Test Centre of McGraw-Hill Ryerson Limited of Scarborough, Ontario, Canada. As stated by the authors: The fundamental purpose of the Canadian Achievement  Tests is to provide information to be used in making educational decisions leading to improved instruction in the basic skills. They are designed to measure achievement in the basics of any instructional program: reading, spelling, language, and mathematics (Canadian Test Center/ McGraw-Hill Ryerson Ltd., 1982: 7). As a series of test batteries (Level 12 to 19), the CAT is designed to measure the achievement of students from grades 1 to 12. Although based on the California Achievement Tests, the redesign, standardization, and norming was done in Canada. The norming group was selected from a stratified random sample drawn from a target population, including a l l elementary and secondary schools in Canada in which English is the language of instruction. The test batteries were designed to supply both norm-referenced and criterion-referenced assessment to enable both norm-based comparison and measurement on specific content objectives. 89 Even though not designed specifically for adult populations, the use of the upper levels (18 and 19) of the CAT for criterion referenced assessment seems appropriate (Ayers, 1986). In this regard Ayers goes on to say that basic skills tests such as the CAT are very useful in determining the strengths and weaknesses of individual students in the very skills needed for study in college programs. This applies particularly to students who have been out of school for some time and for students going into programs that are unlike their high school courses (2). The CAT has been used for this purpose in community colleges since 1983. In most cases, i t is used specifically for the selection and placement of students in education and training programs. In British Columbia i t has been used extensively for pre-entry testing of TRAC program applicants, with each college setting cut scores as entrance requirements. At PVI, the CAT was used as a diagnostic tool rather than as a screening device. After the tests were written, the mathematics results were analyzed by a specialist in basic skills remediation, and the student's program was altered to include extra help with those skills where a weakness was noted. Where the CAT results indicated a major weakness in English, students for whom English was a second language were sent to a college for further testing and, depending on the results, either continued in TRAC or withdrew for ESL upgrading. For students with low CAT reading scores, which were not related to English being their second language, upgrading was also recommended. Because they left before actually beginning their training, those students who withdrew for upgrading were not included in the population. The number of students who actually 90 did withdraw for upgrading was small enough, i.e., less than .25 percent of the population, not to have any noticable effect on the results of the study. The CAT results were used in this research as a measure of academic ability similar to the way in which entrance examination scores have been used in previous studies (Sexton, 1965; Pantages & Creedon, 1978; Lenning, Beal & Sauer, 1980). The raw scores for each of the individual test sections as well as for the combined reading and combined mathematics batteries were compared for persisters and dropouts to determine i f a relationship existed between entrance examination scores and persistence/withdrawal. The results of these analyses determined acceptance or rejection of the related research hypotheses. The fact that standardization and norming of the CAT utilized a population different from that chosen in this research restricts the way in which the test data are recorded and utilized. Derived scores such as national percentiles, stanines, grade equivalents, and scale scores are only valid for comparison purposes i f the norming population and research population are similar. Because the purpose for using the CAT was related to the assessment of basic skills (i.e., criterion-based), and not for the purpose of comparison to the norming group (i.e., norm-based), the scores were expressed in raw score form only. Two different, approaches are utilized in the assessment of reliability of the CAT. In the fi r s t the stability of the instrument during repeated administrations under similar circumstances was assessed using the Kuder-Richardson Formula 20 91 f o r the normed sections of the t e s t s . In addition, the standard error of measurement -was also calculated f o r the normed sections. Table 4 gives the raw score means, standard deviations, standard errors of measurement, and results using formula K20 for those sections of the CAT (Level 18) used in assessing TRAC students. A further description of the stability of the test scores through the calculation of test-retest correlations was planned, but these results were not available for the printing of the 1983 Technical Bulletin (Canadian Test Center/McGraw-Hill Ryerson Limited, 1983), which was used by the researcher as the source for reliability data. Table 4 Raw Score Means (X), Standard Deviations (SD), Standard E r r o r s of Measurement (SE), and KR 20s (KR) f o r Selected CAT Level 18 (Normed Results) Tests  NORMED GRADE 7.7 GRADE 8.7 GRADE 9.7 SECTION X SD SE KR X SD SE KR X SD SE KR Reading Vocabulary 16. 7 5.60 2.34 .83 19.2 5.54 2.24 .84 20.8 5.48 2.14 .85 (30 items) Reading Comprehension23. f40 items) 4 6.52 2.78 .82 25.4 6.55 2.71 .83 26.8 6.65 2.61 .85 Mathematics Computation 20. (40 items) 1 6.57.2.59 .64 23.8 7.40 2.55 .88 28.3 7.71 2.42 .90 Mathematics j Concepts and Applic a t i o n s 23. (45 items) 2 8.22 2.96 .87 27.8 8.62 2.86 .89 31.6 8.28 2.69 .89 Reference S k i l l s 15. 4 4.26.2.17 .74 16.6 4.13 2.10 .74 17.7 4.08 2.01 .76 (25 items) Note: Technical Bulletin (52) by Canadian Test Center, 1983, Scarborough, Ontario: McGraw-Hill Ryerson. The second estimate of r e l i a b i l i t y breaks down the previously assessed normed sections of' the t e s t s i n t o t h e i r inherent category objectives (Table 5 ) . For example, the Mathematics Computation t e s t assessed i n Table 4 i s broken down 92 into Addition, Subtraction, M u l t i p l i c a t i o n , and Di v i s i o n , and the Kuder-Richardson formula 20 i s again applied. Table 5 Means, Standard Deviations (SD), and Kuder-Richardson Formula 20 (KR 20) of the Category Objectives f o r Selected CAT Level 18 Tests  Category Objective No. of Grade 8 Grade 9 Items Mean SD KR 20 Mean SD KR 20 Test 1 Reading Vocabulary 11 Same Meaning 20 12.7 4.13 .80 13.8 4.08 .82 14 Opposite Meaning 5 3.1 1.38 .59 3.4 1.30 .58 15 Multimeaning 5 3.4 1.07 .32 3.6 1.20 .30 Test 2 Reading Comprehension 16 R e c a l l of Facts 6 4.4 1.29 .43 4.7 1.25 .48 17 Inferred Meaning 7 4.2 1.56 .42 4.4 1.55 .45 18 Character Analysis 5 3.2 1.26 .47 3.4 1.24 .50 19 Figurative Language 6 4.0 1.44 .46 4.1 1.43 .49 20 Contextual Analysis 5 2.7 1.23 .34 2.9 1.21 .35 21 Author A t t i t u d e / P o s i t i o n 5 2.9 1.28 .49 3.1 1.27 .51 22 Techniques of Persuasion 6 3.9 1.40 .44 4.1 1.36 .44 Test 6 Mathematics Computation 45 Addition 10 6.8 2.10 .64 7.6 2.10 .69 46 Subtraction 10 5.7 2.18 .67 7.0 2.32 .73 47 M u l t i p l i c a t i o n 10 5.5 2.13 .63 6.9 2.18 .68 48 D i v i s i o n 10 5.9 2.27 .68 6.8 2.30 .72 Test 7 Mathematics Concepts And A p p l i c a t i o n s 49 Numeration 5 2.8 1.36 .51 3.4 1.31 .56 50 Number Theory 4 2.6 1.12 .41 2.9 1.06 .42 51 Number Properties/Sentences 7 4.1 1.76 .60 4.9 1.62 .58 54 Measurement 6 3.9 1.52 .55 4.3 1.42 .55 56 Geometry 5 3.5 1.27 .48 3.8 1.19 .48 57 Problem Solving 7 4.4 1.70 .58 5.0 1.65 .60 58 Rounding/Estimation 5 2.9 1.31 .43 3.2 1.28 .44 59 Functions and Graphs 6 3.6 1.55 .52 4.1 1.48 .54 Test 8 Reference S k i l l s 62 Map 5 3.4 1.19 .39 3.6 1.23 .49 63 Table 5 3.5 1.23 .42 3.6 1.18 .42 65 Dictionary Page 5 3.2 1.19 .42 3.4 1.14 .40 6 6 L i b r a r y Catalogue Cards 5 3.5 1.41 .59 3.7 1.32 .58 68 Form 5 3.1 1.13 .30 3.4 1.10 .32 Note: Technical B u l l e t i n (68-69) by Canadian Test Center, 1983 Scarborough, Ontario: McGraw-Hill Ryerson. The R o t t e r I n t e r n a l / E x t e r n a l C o n t r o l S c a l e The Rotter Internal/External Control Scale (I/-E Scale) was used as a measure of perceived> locus' of control . Locus of control , described i n de ta i l i n Chapter 2, evolved out of soc ia l learning theory research and i s intended to measure whether individuals perceive, generally, that they have control over the outcomes in specific situations (internal control), or that they perceive those outcomes are controlled by forces external to them (external control). The I/E Scale consists of twenty-three test and six f i l l e r items from which a participant selects the one of two possible statements that they "more strongly believe to be the case as far as [they're] concerned" (Rotter, 1966: 1). The participants' scores, out of a possible 23, indicates at which end of the scale they f a l l with externality associated with the numerically higher end of the scale and internality with the numerically lower end of the scale. The I/E Scale was administered by the researcher following the completion of the mathematics sections of the CAT during the TRAC students' second day. The instrument was distributed together with a computer scannable answer sheet. The students were told that an explanation of what the instrument was and its purpose would be given after they had had enough time to complete i t . In addition, they were told that i f , after the explanation, they wished not to hand i t in, they would be free not to do so. The instructions were read aloud by the researcher with the students directed to read them silently. After the researcher had determined that a l l students had finished, a complete explanation was given, and student questions about the I/E Scale and the research project were answered. Responses to the 29 I/E Scale items were indicated on the answer sheet, and a total, out of 23 (29 minus the six f i l l e r items), recorded for each student. The data gathered from the administration of the I/E Scale formed the basis for the examination of the relationship between locus of control and persistence/withdrawal, both in high school and in the TRAC program. The I/E Scale, in its final form, was developed as a collaborative effort by Rotter and his colleagues from a pool of 100 items. Through item and factor analysis, the item pool was reduced to 60 and, after measurement for internal consistency, validity based on two studies (Seeman & Evans, 1962; Rotter, Liverant, & Crowne, 1961), correlation with the Marlowe-Crowne Social Desirability Scale, and measures to eliminate nonselective and irrelevant items, the final 23 items were selected. The effect of social desirability, as i t concerns the validity of the instrument, is discussed by Phares (1976). After examining a variety of studies, he concluded that, while "probably not entirely free from the effects of social desirability, i t would be incorrect to conclude that the scale is seriously impaired" (43) . Because social desirability refers to the extent to which the response to an item is influenced by the respondent's desire to be seen as giving a socially correct answer, the strength of this influence must be assessed in relation to the testing situation. In this research the I/E Scale was administered in a socially neutral situation: the Institute, program, their peers, and the individual administering the instr_kaant were a l l new to the students and, therefore, did not present a preestablished set of social norms. Accordingly, social desirability would be a minor influence in this case. In other words, the ability of the I/E Scale to 95 measure the hypothetical construct of locus of control should not have been compromised by the way i t was administered in this study. Internal consistency estimates for the final form of the scale varied between .65 and .79 which is interpreted by Rotter (1966) as being the result of the additive nature of the scale. In other words, as the scale items include statements related to academic recognition, social recognition, love and affection, dominance, social-political events and general l i f e philosophy, the relatively low scores are acceptable considering the variety of l i f e situations from which the statements were selected (Phares, 1976). In addition, the reliability of the scale, as measured using the test-retest method, gave coefficient of stability figures varying from .49 to .83 dependent upon the time lag between repeated administrations (Rotter, 1966). These figures, and those reported by others, are indicated by Phares (1976) as adequate from a psychometric point of view. Survey Development and Implementation As indicated previously, this study examined student characteristics as a source of factors related to attrition. Because only a limited amount of information is gathered by the Institute regarding individual student characteristics, the bulk of the data for this study had to be collected using a questionnaire. In addition, the way in which the program was delivered i.e., continuous intake and flexible attendance, dictated how the survey instrument was to be constructed and distributed to those TRAC students in the sample. Development of the survey instrument began with an examination of the research literature dealing with attrition in postsecondary education. From these studies, dealt with at length in Chapter II, categories of variables such as "previous educational experience" were established and subcategories, such as "last grade completed" and "skipping or failing a grade" identified. Each variable was then interpreted according to how i t applied within the context of the TRAC program, and hypotheses were developed based upon the expected relationship between variables. Finally, questionnaire items were constructed to gather the kind of information necessary to determine acceptance or rejection of each hypothesis. During the development of the questionnaire, certain factors related to the way TRAC was delivered at BCIT had to be considered. Because students could begin their training on any Wednesday, those who started between April 24, 1985, and October 23, 1985, (i.e., the research sample) would be scattered throughout the three levels of the program: Common Core, Occupational Core, and Specialty, at various stages of completion. A second factor was that approximately 80 percent of those students who withdrew from the program did so during Common Core. Considering these two factors, i f the questionnaire was designed to be answered by a l l sample students, regardless of whether they were in Common Core, Occupational Core, or Specialty, and regardless c2 their enrollment status, i t had to tie any questions regarding the program to a common section that a l l students had completed, or at least had worked in, i.e., Common Core. This meant the wording of items related to events which occurred during the students' time in training had to specify "While in Common Core . . . ." This was further reinforced by the questionnaire instructions which stated: Certain questions refer to Common Core. If you are now in Occupational or Specialty please try to answer the questions according; to the way you felt when you were  in Common Core. In addition to the students' time perspective when answering the questions, the survey could not be mailed until a l l sample students, (regardless of when they began) had had sufficient time to complete or, at least, attempt Common Core. As the estimated time required to complete Common Core was twelve weeks, the earliest the survey could have been mailed would be mid-January, 1986—twelve weeks after the last group of students included in the sample had begun the program. This would have given a l l students the time needed to complete Common Core and begin their Occupational Core or to have begun Common Core only to withdraw. Questionnaire Pilot Testing After completion of the fir s t draft, the questionnaire was examined by the researcher's colleagues, at the Institute, to determine its applicability to the TRAC program and TRAC students. Revisions were made to the wording of some items, the format was altered, and the instructions clarified. On December 2, 1985, the revised draft was administered to a group of 12 TRAC students who agreed to participate by completing the questionnaire. The purpose of the study was explained to them, and they were given a copy of the instrument and letter of transmittal. The time taken to complete the instrument was 98 r e c o r d e d t o p r o v i d e an e s t i m a t e o f the t i m e r e q u i r e d , t o be i n c l u d e d i n t h e f i n a l d r a f t o f the l e t t e r . F o l l o w i n g c o m p l e t i o n o f t h e q u e s t i o n n a i r e , s t u d e n t s were asked t o comment on t h e c l a r i t y o f t h e l e t t e r , t h e q u e s t i o n n a i r e i n s t r u c t i o n s , and the q u e s t i o n s t h e m s e l v e s . A few recommendations were made such as i n c l u d i n g "TRAC" i n f r o n t o f T r a i n i n g C o n s u l t a n t i n t h e q u e s t i o n d e a l i n g w i t h making use o f s t u d e n t s e r v i c e s . G e n e r a l l y , a c c o r d i n g t o t h i s group o f s t u d e n t s , the q u e s t i o n n a i r e seemed t o a c c o m p l i s h what t h e r e s e a r c h e r had d e s i g n e d i t t o d o . A l s o , t h e y f e l t n o t h i n g was i n c l u d e d t h a t c o u l d p o t e n t i a l l y " t u r n o f f " t h e average TRAC s t u d e n t b e i n g asked t o comple te and r e t u r n the s u r v e y i n s t r u m e n t . D u r i n g t h e t i m e t h e s t u d y was b e i n g p l a n n e d , a p p r o x i m a t e l y 60 p e r c e n t o f t h e s t u d e n t s r e g i s t e r e d i n t h e TRAC program were c l a s s i f i e d as E n r o l l m e n t S t a t u s 8: "on h o l d . " Between 1500 and 2000 s t u d e n t s were f l o w i n g t h r o u g h the system a t any one t i m e , and a l l a t d i f f e r e n t s t a g e s o f c o m p l e t i o n and d i f f e r e n t l e v e l s o f a c t i v i t y . T h e r e f o r e , knowing much about each s t u d e n t o t h e r t h a n what he had comple ted and when was, under t h e e x i s t i n g sys tem, v e r y d i f f i c u l t , i f no t i m p o s s i b l e . T h i s meant t h a t S t a t u s 8 s t u d e n t s c o u l d have been work ing t e m p o r a r i l y , on h o l i d a y , w o r k i n g f u l l - t i m e i n t h e shops and n o t w r i t i n g t e s t s , o r t h e y c o u l d have q u i t t h e program w i t h o u t i n f o r m i n g the I n s t i t u t e . I n a d d i t i o n , i t was expec ted t h a t due t o t h e n a t u r e o f t h e s t u d y as o u t l i n e d i n the l e t t e r o f t r a n s m i t t a l , t h a t d r o p o u t s would be l e s s i n c l i n e d t h a n p e r s i s t e r s t o comple te and r e t u r n t h e q u e s t i o n n a i r e . What e f f e c t t h e s e two f a c t o r s would have on t h e r e s p o n s e r a t e c o u l d not be p r e d i c t e d . As a means o f 99 determining what to expect and how to best obtain an adequate response, the researcher decided to pilot test the instrument and survey procedure with a group of students included in the population but not in the research sample. The group selected for the pilot test included twenty-nine TRAC students who had begun the program between February 27, 1985, and April 17, 1985. On December 12, 1985, a copy of the latest draft of the questionnaire, letter of transmittal, and a stamped, self-addressed return envelope was mailed to each of the selected students. This was followed on December 23, 1985, by a letter reminding nonrespondents about the survey and urging them to respond. As i t was received, mail returned by the post office undelivered was checked for the correct address and, i f no new address could be found, changed to the emergency address given by students on their registration form. A final follow-up letter and second copy of the questionnaire was mailed to each of the remaining nonrespondents on January 16, 1986. The pilot test resulted in a response rate of 37.9 percent. Twenty point seven percent of the questionnaires were returned by the post office indicating "wrong address" or "no longer at this address" and half of these were remailed when an alternate address was available. Of a l l those mailed 51.7 percent were not received by the researcher, nor returned by the post office. The results from the pilot study provided an indication of the response rate that could.be expected from the research sample i f the same mail-out procedures were used. This response rate was less than hoped for, and plans were made to alter the follow-up procedure for the actual survey. Each of the returned pilot study questionnaires was examined to determine i f any of the items seemed to cause problems (i.e., question marks beside items, comments, responses of "N.A.11, or blanks where there should have been a response). This information, together with recommendations made by the members of the research committee, resulted in changes to improve the clarity of the instrument. For example, i t was recommended by the committee that in questions dealing with a quantifiable measure that responses such as "very often", "quite a bit", "once in awhile", "never" be changed to "more than once", "once", "never" to reduce the ambiguous nature of the fi r s t set of responses. In other words, the choice of "very often" and "quite a bit" is open to interpretation whereas "more than once", "once", and "never" is more precise. The questionnaire, now determined to be in its final form, was sent for typesetting and printing. Questionnaire Administration A survey package (see Appendix B) including a questionnaire, letter of transmittal, and stamped, self-addressed return envelope was mailed to a l l members of the research sample on March 17, 1986. This f i r s t mail-out was followed by a reminder letter on April 2, 1986, which, in turn, was followed by a second survey package mailed'to a l l nonrespondents on April 28, 1986. As mail came in i t was sorted ii>to completed responses and those returned by the post office undelivered. The address on each undelivered package was checked against the address on the TRAC computer and cross checked against the computer record in 101 Student Admissions. If an alternate address was not listed, and the emergency contact's address was different from the student's mailing address, the package was remailed to the contact person. As the completed questionnaires were collected, a record was kept of the enrollment status of each respondent so that the response rates of each group—persisters and dropouts—could be followed. As responses came in i t became apparent that, in comparison to their numbers in the population, more persisters had completed and returned the questionnaire than had dropouts. At the time that this trend became obvious to the researcher, the Institute began to "purge" its records in an attempt to separate active students from those who had left the program. As part of this activity, students who had been inactive for a period of time were phoned and asked about their intentions regarding the program. As a way of increasing the response from those students who indicated they did not wish to continue (i.e., dropouts), permission was granted for them to be asked i f they had received the questionnaire, and i f they had completed and returned i t . Those who had yet to complete and return i t were urged to do so as soon as possible. Despite the measures taken to solicit increased participation by dropouts, the response by this group remained lower than hoped for by the researcher. In a final attempt to gain a few more percentage points in the response column for dropouts, a final mail-out was sent to the nonrespondents in this group. In addition to the questionnaire, a letter (see Appendix C) was enclosed explaining why i t was important to 102 obtain completed questionnaires from students who had withdrawn, and promising a small honorarium for the time necessary to complete and return the questionnaire upon its receipt. This final mailout resulted in responses being received from eight more TRAC dropouts. Data Analysis As previously stated, one of the purposes of this study was to determine which factors, identified by other attrition researchers, are appropriate in identifying "dropout prone" TRAC students. The data gathered to enable the identification of these factors were primarily nominal or ordinal in nature although test scores, ages of students, socioeconomic related measures, and variables involving money, time, percentages or proportions were of the interval or ratio type. The statistical tests selected for analysis of these data were, of course, dictated by the level of measurement. Had a l l the variables been of the interval or ratio type, Pearson's product moment correlation, the inferential t Test or the F ratio could have been used as the statistical tests. Since this was not the case, the selection of the statistic was determined by what best clarified the relationship between the predictor variables and persistence/ withdrawal. For the purpose of data analysis, the SPSSx "Crosstabulation" program was used in cases where both the predictor and criteria; variables were nominal in nature. This program produces contingency tables and performs chi square calculations to determine the nature of the relationship between the variables. In addition, the Crosstabulation program; 103 calculates "measure of association" which provides a means of quantifying the strength of the relationship between variables. A number of "measures of association" can provide this information. For nominal measures these are based either on the chi square statistic or Goodman and Kruskal's (1954) "proportional reduction in error" (PRE). As stated by Norusis (1983), the chi square-based measures tend to be difficult to interpret as "the 'strength of association' being compared is not easily related to an intuitive concept of association" (55). She goes on to state that with PRE measures, the meaning of association is clearer. These measures are a l l essentially ratios of a measure of error in predicting the values of one variable based on knowledge of that variable alone and the same measure of error applied to predictions based on knowledge of an additional variable (55). She also cautions the reader that each measure of association is designed in a specific way. The use of one measure that indicates zero association does not preclude finding a degree of association using a different measure. She states that although there exists no single measure sensitive to every type of association, i t is not reasonable to use a variety of measures and select the one which gives the most impressive result. For this study the PRE measure "lambda" is used to describe the strength of association between the predictor and criterion variables. In cases where the comparison is between a ratio and a nominal variable, a statistic other than chi square is used. The correlation ratio (eta) ". . . a measure of the strength of association between a nominal variable and an interval-ratio 104 variable" (Ferguson, 1981: 248) was used in this study together with the F ratio which tests the statistical significance of eta. UBC CORN (Parametric and Non-parametric Correlations and Test of Significance) was used as the statistical package to calculate the correlation ratio and the F ratio. In addition, the correlation ratio is expressed as a decimal number which, when converted, describes the percentage of variation in the data attributable to the predictor variable. Because of the few studies directed at the research population, i t was felt by the researcher that certain license was justified in terms of the selection of the statistical criterion for significant findings. Even though the sample for this study was quite large, making even small differences statistically significant, the means of measurement used in the collection of data lacked the precision necessary to confidently restrict p to the .05 level. In addition, the large number of statistical tests involving the research sample would normally result in a even stricter criterion to guard against chance findings (i.e., Bonferroni t procedure). Even though drawing inferences or predicting trends from results based upon a less stringent level of statistical significance increases the likelihood of a Type I error, i t was felt i t was better to risk indicating a relationship existed when i t did not than to overlook a relationship by being too strict with the criterion for rejection of the null hypot:yi.ses. Although the level of significance selected to determine acceptance/rejection of each hypothesis was p < .05, results with significance levels between p = .05 and p < .10 were interpreted as to their possible ' .. " .• . • .•'•<1' - :- • .. 105 meaning in this study and were indicated to f a l l in this range in summaries of the statistical analyses. In the statement of each hypothesis "significant" was meant to be interpreted from a statistical perspective. Summary In this chapter the process for gathering the information needed to answer the research questions has been outlined. Site selection and selection of the research population and sample were described. Having established the where and who of the study, how the data were to be collected was then outlined. The major portion of this description revolved around the design and development of the survey instrument. Having laid out the process followed in the collection of data, the statistical methods needed to give them meaning were finally described. In the following chapter the research hypotheses are stated and explained in relation to the findings of previous studies. The data gathered for decisions regarding the acceptance or rejection of each hypothesis is analyzed and the results of each analysis described. In addition, the survey response rate is examined and the validity of the results, based on the response rates for both persisters and dropouts, is discussed. 106 CHAPTER IV RESEARCH FINDINGS: PRE-ENTRY FACTORS It is generally acknowledged that decisions to withdraw from an educational program are complex and related to a variety of factors. Because of this variety i t is useful to separate these factors into categories giving form to this complexity. For example, Lenning, Beal, and Sauer (1980) classify these factors as those related to students and institutions, the interaction between the two, and factors external to both but which are s t i l l related to them. Student factors are subsequently divided into academic, demographic, and financial. Those concerning institutions are the objective environment, student involvement, and administrative policies and procedures. External factors include economic cycles and current social forces. Tinto (1987) also differentiates between attrition factors, which he states "pertain on one hand to the dispositions of individuals who enter higher education and, on the other, to the character of their interactional experiences within the institution following entry" (1987: 39). Regarding the individual, he mentions "intention" and "commitment" as the primary categories, with "adjustment", "difficulty", "incongruence", and "isolation" describing those factors related to the individual's experience within the institution. Although different in the way they categorize factors related to withdrawal, both writers differentiate between those factors determined prior to institutional entry and those the student encounters after beginning his postsecondary schooling. In this study a similar system is used in organizing and presenting the hypotheses and 107 the results from the data collection and analysis. The response to the mailed questionnaire is described first in this chapter. Because persisters and dropouts did not respond to the questionnaire in proportions equal to their numbers in the research sample, and because the response rate was less than 100 percent, the validity of the assumption that respondents and nonrespondents were not significantly different was explored. This is followed by an explanation of the hypothesized relationships between factors indicated in the literature and believed by the researcher to be related to attrition and the criterion variable. In this chapter those factors considered as "pre-entry" i.e., having been determined prior to postsecondary enrollment are examined. They are divided into previous educational experience, academic factors, demographic factors, motivational factors, and learner self-confidence. For each of these factors the hypothesized relationship between i t and persistence/withdrawal and the logic surrounding the hypothesis development is stated, the data analyzed, and the conclusion regarding the validity of its inclusion as a characteristic of either persisters or dropouts is drawn. This process is continued in Chapter V but for postentry factors, i.e., those encountered after the student enrolls in his postsecondary education. Prior to the final chapter, factors found to be significantly related (from a statistical perspective) to persistence/withdrawal are reexamined. The purpose of this reexamination is to develop a prediction formula which can be used to identify those students most likely to dropout. 1 0 8 Response to the Questionnaire In Chapter III the process by which the population was defined and how the sample was drawn from that population was described. As stated, the population includes "the 1473 male students who enrolled in PVI's TRAC program (Burnaby Campus) between September 19, 1984, and May 30, 1986", but excludes those enrolled in the horticulture program. From this population the 634 TRAC students who began their programs between April 24, 1985 and October 23, 1985 were selected as the research sample. Research data were collected from two sources: students' records maintained by PVI and student responses to a mailed questionnaire. Of the 629 questionnaires mailed out to the research sample members (no address could be found for five individuals), 298 were completed and returned and 72 were returned undelivered by Canada Post. Therefore, of those questionnaires which were mailed to and apparently received by members of the research sample (N = 557), the response rate was 53.5 percent. Of those who responded, 61.4 percent were persisters (compared to 41.2 percent persisters in the research sample), and 38.6 percent were dropouts (compared to 58.8 percent dropouts in the research sample). As with any response rate of less than 100 percent, the possibility exists that those who did not respond to the {|§festionnaire were in some significant way different from tncsse who did. Therefore, generalizing to the population, based only upon results from those sample members who responded, may have led to statements which were true only for the research sample 109 respondents and not the population as a whole. As indicated in Rosenthal and Rosnow's (1975) review of studies dealing with volunteer subjects, even though there appear to be no significant differences between respondents and nonrespondents on personality variables, nonrespondents tend to be less successful academically. Considering the nature of this research, and the response rate, i t was important to test whether those who responded were significantly different from those who did not. To determine i f persisters and dropouts who responded were different from persisters and dropouts who chose not to respond, each of the groups (i.e., responding persisters vs. nonresponding persisters and responding dropouts vs. nonresponding dropouts) were compared by age, CAT scores, I/E Scale scores, the amount of credit received for previous education or work experience, and by the number of theory or practical tests on which the student failed, passed, or exceeded the mastery criteria, and the total number of tests attempted during their f i r s t six weeks of enrollment in the TRAC program. Tables 6 and 7 give the results of these analyses. Selecting p < .05 as the probability level indicating statistical significance, the results of the differences between the means of responding and nonresponding persisters on the selected variables indicate that there are no statistically signifi-di&t differences between the two groups (see Table 6). Except for "Tests Failed", "Tests Passed", and "Tests Attempted", a similar statement could be made for responding and nonresponding dropouts (see Table 7). 110 Table 6 Responding (R) and Nonresponding (NR) Persisters: A Comparison of Their Mean Scores on Selected Variables  Variable n Mean S.D. t df E> Age R 145 22.86 5.99 .28 200. 12 .78 NR 90 23.07 5.53 Reading Vocabulary R 150 25.73 4.48 -0.70 207. 77 .48 NR 95 25.33 4.26 Reading Comprehension R 150 30.80 6.37 -0. 38 204. 14 .70 NR 95 30.48 6.20 Reference Skills R 150 19.51 3.15 -0.15 206. 66 .88 NR 95 19.45 3.02 Math Computation R 151 30.13 7.53 -0.50 181. 30 .62 NR 95 29.60 8.54 Math Concepts and Applications R 151 36.18 7.37 -1.57 190. 54 .12 NR 95 34.60 7.85 Locus of Control R 146 9.25 3.79 1.45 185. 32 .15 NR 91 10.00 3.94 Credits R 144 22.95 20.41 -1.86 187. 55 .07 NR 88 17.90 19.91 Tests Failed R 144 9.24 7.41 -0.44 145. 39 .66 NR 88 8.70 9.99 Tests Passed R 144 28.40 12.39 -1.85 191. 05 .07 NR 88 25.39 11.79 Tests Exceeded R 14r'4- 17.58 11.23 -0.68 205. 12 .50 NR 88 16.63 9.65 Tests Attempted R 144 . 55.22 22.91 -1.49 190. 14 .14 NR 88 50.72 21.95 *p < .05 I l l Table 7 Responding (R) and Nonresponding (NR) Dropouts: A Comparison of Their Mean Scores on Selected Variables  Variable n Mean S.D. t df o Age R 115 21.59 5.34 .52 221. 68 .60 NR 222 21.91 5.10 Reading Vocabulary R 115 23.95 5.57 -0 .69 230. 60 .49 NR 232 23.50 5.66 Reading Comprehension R 115 29.02 6.48 -1 .48 244. 71 .14 NR 231 27.89 7.02 Reference Skills R 115 18.50 3.62 -0 .96 241. 14 .34 NR 231 18.10 3.86 Math Computation R 117 26.78 8.72 -1 .17 219. 95 .24 NR 235 25.65 8.22 Math Concepts and Applications R 117 32.24 8.88 -0 .98 218. 11 .33 NR 235 31.28 8.29 Locus of Control R 114 9.63 3.83 0 .40 223. 74 .69 NR 222 9.81 3.75 Credits R 109 11.95 17.51 -0 .37 201. 36 .71 NR 234 11.21 16.63 Tests Failed R 109 8.51 8.97 -2 .38 160. 12 .02* NR 243 6.25 6.34 Tests Passed R 109 18.79 11.51 -3 .69 215. 89 .01* NR 234 13.83 11.81 Tests Exceeded R 109 9.49 8.99 -1 .86 201. 66 .06 NR 243 7 .68 8.56 Tests Attempted R 109 36.79 22.94 -3 .47 205. 26 .01* NR 234 27.65 22.26 *p < .05 112 Those dropouts who chose to respond to the questionnaire had significantly more test failures, passes, and attempts during the f i r s t six weeks of their program than did those who chose not to respond. A possible explanation for these differences could be that those dropouts who responded were more active in the program during their f i r s t six weeks. The term "more active" in this case refers to attempting more theory and practical tests. This would require the student to be in attendance for a longer period of time. Following this logic i t is possible that nonresponding dropouts may have left the program sometime before the responding dropouts. Whether these results represent a real difference between responding and nonresponding dropouts is difficult to determine given the limited number of shared variables available for comparison. To proceed with further analysis, an assumption was made by the researcher that, based upon the findings, these differences between responding and nonresponding dropouts did not preclude generalizing the research findings to the population. Pre-Entry Factors Related to Attrition i No student's postsecondary schooling stands in isolation from that which went before. Students bring to the college or institute many years of public schooling which have provided the students with certain skills and also shaped their attitudes towards education. As participants in a larger society, their perceptions regarding the value of a "good education" have similarly been influenced. These factors have in turn worked to shape the student's occupational goals resulting in the decision to further his education. In sum, each of these factors has 113 undoubtedly left the student with a perception of his ability as a learner and continues to exert an influence as the student pursues postsecondary completion. Previous Educational Experience Approaches to new educational experiences are influenced by previous experience. On this point, both adult and higher education researchers agree (Anderson & Darkenwald, 1979; Sexton, 1965; Pantages & Creedon, 1978; Lenning, et. al., 1980). Although, in considering the relevance of "previous educational experience" to the research sample, the most that can be assumed is that the way in which these relate to persistence or withdrawal in higher education populations may only apply to those students who completed high school and met university or college entrance requirements. For those who failed to complete, or even reach high school, the definition of this factor needs to be broadened to better reflect their previous educational experience. Information on such things as last grade completed (including any postsecondary experience), grades, time lapsed since previous education or training, and type of program i (academic, general, business, technical/vocational), may be more appropriate indicators of previous experience for low educational attainment students. In addition, research on high school dropouts indicates that those who f a i l to complete high school have a different perception regarding their educational experience than do those who graduate (Bachman, 1967). Factors such as failing to graduate from high school, being held back a grade, and selecting negative statements in describing past educational experiences are indications that dropouts may 114 perceive these experiences as less than positive. This perception could, in turn, be related to similar outcomes in subsequent educational activities. In essence, the researcher believes that as one moves through the public education system there are certain touchstones serving to measure the impact of this experience in comparison to a set of standards. How one measures up to these standards is related to subsequent educational and employment options. The idea that certain prerequisite factors are related to whether one completes or withdraws from an educational program forms the basis for most attrition research. Following this argument, i t seems logical to hypothesize that there exists a threshold value for these factors above which one persists. In the case of previous educational experience, the variables examined in Hypotheses la to lk have been selected from the research as those related to students* decisions to persist or withdraw. The order in which they are examined is loosely chronological, starting with whether one was held back or accelerated during the primary grades. Following this, high school marks, and behavior in and enjoyment of school is examined. The high school program taken, the last grade completed, and i f the student graduated is examined next. Finally, the student's postsecondary experience and the time lapse between TRAC and any previous educational experience is considered. The statistical analyses answer the questions "are these variables related to attrition", and, taken together with a l l other attrition factors, the answer to "is there a threshold value" is examined in Chapter VI with the development of a 115 prediction formula. Generally, i t is believed that factors, identified in previous studies as being related to a "negative" educational experience, will be more common to TRAC dropouts than TRAC persisters. Having to repeat a grade in school is indicated in the literature to be a significant predictor of subsequent school dropout (Bachman, Green & Wirtanen, 1967; Sainty, 1971; Self, 1984; Hahn, 1987). As indicated by Hahn (1987), "approximately one-third of a l l high school students are behind the modal grade by one year, and another 5% are at least two years behind" (258-9). He goes on to state that these students are four times as likely to withdraw from high school than are students who have not been held back. Bachman, Green and Wirtanen (1967) make the connection between one's experience in school regarding being held back and similar subsequent educational experiences. This seems to translate into a situation where students who have been held back a grade in school are more likely to dropout of postsecondary programs. Hypothesis la: There is no significant relationship between i failing a grade in elementary school and persistence/withdrawal. The relationship between being held back and dropping out does not appear to apply to TRAC students (Table 8). The difference between the number of TRAC persisters and TRAC dropouts who repeated a grade in elementary school varied by less than two percentage points. A chi square value of .17 (p = .68) indicates that there is no statistically significant relationship between failing a grade and persisting in or 116 Table 8 Persisters and Dropouts Compared by Failing/Not Failing a Grade in Elementary School . Student Status Failed a Grade Yes NO Total (%) Persisters 26 135 161 (55.7) Dropouts 23 105 128 (44.3) Total 49 240 289 (%> (17.0) (83.0) (100.0) withdrawing from the TRAC program at PVI. The failure of these results to substantiate those found in previous studies may be due in part to the way the question was asked on the questionnaire. When students reach high school they f a i l or are held back in subjects rather than grades, therefore i t would be difficult to determine what constituted "failing a grade." Even i f a definition could be arrived at, obtaining this information would require the examination of each student's high school transcript to see i f he f i t the definition. In addition to being a tedious task i t would not be possible in this study because TRAC applicants were not required to submit a copy of their high school transcript for admission to the program. Even to rely upon the memory of each student in recalling and stating his high school record on the questionnaire would have been inadvisable as the reliability of such data would be open to question. Because of these factors, students where asked to indicate on the questionnaire only whether they had failed a grade in pigmentary school. Therefore, what this may indicate, is by *ehe time a student reaches postsecondary school, any relationship between being held back a grade in elementary school and subsequent withdrawal from training has disappeared. Had a means 117 been available to determine i f a student had "failed a grade" in high school these results may have been different. Because being held back a grade was found in previous research to be related to a student's subsequent educational experience, i t was felt that the opposite condition, i.e., being advanced a grade, may also be related. However, the way in which skipping a grade is related to high school dropout is not obvious from the research. It was expected by the researcher that skipping a grade, an indication of superior skills, may indicate that the student would be better prepared for the academic requirements in a postsecondary program. Hypothesis lb: There is no significant relationship between skipping a grade in elementary school and persistence/withdrawal. Based on the data in Table 9 a chi square value of 3.03 was calculated. This value, which can be expected to occur only in 8 out of every 100 samples (p =.08), falls within the range of probability values that were going to be "closely examined" by the researcher (See page 99). Table 9 Persisters and Dropouts Compared by Skipping/Not Skipping; a Grade in Elementary School  Student Status Skipped Yes a Grade No Total m Persisters 6 152 158 (55.6) Dropouts 11 115 126 (44.4) Total (%) 17 (6.0) . 267 (94.0) 284 (100.0) Of those TRAC students who skipped a grade, 64.7 (11 of 17) percent were dropouts. In addition, 8.7 percent of a l l TRAC 118 dropouts, compared to 3.8 percent of a l l TRAC persisters, skipped a grade. This indicates that for TRAC students skipping a grade is more closely related to dropping out than persisting. This outcome is opposite to what was anticipated. Being held back a grade indicates that, compared to others in his class, the student's progress was so poor that repeating a grade was considered necessary. Being held back he is considered a "failure" by his teachers, peers, and family, and, based upon the research, that which the student is lacking i.e., adequate progress, is closely related to early school leaving. On the other hand, being advanced a grade indicates that the student is operating at a level superior to his classmates. That a student who obviously had superior ability in public school is more prone to dropout in postsecondary education is puzzling however, as has been mentioned previously (Tinto, 1987) in regard to voluntary dropouts, the student's reasons for dropping out may have had l i t t l e to do with his ability to successfully complete. When skipping a grade is compared to persistence or dropout i from high school for members of the research sample, 17.6 percent of those who skipped a grade were high school dropouts. This means that the majority of high school dropouts (82.4 percent) did not skip a grade and that skipping appears to be less related to high school dropout than to dropout from TRAC. From the high school perspective the relationship is consistent with the view of the researcher: skipping a grade seems to be less related to dropping out in high school. Therefore, the explanation advanced in Hypothesis la is supported by these 119 results: skipping a grade in elementary school seems to be related to persistence in high school but this does not appear to be the case by the time the student reaches postsecondary school. Academic ability in high school, as defined by class standing and GPA, is the best single variable predictor of attrition for college students (Pantages & Creedon, 1978). However strong the relationship, i t s t i l l only accounts for a small percentage of a l l that is related to withdrawal. Pantages & Creedon (1978) go on to say that a student's high school record is a better predictor of how a student will do in college than whether he will dropout. But good grades in high school should at least be a sign that a student has mastered the basics. It follows, therefore, that students who indicated on the questionnaire that they obtained average or higher grades in high school should be able to cope with the academic demands of the TRAC program. Lacking basic skills, those who obtained less than average marks in high school would not be expected to be as prepared to meet these demands, which may be related to their decisions to withdraw. Hypothesis lc: There is no significant relationship between self- reported high school marks and persistence/withdrawal. Knowledge of a student's academic standing in high school appears to contribute l i t t l e to the prediction of persistence/withdrawal iii the TRAC program. A chi square value of 3.33 (p = .50) indicates that, for this sample, there is no statistically significant relationship between the predictor and criterion variables. 120 Table 10 P e r s i s t e r s and Dropouts Compared by Se l f - repor ted High School Marks  Student Status Hicrh School Marks A B C D F T o t a l (%) P e r s i s t e r s 8 60 88 3 1 160 (55.6) Dropouts 5 38 82 3 0 128 (44.4) T o t a l 13 98 170 6 1 288 (%) (4.5) (34.0) (59.0) (2.1) (.3) (100.0) One reason why the r e s u l t s from t h i s study do not agree with most other research may be due to the way t h i s information was gathered. Students were asked whether they considered themselves to be "A", "B", " C " , "D", or "F" students based on t h e i r s e l f - r e p o r t e d secondary school marks. This would require that the student remember and t r u t h f u l l y record t h i s information—a method which may not be h igh ly r e l i a b l e . More accurate information could have been gathered from the students' high school t r a n s c r i p t s but , as s tated before, because t r a n s c r i p t s were not required for entrance to TRAC, t h i s approach was not f e a s i b l e . Behavior i n school has a l so been indicated to be r e l a t e d to pers istence/withdrawal from postsecondary school ing . In S e l f ' s (1985) review of the l i t e r a t u r e on high school dropout, d i s c i p l i n e problems were c h a r a c t e r i s t i c of dropouts, e s p e c i a l l y j u s t p r i o r to dropping out . Because t h i s was seen as r e l a t e d to an a t t i t u d e that high school dropouts may b r i n g with them to the TRAC program, i t was added as a poss ib le c o n t r i b u t i n g fac tor to dropout from TRAC. On the quest ionnaire , students were asked which of four statements regarding t h e i r behavior i n high school they f e l t would be se lec ted by t h e i r former teachers . These 121 statements ranged from having "perfect" or "average" behavior, to being "involved" or to "initiating" behavior related classroom problems. Hypothesis Id: There is no significant relationship between self- perceived behavior in public school and postsecondary persistence/withdrawal. Analysis of the data indicated that none of the behavior categories were related to persistence or withdrawal (chi square = 4.33, p = .23). Table 11 Persisters and Dropouts Compared bv Behavior in Public School Student Status Self-Perceived Behavior Perfect Student Average Student Problem Participant Problem Initiator Total(%) Persisters 20 121 17 2 160 (55.4) Dropouts 16 106 7 0 129 (44.6) Total (%) 36 (12.5) 227 (78.5) 24 (8.3) 2 (.7) 289 (100.0) The attitude towards school would also include whether the student enjoyed or disliked the experience. Disliking school or having a negative attitude towards i t has been indicated in previous research (Self, 1984; Bachman, Green & Wirtanen, 1967) as related to high school dropout. Considering that high school graduation is subsequently shown to be related to TRAC persistence (Hypothesis lh), attitudes towards school by nongraduates taking TRAC may have been carried forward to their postsecondary school experience, possibly relating to withdrawal from the program. Hypothesis le: There is no significant relationship between the attitude towards public school and postsecondary 122 persistence/ withdrawal. Although not statistically significant, the results listed in Table 12 (chi square = 6.30, p = .10) do, according to previously specified criteria (See page 99), warrant further examination. Table 12 Persisters and Dropouts Compared by Feelings Towards Public Student Status Feelincrs Towards School Enj oyed Enjoyed Disliked Disliked Total (%) Very Much Very Much Persisters 18 114 24 5 161(55 .3) Dropouts 27 76 23 4 130(44 •7) Total 45 190 47 9 291 (%) (15.5) (65.3) (16. 2) (3.1) (100 •0) Both TRAC dropouts and TRAC persisters, at 79.2 percent and 81.9 percent, reported enjoying school, but TRAC dropouts claim to have enjoyed i t more than TRAC persisters (enjoyed "very much": dropouts, 20.8 percent; persisters, 11.2 percent). If these TRAC dropouts are also high school dropouts then the fact that they enjoyed school more than TRAC persisters is opposite to that found in high school studies. Additional analysis, utilizing high school persistence and dropout as opposed to persistence and dropout in TRAC, produced a relationship similar to that stated in the research: high school dropouts tend to like school less than high school graduates (enjoying school: high school dropouts = 64.4 percent, high school graduates = 86.4 percent). Therefore, the relationship between the research population as high school persisters or dropouts follows the; findings of others, while as postsecondary students the results are opposite to these findings. 123 The program that students find themselves in in high school, because of the relationship between their previous school achievement and the stream into which they are placed, may also be related to their subsequent experience in postsecondary school. For example, vocational programs in high schools have consistently been used as a "dumping ground" for those students who cannot or choose not to succeed in academic programs. As pointed out by Weber and Silvani-Lacey (1983), students in high school vocational programs f a l l between the thirty-fifth and fortieth percentile on standardized tests of basic sk i l l s . They also found that the scores of dropouts from academic programs were similar to those of vocational persisters and that vocational dropouts had scores that were considerably lower than either academic dropouts or vocational persisters. Because of the anticipated differences in levels of basic skills between students in academic and nonacademic high school programs, i t seemed logical that academic students enrolling in TRAC would be better equipped to successfully complete the program. On the other hand, students from nonacademic programs, and especially from vocational programs, would find TRAC a struggle and be more likely to withdraw. It was also felt that students from academic programs may cope better with the self-paced aspect of the TRAC program and do what was necessary to maintain adequate progress. Hypothesis If: There is no significant relationship between the program taken in high school and persistence/withdrawal. Based upon the data in Table 13, knowledge of the program a student took in high school adds l i t t l e to the ability to 124 predict persistence or withdrawal. The resulting chi square value of 2.99 can be expected to appear by chance in 56 of each 100 samples (p = .56) drawn from the population thereby exceeding the limits set for rejection of the hypothesis. Table 13 Persisters and Dropouts Compared bv High School Program Taken Student Program Taken Total Status University Vocational Trades Business Emolovment (%) Persisters 42 69 15 5 16 147 (57.6) Dropouts 25 51 9 4 19 108 (42.4) Total (%) 67 (26.3) 120 (47.1) 24 (9.4) 9 (3.5) 35 (13.7) 255 (100.0) Because the benefits of education would likely accrue with each year of schooling, how long a student stayed in school may be related to his persistence in TRAC. PVI's open door policy did not bar students who failed to complete grade twelve from taking the TRAC program. However, based upon the idea of accrued benefit, i t seems logical that the more grades a student had completed prior to taking the program the better prepared he would be to successfully complete his trades training. The more complete the student's grbunding in the basic skills and the more time he had had to practice and refine his study techniques, the better would be his ability to understand and apply that taught in the TRAC program. Hypothesis lg: There is no significant relationship between last grade completed and persistence/withdrawal. Seventy-seven point five percent of a l l TRAC students, both persisters and dropouts, came to the program having completed grade twelve (Table 14). A chi square value of 1.12 (p = .89) 125 indicates that results similar to these findings would be found by chance in 89 out of every 100 samples drawn from the research population. Table 14 Student Status Last Grade : Completed Total (%) 8 9 10 11 12 13 Persisters 3 0 16 11 127 2 159 (55.8) Dropouts 3 2 16 11 94 2 126 (44.2) Total 6 (2. 2 1)(.7) 32 (11.2) 22 (7. 221 7) (77.5) 4 (1.4) 285 (100.0) Graduation from high school is a milestone in a young person's career. It represents not only the successful completion of twelve years of public school but also indicates to society that the student had the ability and stamina to persist. Failure to graduate carries with i t the stigma of being labeled a "dropout," inferring that one is a failure. But graduation from high school has a cognitive as well as an affective component. It may also indicate that a student has come away from his public school experience with a set of basic skills necessary for success in future endeavors. It is this set of academic tools that is believed to be the active component in the relationship between high school graduation and successful postsecondary participation and completion. Hypothesis lh: There is no significant relationship between high school graduation and persistence/withdrawal. The results of the chi square calculations, based on the data in Table 15, (chi square = 5.12, p = .02) indicates that the relationship between high school graduation and persistence/ withdrawal is statistically significant at the p < .05 level. In 126 addition, the "measure of association" (lambda = .07) indicates that a 7 percent reduction in the error of predicting the criterion variable was possible by using high school graduation as a predictor variable. Table 15 Student Status Hiah School Graduate Yes No Total (%) Persisters 127 32 159 (55.2) Dropouts 88 41 129 (44.8) Total 215 73 288 (%) (74.7) (25.3) (100.0) In summary, the rejection of the null hypothesis indicates that a relationship exists between graduating or not graduating from high school, and persisting or not persisting in the TRAC program. As was stated in selecting a significance level, had a more stringent criterion been selected, the null hypothesis would not have been rejected. Given that the relationship between persistence/withdrawal and high school graduation is a true relationship, to f a i l to reject the null hypothesis would have been a Type II error. Furthermore, the relationship is direct: more TRAC persisters and fewer TRAC dropouts graduated from high school. In addition, the lambda statistic also indicates that by knowing whether a student graduated from high school, the error in predicting whether he will persist or withdraw in TRAC is reduced by 7 percent. Participation in other postsecondary programs may also have been positively related to TRAC persistence. For example, TRAC students who had previously been enrolled in a degree program would, due to university entrance requirements, have been high 127 school graduates with better than average academic skills. This would have ensured that they had the basic skills as well as the study skills necessary to successfully complete TRAC. A different outcome may have been found i f the TRAC student had previously completed an adult upgrading program. Hypothesis l i : There is no significant relationship between the postsecondary program taken and persistence/withdrawal. In this comparison chi square is 4.08, a value which could be expected to appear by chance in 40 of each 100 samples drawn from the population. Therefore, there is no statistically significant relationship between taking a particular postsecondary program previous to TRAC and persistence or withdrawal. Table 16 Student Status Program Taken* Total 1 2 3 4 5 (%) Persisters 13 7 5 22 9 56(60.2) Dropouts 6 8 7 11 5 37(39.8) Total 19 15 12 33 14 93 (%) (24. 4) (16.1) (12. 9) (35.5) (15.1) (100.01 *1 = Degree, 2 = Technical, 3 = Occupational, 4 = Vocational 5 = Upgrading In addition to the kind of postsecondary program that students select prior to taking TRAC, the fact that they are participating in training after high school is also believed to be related to whether they persist or withdraw. That participation in adi.it education activities leads to further participation is a well accepted maxim in the field of adult education. From this i t seems safe to assume that "participation" refers to successful experiences by those who 128 choose to participate again and again. This would seem to justify the belief that successful participation in a postsecondary program prior to beginning TRAC may also be related to successful completion of TRAC. This relationship may also hold true for TRAC dropouts: an unsuccessful pre-TRAC experience may be related to withdrawal from TRAC. Hypothesis l j : There is no significant relationship between previous postsecondary graduation and persistence/ withdrawal. Based upon the statistical analysis completed on the data from Table 17, having graduated from a postsecondary program previous to enrolling in TRAC is not related to persistence/withdrawal in the TRAC program (chi square = .33, p = .58). Table 17 Persisters and Dropouts Compared by Postsecondary Graduation  Student Status Postsecondary Graduation Yes No Total (%) Persisters 34 12 46 (59.7) Dropouts 21 10 31 (40.3) Total 55 22 77 (%) (71.4) (28.6) (100.0) From these results and similar result from Hypothesis l i , i t seems that participation in a postsecondary program before enrolling in TRAC is not related to persistence or withdrawal from TRAC. Whether the time is measured from secondary or postsecondary schooling, how long a student spends out of school prior to taking TRAC may be related to his persistence in TRAC. Similar 129 to most skills that go unpracticed for a long period of time, academic skills weaken without a sustained effort to make use of them. Calculators and television substitute for arithmetic and reading skills practiced while in school. In addition, anxiety about returning to school after spending many years away is a fear which is not foreign to anyone who has experienced working with adults in an educational context. It was believed by the researcher that the length of time that a student had been out of school before beginning the TRAC program would be inversely related to persistence. Hypothesis lk: There is no significant relationship between the length of time since the last formal educational experience and persistence/withdrawal. The actual length of time since last attendance, either secondary or postsecondary, varied from 0 to 36 years with the mean length of time being 2.67 years (Table 18). A correlation ratio (eta) between the number of years and persistence or withdrawal proved to be .06. Table 18 Persisters and Dropouts Compared by Number of Years Since Previous Educational Experience  Student Status n Mean S.D. eta r> Persisters 159 2.67 3.83 .06 .43 Dropouts 127 2.67 4.63 Total 286 2.67 4.20 This figure (eta) represents the proportion of the variation attributed to the independent variable (i.e., between-group sum of squares) compared to the total variation from a l l sources (i.e. total sum of squares = that attributable to the predictor variable + variation from a l l other sources) indicating the: 130 strength of the association between the nominal variable (persistence/withdrawal) and the interval-ratio variable (length in years). In this case the proportion is not statistically significant and could be expected to appear by chance in 43 out of every 100 samples drawn randomly from the population (p = .43). This means that for TRAC students there is no statistically significant relationship between how long a student is out of school and decisions to persist in or withdraw from TRAC. In the above section, factors categorized as part of a student's "previous educational experience" have been examined to determine i f a relationship exists between each factor and the students' decision to persist or withdraw. Table 19 lis t s these factors and gives the results of the statistical analyses. Those factors for which the results indicated statistical significance, i.e., that a relationship did exist between the variables, are highlighted. Table 19 Summary of the Statistical Analyses of Factors Related to Previous Educational Experiehce vs. Persistence/Withdrawal  Factor n chi square eta p Lambda la) Failing a grade 289 .17 .68 lb) Skipping a grade 284 3.03 .08+ .04 lc) High school marks 208 3.33 .50 Id) Behavior 289 4.33 .23 le) Enjoyment of school 291 6.30 .10+ .07 If) High school program 255 2.99 .56 lg) Last grade completed 285 1.12 .89 lh) High school 288 5.12 .02* .07 graduation li ) Postsecondary program 93 4.08 .40 lj) Postsecondary 77 .33 .58 graduation lk) Time since last educational experience 286 . 06 .43 Note: *p < .05; +p > .05 < .10 131 Only for "high school graduation" did the relationship reach the p = .05 level of significance. The relationships between "skipping a grade", and "enjoyment of school" and TRAC persistence/withdrawal were within the range (p > .05 < .10) selected previously as warranting a closer look. But the three relationships do not favour only persisters. High school graduation is related to persistence whereas skipping a grade and enjoying school is related to dropout from the TRAC program. Only the relationship between graduating from high school and TRAC persistence conforms to that found in the literature. In terms of predicting which students are more likely to withdraw from TRAC, graduation from high school would seem to provide a convenient characteristic for use as a predictor. It could be used either as a means of selectively limiting enrollment or to target candidates for participation in a retention program. However, high school graduation is only one of a variety of factors which could be related to persistence in TRAC. As stated in the literature review, a single variate answer to what is obviously a multivariate problem betrays a overly simplistic understanding of attrition. Academic Achievement Three factors concerning academic achievement are indicated in previous research as being related to postsecondary persistence: entrance examination scores, self-rating of study habits, and early program performance (Lenning, et. al., 1980). Hypotheses 2a through 2c examine entrance examination scores based on results from the Canadian Achievement Tests (CAT) battery for reading and mathematics. Because self-rating of 132 study habits and early program performance pertain more to that which a TRAC student does after he enters the program, these are examined in Chapter V, also under academic skill s . As was evident in the previous section, high school graduation is related to persistence in TRAC. Academic factors are believed to be the operational components of high school graduation because each would be part of what a high school student is expected to have upon graduation. Upon entering the TRAC program a l l students wrote math and reading tests selected from the CAT battery. In this study the marks from these tests were considered as "entrance examination scores". These scores provided a measure of the basic math and reading skills which were gained in secondary school. Hypothesis 2a: There is no significant relationship between the raw scores of TRAC students on the Reading Vocabulary, Reading Comprehension, Reference Skills, Math Computation, and Math Concepts and Applications sections of the Canadian Achievement Test and persistence/withdrawal. As can be seen from Table 20, the relationship between persistence/withdrawal and the results from each of the CAT sections was statistically significant. Therefore, Hypothesis 2a is rejected. Taken as a percentage of difference between persisters and dropouts, the mean scores on the CAT vary from a low of 6.5 percent on the Reading Comprehension test to a high of 9.8 percent on Math Computation. According to the CAT norms, these scores indicate differences of between .9 and 1.5 grade levels between the scores of persisters and those of dropouts depending 133 on the test being examined. Because of the close relationship between the Reading Vocabulary, Reading Comprehension, and Reference Skills tests, i t was decided to combine the scores for each of these tests to determine i f a stronger relationship between reading skills and persistence/withdrawal would be evident using the combined scores. Table 20 Persisters and Dropouts Compared by Scores on the Canadian Achievement Tests  Student Status n Mean S.D eta P Reading Vocabulary Persisters 245 25.63 4.36 .19 .01* Dropouts 347 23.61 5.63 Total 592 24.45 5.23 Reading Comprehension Persisters 245 30.78 6.22 .19 .01* Dropouts 346 28.20 6.88 Total 591 29.27 6.73 Reference Skills Persisters 245 19.55 3.05 .19 .01* Dropouts 346 18.19 3.74 Total 591 18.76 3.56 Math Computation Persisters 246 29.94 7.94 .23 .01* Dropouts 352 26.01 8.38 Total 598 27.63 8.41 Math Concepts Persisters 246 35.62 7.60 .24 .01* Dropouts 352 31.57 8.46 Total 598 33.23 8.35 *p < .05 Hypothesis 2b: There is no significant relationship between the combined raw scores for the Reading Vocabulary, Reading Comprehension, and Reference Skills sections of the Canadian Achievement Test and persistence/withdrawal. As is obvious from Table 21, combining the raw scores for 134 the CAT reading tests resulted in a Correlation Ratio (eta = .22, p = .01) which was greater than that obtained using the individual test scores. The combined reading scores account for 22 percent of the variability in whether a TRAC student persists or withdraws. Table 21 Persisters and Dropouts Compared by Scores on the Canadian Achievement Tests Combined Reading Scores Student Status n Mean S.D eta r> Persisters 245 75.95 12.19 .22 .01* Dropouts 347 69.87 14.96 Total 592 72.39 14.19 *p < .05 Again, because of the close relationship between the Math Computation and Math Concepts and Applications sections of the CAT, TRAC students' raw scores were combined and the calculations repeated. Hypothesis 2c: There is no significant relationship between the combined raw scores for the Math Computation and Math Concepts and Applications sections of the Canadian Achievement Test and persistence/withdrawal. Similar to the findings in Hypothesis 2b, the results from the calculation using the combined raw scores from the CAT math test lead to the rejection of Hypothesis 2C. Based on the data in Table 22, a Correlation Ratio of .25 (p = .01) was found Table 22 Persisters and Dropouts Compared by Scores on the Canadian Achievement Tests Combined Math Scores Student Status n Mean S. .D eta Persisters 246 65. 56 14. .63 .25 .01* Dropouts 352 57. 58 16. .01 Total 598 60. 86 15. .94 *p < .05 135 indicating that 25 percent of the variability in the data is accounted for by the combined math scores. Here again persisters exhibited higher math scores than did TRAC dropouts. Table 23 l i s t s the results of the statistical analyses comparing factors, described as "academic", to persistence/withdrawal from TRAC. Academic factors can be described as those skills and abilities students bring with them from previous educational experiences. In this chapter TRAC students' scores on the reading and mathematics sections of the Canadian Achievement Tests battery are included as academic skills. Other skills also classified as academic, i.e., study skills and early program performance, are examined in Chapter V. Table 23 Summary of the Statistical Analyses of Academic Achievement vs. Persistence/Withdrawal Factor n eta o Lambda 2a) Scores on CAT: Reading Vocabulary 592 .19 .01* Reading Comprehension 591 .19 .01* Reference Skills 591 .19 .01* Math Computation 598 .23 .01* Math Concepts 598 .24 .01* 2b) CAT reading scores 592 .22 .01* 2c) CAT math scores 598 .25 .01* *p < .05 As mentioned in the previous section, which examined past educational experience, the connection between high school graduation and TRAC persistence is more likely a product of the skills that a student develops in high school rather than simply the fact that he has graduated. This is substantiated by the results from Hypotheses 2a to 2c. But to be justified in making this statement i t was necessary to examine the relationship between high school graduation and CAT scores. For each of the 136 tests in the CAT battery there was also a statistically significant difference between the means of high school persisters and high school dropouts. In every case these differences favored the high school graduate. These results help clarify how high school graduation, now interpreted in terms of the graduates' superior reading and mathematics skills, is related to TRAC persistence. Demographic Factors In this study demographic factors included age and socioeconomic status. Socioeconomic factors, defined rather broadly, were subdivided into variables such as the number of job changes in the year previous to beginning TRAC, the rate of pay in the last steady job, the socioeconomic status of the student (or of his parents i f the student lives at home) and social mobility with regard to the student's previous job (or parent's job i f the student is s t i l l living at home) compared to the job he was training for. Age, on the other hand, and the relationship between i t and persistence/withdrawal as described in the higher education literature is that students younger or older than students of traditional college age exhibit increased persistence (Sexton, 1965). Intuitively, and based on experience with the program, the researcher believed that the opposite was true for TRAC students. Students in this program range from 16 to over 50 years of age. Younger students come to the program attracted, in part, by the open access policy which recommends, but does not require, grade 10 completion. It is also believed that sponsored older students came as part of an increasing trend towards the 137 use of retraining as a means to client economic independence. Because the younger students were likely not to have completed high school, and because the older sponsored students may have seen the program as a means of obtaining (or retaining) financial support rather than as a means of increasing their chances for employment, the researcher felt each group would be more prone to dropping out than students of traditional college age. Because many younger students lacked the basic academic skills which come from high school graduation and older students may have been at odds with the objectives of the program, i t was believed that students in both age groups would be more likely to dropout than students closer to the mean age. If TRAC dropouts were in fact either older or younger than TRAC persisters, i t would be reflected in the difference in variance. The value of F and its probability would determine whether the difference between the variances in age is statistically significant. If this proved to be the case, i t was expected that the age of persisters would tend to cluster about the mean. Hypothesis 3: There is no significant difference between the variances in age for TRAC persisters and TRAC dropouts. As can be seen by Table 24 the difference between the variances is statistically significant although the ages of persisters rather than dropouts tend to exhibit more spread. Hypothesis 3 is redacted. Rather than being "older than or 138 younger than" these results would seem to indicate that persisters ages are skewed towards the "older" end of this continuum. Table 24 Persisters and Dropouts Compared by Variance in Age Student Status n Mean S.D. F p Persisters 235 22.96 5.83 1.28 .04* Dropout 337 21.78 5.16 *p < .05 Additional analysis indicated that no relationship existed between age and persistence/withdrawal (eta = .00, p = .92), however the difference between the mean ages of dropouts and persisters was statistically significant (t = 2.50, p = .01) with persisters being a l i t t l e more than one year older than dropouts. Conclusions regarding the importance of socioeconomic status (SES) as a factor related to attrition vary in the higher education literature. Lenning et al. (1980) indicate that i t may be a factor only for distinctly disadvantaged students. For many TRAC participants, low SES could be assumed i f they are sponsored, and may apply even i f they are fee payers. For sponsored students this assumption was based on the fact that sponsorship, in the form of social assistance or unemployment insurance benefits, is granted only to the unemployed. In addition, because TRAC is seen by many fee payers as a means of upgrading, and considering the occupations i t prepares students to enter are themselves rather low in terms of SES, those who choose TRAC likely came from employment which was already near the bottom end of the wage and occupational scale. 139 In this study SES was divided into two variables: socioeconomic rank of the student or his parent's (Hypothesis 4a and 4b), and social mobility, defined as the change in socioeconomic rank between the student's previous occupation (Hypothesis 5a), or his parent's occupation (Hypothesis 5b), and his projected posttraining occupation. In both cases SES is as defined by the revised Blishen scale (McRoberts, 1976). The updated Blishen scale ranks 500 occupations by combining income, level of education, and occupational prestige. For example, at the top of the scale, ranked as number one are "administrators, teaching & rel. [related] fields" (74) and ranked at the bottom (number 500), are "hunting, trapping & rel. [related] fields" (75). It should be noted that in using the scale "higher" SES is actually a misnomer—it is actually represented by a lower numerical rank. On the other hand, a "lower" SES is represented on the scale by a higher numerical rank. Because not a l l TRAC students lived with their parents before beginning the program, i.e., they were independent adults, this group was ranked according to the SES of their previous occupation. Hypothesis 4a: For those students who during the 12 month period prior to beginning the TRAC program held a full-time job and were not living with their parents, there is no significant relationship between their socioeconomic status and persistence/withd_*_wal. The relationship of the SES of independent students (i.e., working and not living with their parents) to persistence/withdrawal proved to be statistically significant 140 (Table 25: eta = .24, p = .04). Based upon this result Hypothesis 4b is rejected. Table 25 Persisters and Dropouts Compared by Socioeconomic Status Student Status n Mean S.D. eta r> Persisters 50 351.40 111.49 .24 .04* Dropout 29 400.86 54.93 Total 79 369.56 97.30 *p < .05 As indicated by the mean SES rank, a higher SES is related to persistence whereas a lower SES is related to dropout. Similar to high school graduation, SES has components which are the functioning variables. As stated by Lenning, Sauer, and Beal (1980): the operating variables of SES are more likely "level of familial aspiration, educational level of parents, personal educational aspirations, and involvement with the college" (16). Although the McRoberts (1976) scale is useful as a means of differentiating between persisters and dropouts, i t may be more beneficial to concentrate future research on how the antecedents of SES relate to attrition. While s t i l l living at home, a student's SES is basically that of his parents. This is especially true while the student is fully supported and part of the family unit. Being of higher SES opens up opportunities not readily available to children whose parents are fully involved in simply making ends meet. For lower SES families cable television, an at home library, travel, and private lessons in sports or music that tend to supplement the public system of education, may be unavailable options. In addition, the values regarding a "good education" may not 141 support college attendance or even high school completion for the children of lower SES parents who themselves are not high school graduates. Based on this, i t was anticipated that students of high SES parents, being better prepared and supported, would tend to be TRAC persisters. Hypothesis 4b: There is no significant relationship between the socioeconomic status of the highest ranked parent and persistence/withdrawal. Even though in terms of the correlation ratio (Table 26) the results were not statistically significant (eta = .10, p = .10), they were within the range of scores selected for further examination. Table 26 Persisters and Dropouts Compared by Socioeconomic Status of Highest Ranked Parent  Student Status n Mean S. D. eta p Persisters 143 291. 99 136 .66 .10 .10+ Dropout 106 331. 08 142 .61 Total 249 308. 53 140 .01 +p > .05 < .10 Additional analysis indicated that the difference between the mean SES ranks of persisters and dropouts was statistically significant (t = -2.18, p = .03). According to mean scores for each group, persisters came from families having higher SES than dropouts (see Table 26). Therefore, even though significantly different in terms of the SES scores of the highest ranked parent, the variable does not contribute much to the variability in the data in relation to persistence/withdrawal. Social mobility is also considered a part of SES (Sainty, 1971). Social mobility is defined as a change in SES: moving 142 towards a higher status occupation (i.e., "social climbing") versus moving towards a lower status occupation (i.e., "social sliding"), and was examined in relation to persistence /withdrawal. It was believed that a student who was taking training which was going to result in a move towards a higher status occupation would be more motivated to complete the program than a student who saw his future occupation as a step down. To determine which direction a student was moving, his SES (or his parent's) was compared to that of the occupation for which he was training. In both hypotheses (5a and 5b), the former rank is compared to that of the student's anticipated posttraining occupation to determine i f he was a social climber or social slider. To obtain a scale value for the student's posttraining occupation, each of the TRAC specialties was located on McRobert's (1976) scale and the rank of that occupation became the student's "posttraining occupation SES." For example, an Automotive Mechanics student would have a rank of 358 ("motor vehicle mechanics & repairmen" McRoberts, 76). Hypothesis 5a: For those students who during the 12 month period previous to beginning the TRAC program held a full-time job and were not living with their parents, there is no significant relationship between the difference in the SES of their previous occupation compared to their projected posttraining occupation and persistence/withdrawal. The results of the calculations for Hypothesis 5a (Table 27: eta = .17, p = .33) indicate that there is no relationship between a student's social mobility (based upon his last 143 occupation prior to taking TRAC) and decisions to persist or withdraw. Table 27 Persisters and Dropouts Compared by Social Mobility, (i.e., the Socioeconomic Status of the Student, Based Upon Previous Full-Time Employment, Versus the Student's Anticipated Posttrainincr Occupation)  Student Status n Mean* S.D. eta p Persisters 27 -43.22 119.95 .17 .33 Dropout 10 -92.50 63 .43  Total 37 -53.30 108.07  *A negative number indicates the student's anticipated posttraining occupation has a lower socioeconomic status than that of his previous occupation. A typical calculation would be: Student's Previous Occupation's Socioeconomic Status Rank = 437 Student's Anticipated Posttraining Socioeconomic Status Rank = 422 Social Mobility = 15 This student would be termed a "social climber". The idea of social mobility was also examined for students who lived with their parents. In these cases the SES of the highest ranked parent was compared to the SES for the occupation that the student was training for in calculating mobility. Hypothesis 5b: There is no significant relationship between the difference in the SES of the highest ranked parent's occupation compared to the SES of the student's projected posttraining occupation and persistence/withdrawal. The results of the correlation ratio calculation (Table 28: eta = .06, p = .47) indicate that there is no relationship between whether a student is changing his SES (as measured by the SES of his highest ranked parent) by taking the TRAC program and persistence or withdrawal. 144 Table 28 Persisters and Dropouts Compared by Social Mobility, (i.e., the Socioeconomic Status of Highest Ranked Parent Student Status n Mean* S.D. eta p Persisters 85 -72.44 150.14 .06 .47 Dropout 60 -52.32 181.00 Combined Scores 145 -64.11 163.32 *A negative number indicates that the student's anticipated posttraining occupation has a lower socioeconomic status than his highest ranked parent. A typical calculation would be: Highest Ranked Parent's Socioeconomic Status Rating = 95 Student's Anticipated Posttraining Socioeconomic Status Rank = 264 Social Mobility = -169 This student would be defined as a "social slider." For students in a program similar to TRAC, the number of job changes in the year that they were last employed before returning to school and the rate of pay in their last steady job was found by Sainty (1971) to be related to persistence/withdrawal. In his findings more job changes and a lower rate of pay was more often the case for dropouts than persisters. Although not directly stated, i t seemed inferred that those students who had a checkered job history would similarly have difficulty sticking with a training program long enough to complete. This relationship is examined in Hypothesis 6a. The fact that these students did not remain with one employer for an extended period of time may also be related to their *ate of pay assuming that rate of pay is directly related to the length of time an individual is with a single employer. The relationship between rate of pay and persistence/withdrawal is examined in Hypothesis 6b. 145 Hypothesis 6a: There is no significant relationship between changing jobs and persistence/withdrawal for those TRAC students who held jobs in the 12 months previous to beginning the program. Based upon the data in Table 29 a chi square value of .35 was calculated for Hypothesis 6a, a value that could be expected to occur by chance in 95 of every 100 samples taken from the population. Therefore, the number of times that a student changed jobs in the 12 months prior to beginning the TRAC program is not related to persistence or withdrawal. Table 29 Persisters and Dropouts Compared by the Number of Job Changes in the Twelve Months Previous to Beginning; TRAC Student Status Number of Job Changes 0 1 2 3+ Total (%) Persisters 53 15 16 6 90 (58.8) Dropouts 39 11 9 4 63 (41.2) Total 92 26 25 10 153 (60 .1) ( 1 7 . 0 ) (16.3) (6.5) (100.0) Sainty's (1971) finding, which appears to indicate that individuals who change jobs often carry this characteristic to school, is not substantiated by the results of this study. That students return to school to train for an occupation offering more stable employment appears to be an alternate and opposite explanation which would logically relate an unstable work history to increased persistence in training. Neither of these relationships appears to be evident for the research sample which, for those who were working, did tend to have a rather stable work history prior to taking training. This tendency towards a stable work history may have been influenced by the 146 fact that the "12 months previous to beginning TRAC" for the research sample would have been between April and September of 1984, a period when the unemployment rate in the Lower Mainland of British Columbia was high. The result may have been a general reluctance to change their place of employment i f they felt their present job was relatively permanent. Rate of pay was, as stated by Sainty (1971), also related to persistence/withdrawal. TRAC students were asked to indicate on the questionnaire in what range their hourly wage f e l l in their last job. These data were then compared for persisters and dropouts to determine i f a relationship existed between rate of pay and persistence/withdrawal. Hypothesis 6b: There is no significant relationship between rate of pay in the last job and persistence/withdrawal for those TRAC students who held jobs in the 12 months previous to beginning the program. Table 30 gives the figures for Hypothesis 6b from which a chi square value of 6.59, p = .16, was calculated. This value was larger than the criteria accepted for statistical significance, therefore, rate of pay in the last job prior to beginning TRAC was not related to students' decisions to persist or withdraw. Table 30 Persisters and Dropouts Compared by Rate of Pay in the Last Job  Student ^ Status Hourly Wage Rate Total $14 + $11-14 $8-11 $5-8 $< 5 m Persisters 14 13 22 51 14 114 (55. 1) Dropouts 10 5 14 42 22 93 (44. 9) Total 24 18 36 93 36 207 (%) (11.6) (8.7) (17.4) (44. 9)(17.4) (100. 0) 147 The results of these calculations indicate that for TRAC students their previous work history, i.e., job changes and rate of pay, are not related to their decisions to persist or withdraw from training. It is likely that the reasons why one stays with or leaves a job and the rates of pay in a job are dependent upon a number of complex and interrelated factors. Some of these factors may be related to a student's experiences upon returning to school but this is not obvious from these results. Table 31 li s t s the results of the statistical analyses comparing factors categorized as demographic with persistence/withdrawal. As can be seen from this table, the only factor which is related in a statistically significant way to persistence/withdrawal is socioeconomic status of students not living at home. The SES of the student's family, although not significant at the p = .05 level, does f a l l within the range warranting further examination. The relationship between SES and persistence in both cases, i.e., persisters tend to have higher SES than dropouts, follows the hypothesized relationships stated by other researchers. Because more prestigious occupations require a higher level of education and command a higher salary, those employed in these occupations are placed at the higher level of the SES scale. But the active ingredient which influences persistence in training may be the relationship drawn be-seen education and the prestige and salary which have resulted from i t . The value held by the family for a "good" education and the resulting support they give to those members who return to school, added to the 148 educational advantages that the children have had by virtue of their parent's income, likely a l l play a part in the relationship between SES and persistence. Table 31 Summary of the Statistical Analyses of Demographic Factors vs. Persistence/Withdrawal  Factor n chi square eta F x> Lambda 3 ) Variances in age: Persisters vs. Sample 572 1.10 .36 Dropouts vs. Sample 572 1.16 .14 4a) Student's SES 79 .24 .04* 4b) Parents' SES 249 .10 .10+ 5a) Social mobility based on student's SES 37 .17 .33 5b) Social mobility based on parent's SES 145 .06 .47 6a) Changing jobs 153 .35 .95 6b) Rate of Pay 207 6.59 ._16 *p < .05; +p > .05 < .10 Motivational Factors Because motivation is an important factor in any decision making process, i t must also play a role in students' decisions to persist in or withdraw from an educational program. As stated by Pantages and Creedon (1978) "the problem with studies that deal with this variable is that i t is extremely difficult to determine which motivational factors are predictive of persistence or how to accurately measure these motives once they are known" (65). They go on to define motivation as i t applies to attrition by identifying commitment, educational and occupational goals, the clarity of these goals, parental support, the value placed upon this support by the student, and the influence of the student's peers as related factors. Therefore, the problem in examining motivational factors is that there are only general guidelines, other than the intuition and experience of the researcher, available in the selection of 149 specific variables. This is especially true for short-term vocational programs where the research base is limited. Based upon the broad guidelines stated by Pantages and Creedon (1978), motivational factors believed relevant for TRAC students included: level of commitment, perceived support from parents and family members, perceived support from friends outside the Institute, long-term educational aspirations, and satisfaction or dissatisfaction with the program. In this study, level of commitment was divided into a number of variables: a stated intention to complete the total program (Hypothesis 7a), the selection of a specific area of specialization prior to entry (Hypothesis 7b), the certainty with which that choice was made (Hypothesis 7c), whether that choice was changed (Hypothesis 7d), the reasons for that choice (Hypothesis 7e), and whether the choice indicated commitment (Hypothesis 7f). A question which seems to get overlooked by attrition researchers when examining what is related to student withdrawal is whether they intended to complete the program. Failing to account for students who never intended to obtain a certificate, diploma, or degree may inflate attrition figures. These students, defined previously as "attainers," may see the mastery of certain skills or the acquisition of certain knowledge, and not the completion of a set curriculum, as the goal. Even though the TRAC philosophy included the option of leaving training once sufficient skills for obtaining employment had been gained, attrition was s t i l l calculated using the traditional yardstick of "completion versus withdrawal." Hypothesis 7a examines 150 whether students intended to complete but associates the intention to withdraw with a lack of commitment. The issue of attainers is addressed as a subsequent and separate factor. Hypothesis 7a: There is no significant relationship between a decision, made prior to beginning TRAC, to complete a l l or only part of the program and persistence/withdrawal. The result of the calculation, based upon the data in Table 32 (chi square = 1.01, p = .32), indicates that there is no relationship between intentions to complete the TRAC program and decisions to persist or withdraw. Hypothesis 7a is accepted. These results also indicate that almost a l l of the respondents (96.6 percent) began the program with the intention of completing and obtaining their certificates. Table 32 Persisters and Dropouts Compared by Intentions Regarding TRAC Program Completion  Student Status Intend to Complete YES NO Total (%) Persisters 157 4 161 (55.5) Dropout 123 6 129 (44.5) Total 280 10 290 (%) (96.6) (3.4) (100.0) The significance of this finding is that even though percent of the respondents began the program with the intention to complete, 58.8 percent of the sample withdrew. What seems obvious is that few students had intentions to complete only part of the program upon enrolling but that something happened after they began that changed their minds. This finding is not astounding given that a l l educational programs have students that withdraw prior to completion, but that more than half would 151 make the decision to dropout gives obvious reason for concern. Being motivated towards the attainment of a goal can only play a part in reaching that goal provided the objective is clearly defined in one's mind. Students who made a specific choice of a program area, such as Joinery or Steel Fabrication, exhibited a clarity of occupational goal. On the other hand, those students who began without a clear occupational goal may have difficulty seeing the program as meeting their needs and, therefore, would be more likely to withdraw. Deciding on a career goal and the subsequent selection of a specific trade prior to beginning training is examined in Hypothesis 7b in relation to persistence/withdrawal. Hypothesis 7b: There is no significant relationship between having selected or not having selected a specific specialty prior to beginning the TRAC program and persistence/withdrawal. Even though the selection of a specific specialty was optional and students could delay making this decision until they had completed the Occupational Core, the majority (71.8 percent) of the respondents (Table 33) had made a choice prior Table 33 Persisters and Dropouts Compared by Selection of a TRAC Specialty Before Beginning the Program  Student Status Specialty Selection Before YES NO Total (%) Persisters 121 41 162 (55. 7) Dropout 88 4i 129 (44. 3) Total 209 82 291 (%) (71.8) (28.2) (100. 0) to beginning the program. These results, based upon the data 152 from Table 33 (chi square = 1.49, p = .22), indicate that there i s no r e l a t i o n between choosingor not choosing a TRAC spe c i a l t y p r i o r to beginning the program and persistence/withdrawal. Because TRAC was designed to enable students to put o f f the se l e c t i o n of t h e i r trade s p e c i a l t y u n t i l they had completed the Occupational Core, there was no penalty for ind e c i s i o n . Changing from one trade to another within the same occupational family was r e l a t i v e l y easy and d i d not require the student to go back and complete d i f f e r e n t competencies. This f l e x i b i l i t y and the a c c e p t a b i l i t y of changing one's occupational goals seemed to have lessened any impact that indecision may have had upon students' decisions to p e r s i s t or withdraw. In addition to s e l e c t i n g a s p e c i f i c s p e c i a l t y p r i o r to beginning the program, the certainty with which that decision was made may have been related to subsequent decisions to p e r s i s t or withdraw. The cert a i n t y with which a student selected a s p e c i a l t y was believed to be t i e d to the c l a r i t y of h i s occupational goal and thus h i s commitment to complete the program. Indecision i s a force which was believed to be rela t e d more to withdrawal than persistence. Hypothesis 7c: There i s no s i g n i f i c a n t r e l a t i o n s h i p between the degree of cert a i n t y regarding the choice of a s p e c i f i c s p e c i a l t y and persistence/withdrawal. Although the r e s u l t s of Hypothesis 7b indicate that there i s no r e l a t i o n s h i p betwit.i when a sp e c i a l t y i s chosen and persistence/ withdrawal, there i s a considerable difference when cer t a i n t y of choice i s considered. This difference i s s t a t i s t i c a l l y s i g n i f i c a n t (Table 34: c h i square = 11.15, p = 153 .01) and knowledge of the predictor variable reduces the error in persistence/withdrawal prediction by 12 percent (lambda = .12) . Table 34 Persisters and Dropouts Compared by Certainty of TRAC Student Status How Certain in Choice Very Certain Quite Certain Uncertain Very Uncertain Total(%) Persisters 90 27 5 1 123 (56.9) Dropouts 50 32 11 0 93 (43.1) Total (%) 140 (64.8) 59 (27.3) 16 (7.4) 1 (.5) 216 (100.0) Increasing certainty about the choice of a specialty favors persistence. In comparing persisters to dropouts on a degree of certainty, i.e., "very certain", "quite certain", and "uncertain", the percentage of persisters versus dropouts in each of the three categories (64.3 percent vs. 35.7 percent, 45.8 percent vs. 54.2 percent, and 31.3 percent vs. 68.9 percent) highlights this relationship. In other words, in moving towards increasing certainty the percentage of persisters compared to dropouts increases; in moving towards uncertainty the reverse is true. This seems to indicate that students with a strong conviction that they have made the right choice stand a better chance of completing. Considering the results from Hypothesis 7b, when this choice is made is unimportant compared to how certain the student is that the choice is the right one. As stated previously, students were not required to select a specific TRAC specialty upon entering the program. This decision could be left until the student had a more definite idea of which trade he wished to pursue. As shown by the results from 154 Hypothesis 7c, lack of certainty regarding the choice of specialty is directly related to withdrawal from TRAC. By changing specialties after beginning the program a student would be making his lack of certainty obvious and, therefore, such a change could also be a predictor of withdrawal. Hypothesis 7d: There is no significant relationship between changing or not changing specialties after beginning the TRAC program and persistence/withdrawal. The results based upon the data in Table 35 confirm this expectation. A chi square value of 3.82 (p = .05) indicates that these results are statistically significant. Hypothesis 7d is rejected. In addition, a lambda figure of .05 indicates that the error in predicting persistence/withdrawal is reduced by 5 percent by using "changing specialties" as an predictor variable. Even though the greater majority of students (93.8 percent) remained with their f i r s t choice of specialty, the relationship between these variables connects not changing and persistence. Of those who changed their specialty, 66.7 percent were dropouts while only 33.3 percent were persisters. Table 35 Persisters and Dropouts Compared by Changing Specialty While in the Program  Changed No Total (%) Specialty Chancre Persisters 6 155 161 (55.5) Dropouts 12 117 129 (44.5) Total 18 272 290 (%) (6.2) (93.8) (100.0) These results reinforce the finding in Hypothesis 7c: students who are certain about their choice of specialty 155 persist. That they were certain is confirmed by the fact that dropouts were more likely to change their minds and select a specialty different from their original choice. The reasons behind choosing a particular specialty were also believed to be associated with a student's decision to persist or withdraw. Reasons based on a long term desire to practice a particular trade, previous training, or work experience in that trade, because they seem to indicate a focus on a particular trade as a career goal, were believed by the researcher to indicate commitment. Decisions based on such factors as anticipated high earnings, a friend's or relative's employment in the field, or the knowledge of cyclical personnel shortages in that trade, because they seem to focus more on the trade as a job rather than a career, were thought to represent a lesser amount of personal commitment. A lower level of commitment was believed related to withdrawal. The question to be answered was whether commitment to a specific career can be used to differentiate between dropouts and persisters. Hypothesis 7e: There is no significant relationship between the reason for selecting a specific specialty and persistence/ withdrawal. Table 36 Persisters and Dropouts Compared by Reason for Choice of Specialty  Student Reason for Choice Status Career Worked Previous Are High Friends Relatives Total Goal Before Trainincr Jobs Wacre Workincr Working (%) Persisters 66 6 5 21 6 1 2 123 Dropouts 49 8 9 19 4 0 1 95 Total 115 (%) (52. 14 8) (6.4) 14 (6, 40 .4) (18. 10 1 3W4.6) (.5) 3 (1.4) 218 (100) 156 The analysis of data relevant to this hypothesis was done twice: once separating the reasons for selecting a specific specialty, and once by combining them into reasons indicating commitment and those believed by the researcher to indicate lack of commitment. The data from Table 36, analyzing each reason separately, resulted in a chi square value of 8.07 and p = .33. Therefore, none of the stated reasons are related to persistence or withdrawal. Hypothesis 7f: There is no significant relationship between a choice of specialty indicating commitment and persistence/ withdrawal. Similar results were found when the reasons were combined into two categories showing either commitment or lack of commitment (Table 37, chi square = .05 and p = .83). Table 37 Persisters and Dropouts Compared by Choice Indicating Commitment  Student Status Choice Indicating: Commitment Lack of Commitment Total (%) Persisters 77 30 107 (54. 3) Dropouts 66 24 90 (45. 7) Total (%) 143 (72.6) 54 (27.4) 197 (100. 0) Both methods failed to produce statistically significant results. The reason for choosing a particular specialty (i.e., commitment) is evidently not related to decisions to persist or withdraw. An alternate possibility is that the reasons for choosing a particular specialty selected by the researcher did not include any that were related to persistence/withdrawal. Hypotheses 7a to 7f examined motivational factors related to 157 the student's decision to take training. The questions asked were "did he intend to complete a l l or only part of the program"; "had he selected a specialty prior to beginning the program"; "how certain was he of his choice"; "did he change specialties after beginning the program"; and "what were the reasons behind this choice and did they indicate commitment or a lack of it"? Of these, the two related to how certain he was about his choice (Hypothesis 7c and 7d) proved to be related to persistence/withdrawal. If a student was sure the choice he had made was the right one and stuck with i t he was more likely to complete the TRAC program. The influence that parents have on their child's progress in college is indicated by Sexton (1965) to be a significant variable affecting the child's achievement motivation and educational and occupational aspirations. This was interpreted to mean that the TRAC student who believes he has his parent's support will persist and complete the program. On the other hand, those students who do not believe they have this support will be more likely to withdraw. In addition, the extent to which the student values this support was also believed to be a factor. Hypotheses 8a through 8c examine the relationship between family support, and how i t is perceived by the student, and his decision to persist or withdraw. Hypothesis 8a: There is no significant relationship between fcjje student's perception that his family supports or does not support his decision to return to school and persistence/withdrawal. The results based on the data in Table 38 indicate that for 158 TRAC students there is no relationship between perceived parental support and persistence or withdrawal (chi square = .18, p = .98). Less than 2 percent of either the TRAC persisters Table 38 Persisters and Dropouts Compared by Perception of Family Support for the Decision to Return to School  Student Status Perception of Support Very Much For For Against Very Much Against Total (%) Persisters 103 56 2 1 162 (56.6) Dropouts 78 44 1 1 124 (43.4) Total (%) 181 (63.3) 100 (35.0) 3 (1-0) 2 (-7) 286 (100.0) or dropouts believed that their parents were "against" or "very much against" their participation in postsecondary training. As previous studies (Pantages & Creedon, 1978) indicate, not only is the perception of support related to persistence/withdrawal, but i t also is related to the extent that the student values this support. This may in fact provide a better indicator than the student's perceptions regarding whether he has his parents' support. The student who has this support but does not value i t may react differently to the pressures of being a college student from the student who values his parents' support. Table 39 Persisters and Dropouts Compared by Extent that Family Support, Regarding Return to School, is Valued  Student Status • — — »«-•—— —•»* Extent Opinion Valued Very Much Quite Not Very Not Total (%) a Bit M__h at a l l Persisters 45 ' 79 22 16 162 (56.1) Dropouts 52 52 14 9 127 (43.9) Total 97 131 36 25 289 (%) (33.6) (45.3) (12.5) (8.7) (100.0) 159 Hypothesis 8b: There is no significant relationship between the student's valuing/not valuing his family's opinion regarding his return to school and persistence/withdrawal. The results of this analysis (Table 39: Chi square = 5.65, p = .13) are not statistically significant. To examine either value or support separately does not allow for the possibility that a relationship between combinations of these factors is related to the criterion variable. For example, a student who perceives a lack of family support but who does not value his family's opinions may react differently from the student who perceives this lack of support and also values his family's input. Hypothesis 8c: There is no significant relationship between believing that one's family supports the decision to return to school and valuing that opinion, believing that one's family does not support the decision to return to school and valuing that opinion, believing that one's family supports the decision to return to school and not valuing that opinion,. or believing that one's family does not support the decision to return to school and not valuing that opinion; and persistence/withdrawal. Table 40 indicates that the majority of students (78.7 percent) believed their return to school was supported by their family, and that they valued this support. The relationship between these mixed variables and persistence/withdrawal is not statistically significant (chi square = 2.53, p = .47). The college student's peer group is stated by Pantages and Creedon (1978) as the "most significant external influence on the college student and is second only to the personal 160 Table 40 Persisters and Dropouts Compared by Varying Perceptions of Family Support and Valuing; of their Opinion  Student Support and Value Combined Status Support & Valued No Support & Valued Support & No Value No Support & No Value Total (%) Persisters 123 1 36 2 162 (56. 6) Dropouts 102 0 20 2 124 (43. 4) Total (%) 225 (78.7) 1 (.3) 56 (19.6) 4 (1.4) 286 (100. 0) characteristics of the student" (70). Related primarily to academic performance, which has an effect on attrition, the most important aspect of these relationships is that he finds them positive and satisfying. Similar to the way in which the student's family influenced persistence/ withdrawal, Hypotheses 9a through 9c examine the relationship between the influence of the student's friends and persistence/withdrawal. Their friends' opinions, and the extent to which they are valued by the student, were examined to determine the impact they have on his decisions to stay in school. Hypothesis 9a: There is no significant relationship between the student's perception of whether his friends support or do not support his decision to return to school and persistence/ withdrawal. Table 41 Persisters and Dropouts Compared by Perception of Friends' Support for the Decision to Return to School Student Status Perception of Support Very Much For For Against Very Much Ac^inst Total (%) Persisters 42 111 3 1 157 (55.5) Dropouts 30 88 6 2 126 (44.5) Total (%) 72 (25.4) 199 (70. 9 3) (3.2) 3 (1.1) 283 (100.01 161 The results based on the data in Table 41 (chi square = 2.63, p = .45) do not substantiate the hypothesized relationship between the student's perception that his friends support his decision to return to school and persistence or withdrawal. Because of the importance of the relationship between the college student and his peers, the extent to which peer approval was valued by the student was also of interest. Hypothesis 9b: There is no significant relationship between whether a student values his friends' opinion regarding his return to school and persistence/withdrawal. The relationship between valuing his friends' opinion and persistence/withdrawal was not statistically significant (Table 42: chi square = 5.66, p = .13). Table 42 Persisters and Dropouts Compared by Extent Friends' Support, Regarding Return to School, is Valued  Student Status » — —* . * - . _ — . > _ „ Extent Opinion Valued Very Much Quite a Bit Not Very Much Not at a l l Total(%) Persisters 14 65 61 21 161 (56. 1) Dropouts 20 47 50 9 126 (43. 9) Total (%) (11.8) 112 (39.0) 111 (38.7) 30 (10.5) 287 (100. 0) Similar to Hypothesis 8c, Hypothesis 9c examines combinations of varying student perceptions regarding their friends' opinions of their returning to school and the extent to which these opinions are valued. Hypothesis 9c: There is no significant relationship between the student who believes that his friends support his decision to return to school and values their opinion, the student who believes that his friends do not support his 162 decision to return to school and values their opinion, the student who believes that his friends support his decision to return to school but does not value their opinion, and the student who believes that his friends do not support his decision to return to school but does not value their opinion; and persistence/withdrawal. The results, based on data from Table 43, produced a chi square of 3.39, p = .33. Therefore, no combination of perceiving friends' support and valuing that support is related to persistence or withdrawal. Table 43 Persisters and Dropouts Compared by Perception of Friends' Support and Valuing of their Opinion  Student Support and Value Combination Status Support & Valued No Support & Valued Support & No Value No Support & No Value Total (%) Persisters 84 1 74 4 163 (55. 6) Dropouts 68 4 53 5 130 (44. 4) Total (%) 152 (51.9) 5 (1.7) 127 (43.3) 9 (3.1) 293 (100. 0) Planning further study, beyond that in which the student is presently registered, is considered by Lenning, Beal, and Sauer (1980), to be related to persistence. Although they refer to undergraduate students who aspire to a doctorate or professional degree, the idea of the present program of studies being a single step towards some greater objective may also have some significance for entry level trades students. Hypothesis 10: There is no significant relationship between planning to or not planning to participate in further education related to a long term career goal and persistence/withdrawal. 163 The calculation based upon the data in Table 44 (chi square = .28, p = .59) was not statistically significant. Because entry level trades training is the f i r s t step towards an apprenticeship and journeyman status, different results may have been found had students been asked about their intention to enter an apprenticeship. Table 44 Persisters and Dropouts Compared by Planned Participation In Further Education Related to a Loner term Career Goal  Student Status Planned Participation YES NO Total (%) Persisters 116 43 159 (56.2) Dropouts 86 38 124 (43.8) Total 202 81 283 (%) (71.4) (28.6) (100.0) Table 45 li s t s the results of the statistical analyses comparing factors categorized as motivational with persistence/withdrawal. Table 45 Summary of the Statistical Analyses of Motivational Factors vs. Persistence/Withdrawal  Factor n chi square V 7a) Intention to complete 290 1. 01 .32 7b) Selected a specialty 291 1. 49 .22 7c) Certainty of choice 216 11. 15 .01* 7d) Changing specialty 290 3. 82 .05* 7e) Reason for selection 218 8. 07 .33 7f) Indication of Commitment 197 • • 05 .83 8a) Family support 286 « 18 .98 8b) Family support valued 289 5. 65 .13 8c) Family support/valued Friend's support 286 2. 53 .47 9a) 283 2. 63 .45 9b) Friend's support valued 287 5. 66 .13 9c) Friend•s support/valued 293 3. 39 .33 10) Further education 283 • 28 .59 *p < .05 The only factors which attained statistical significance, "certainty of choice" and "changing specialty", were related. 164 How certain the student was about his choice of specialty and i f he changed his mind while enrolled are different approaches to the same result—a student who was unsure about his f i r s t choice would be more likely to make a change. For TRAC students both forms of uncertainty were related to withdrawal. Taken in total, the extent that motivation is related to TRAC students' decisions regarding persistence or withdrawal appears to be minimal. However, the way in which "motivation" was defined must be considered. The variables chosen to represent this factor came from other studies—studies examining the college and university population—not students participating in short-term, entry level vocational programs. As stated in Chapter 2, a major difference between these two populations is the length of their programs. As pointed out by Tinto (1987) the time in college or university is a time when educational and occupational goals evolve, students' intentions regarding completing school can change, as do their reasons for selecting a particular field. Even their perceptions and values regarding their families' and friends' opinions of their participation can shift during their two- or four-year programs. What these results indicate is that whatever motivates entry level trades students and students in other short term programs s t i l l remains to be discovered. Following this discovery, the way in which these motivational factors are related to attrition can be better explored. Learner Self-Confidence Self-confidence has been discussed by previous researchers (Darkenwald, 1981; Londoner, 1972; Fisher, 1969) but i t has 165 never been described in terms which allow i t to be measured. In this study the instrument used to measure learner self-confidence was Rotter's IE Scale. Rotter's instrument is a 23 point scale which ranges from "0" (internally controlled) to "23" (externally controlled). The researcher's belief was that students who were high school dropouts and TRAC dropouts will tend to score more to the external end of the IE Scale. Basically, this means that the dropouts tend to believe that factors other than their own abilities, such as luck or fate, have the primary role in determining the outcomes of their educational experience (low learner self-confidence). Alternately, high school graduates and TRAC persisters would tend to score towards the internal end of the scale, indicating a belief that they themselves play the primary role in their success or failure as high school or TRAC students (high learner self-confidence). Hypothesis 11: There is no significant relationship between scores on the I-E Scale and persistence/withdrawal from the TRAC program. The calculation of the correlation ratio from the data in Table 46 resulted in eta = .07 and p = .09. Table 46 TRAC Persisters IE Scale and Dropouts Compared by Score on Rotter's Student Status n Mean S.D. eta p Persisters 237 9.51 3.88 .07 .09+ Dropout 336 9.77 3.75 Total 573 9.66 3.81 + p > .05 < .10 According to the previously set criteria for statistical 166 significance, the relationship between locus of control (i.e., learner self-confidence) and persistence/withdrawal is not significant but warrants closer examination. TRAC dropout appears to be more related to external factors than TRAC persistence. According to the rationale stated in Chapter II by the researcher, this would indicate that dropouts have less confidence in their ability as learners than TRAC persisters. The direction of the relationship between lack of self-confidence as a learner and withdrawal from TRAC is consistent with that envisioned by the researcher. Hypothesis 12: There is no significant relationship between scores on the I/E Scale and graduating or failing to graduate from high school. The data in Table 47 produce a statistically significant result (eta = .12, p = .04). Hypothesis 13 is rejected. What these results indicate is that high school dropout is related more to internal factors than is high school persistence. In other words, high school dropouts, not graduates, are more inclined to believe that they play the major role in determining what happens to them in an educational context. In terms of self-confidence as a learner these are the students who know that their success or failure is dependent upon them and not on forces which are beyond their control. This Table 47 High School Graduates and Nei;graduates Compared by Score on Rotter's I/E Scale Student Status n Mean S.D. eta V Graduate 182 9.70 4.03 .12 .04* Noncrraduate 64 8.58 3.14 Total 246 9.43 3.83 *p < .05 167 finding is opposite to that believed to be the case by the researcher. In Table 48 results of the statistical analyses comparing learner self-confidence and completing or dropping out of both TRAC and high school are listed. As indicated, both correlations reach or approach statistical significance. An internal orientation is related to persistence in the TRAC program, whereas, in comparison with high school graduation, this orientation is more closely related to dropping out. Table 48 Summary of the Statistical Analyses of Learner Self-Confidence Factors vs. Persistence/Withdrawal  Factor n eta 11 ) TRAC persistence/withdrawal 573 .07 .09+ 12 ) High school persistence/ 246 .13 .04* withdrawal *p < .05; +p > .05 < .10 An internal locus of control is synonymous with seeing one's self in control of the events which effect one's l i f e . In this research high school dropouts and TRAC persisters appear to have this orientation. Regarding a student's experience in high school, these results may indicate that dropping out is a conscious decision made by the student as a means of regaining control over his l i f e . This decision is not necessary for those who persist. For them the decision of when to leave high school is "external"—it is made by others—they leave upon graduation. In the TRAC program this is different—students left when they _fi_.se. There were not the legal and social constraints attadned to withdrawal from the TRAC program that there were in high school.It is quite possible that TRAC dropouts, when questioned about the reason for leaving the program, may give reasons which 168 attach "blame" to something other than their inability to complete. It is quite common for dropouts in general to indicate reasons for withdrawal other than those under their own control. Being aware of this orientation when students enroll may be useful in tuning in to this type of behavior as a withdrawal warning signal when external factors begin to negatively affect their progress. More research is needed to clarify this relationship. Conclusion In this chapter factors "borrowed" from research on attrition from secondary and postsecondary school were examined in relation to how they applied to TRAC students. More specifically, this chapter dealt with a l l those things that may be related to students' decisions to persist or withdraw which are acquired prior to the student's actual enrollment in TRAC. These factors included previous educational experience, academic factors, demographic factors, motivational factors, and learner self-confidence. That a student's educational experiences are related to his subsequent experiences is obvious from this research. In some cases this is direct, whereas in other cases i t tends to be more subtle. Upon leaving school, the student takes with him both skills and perceptions. The skills, about which the high school diploma provides a certification of competence, are applied in subsequent learning. As seen in this study, high school graduation was related to the successful completion of TRAC and higher level math and reading skills, also tied to high school graduation, were also related 169 to TRAC persistence. For TRAC students, socioeconomic status also proved to be related to persistence. This was the case for students who were self-supporting prior to beginning the program. As stated previously the operating variables of SES may have been the access the student had to resources which supported their public school education and the extent to which education was valued by their parents, not where they or their parents f e l l on a scale of income, education, and occupational prestige. Unfortunately, instructors, counsellors, and administrators can not do much to compensate for a lack of educational opportunities experienced as a child. What this finding may provide, however, is a factor that can be used to identify adults who may need extra educational support in order to successfully complete their training. Another factor that discriminates between TRAC persisters and dropouts was indecision. The TRAC student who was unsure about his choice of trade specialty, and who later changed his occupational objective, was more likely to dropout. For the TRAC student, knowing what he wanted, having faith in his decision, and sticking with that choice, was related to completing the program. Students who request general rather than specific information about program offerings, who inquire about two or more unrelated trade programs, and/or who select a career progr_li, based upon which will get them into school most quickly may be giving clues about their indecisiveness. This kind of behavior should prompt the person dealing with the prospective student that vocational guidance may be appropriate prior to 170 accepting an application. The finding that high school graduates from the research sample were, according to the definition, less confident learners than those who dropped out was opposite to that anticipated by the researcher. A possible explanation was that high school dropouts, by walking away from what was perceived as a bad situation, were exercising control over their fate. This finding may indicate that these high school dropouts tend to make decisions based upon what they perceive to be in their own best interests as learners. If the educational program is perceived as meeting a need, they will persist. If the opposite is true, they will withdraw. Considering that dropping out of high school is also related to dropping out of TRAC this group of students may carry this characteristic with them to subsequent attempts at education. In the following chapter those factors which are related to a student's decision to persist or withdraw but which are encountered after the student has started postsecondary school are examined. Following this, both pre-entry and postentry significant factors are combined in the development of a prediction formula to indicate which are the strongest predictors and which combination of factors has the greatest predictive u t i l i t y . 171 CHAPTER V RESEARCH FINDINGS: POSTENTRY FACTORS T i n t o ' s (1987) theory of student departure is partially based on the transition a student makes as he moves from the role of family member and high school student to that of college student. T i n t o refers to Van Gennep's (1960) "rites of passage" and applies the stages of "separation", "transition", and "incorporation" to the changing role of the student as he moves from his precollege experiences to those encountered as part of his postsecondary schooling. The essential point is that T into differentiates between the pre- and postentry phases of a student's career. This distinction is observed in this study. Chapter V is the second of three chapters in which the research findings are examined. In the previous chapter factors which were a part of the student's experiences before he began his postsecondary training were examined. In this chapter factors which were part of his experiences after he began his postsecondary career are studied. The final chapter of the three reexamines variables found to be related to persistence or withdrawal in an attempt to construct a prediction formula for identifying potential dropouts. In this chapter factors labeled as academic, motivational, financial, and institutional, indicated in previous studies to be related to persistance/withdrawal, are examined. In addition, students Identified as attainers i . e . , who define "completion" in terms of the attainment of personal rather than institutional goals, are compared to persisters and dropouts to determine under which of these two classifications they should f a l l . 172 Throughout the chapter, each variable is identified, a hypothesized relationship is stated, and the data gathered are analyzed, leading in turn to the acceptance or rejection of each hypothesis. Postentry Factors Related to Attrition The transition from high school to a postsecondary institute can be a rather traumatic experience. This is substantiated by the fact that some students, whose performance in high school was sufficient to gain them acceptance to college or university, leave prior to completion. Apparently these students enter postsecondary schooling with preconceived notions and expectations, based upon their past educational experiences, which do not f i t the reality of actual participation. It seems reasonable to believe that few students venture into higher education planning from the outset to withdraw. Therefore, something happens after they enroll which leads to the decision to dropout. Although Tinto (1987) acknowledges that what a student brings with him plays a major part in how he deals with his college experiences, he goes on to state that ". . . researchers generally agree that what happens following entry is, in most cases, more important to the process of student departure than what occurs prior to entry" (47). These postentry factors, as they pertain to TRAC students at PVI, are examined in following sections. Academic Factors Study habits and early program performance are categorized as postentry "academic factors" in this research. Even though study habits can be considered as skills the student brings from 173 high school i.e., a pre-entry factor, what determines their classification as a postentry factor is how they were applied by the student while he was in the TRAC program. Variables such as believing enough time was spent studying (Hypothesis 13a), perception of actual time spent studying compared to others (Hypothesis 13b), use of a variety of study techniques (Hypothesis 13c), average number of hours spent at PVI (Hypothesis 13d), and where the majority of study time was spent (Hypothesis 13e), were used to define "study habits" in this research. The student's performance in the i n i t i a l phases of his college program has also been indicated to be related to subsequent decisions to persist or withdraw (Pantages & Creedon, 1978). Success early in the program is related to subsequent success and to persistence. Because the TRAC program is competency-based, the content is divided into individual competencies, each of which is evaluated via a practical or written test. The student begins the process of evaluation the fi r s t day and proceeds through the material at his own pace. How the number of tests attempted, passed, and excelled upon is related to persistence/withdrawal is examined in Hypotheses 14a and 14b. Failing to "pass" a theory or practical test would be a clear indication to the student that his pretest preparation was inadequate. This would be reinforced each time he failed. Continual failure and the need to rewrite many tests a second or third time was believed to be a characteristic more common to dropouts than persisters. It was also believed that students who 174 perceive that their study time was inadequate would tend to be dropouts rather than persisters. Data regarding the student's perception of the adequacy of his pretest study were obtained indirectly from answers to two questionnaire items. One item asked students whether other TRAC students spent enough time studying prior to writing a theory test, and a second item asked them to compare their study time to that of others. Those students stating that they thought others spent enough time and who indicated that they themselves studied "very much more", "more", or the "same", and those who felt others did not spend enough time but felt they themselves spent "more" or "very much more" were categorized as perceiving their study time as adequate. Those students who felt that others spent enough time but they themselves spent "less" or "very much less", and those who felt others did not spend enough time and who themselves felt they spent the "same", "less" or "very much less" time, were categorized as perceiving their study time as inadequate. Hypothesis 13a: There is no significant relationship between a student's perception that he spends enough/not enough time studying before writing a theory challenge and his persistence/withdrawal. A chi square value of 10.4 (p = .01), from the data in Table 49, indicates that the perceived adequacy of study time differentiates between persisters and dropouts. Hypothesis 13a is rejected. In addition, a lambda statistic of .12 indicates that this information reduces the error in predicting the criterion variable by 12 percent. 175 appears to favor persisters: 75.8 percent felt their study time Table 49 Persisters and Dropouts Compared by Perception of Spending Enough or Not Enough Time Studying Prior to Writing a Student Status Spending Enough Time Studying Enough Not Enough Total (%) Persisters 119 38 157 (55.9) Dropouts 71 53 124 (44.1) Total 190 91 281 (%) (67.6) (32.4) (100.01 to be adequate. On the other hand, only 57.3 percent of TRAC dropouts felt the same way. What this indicates is that students who dropped out tended to feel that they were not expending the time necessary to prepare for tests. If, upon further examination, the relationship between the number of attempts required to pass a test and persistence/withdrawal indicates that dropouts require more attempts than persisters, then i t would seem reasonable to conclude that dropouts knew they were not doing well and attributed this in part to a lack of time spent studying. While the conclusion reached in the previous calculation indicates that persisters regard their study time as adequate, i t does not indicate who works harder at success: persisters or dropouts. It may be that persisters "work smarter, not harder" and therefore do not have to spend as much time to successfully master the material. An alternate and perhaps more plausible explanation may be that persisters have learned through experience that increased study time increases the likelihood of being successful. Hypothesis 13b: There is no significant relationship between 176 the student's perception regarding the amount of time spent in pretest study compared to other TRAC students and his persistence/withdrawal. The calculations, based on the data from Table 50, indicate that the results are statistically significant (chi square = 23.24, p =.01). Hypothesis 13b is rejected. A lambda value of .11 indicates that an 11 percent reduction in the error of predicting the criterion variable is possible by knowing which group believes they spend more time studying compared to other students. Table 50 Persisters and Dropouts Compared by Perceptions of Amount of Student Amount of Time Spent Compared to Others Total (%) Status Very Much More More Same Less Very Much Less Persisters 22 59 61 17 2 161 (56.3) Dropouts 5 26 62 26 6 125 (43.7) Total (%) 27 (9.4) 85 (29. 123 7) (43. 43 0) (15.0) 8 (2.8) 286 (100.0) With 50.3 percent of the persisters compared to 24.8 percent of the dropouts believing they spend more time studying than other students, and 25.6 percent of the dropouts compared to 11.8 percent of the persisters indicating less time spent than others, the second alternative i.e., persisters work harder, seems to be the case. In addition to spending time studying, knowing how to study would make the most effective use of this t i s _ . Having a repertoire of study skills to apply to learning new material is believed to be related to successful program completion. On the questionnaire students were asked to check off, from a l i s t of 1 7 7 seven study techniques, those that they used in preparing to write a theory test. A correlation ratio (eta) was calculated to determine i f a statistically significant relationship existed between the number of study skills used and persistence/ withdrawal. Hypothesis 13c: There is no significant relationship between the number of study skills used and persistence/withdrawal. Calculations, based on the data in Table 51, produced a nonsignificant result (eta = .01, p = .85). Table 51 Persisters and Dropouts Compared by Number of Study Skills Used  Student Status n Mean S.D. eta Persisters 161 2.39 1.24 .01 .85 Dropout 125 2.42 1.56 Total 86 2.40 1.39 These results indicate that both persisters and dropouts use about the same number of study skills. It was felt that where the two groups failed to differ in number they may differ in kind. Further analysis was done to determine what skills persisters and dropouts used and i f there was a difference between the two groups. The study techniques listed on the questionnaire and the percentage of each group who used them are listed in Table 52. Table 52 Persisters and Dropouts Compared by Percentage of Each Group Who Used Selected Study Techniques ' Study Technique % of Persisters % of Dropouts Read the Learning Guide 64.4 63.8 Read Self Test f i r s t 16.6 23.8 Underlined in book 36.8 35.4 Made notes 23.3 19.2 Did Self Test 73.6 62.3 Others quizzed me 9.8 16.2 Did practical f i r s t 8.5 8.0 178 Based on these results the most popular study methods were reading the Learning Guides and completing the Self Test at the end of each module prior to writing the test. Considering that the Learning Guides were the primary means of delivering the course content, i t was anticipated that this percentage would be higher. Even so, i t appears that 33.7 percent of the persisters successfully completed the program without selecting this as a method of study. The only major difference between persisters and dropouts is the extent to which each group used Self Test questions as a means of preparing for module tests. Self Tests were at the end of each module and were designed to test the student's knowledge of the content prior to writing the test. Because many of the questions on the Self Test were similar to those found on the theory tests i t appears that their use may have given persisters a slight edge. That persisters had some advantage becomes obvious when comparing the number of times both groups had to write tests to meet or exceed the criteria of competence (Hypothesis 14a and 14b). TRAC was structured in such a way that students did not have to attend according to a rigid timetable. Students could, theoretically, come to PVI only to write tests or to participate in scheduled shop activities. The rest of their study time could be spent off campus. Officially, the length of the training day was six hours and the training week ran from Monday through Friday. Therefore, the maximum amount of scheduled time that students could be in attendance per week was thirty hours. Hypothesis 13d: There is no significant relationship between 179 the average number of hours per week spent at PVI and persistence/withdrawal. On the questionnaire students were asked how many hours per week, on average, they spent at PVI. The results of the calculation (eta = .17, p = .01), based on these numbers (Table 53), indicates that the relationship between hours spent at PVI and persistence/withdrawal is statistically significant. Hypothesis 13d is rejected. Table 53 Persisters and Dropouts Compared by Hours per Week Spent at PVI  Student Status n Mean S.D. eta p Persisters 159 25.35 9.25 .17 .01* Dropout 125 21.96 9.58 Total 284 23.86 9.53 *p < .05 A comparison of the mean number of hours per week that persisters and dropouts spent at PVI differed by 3.39 hours with persisters spending more time at school than dropouts. Therefore, the TRAC persisters' perception that they spend more time studying than TRAC dropouts is substantiated by this finding. The 40 minutes more per day that persisters spent at school seem to have paid off in that they completed the program. As previously noted, TRAC students had considerable flexibility regarding where they prepared to write their theory tests. It is possible that many students chose to do their preparation off campus and the fact that dropouts spent less time at PVI did not necessarily mean that they were not engaged in study elsewhere. Generally, i t was believed by the researcher that doing school work at school would be more characteristic of 1 8 0 persisters. Hypothesis 13e: There is no significant relationship between spending the majority of study time at/away from PVI and persistence/withdrawal. As can be seen from Table 54, off campus study was an option used by only 10.8 percent of persisters and 15.4 percent of the dropouts. The chi square value of .97 (p =.32) indicates that there is no statistically significant relationship between on/off campus study and persistence/withdrawal. Table 54 Persisters and Dropouts Compared by Majority of Study Time At/Away from PVI  Student Status Majority of Study Time Spent At Awav Total (% ) Persisters 141 17 158 (56. 2) Dropouts 104 19 123 (43. 8) Total 245 36 281 (%) (87.2) (12.8) (100. 0) Even though dropouts did choose to study off campus more than persisters, i t is not possible to conclude from these results that the additional 40 minutes per day that persisters spent at PVI were also utilized by dropouts, but not at school. Even i f i t were possible to make this statement, the conclusion from Hypothesis 13d clearly indicates that on campus study is directly related to persistence. Superior performance early in the program has been indicated in previous studies to be related to persistence (Pantages & Creedon, 1978). It is believed by these researchers that good performance at the beginning of a student's program is self-reinforcing and leads to sustained effort which keeps the 181 student in school. In the present study, early program performance is measured by examining the proportion of tests passed (Hypothesis 14a) and/or excelled at (Hypothesis 14b) compared to tests attempted during the early stages of a student's program. Because TRAC is competency-based, performance is measured in relation to a criterion representing a minimum level of competence. This minimum passing grade (80 percent) is recorded as a mark of "2" on computer records and represents a student's results on a theory test. Students are given a mark of "3" i f they exceed the criteria for competence and a "1" indicates that competency had not been attained. Practical tests were graded with a pass/fail system with a pass marked as a "2" and a f a i l as a "1." To determine early program performance, the f i r s t six weeks of each student's record was examined and the total of each of the three marks was tallied. Six weeks were chosen to give students time to become familiar with the program and to allow them enough time to complete about half of Common Core. The proportion of tests passed or exceeded was calculated by dividing the number of "2"'s and "3"'s by the total number of tests attempted. If a student passed or exceeded a l l tests on the f i r s t attempt, proportions for tests passed or exceeded would be closer to 1.00. As the number of attempts increased relative to the number of tests passed or exceeded this number would become smaller. Hypothesis 14a: There is no significant relationship between the proportion of tests passed to tests attempted during the fir s t six weeks of the program and persistence/withdrawal. 182 As can be seen from Table 55 the relationship between the proportion of tests passed to tests attempted i.e., early program Table 55 Persisters and Dropouts Compared by the Proportion of Tests Passed to Tests Written During the First Six Student Status n Mean S.D. eta Persisters 230 .98 .04 .30 .01* Dropout 340 .87 .23 Total 570 .91 .19 *p < .05 performance, is related to the criterion variable (eta — .30, p = .01). Hypothesis 14a is rejected. Persisters passed significantly more tests on their first attempt than did dropouts. In addition, the proportion of tests passed to attempted shows considerably greater variation (Standard Deviation: persisters = .04, dropouts = .23) for dropouts than persisters. This would indicate that dropouts were far less consistent in the proportion of tests passed than were persisters. Similar results were found when comparing the proportion of tests which exceeded the criteria for competence to a l l tests written for persisters and dropouts during the fi r s t six weeks of their program. In this case, the proportion of tests exceeding the criteria was calculated by dividing the number of "3"1 s by the total number of tests attempted. <^_)othesis 14b: There is no significant relationship between the proportion of tests exceeded to tests attempted during the f i r s t six weeks of the program and persistence/withdrawal. 183 Again the relationship is statistically significant (eta = .25, p = .01) and favours persisters. Not only do persisters pass significantly more tests on the fi r s t attempt (Table 55), they also obtain significantly higher scores on these attempts than do dropouts (Table 56). Table 56 Persisters and Dropouts Compared by the Proportion of Student Tests Exceeded to Tests Written During the First Student Status n Mean S.D. eta P Persisters 230 .36 .15 .25 .01* Dropout 340 .27 .19 Total 570 .31 . 18 *p < .05 Table 57 l i s t s the results of the statistical analysis comparing factors described as "academic" to persistence/ withdrawal. Academic factors were defined in this study as those skills and abilities students bring with them from previous educational experiences. In this chapter, however, the focus is on how TRAC students applied these skills after they began the program. A l l of the factors except the "number of study skills" and "study at/away from PVI" were related to the criterion variable. In each case, the relationship was between those factors which could be used to describe a "good student": one Table 57 Summary of the Statistical Analyses of Academic Factors vs. Persistence/Withdrawal  Factor chi square eta p Lambda 13a) Enough study time 10.40 .01* .12 13b) Study time compared 23.24 .01* .11 13c) Number of study skills .01 .85 13d) Hours per week at PVI .17 .01* 13e) Study at/away from PVI .97 .32 14a) Tests passed/attempts .30 .01* 14b) Tests exceeded/attempts .25 . 01*  *p < .05 184 who spends more time studying, spends more time at school, and demonstrates better performance early in the program; and persistence. Because students' performance was measured during the i n i t i a l six weeks of the program, i t seemed to substantiate that in addition to already being a good student, getting off to a good start may also have been related to persistence. Even though i t is not possible to know how many potential dropouts gained enough momentum during those fi r s t six weeks to set a precedent which carried them through the rest of the program, i t does suggest the need for examining the relationship between i n i t i a l successful experience and persistence. Because TRAC was self-paced and students had minimal contact with instructors, the confirmation and reinforcement for early successes was largely internal. Motivational Factors In the previous chapter motivational factors such as level of commitment, perceived support from family and friends, and long term educational aspirations, a l l which the student brought with him to his postsecondary experience, were examined. But i n i t i a l motivation may change upon confrontation with the realities of actual participation. Even though persisters are believed to be more willing to endure dissatisfaction with the program, satisfaction is s t i l l thought to be more closely related to persistence (Lenning, et al., 1980). A major determinant of a student's satisfaction is the extent to which he believes his goals are being met through participation in the program. In this chapter the extent to which students believed 185 they and their friends were gaining from the program (Hypotheses 15a to 15c), their willingness to recommend TRAC and/or PVI (Hypotheses 16a to 16c), and their estimate of the "success rate" of the program (Hypothesis 17), are examined as a means of validating the anticipated effects of this kind of motivation on persistence/ withdrawal. On the questionnaire students were asked: "During Common Core how much did you feel you were getting from the program?" Choices ranged from "a great deal" to "nothing at a l l " . The reason that their estimation was limited to Common Core was because of a l l the students who dropped out, 80 percent did so during this f i r s t part of the program and,..therefore, i t is the only part with which every student would have had at least some experience. Because Common Core appeared to be the hump over which students had to get in order to succeed in the program, i t was believed that i f they felt i t held some value for them in meeting their educational goals, they would persist.' Hypothesis 15a: There is no significant relationship between a student's belief that he was/was not gaining something from the program while in Common Core and his persistence/withdrawal. Table 58 Persisters and Dropouts Compared by Belief that they were Gaining Something; From the Program During Common Core Student Gaining How Much Total status Very Much Quite a Bit A Bit Not Very Nothing Much (%) Persisters 7 28 45 62 19 161 (56. 5) Dropout 9 28 33 33 21 124 (43. 5) Total (%) 16 (5.6) 56 (19.6) 78 (27. 95 4) (33.3) 40 (14.0) 285 (100. 0) 186 The results of the calculation (Chi square = 6.35, p = .17) indicates that there is no statistically significant relationship between believing that he was gaining something from Common Core and the student's persistence or withdrawal. Because of the important influence that a student's peers exert upon his college behaviour (Pantages and Creedon, 1978), what he believes his friends were gaining from the program may also be related to his decisions to persist or withdraw. If his friends felt that Common Core had something of value to contribute to their learning of a trade, and this perception was obvious to the student, then i t is believed that he too would see the value and persist. Hypothesis 15b: There is no significant relationship between a student's belief that his friends were/were not gaining something from the program while in Common Core and his persistence/withdrawal. The results of the calculation (chi square = 11.14, p = .03, lambda = .09) indicate that there is a statistically significant relationship between the criterion and predictor variables (Table 59). Hypothesis 15b is rejected. Table 59 Persisters and Dropouts Compared by Belief that his Friends were Gaining Something from the Program During Common Core  Student Gaining How Much Total Status Very Much Quite a Bit A Bit Not Very Nothing Much (%) Persisters 4 14 43 81 16 158 (56. 6) Dropouts 6 21 35 41 18 121 (43. 4) Total (%) 10 (3.6) 35 (12.5) 78 (28. 122 0) (43.7) 34 (12.2) 279 (100. 0) The results from Table 60 indicate that dropouts were more 187 positive regarding what they believed their friends were gaining from the program than were persisters. The fact that these results are statistically significant and yet opposite to the anticipated results could possibly mean one of a number of things. The fir s t and most obvious conclusion would be that TRAC students operate independently from the influence of their friends—regardless of what others felt about the value of the program students would persist or withdraw unimpeded by the influence of others. A second possibility may be that participation in Occupational Core and Specialty, the two parts of the program most directly related to hands-on trades skills, may have clouded persisters' recollections of their friends' comments about the value of Common Core resulting in a more negative rating. It is also possible that dropouts may have had friends who were persisters thereby attributing these friends' successes to what they learned in Common Core. It was believed that a truer picture could be obtained i f the student's own feeling of gain plus those perceived to be his friends' feelings were considered together. Hypothesis 15c: There is no significant relationship between a student's belief that both he and his friends benefitted from Common Core, belief that he benefitted while his friends did not, belief that he did not benefit while his friends did, or a belief that neither he nor his friends benefitted; and his persistence/ withdrawal. The result of combining the four possible options of believing/not believing anything was gained by either the student or his friends was not statistically significant (Table 188 60: chi square = 5.05, p = .17). Table 60 Persisters and Dropouts Compared by Combined Beliefs that he and /or his Friends were Gaining Something; From Common Core  Student He and/or Friends Gain  Status He/Friends He Gains Friends Neither Total(%) Gain Only Only He/Friends  Persisters 52 26 9 71 158 (57.0) Dropouts 52 15 10 42 119 (43.0) Total 104 41 19 113 277 (%) (37.5) (14.8) (6.9) (40.8) (100.0) Although none of the possible combinations differed from the expected results by an amount which was statistically significant, the results are consistent with the finding of the other hypotheses. Persisters and dropouts present almost a mirror image of each other; 44.9 percent of persisters believed that neither they nor their friends gained, while 43.7 percent of the dropouts believed that both they and their friends had gained from the Common Core (Table 60). The results from Hypotheses 15a through 15c only partially substantiate that found in the literature: persisters, who felt they gained l i t t l e from Common Core, seem able to endure their dissatisfaction. On the other hand, dropouts, who, according to the research should have have shown greater dissatisfaction with the program, were more satisfied with what they got. This leaves unanswered the question of whether the positive perception of the benefits gained during Common Core i.e., satisfaction, or the ability to put up with dissatisfactions with this part of the program, is more closely related to persistence. The culmination of a student's belief that the program ful f i l l e d his needs, i.e., an indication of his basic 189 satisfaction with TRAC, would be his recommending i t to others (Hypothesis 16a). Because a willingness to recommend is considered indicative of one's final evaluation, representing a l l positive minus a l l negative aspects, i t can be used as a measure of satisfaction which may be more valid than simply asking students i f they were satisfied with the TRAC program. Simply put, i t is believed that a student who was satisfied with the program would persist. In addition, because satisfaction may be based more upon how one was treated by the Institute, recommendation of PVI was included as a separate variable in Hypothesis 16b. And, to determine i f a combination of recommending/not recommending TRAC and/or PVI was related to whether a student persisted, the four possible combinations were examined in Hypothesis 16c. Hypothesis 16a: There is no significant relationship between a student's recommending/not recommending the TRAC program to others and his persistence/withdrawal. A chi square value of .51 and p = .48 (Table 61) indicates that no relationship exists between recommending or not recommending the TRAC program and persistence or withdrawal. Table 61 Persisters and Dropouts Compared by Willingness to Recommend TRAC  Willing To Recommend YES NO Total (%) Persisters 78 85 163 (56. 4) Dropouts 55 71 126 (43. 6) Total 133 156 289 (%) (46.0) (54.0) (100. 0) Neither persisters or dropouts were overwhelmingly positive 190 in their willingness to recommend TRAC to others (persisters: 47.9 percent, dropouts: 43.7 percent). By translation this would indicate that less than half of students in either group were satisfied with the program. While a student may be satisfied with the program (i.e., willing to recommend) he may not be satisfied with the institution where i t is delivered. His relative level of satisfaction with the institution may vary for reasons which are beyond the institute's control, such as the distance the student has to commute to attend classes, or, for reasons directly related institute policies and procedures, such as the hours of operation. Satisfaction with PVI was also believed to be related to students' decisions to persist or withdraw. Being satisfied with PVI (i.e., recommending PVI) was believed to be more characteristic of persisters. Hypothesis 16b: There is no significant relationship between a student's recommending/not recommending PVI as a place to take training and his persistence/withdrawal. The results of the calculation (chi square = .73, p = .39) indicate that there is no relationship between satisfaction with PVI and persistence/withdrawal (Table 62). Table 62 Persisters and Dropouts Compared by Willingness to Recommend PVI  Willina to Recommend? YES NO Total (%) Persisters 137 21 158 (56.0) Dropouts 103 21 124 (44.0) Total 240 42 282 (%) (85.1) (14.9) (100.0) 191 Although not willing to recommend the TRAC program, the greater majority of both persisters and dropouts were willing to recommend PVI as a place to take training (persisters: 86.7 percent; dropouts: 83.1 percent). In general, TRAC students seem very satisfied with PVI. It is possible that persisters were generally satisfied with both TRAC and PVI and that their willingness to recommend both was more strongly related to persistence than was their willingness to recommend only one, the other, or neither. Combinations of willingness to recommend/not recommend both or either TRAC and PVI were examined to determine the strength of this relationship. Hypothesis 16c: There is no significant relationship between recommending TRAC and PVI, recommending TRAC but not PVI, not recommending TRAC but recommending PVI, or not recommending TRAC or PVI; and persistence/withdrawal. The chi square results, based on the data from Table 63 (Chi square = 1.33, p = .72) give no indication that such a relationship exists. Table 63 Persisters and Dropouts Compared by Willingness to Recommend TRAC and/or PVI  Student Status Williner to Recommend TRAC PVI and TRAC Not PVI PVI Not TRAC Not PVI Not TRAC Total(%) Persisters 65 10 72 11 158(56.6) Dropouts 46 8 54 13 121(43.4) Total (%) 111 (39. 8) 18 (6.5) 126 (45.2) 24 (8.6) 279 (100.0) Again the differences between persisters and dropouts were small and the students' willingness to recommend PVI but not 192 TRAC was obvious with 45.6 percent of the persisters willing to recommend PVI but not TRAC compared to only 6.3 percent who would recommend TRAC and not PVI. Similar results were found among the dropouts: 44.6 percent recommend PVI but not TRAC and 6.6 percent recommend TRAC but not PVI. Although none of the variables examined in Hypotheses 16a through 16c produced statistically significant results, the similarity of the responses of both persisters and dropouts indicates that satisfaction or lack of satisfaction with the program or the institute was not related to students' decisions to persist or withdraw. These results are important because they indicate that the decision not to include the "program" as a major factor in decisions by students to withdraw did not result in a failure to examine a variable accounting for a major portion of the withdrawal variance. Had i t become obvious from these results that satisfaction with the program clearly differentiated persisters from dropouts then the various components of the TRAC system would need to be examined in detail. A student's estimate of the number of TRAC students who graduate compared to the total number who began the program was also considered" as a way in which he evaluates the program's success. It was felt that students who believed the program to be a failure would tend to believe that very few students graduate. The opposite wail* felt to be the case for students who see the program as a success. The estimation of the "success" or "failure" of the program was believed to be a reflection of the success or failure of the student being asked. Therefore, i t was 193 hypothesized that "failures" i.e., dropouts, would tend to have a low estimation of completion compared to that of persisters. Hypothesis 17: There is no significant relationship between a student's estimate of the percentage of students who successfully complete the program and his persistence/withdrawal. To determine i f students' evaluation of the program's success was related to persistence/withdrawal students were asked on the questionnaire to estimate how many out of every ten students who began TRAC would complete the program. As can be seen from Table 64 the relationship between persistence/withdrawal and the estimation of student completion rate is statistically significant (eta = .15, p = .01). Hypothesis 17 is rejected. Table 64 Persisters and Dropouts Compared by Their Estimation of the Completion Rate for TRAC Students.  n Mean(%) S.D. eta p Persisters 155 62.3 18.9 .15 .01* Dropout 126 57.0 21.1 Total 281 59.9 20.1 *p < .05 These results indicate that those who succeed in the program were more likely to make a higher estimate of the completion rate for TRAC students (persisters: 62.3 percent completion rate estimate) than were those who dropped out (dropouts: 57.0 percent completion rate estimate). The actual completion rate for the population from which the sample was drawn was 40.6 percent, a figure far below the estimation of either persisters or dropouts. 194 Table 65 summarizes the results of the statistical analyses comparing factors categorized as motivational with persistence/ withdrawal. The only factors which attained statistical significance were the relationships between the extent to which the student believed his friends gained from Common Core, and the student's estimate of the completion rate for the TRAC program, and persistence withdrawal. Table 65 Summary of the Statistical Analyses of Motivational Factors vs. Persistence/Withdrawal  Factor chi square eta p Lambda 15a) Gained in Common Core 6.35 .17 15b) Friends gained 11.14 .03* .09 15c) He/Friends gained 5.05 .17 16a) Recommending TRAC .51 .48 16b) Recommending PVI .73 .39 16c) Recommending TRAC/PVI 1.33 .72 17 ) Success of Program . 15 . 01*  *p < .05 Because of the possible reasons stated previously for results contrary to that expected for Hypothesis 16b, the role that believing that the program met your goals as a student (i.e. "satisfaction") played in attrition from TRAC is uncertain. In addition, knowing that successful students have a higher estimation of the success of the program is similarly of limited value in terms of any practical significance in predicting success. Even when combined with factors which motivate students to i n i t i a l l y enroll in the program, such as those examined in Chapter IV, there is very l i t t l e from these findings which could be considered as definitive. Again, as in Chapter IV, the reason may be attributable to the fact that for short term, entry level programs, the factors identified in other studies as motivational, and related to decisions to 195 persist or withdraw, may not apply because of differences between the research population and the populations utilized in these other studies. For example, the ability to "put up with" dissatisfaction is probably dependent on the length of time that a student is subjected to i t . Dissatisfaction with a program may be a minor annoyance for a student in a six month program, but for the student in a two- or four-year program i t may, over time, be enough to cause him to withdraw. Financial Factors Financial problems are often mentioned by dropouts as reasons for leaving educational programs. The validity of this response is questioned by researchers such as Cross (1981) who believes reasons such as these tend to be seen by the dropout as socially acceptable, thereby masking more truthful responses perceived to be esteem threatening. Concern about the adequacy of financial resources (Hypothesis 18), the amount borrowed through student loans (Hypothesis 19), whether the student was sponsored while enrolled (Hypothesis 20), and the number of hours a student worked while taking training (Hypothesis 21) were examined under the label "financial factors." Higher education researchers believe there is a difference between concerns regarding the perceived adequacy of personal finances and the actual adequacy of the student's financial resources (Lenning, et al., 1980). As they point out, concern aboUt one's financial situation does not always translate into action to correct the situation such as applying for financial assistance. Although they believe this lack of action brings into question the validity of this concern, i t s t i l l seems to be 196 more of a factor in decisions to withdraw than is the actual adequacy of funds. Hypothesis 18: There is no significant relationship between concern/lack of concern regarding the adequacy of a student's financial resources and his persistence/withdrawal. The results of the statistical analysis based on the data in Table 66 (chi square = 8.04, p = .02, lambda = .09 ) indicate that a relationship exists between financial concern and decisions to persist or withdraw. Hypothesis 18 is rejected. Table 66 Persisters and Dropouts Compared by Concern Regarding the Adequacy of Personal Financial Resources  Student Status Concern Regarding Finances Major Minor No Total(%) Concern Concern Concern Persisters 44 81 36 161 (55.9) Dropouts 55 50 22 127 (44.1) Total 99 131 58 288 (%) (34.4) (45.5) (20.1) (100.0) This relationship indicates that dropouts were more concerned about their financial situation than persisters: of those students who selected, "It seemed I was always worried about not having enough money to make ends meet," from the questionnaire, 55.6 percent were dropouts compared to 44.4 percent who were persisters. Conversely, of those selecting "Money was a concern, but not a major concern", 61.8 percent were persisters compared to 38.2 per.C-nt who were dropouts, and, of a l l respondents selecting "Money was never a concern; I always felt I had enough to get by", 62.1 percent were persisters compared to 37.9 percent who were dropouts. In other 197 words, there seems to be a direct relationship between financial concern and withdrawal: as concern increases, so does the tendency to dropout. As previously indicated, concern over inadequate finances is questioned as concern does not always translate into actions taken to remedy i t (Lenning, et al., 1980). For TRAC students this does not seem to be the case. It appears that the greater concern among dropouts regarding their financial situation did result in individuals in that group applying for student loans more often than persisters did. This comparison reveals that 24.6 percent of the dropouts applied for and 20.0 percent received student loans, whereas similar figures for persisters were 19.6 percent and 15.3 percent. A review of the higher education research indicates that a direct relation exists between the amount of student loans and withdrawal from educational programs (Lenning, et al., 1980). The results of testing Hypothesis 18 indicates that there is a direct relationship between financial concern and withdrawal. In addition, i t has been shown that dropouts were more likely to apply for and receive student loans. Hypothesis 20 takes another step, determining i f a larger student loan was also related to withdrawal. Hypothesis 19: There is no significant relationship between the amount borrowed on a student loan and persistence/withdrawal. The results indicate that there is no statistically significant relationship between the amount of money borrowed and persistence or withdrawal (Table 67: eta = .07, p = .64). 198 Table 67 Persisters and Dropouts Compared by The Amount Borrowed on a Student Loan  Student Status n Mean S.D. eta r> Persisters 25 2840. 00 1152.17 .07 .64 Dropouts 26 3000. 00 1240.97 Total 51 2921. 57 1189.00 The results do show, however, that on average dropouts borrowed about $160.00 more than did persisters. It is believed that these results may give only an indication of what would have been found i f each TRAC student who had received a loan had responded with the amount borrowed. In reviewing the answers to this questionnaire item i t was discovered that while some students confirmed that they had applied for and received a loan, a number of them would not respond to the question which asked them to state the amount borrowed. As specific information on which student received how much was not available through BCIT's Financial Aid department, due to the confidential nature of this information, i t was necessary to use only the data provided in the questionnaire. The possibility exists, therefore, that dropouts did borrow larger amounts which may have added to their financial concerns which, in turn, may have been related to their decision to withdraw from training. A number of social agencies use TRAC as a vehicle for providing their clients with marketable skill s . Sponsorship by one of these agencies means the student receives financial support while in the program. It was believed that being "paid" to attend training, a condition which would be discontinued should the student withdraw, would be related to persistence. Hypothesis 20: There is no significant relationship between 199 whether a student is agency sponsored and his persistence/ withdrawal. Based on the data in Table 68 a chi square value of 3.96 and p = .03 was calculated. Hypothesis 20 is therefore rejected. Table 68 Persisters and Dropouts Compared by Agency Sponsorship Student Status Agency Sponsorship YES NO Total (%)  Persisters 46 114 160 (55.6) Dropouts 23 105 128 (44.4) Total 69 219 288 (%) (24.0) (76.0) (100.0) A greater percentage (28.8) of persisters were sponsored than were dropouts (18.0 percent). This relationship appears to connect sponsorship and persistence: sponsored students tend to persist. The relationship between sponsorship and persistence carries more weight when sponsored students as a group are considered. The majority of students who obtain sponsorship do so through Employment and Immigration Canada. Because the requirements of sponsorship are tied primarily to unemployment or underemployment these students, had they not received sponsorship, would have needed some other form of financial assistance to attend school. It seems likely that i f sponsored students had not received support while attending they would have had financial characteristics similar to dropouts (i.e., greater finpacial concern, slightly larger loans, working and working more hours). However, when comparing financial concern of sponsored and unsponsored students, sponsored students indicated more concern than did those not receiving funding 200 ("always worried about not having enough money": sponsored 50.7 percent, unsponsored 29.4 percent). What this may indicate is that, while sponsorship promotes persistence, i t does not provide enough support to allay students concerns about their finances. Another possibility is that students receiving support while attending school may expect to be able to maintain the l i f e style they enjoyed while employed. Finding this was not possible while collecting Unemployment Insurance benefits or social assistance may have heightened their concerns regarding the adequacy of their finances. For the student paying his own way or living at home while attending school these expectations may be more realistic resulting in less concern. Working while attending school has also been indicated in previous research to be related to persistence/withdrawal (Lenning, et al., 1980). This research indicates that both not working and working more than 25 hours per week are related to withdrawal, whereas working between 1 to 25 hours per week is related to persistence. Hypothesis 21: There is no significant relationship between the number of hours worked per week and persistence/withdrawal. According to the data in Table 69, the relationship between the criterion and predictor variables is not statistically Table 69 The Relationship Between the Number of Horns Worked Per Week and Persistence/Withdrawal  Student Status n Mean S. D. eta V Persisters 56 23 .43 12 .90 .07 .21 Dropout 56 25 .38 11 .96 Total 112 24 .40 12 .42 201 significant (eta = .07, p = .21). Even though there is no statistically significant relationship between the number of hours worked per week and persistence or withdrawal, more dropouts worked while attending school, and for more hours than did persisters. However, as is indicated in Table 70, the difference between the mean numbers of hours worked is not statistically significant (t = -0.83, p = .41). Therefore, when examining either the relationship between the variables (Table 69), or the difference between the means for persisters and dropouts (Table 70), neither method clearly differentiates persisters from dropouts. When comparing the percentage of dropouts who worked less or more than the number of hours (i.e., 1-25) indicated by Lenning, et al. (1980) to be related to persistence, there was very l i t t l e difference between dropouts and the persisters (dropouts: 74.8 percent, persisters: 77.5 percent). Table 70 A Comparison of the Mean Number of Hours Worked per Week by Persisters and Dropouts  Student Status n Mean S.D. t o Persisters 56 23.43 12.90 -0.83 .41 Dropout 56 25.38 11.96 Total 112 24.40 12.42 Lenning and his colleagues' review (1980) of the research on working while at school and attrition would seem to indicate that a curvilinear relationship exists between hours worked per week and dropping out. Dropouts either did not work or worked more than 25 hours per week. Persisters, on the other hand, worked between one and 25 hours per week. A U-shaped curve would seem to f i t these findings nicely with dropouts at the upper 202 ends of the U, indicating that they either work no hours or too many, and persisters at the bottom of the U's curve, representative of working the optimum number of hours. However, as stated by Ferguson (1981) " i f one variable . . . is a nominal variable and the other an interval-ratio variable, the idea of linearity or nonlinearity of regression is quite meaningless" (248). In examining the mean number of hours worked per week, the variation of the scores about the means, and the correlation ratio, which measures the strength of association between interval-ratio and nominal variables, i t is obvious that, in terms of hours worked per week, persisters and dropouts were not significantly different nor was there a relationship between the predictor variable and persistence/withdrawal. Table 71 displays the results of the statistical analyses comparing financial factors and persistence/withdrawal. Only financial concern and agency sponsorship are related to the criterion variable. What these results seem to indicate is that reducing financial concern may be a means of reducing attrition but sponsorship, while i t is related to persistence, does not appear to operate by promoting persistence through reducing these concerns. In other words, although being paid to attend keeps students in school, the amount is not enough to allay Table 71 Summary of the Statistical Analyses of Financial Factors vs. Persistence/Withdrawal  Factor Chi Square Correlation Ratio p Lambda 18 ) Financial concern 8.04 .02* .09 19 ) Amount of student loan .07 . 64 20 ) Agency sponsorship 3.96 .03* .01 21 ) Hours worked oer week 3.82 .07 .21 *p < .05 203 concerns regarding the adequacy of students' financial resources. However, even though concern in unsponsored students is related to withdrawal, for sponsored students these concerns seem to be sufficiently weakened to promote persistence. Institutional Factors Pantages and Creedon (1978) consider the socialization aspect of on-campus living important in positively influencing persistence. Although PVI does have a student residence, i t differs from that found at most colleges and universities as i t is designed for short stays and is less communal than other student residences. Redford House offers strictly accommodation—there are no formal attempts to imbue a sense of community. In * addition, the small number of PVI's students who actually stay there make i t difficult to measure the effect that on-campus living has on persistence or withdrawal. Pantages and Creedon (1978) agree, however, that living away from home is also positively related to persistence. Hypothesis 22a examines the relationship between moving away from home, either the parents' residence or where the student's family resides, and persistence/withdrawal. The idea that a relationship may exist between where a student lives while at school and his decision to persist or withdraw is expanded in Hypothesis 22b. The variable of moving to take training was designed to cover a variety of changes of accommodation, for example, a change from living with one's parents to living at Redford House, with a friend or relative, or to living on one's own. This would similarly apply to the married student who must relocate to take training. In accordance with the research i t 204 was believed that students who changed their place of residence would tend to persist while those who did not change would be more likely to withdraw. Hypothesis 22a: There is no significant relationship between changing/not changing one's place of residence and persistence/ withdrawal. The data from Table 72 indicate that there is no relationship between moving away from home and persistence or withdrawal (chi square = .02, p = .90). Table 72 Persisters and Dropouts Compared by Changing/Not Changing their Place of Residence to Attend PVI  Student Status YES NO Total (%) Persisters 30 133 163 (55.8) Dropouts 23 106 129 (44.2) Total 53 293 292 (%) (18.2) (81.8) (100.0) The results show that less than 20 percent of a l l TRAC students changed their place of residence to take training and that the percentage of persisters and dropouts was almost identical (persisters: 18.4 percent, dropouts: 17.8 percent). Again, the short term nature of TRAC programs may be a factor in the difference between these results and those found by other researchers. To determine i f living at Redford House or other locations was related to persistence or withdrawal students were given a number of residence options to choose from on the questionnaire. Hypothesis 22b: There is no significant relationship between where a student lived during the time he was participating in the Common Core and his persistence/withdrawal. 205 The results of the chi square calculation (chi square = 6.51, p = .37) indicates that there is no relationship between any of these options, including living in residence, and the criterion variable (Table 73). Table 73 Persisters and Dropouts Compared by Where they Lived During Common Core  Student Residence Total(%) I Status Parent Relative Spouse Self Friend Redford Persisters 87 14 20 29 5 5 162 (56. 1) Dropouts 80 7 10 23 5 1 126 (44. 1) Total (%) 167 (58.0) 21 (7.3) 30 52 (lO.4)(18. 12 1)(4.2) 6 (2.1) 288 (100.0) The majority of both persisters (53.7 percent) and dropouts (63.0 percent) lived with their parents while only six students out of the 288 respondents lived at Redford House. Even though i t seems that more dropouts lived at home, there is no statistically significant relationship between living at home and dropping out. Socialization into the college l i f e style does not appear to be part of the TRAC experience. Procedures such as taking students in as individuals rather than as members of a class, starting every student in Common Core where the mode of learning is individualized, and making no effort through organized social events to foster a sense of community results in a program where students operate as individuals rather than group members. This and the short-term nature of the program tend to negate the possible positive influence that being a member of a student society may have on promoting persistence. Under these conditions, i t seems that where one lives or whom one lives with 206 w i l l be unrelated to whether a student decides to withdraw from school. Previous research has shown that students are more l i k e l y to p e r s i s t i f they are aware of and u t i l i z e student services (Lenning et a l . , 1980). At PVI these services include counselling, used by students for personal/social counselling and vocational guidance, extra help for math and science related problems through the Developmental Studies Center, f i n a n c i a l assistance through the F i n a n c i a l Aid O f f i c e , program information through Student Advising, and educational and performance counselling s p e c i f i c to the TRAC program through the Training Consultants. I t was anticipated that students who reported on the questionnaire that they had taken advantage of these services would most l i k e l y be p e r s i s t e r s . Hypothesis 23: There i s no s i g n i f i c a n t r e l a t i o n s h i p between the use of s p e c i f i c student services and persistence/withdrawal. Table 74 includes each of the services l i s t e d on the questionnaire, states i f each service was used, and indicates the extent that each was used by TRAC students. Based on the data from Table 74 the only service f o r which the r e l a t i o n s h i p was s t a t i s t i c a l l y s i g n i f i c a n t was use of the Training Consultants (chi square = 8.81, p = .01). The r o l e of the TRAC Training Consultant was as a replacement f o r the i n s t r u c t o r i n such things as monitoring student performance and progress, providing front l i n e p e rsonal/social, vocational and educational counselling, and acting as the primary l i a i s o n between the student and the 207 Table 74 Persisters and Dropouts Compared by Use of Specific Student Services  Student Status Used Student Service No Yes More than once Total (%) Counselling Persisters 91 Dropout 62 28 24 18 25 137 111 (55. (44. 2) 8) Total 153 (%) (61.7) 52 (21. 0) 43 (17.3) 248 (100. 0) Student Advising Persisters 111 Dropouts 74 21 17 4 3 136 94 (59. (40. 1) 9) Total 185 (%) (80.4) 38 (16. 5) 7 (3.0) 230 (100. 0) Developmental Studies Persisters 79 Dropouts 62 Center 19 10 3 33 135 105 (56. (43. 3) 8) Total 141 (%) (58.8) 29 (12 . 1) 70 (29.2) 240 (100. 0) Student Finance Persisters 98 Dropouts 71 23 26 11 8 132 105 (55. (44. 7) 3) Total 169 (%) (71.3) 49 (20. 7) 19 (8.0) 237 (100. 0) Training Consultants Persisters 27 Dropouts 26 47 17 79 70 153 113 (57. (42. 5) 5) Total 53 (%) (19.9) 64 (24. 1) 149 (56.0) 266 (100. 0) Institute. In the design of the competency-based, self-paced system, the instructor's role was primarily to answer questions that were not obvious from the written learning material, provide practical demonstrations, and evaluate students' practical work. The role the instructor played changed for each student as he moved from Common Core to Occupational Core and finally to Specialty. By the time the student had completed the fi r s t two stages of the program and entered his chosen specialization, the instructor had taken on many of the tasks 208 that had i n i t i a l l y been the responsibility of the consultant. As stated previously, students' progress was monitored by a computerized tracking system. Students were expected to acquire a set number of competencies each week. Each time they wrote a test or completed a practical assignment i t was added to their weekly tally. Should the student f a i l to accomplish what was expected he was required, after a certain period of time, to vi s i t a consultant. During these meetings the reasons for the student's lack of progress were discussed. Barriers to performance could be motivational, the result of poor study habits, due to the student's job or family commitments, or any combination of these. It was the consultant's job to devise strategies to assist the student in overcoming these barriers thereby improving his performance. From the data i t is shown that a greater percentage of dropouts (23.0) than persisters (17.6) did not v i s i t a Training Consultant. This would appear to indicate a relationship exists between these visits and persistence. But, in examining which group made repeated visits, i t was the dropouts who more often saw a Training Consultant more than once. This, on the other hand, would seem to indicate a relationship between dropping out and visiting a consultant. At f i r s t glance these findings seem to conflict. Because poor progress would result in students being required to see a consultant more often, and because poor progress would logically be associated with lack of success, i t appears that more contact with a consultant was related to withdrawal. Rather than being a negative influence on the persistence of TRAC students, this simply means that the 209 Training Consultants spent more of their time counselling students who had been required to make an appointment and who could not maintain a sufficient rate of progress and ultimately withdrew. On the other hand, students who never ran afoul of the monitoring system may never have seen a Training Consultant. The amount and quality of student contact with instructors is indicated to be related to persistence (Lenning et al., 1980). The quality of this contact could be indirectly measured by the amount because, logically, a student will seek assistance more often i f he has found i t beneficial in the past. To measure this, students were asked on the questionnaire i f they went to the Common Core instructors for assistance and how often they made use of this service (i.e., "once", "more than once"). Hypothesis 24: There is no significant relationship between making use of instructor assistance and persistence/withdrawal. Calculations based on the data in Table 75 result in a chi square value of 1.35 (p = .51) which indicates that there is no relationship between instructor contact and persistence/ withdrawal. Table 75 Persisters and Dropouts Compared by Use of Instructor Assistance  Student Status Obtained Instructor Assistance No Yes More than once Total (%) Persisters 29 42 89 160 (55. 7) Dropouts 26 26 75 127 (44. 3) Total (%) 55 (19.2) 68 (23.7) 164 (57.1) 287 (100. 0) Approximately 80 percent of both persisters and dropouts did 210 seek instructor assistance with more than half seeking help more than once. The difference between the two groups was minimal. It is possible that these results do not parallel those found in other studies because TRAC, as competency-based and self-paced program, is designed so students learn primarily through the use of individualized materials. Instructor assistance was sought only when difficulties were encountered with these materials or when a practical test was attempted. Students did not have an instructor in the traditional sense and therefore the relationship between student and teacher was different from that described in previous studies as contributing to persistence. Student " f i t " , defined as being more alike than different from the majority of students, has also been indicated in previous research as being related to persistence (Lenning, et al., 1980). In other words, persisters have been found to be similar to their peers and this perception of sameness is synonymous to a feeling of belonging. Tinto (1987) also cites the importance of f i t , or, as used by him, "congruence": Few college settings are so homogeneous that virtually no disagreement occurs on campus as to the appropriate character of intellectual and social behavior. But when that perception leads the person to perceive him/herself as being substantially at odds with the dominant culture of the institution and/or with significant groups of faculty and student peers, then withdrawal may follow (57). Feeling at odds with teachers and fellow students, i.e., "incongruence", is also cited by Boshier (1973) as a factor in decisions to withdraw. Each of these authors implies that each educational institution exhibits a characteristic ethos that students measure against their own set of values and then make 211 decisions regarding its appropriateness in meeting their needs. A student who relates to the college's identity tends to persist while one who fails to either share these values or to find a niche within the college with values similar to his own, is likely to withdraw. The measurement of such a nebulous trait is difficult. In this research, measurable student characteristics are selected and compared to values found for both persisters and dropouts. In this way i t can be determined i f , as found in other studies, persisters are closer to the norm than dropouts. The characteristics chosen for comparison, place of birth, age, marital status, having children, SES, and high school graduation are believed by the researcher to be common to the majority of TRAC students. The "typical" TRAC student is believed to be Canadian born, 19 years of age, single and childless, have a lower middle class background, and be a grade 12 graduate. If " f i t " , as defined in this study, is related to persistence then these characteristics would also describe persisters. Hypothesis 25: There is no significant difference between persisters and the research sample on selected variables used to define " f i t " . Table 76 identifies which of the factors selected to define the concept of " f i t " produced a statistically significant relationship with persistence/withdrawal. These results previously identify persisters as older, having a higher SES, and being high school graduates. However, defining the typical TRAC student by "averaging" each of these characteristics and then comparing persisters and dropouts to the "norm" violates 212 the idea of mutual exclusion for the chi square statistic and averages out any difference between persisters or dropouts and the "typical" student for the t statistic. For these reasons i t is not possible to provide a statistical test which will lead to the rejection of the null hypothesis. Table 76 Comparison of Persisters and Dropouts on Factors Used to Define Fit  Factor Chi t (p) Square (p)  1) Place of birth 2.25 (0.13) 2) Age 2.50 (0.01)* 3) Marital status 0.01 (0.99) 4) # of children -0.03 (0.97) 5) SES -2.18 (0.03)* 6) High school grad 5.12 (0.02)*  *p < .05 Another aspect of " f i t " is the extent to which a student feels a part of the social l i f e at the Institute. As stated previously congruence infers fitting the social as well as the academic character of the college. Because participation in TRAC brings students into contact with their peers, i.e., the social aspect of postsecondary participation, i t was believed that having friends at the Institute would tend to increase persistence, whereas students without friends at the Institute would tend to withdraw. Hypotheses 26a through 26d examine the relationships between persistence/ withdrawal and the characteristics of the social relationships a student forms at school. 'Hypothesis 26a: There is no significant relationship between 213 the number of friends a student has who are also attending the Institute and his persistence/withdrawal. A chi square value of 7.46 (p = .11), based on the data from Table 77, indicates that there is no statistically significant relationship between the number of friends a TRAC student has and persistence or withdrawal. Table 77 Persisters and Dropouts Compared by Number of TRAC Friends They Socialized With  Student Status Number O f Friends Total 5> 4 3 2 1 (%) Persisters 11 16 22 28 25 102 (55.7) Dropouts 17 10 24 13 17 81 (44.3) Total 28 26 46 41 42 183 (%) (15.3) (14. 2) (25. 1) (22.4) (23.0) (100.0) The nature of the association between TRAC students was also examined. In Common Core a l l students covered basically the same content, took the same shop activities, and worked on their individualized learning materials in the same location. As they moved on to Occupational Core and, later, Specialty, they were split off from this common body of students. They may have completed their theory and practical activities, and even had coffee, in different locations around campus. Unlike in group-paced programs, TRAC students did not form into classes and complete the program as members of a small identifiable cohort. The only program grouping which would infer membership and could, therefore, be translated by students as fitting in, would be having similar occupational goals. This would translate into entering the same Occupational Core and Specialty after completing Common Core. If this inference was correct and i f 214 fitting in is related to persistence then i t was expected that TRAC students who associate with other students having the same Occupational Core would tend to persist. Hypothesis 26b: There is no significant relationship between having friends who are taking/not taking the same Occupational Core as the student and his persistence/withdrawal. Table 78 Persisters and Dropouts Compared by Having/Not Having Friends Taking the Same Occupational Core  Student Status Same Occupational Core? YES NO Total (%) Persisters 56 47 103 (54.5) Dropouts 43 43 86 (45.5) Total 99 90 189 (%) (52.4) (47.6) (100.0) The data from Table 78 resulted in a chi square value of .20 (p = .65) indicating that having friends going into the same Occupational Core is not related to persistence or withdrawal. The numbers of TRAC students having friends taking or not taking Occupational Core is almost identical for both persisters and dropouts. The idea of belonging to a cohort was further defined in Hypothesis 26c which explores the relationship between having friends training for the same trade and persistence/withdrawal. Basically, i t was believed that students who associated with others having the same career goal may tend to persist. For example, Carpentry students would have similar occupational interests, would work on identical content in the same location, and would encounter the same problems. The fact that their 215 fellows had similar experiences may reduce any feelings of isolation and lead to increased persistence. Hypothesis 26c: There is no significant relationship between having friends who are taking/not taking the same Specialty as the student and his persistence/withdrawal. Again, having friends at the Institute taking the same Specialty is not related to persistence or withdrawal (Table 79: chi square = .02, p = .88). Table 79 Persisters and Dropouts Compared by Having/Not Having Student Status Same Specialization? YES NO Total (%) Persisters 45 58 103 (54. .8) Dropouts 39 46 85 (45. .2) Total 84 104 188 (%) (44. 7) (55.3) (100. .0) TRAC students were admitted on a continuous entry/exit basis. This, together with the self-paced, individualized nature of the program meant that students in the same program could be working at any point in that program from start to finish. Meeting students and forming friendships on the fi r s t day may, therefore, have also promoted a feeling of belonging which was believed to be related to persistence. Hypothesis 26d: There is no significant relationship between having friends who began the program the same or a different day and persistence/withdrawal. Results from the calculation, based on the data in Table 80, again showed no relationship between forming friendships early in the program and persistence or withdrawal (chi square = .00 and p = .95) . Table 80 Persisters and Dropouts Compared by Having/Not Having Friends Starting; on the Same Day  Student Status Started the Same Day? YES NO Total (%) Persisters 49 53 102 (54.3) Dropout 40 46 86 (45.7) Total 89 99 188 (%) (47.3) (52. 7) (100.0) It is apparent from the results of Hypotheses 26a through 26d that belonging to a group identified by similar career aspirations was not related to either persistence or withdrawal from TRAC. It is also obvious that forming friendships the fi r s t day was not related to attrition. It is possible that the design of the TRAC program did not promote the formation of cohorts of students which might have added to individual students' feeling of fitting in. It is also possible that the idea of f i t as a factor related to persistence was not applicable to TRAC students. A possible conclusion reached by the researcher is that because TRAC students operated as individuals rather than as members of a group from the fi r s t day, and, because of the short-term nature of the program, the need for the types of support or sense of identity that students in longer term, traditional programs benefit from, was not required. Institutional factors combined the student's place of residence, the institutional services accessed, instructor contact, and f i t as variables possibly related to persistence or withdrawal. Table 81 summarizes the results of the statistical 217 analyses. ( As can be seen from the table, the only factor in which the relationship between independent and dependent variables reaches statistical significance is visiting a Training Consultant. The relationship of these visits to persistence or withdrawal from TRAC is not clear. In other words, where TRAC students lived, the amount of contact they had with instructors and institute services, and whether they exhibited characteristics believed to be synonymous with social congruence, appeared to have l i t t l e relationship to their decisions to persist or withdraw. A possible reason for these results, and one advanced previously to explain similar findings, is that TRAC students in particular, and entry level vocational students in general, are different from students who participated in the studies which fi r s t identified the attrition factors used in this research. As pointed out previously, very l i t t l e research on postsecondary attrition has focused exclusively on entry level vocational students. The research from which the attrition factors used in this study were selected focused upon populations from high school, adult education, and two- and four-year postsecondary programs. Differences such as the length of time TRAC students were at school compared to students attending college or university, the job specific focus of vocational training compared to that of diploma or degree programs, and the specific occupational objectives of vocational students a l l tend to set TRAC students apart from the students studied in most attrition research. These differences may account for many of the discrepancies between what the 218 Table 81 Summary of the Statistical Analyses of Institutional Factor n chi square O 22a) Changing residence 292 .01 1.00 22b) Resided during program 288 6.51 .36 23 ) Use of Student Services: Student Counselling 248 4.27 .12 Student Advising 230 .30 .86 Developmental Studies Center 240 1.34 .52 Financial Aid 237 1.92 .38 Training Consultants 266 8.81 .01* 24 ) Instructor assistance 287 1.35 .51 25 ) Student Fit: Place of birth Marital status Number of children (Refer to Table 76) SES of highest parent Age High school graduation 26a) Number of friends 183 7.46 .11 26b) Occupational friends 189 .20 .65 26c) Specialization friends 188 .02 .88 26d) Starting on same dav 188 .01 .95 *p < .05 literature states and what was found by the researcher. Attainers, Dropouts, and Persisters As stated before, attainers, described as "those students who have indicated on the survey instrument that they left the program prior to completion because they felt their needs were sufficiently met", may be similar in many regards to persisters. This is because attainers define "completion" as having met their personal needs in regards to a l l that the program has to offer, rather than in terms of receiving a certificate of completion. However, attainers do not receive a certificate, and are, therefore, sonsidered as dropouts by the Institute. If they do share many characteristics with persisters their inclusion with dropouts could, depending upon their numbers, dilute the differences between persisters and dropouts and weaken the 219 predictive u t i l i t y of the significant factors. The f i r s t step in answering whether attainers were more like persisters or dropouts was to determine i f attainers were an identifiable group based upon their responses to selected questionnaire items. In this study a student would be classified as an attainer i f he: was classified as a dropout, did not select family responsibilities, illness, personal problems, changing goals, money problems, or the course not being what he had expected, as a reason for withdrawing from TRAC, stated his intention to complete only part of the program, stated that his main reason for taking the program was to gain knowledge and skills useful to him even i f he did not obtain employment in his chosen trade, or, as obtaining employment and indicating that program status upon withdrawal as withdrawn due to finding full-time employment, stated that the most important reason for taking TRAC was having usable skills rather than a TRAC certificate. Of the 298 respondents, eight f e l l into this category. The next step in this process was to select those factors previously identified as related to, or that differentiated between, persistence and dropout. Attainers are then compared to both groups on each factor to see i f they are consistently more like persisters than dropouts. Table 82 l i s t s those factors that reached the criteria for statistical significance in a l l previous calculations. Hypothesis 27: There is no significant difference between attainers and persisters or dropouts on variables selected for their ability to differentiate between persisters and 220 Table 82 Statistically Significant Results from Previous Calculations  Factor Chi Square Correlation t p Lambda Ratio (eta)  Previous Educational Experience lh) High school graduation 5. 12 .02* .07 Academic Factors 2a) Scores on CAT: Reading Vocabulary .19 .01* Reading Comprehension .19 .01* Reference Skills .19 .01* Math Computation .23 .01* Math Concepts .24 .01* 2b) CAT reading scores .22 .01* 2c) CAT math scores .25 .01* 13a) Enough study time 10. 40 .01* .12 13b) Study time compared 23. 24 .01* .11 13d) Hours per week at PVI .17 .01* 14a) Tests passed/attempts .30 .01* 14b) Tests exceeded/attempts .25 .01* Demographic Factors 3 ) Age (mean difference) 2.50 .01* 4a) Student's SES .24 .04* Motivational Factors 7c) Certainty of choice 11. 15 .01* 7d) Changing Specialties 3. 82 . 05* 15b) Friends gained 11. 14 .03* 17 ) Success of program .15 .01* Financial Factors 18 ) Financial concern 8. 04 .02* .09 20 ) Agency sponsorship 3. 96 .03* Institutional Factors 23 ) Use of Student Services: Training Consultants 8. 81 .01* Learner Self-Confidence 12) High school .13 .04* persistence/withdrawal Note: *p < .05 221 and dropouts. If attainers were simply persisters who had not completed the program but had completed those parts of the program deemed necessary to meet their personal goals, they would be consistently different from dropouts on the selected variables. As indicated in Table 83 only one of the selected variables—"study time compared"—produced a statistically significant difference between attainers and dropouts. Looked at from the other perspective, i f attainers were a subgroup of persisters they would not differ from persisters on those variables which differentiate persisters from dropouts. However, attainers and persisters did differ on two variables: "study time compared" and "student's SES." These results f a i l to substantiate the statement that attainers are more like persisters than dropouts. As a result, statements cannot be made regarding the group characteristics of attainers other than to say they could be identified as a group using the criteria set out in this study. Therefore, Hypothesis 27 is accepted. Had this group been comprised of more than 2.7 percent of the research population these results may have been different. Because attainers made up only 6.9 percent of TRAC dropouts, i t is also doubtful that their results and responses, even i f similar to those made by persisters, would have significantly diluted the differences between persisters and dropouts. 222 Table 83 Comparison of Persisters and Dropouts to Being More/Less Like Attainers ; \ Hypothesis Factor Persisters Dropouts Number & Attainers & Attainers lh) High school graduation chi square .01 .67 p .93 .41 2a) Scores on CAT: Reading Vocabulary t .36 -.56 p .74 .60 Reading Comprehension t -.09 -1.12 p .93 .31 Reference Skills t -.62 -1.71 p .56 .15 Math Computation t .43 -.45 p .68 .67 Math Concepts t .46 -.42 p .67 .67 2b) CAT reading scores t -.04 -1.09 p .97 .32 2c) CAT math scores t .45 -.44 p .67 .68 13a)Enough study time chi square .27 .69 p .60 .40 13b)Study time compared chi square 19.14 5.57 p .01* .02* 13d)Hours per week at PVI t -.78 .12 p .46 .90 14a)Tests passed/attempts t 2.47 .23 p .09 .83 14b)Tests exceeded/attempts t 2.06 1.11 p .13 .35 223 Table 83 (cont.) Hypothesis Factor Number  Persisters Dropouts & Attainers & Attainers 3) Age F 4.05 3.61 p +.55 +.08 4a) Student's SES t -5.55 .02 p .01* .99 4b) Parent's SES: Father's t -.21 -.15 p .84 .89 Mother's t -.91 -.54 p .41 62 7c) Certainty of choice chi square .04 .00 p .83 1.00 7d) Changing Specialty chi square .02 .00 p .95 1.00 15b)Friends gained chi square 2.81 1.05 p .09 .48 17) Success of program t 1.71 1.19 p .14 .28 18) Financial concern chi square 1.02 2.67 p .60 .26 21) Agency sponsorship chi square .02 1.02 p .89 .31 23) Use of Student Services: Training Consultants chi square .31 .78 p .85 .68 11) TRAC persistence /withdrawal (IE Score) t .01 .14 p 1.00 .90 12) High school persistence *** /withdrawal (IE Score)  Note: *p <= .05 ***as a l l students who completed the IE Scale (6) and who were classified as attainers were also TRAC persisters i t was not possible to do a comparison. 224 C o n c l u s i o n I n t h i s s t u d y t h e d i s t i n c t i o n was made between t h e e f f e c t o f t h o s e f a c t o r s which t h e s t u d e n t b r i n g s w i t h him t o p o s t s e c o n d a r y s c h o o l and t h o s e f a c t o r s r e l a t e d t o h i s e x p e r i e n c e i n the program. P o s t e n t r y f a c t o r s have been examined i n t h i s c h a p t e r . A l t h o u g h some o f t h e f a c t o r s s e l e c t e d from h i g h e r e d u c a t i o n , a d u l t e d u c a t i o n , and h i g h s c h o o l a t t r i t i o n s t u d i e s had u t i l i t y i n p r o d u c i n g s t a t i s t i c a l l y s i g n i f i c a n t r e s u l t s w i t h TRAC s t u d e n t s , many d i d n o t . T h i s draws i n t o g u e s t i o n t h e assumpt ion t h a t t h e p o p u l a t i o n s used i n t h o s e r e s e a r c h s t u d i e s were s i m i l a r t o TRAC s t u d e n t s . What r e s u l t s from t h i s c h a p t e r i n d i c a t e as a major f a c t o r i n d e t e r m i n i n g whether a s t u d e n t w i l l p e r s i s t o r wi thdraw i s t h e way i n which he a p p l i e s h i s academic s k i l l s . I n s h o r t , "good" s t u d e n t s p e r s i s t and s u c c e e d . TRAC s t u d e n t s who b e l i e v e d t h e y p u t i n enough t i m e s t u d y i n g p r i o r t o w r i t i n g a t e s t , who b e l i e v e d t h i s t i m e t o be i n excess o f what o t h e r s t u d e n t s s p e n t , and who r e p o r t e d s p e n d i n g more t ime a t P V I , p e r s i s t e d . The f a c t t h a t t h i s group t o o k fewer a t tempts t o pass t h e o r y t e s t s and exceeded t h e 80 p e r c e n t minimum pass mark more o f t e n t h a n d i d d r o p o u t s i n d i c a t e s t h a t t h i s e x t r a e f f o r t p a i d o f f . P e r s i s t e r s a l s o c o n s i d e r e d t h e program t o be more s u c c e s s f u l i n g r a d u a t i n g s t u d e n t s t h a n d i d d r o p o u t s which may i n d i c a t e t h a t p e r s i s t e r s had a more p o s i t i v e a t t i t u d e towards TRAC. F i n a n c i a l c o n c e r n w h i l e a s t u d e n t p r o v e d t o be a n e g a t i v e f a c t o r f o r d r o p o u t s . C o n c e r n r e g a r d i n g the adequacy o f t h e i r f i n a n c i a l r e s o u r c e s was common among d r o p o u t s whereas p e r s i s t e r s 1 c o n c e r n s were n o t as g r e a t . B e i n g sponsored w h i l e 225 attending TRAC was related to persistence but even sponsored persisters shared the concerns of dropouts regarding their finances. What remains to be done is to develop what has been shown to be related to persistence/withdrawal into a method of predicting which students are most likely to withdraw from training. If i t can be shown which factors are related to dropping out, and their relative strengths as predictors, then i t will be possible to consider how this information can be used to reduce attrition in similar programs. 226 CHAPTER VI THE PREDICTION OF DROPOUT Withdrawing from an educational program has a negative impact on the student, the educational i n s t i t u t e , and, i f the student i s sponsored, on the agency paying f o r h i s or her education. For each there i s a cost. For students t h i s includes the time invested p r i o r to withdrawal, the costs associated with school attendance, l o s t wages while i n school, a p o t e n t i a l loss of future wages, and possible damage to t h e i r self-esteem and self-confidence as learners. For the i n s t i t u t e , a t t r i t i o n costs are the r e s u l t of having an empty seat which uses up resources i n terms of i n s t r u c t i o n a l and support services, but which generates no revenue. This i s p a r t i c u l a r l y c o s t l y i f the student was sponsored and the i n s t i t u t e received a per diem rate which terminates upon the student's withdrawal. In addition, the loss of a classmate may have a negative impact on the morale of the remaining c l a s s members. F i n a l l y , i f t h e i r c l i e n t withdraws, the sponsoring agency receives a l i m i t e d return on i t s investment. As indicated i n Chapter I, a t t r i t i o n from t r a i n i n g programs sponsored by Employment and Immigration Canada costs Canadian taxpayers 61 m i l l i o n d o l l a r s i n 1983-84 (Abt Associates of Canada, 1985). Ear l y leaving, as concluded from a review of the l i t e r a t u r e on student a t t r i t i o n , i s related to a v a r i e t y of factors each of which contributes i n varying amounts to an i n d i v i d u a l student's dec i s i o n to withdraw. In t h i s study, each of these factors was considered f o r i t s a p p l i c a b i l i t y to male students i n the TRAC program at PVI. For example, i t was evident from the search of the literature on attrition that a student's previous educational experience had an impact upon subsequent attempts. A review of the studies of college and university populations identified variables such as high school grade point average, class rank, scholastic aptitude, and study habits as related to postsecondary attrition (Sexton, 1965; Pantages & Creedon, 1978; Lenning, Beal, and Sauer, 1980; Tinto, 1987). A similar emphasis on educational experience and its relation to withdrawal was found in the adult education literature (Verner & Davis, 1964; Darkenwald, 1981). Because the entrance requirements differ for college or university and entry level vocational programs, variables such as last grade completed, time lapse since previous schooling, type of high school program, failing to graduate, being held back a grade, and agreeing with negative statements about their high school experience were selected as variables related to previous educational experience and appropriate to the research population. A similar method was used in selecting variables for each of the categories of attrition factors investigated in this study. As indicated in Chapter I, the objectives of this study were to validate for use with male entry level vocational students those attrition factors "borrowed" from research done with high school, college, university, and adult education populations, and to develop a means of identifying potential TRAC dropouts shortly after they have begun the program. The f i r s t objective stems from a lack of attrition research aimed specifically at students in short-term vocational programs. The second from a guestion of whether factors, found to be appropriate for male 228 TRAC students, could be developed into a prediction formula for the identification of those at risk. Through the identification of relevant factors, and subsequent development of the prediction formula, information about TRAC students could be gathered and used to select entrance requirements limiting access to those students with the best potential for completion or, alternatively, to identify potential dropouts for inclusion in a special program designed to improve their chances for success. In addition to its use in the identification of potential dropouts, a prediction formula could also be used to identify factors for inclusion in a retention program. For example, i f i t is obvious that weak mathematics skills are related to withdrawal i t would seem logical to include mathematics upgrading as part of the program for those lacking these skills. It may even be possible to identify the kinds and level of skills required for successful completion. Similarly, i f receiving financial assistance is related to persistence and working full-time is related to withdrawal, then i t would be important to ensure that students were cautioned against working full-time while attending school and were supplied with information on various sources of financial assistance. Used either as a means of restricting entry, or as a means of guiding the development of retention programming, the desired outcome, attrition reduction, would be the resuinl,,-In this chapter, variables found to be related to persistence or withdrawal, identified from the results found in Chapter IV (pre-entry attrition factors) and Chapter V 229 (postentry attrition factors) are developed into a prediction formula using multiple regression analysis. The Development of a Prediction Formula In Chapters IV and V certain variables were identified as being related to persistence/withdrawal for male TRAC students. Due to the nature of the research questions, both nominal/ordinal and interval/ ratio data were obtained from the questionnaire and from PVI records. The criterion variable, i.e., persistence/withdrawal, was also nominal in nature. For the hypothesis testing analyses, therefore, chi square was used for nominal/nominal or nominal/ordinal comparisons and the correlation ratio (eta) was calculated for nominal/interval or nominal/ratio comparisons. Although both of these statistics t e l l whether the relationship between variables is statistically significant and, to a certain extent, indicate the strength of this relationship, i t is not possible to directly compare the measure of association between one (lambda for chi square) and the other (eta). It is, however, possible to include nominal/ordinal variables in multiple regression analyses by assigning dummy weights to indicate either the presence or absence of a characteristic for both the dependent, i.e. criterion, and independent, i.e., predictor, variables. For example, persistence/withdrawal and skipping a grade are either/or situations and can be coded as such using the dummy weights of 5a0" and "1". In addition, the fact that certain variables can be ranked implies that they f i t on a continuum which, in turn, permits statements to be made about one rank being greater or less than another. A variable which can be 230 interpreted as fitting this definition is "enjoyment of school." Students were asked on the questionnaire to indicate how much they enjoyed secondary school: "enjoyed i t very much," "enjoyed i t most of the time," "disliked i t most of the time," and "disliked i t very much." Even though i t is not possible to say that one response is twice as large as another, an underlying continuous scale is assumed. These coded data, combined with data utilizing interval measures, can then, through multiple regression analysis, be used to construct a prediction formula. The use of a dummy variable as the dependent or criterion variable is sometimes questioned as its use in regression analysis infers the measure underlying i t is continuous in nature. For example in the present research persistence or withdrawal, an either/or situation, is translated into the propensity to persist or withdraw. However, in the prediction of persistence/withdrawal, this is subsequently changed back as decisions are considered regarding the selection of a score below which a student is either not accepted for admission or selected for participation in a retention program. The use of dummy variables in multiple regression analysis is defended by Gillespie (1977). He states that the other most commonly used method, log-linear techniques, even though statistically superior, produces results similar to multiple regression when the split between the sample on the dichotomous dependent variable is between 25 and 75 p^ireent. He also states as an advantage the ability of multiple regression equations to include predictor variables which are continuous. Using log-linear techniques, independent variables must be categorical 231 which results in the loss of a certain amount of information when continuous variables are converted. This method of building a prediction formula is fairly common in attrition research. Astin (1975), in his longitudinal study of 9,750 two and four-year college students, used this method to build a formula which enabled students and administrators to calculate the potential for dropping out. In Sainty's (1971) study of 104 male adult students participating in a short term academic upgrading program, multiple regression analysis was similarly used to construct a prediction formula. In both studies the authors selected attrition factors from previous research. Sainty's factors, intelligence, reading ability, personality factors, and personal biographical data, were selected from high school and adult education attrition studies. Astin's variables, 110 in total, were a product of his previous research as well as the research of others (A. W. Astin, 1971, 1972a; H. S. Astin, 1970; Astin and Panos, 1969; Cope, 1969; DeVecchio, 1972; Newman, 1965; Summerskill, 1962; Trent and Medsker, 1967). The populations, however, in both of these studies are different in a number of respects from students in short term vocational programs in general, and from students in the research population. As stated previously, differences in program length and purpose, and the student's focus on occupational outcomes are believed to set entry level vocational students apart from the students in both Astin's and Sainty's studies. These differences are also expected to influence the form and function of the prediction formula produced in this study. 232 In As-tin's review of previous studies he suggested that students' background characteristics, such as ability, secondary school grades, socioeconomic status, educational aspirations, and students' own predictions about their chances of success, were related to the potential for withdrawing from college. Sainty's study similarly dealt only with factors that students brought to the training program with them. Although Astin does make use of postentry factors to extend the predictive u t i l i t y of his original formula, neither researcher includes in his formula factors which the student encounters after he has begun his postsecondary schooling. While this approach has u t i l i t y i f the ultimate goal is to predict a student's behaviour before he begins his schooling (for example, in setting entrance requirements), i t ignores those factors which come into play after he begins training. And, according to Tinto (1987), "though prior dispositions and attributes may influence the college career and may, in some cases, lead directly to departure, . . . researchers generally agree that what happens following entry is, in most cases, more important to the process of student departure than what occurs prior to entry" (47). Although i t would not be possible to set restrictive entrance standards i f one waited until after the student began, considering both pre-entry and postentry factors would be the most effective method of identifying students who will need special attention to keep them in the program. This point was missed by Sainty (1971) even though his study is directed towards retaining rather than restricting students. In this study the development of a formula for identifying 233 TRAC students most likely to dropout was completed in a number of steps. Because factors which the student brings with him to his postsecondary schooling (i.e., pre-entry factors) and those which he experiences after enrolling are differentiated in the literature, multiple regression analysis was performed separately on each group of factors. This was done to determine which group of factors contributed more to decisions to withdraw. After the relative strengths of the relationships between pre-/postentry factors and students' withdrawal behaviour had been determined, these factors were combined to determine the extent that their combined predictive strength was increased over their individual predictive power and to produce the prediction formula. The Relationship Between Pre-entry Factors and Persistence  /Withdrawal Of the ten variables which were selected for entry into the multiple regression calculation only two met the criterion for inclusion in the equation. In this study the "criterion" was based upon the correlation between the criterion variable and the predictor variables selected for entry into the multiple regression calculation. In the stepwise selection of predictor variables, the F test for the hypothesis that this correlation coefficient is equal to 0 is calculated for each variable, and F is compared to a criterion to determine whether or not i t is to be entered into the multiple regression calculation. This criterion can be either the minimum value for F that a variable must attain in order to enter the multiple regression calculation, or the probability associated with F. In this 234 study, 'the probability associated with the F statistic was chosen and, in keeping with rationale used in the determination of statistical significance in the rest of the study (p < .05), a similar p value was used in the selection of variables for entry into the multiple regression equation. Table 84 lis t s those factors which were found to be related to persistence/withdrawal that the student brought with him from his educational experiences prior to beginning TRAC. The two factors which exhibited the strongest relationship were the students1 combined math scores on the CAT, and their age upon beginning the TRAC program. Together, these two variables account for approximately 8 percent of the dropout variance (Adjusted R Square = .08). Table 84 Statistically Significant Factors and Results from Previous Calculations (Pre-entry Factors)  Factor chi square eta F p Lambda Previous Educational Experience lh) High school graduation 5.12 (2 x 2) .02* .07 Academic Factors 2a) Scores on CAT: Reading Vocabulary .19 .01* Reading Comprehension .19 .01* Reference Skills .19 .01* Math Computation .23 .01* Math Concepts .24 .01* 2b) CAT reading scores .22 .01* 2c) CAT math scores .25 .01* Demographic Factors 3 ) Age (mean difference) 2.50 .01* 4a) Student's SES .24 .04* Motivational Factors 7c) Certainty of choice 11.15 (2 X 4) .01* Learner Self-Confidence 12) High school .13 .04* persistence/withdrawal *p < .05 235 These results can be interpreted to mean that of a l l the variables defined as pre-entry which were examined in this study, only in two cases was the relationship between them and persistence/ withdrawal strong enough to result in their inclusion in the regression equation. Furthermore, from a l l of the variables examined only 8 percent of the dropout variance is accounted for by factors defined as pre-entry. Factors which account for the remaining 92 percent of the variance remain unexplained. The factors which account for the remaining proportion of the attrition variance could come from a number of sources. The most obvious would be from those factors categorized as postentry. The other major source would be those factors that have yet to be identified in this or previous studies as being related to persistence/withdrawal. To this point, however, no study has accounted for sufficient attrition variance to lead researchers or practitioners to the belief that they know, with confidence, most of that which is related to students' decisions to withdraw. Had the intention at the outset been to identify students likely to withdraw before they began the TRAC program, the study of factors related to persistence/withdrawal could have ended here. Using only their CAT math scores from a pre-entrance test and their ages, decisions could have been made regarding their admission or participation in a retention program. However, as these two factors combined only account for 8 percent of the dropout variance, these decisions would be tentative at best. 236 The Relationship Between Postentry Factors and Persistence/  Withdrawal Table 85 li s t s those factors defined as postentry which were found to be related to persistence/withdrawal. Of the ten variables, three: the proportion of tests passed to tests written, the student's study time compared to others, and the number of tests exceeded (i.e., test scores greater than 80 percent) compared to tests written, met the criterion for inclusion in the regression calculation. Together, these three variables account for approximately 12 percent of the dropout variance (Adjusted R Squared = .12). Again, exclusive of that accounted for by the pre-entry factors, the postentry variables considered in this study f a i l to account for 88 percent of that which is included in the dropout variance. Table 85 Statistically Significant Factors and Results from Previous Calculations (Postentry Factors)  Factor chi square eta p Lambda Academic Factors 13a)Enough study time 10.40 (2 x 2) .01* .12 13b)Study time compared 23.24 (2 x 5) .01* .11 13d)Hours per week at PVI .17 .01* 14a)Tests passed/attempts .30 .01* 14b)Tests exceeded/attempts .25 .01* Motivational Factors 15b) Friends gained 11.14 (2 x 5) .03* .09 17) Success of program .15 .01* Financial Factors 18 ) Financial concern 8.04 (2x3) .02* .09 20 ) Agency sponsorship 4.53 (2x2) .03* .00 Institutional Factors 23 ) Use of Student Services: Training Consultants 8.81 (2x3) .01* .00 *p < .05 Even though the difference between the amount of variance accounted for by the pre-entry (8 percent) and postentry (12 percent) variables is not great, these results seem to indicate that what goes on after the student begins his training exerts a greater influence on his decisions to withdraw. This conclusion, although consistent with Tinto's (1987) belief, cannot be considered as proof that this view is valid. Because most of the attrition variance has not been accounted for by either pre-entry or postentry factors, there is no way of knowing i f , in that which remains to be accounted for, there exists additional factors which could be classified as either pre-entry or postentry. If, through future attrition research, additional factors related to decisions to persist or withdraw are discovered, then the question of which, pre-entry or postentry factors, account for what portion of the variance can more easily be answered. The Relationship Between Pre-entry and Postentry Factors and  Persistence/Withdrawal When a l l variables, both pre-entry and postentry, are combined in a single multiple regression equation, five of the twenty variables meet the criteria for entry into the calculation. The following variables accounted for 16 percent (Adjusted R Squared = .16) of the total dropout variance: tests passed to tests attempted, combined CAT math scores, the student's study time compared to others, the student's age on entry, and the student's perception of how much his TRAC friends gained from Common Core. The fact that a relatively small percentage of the variance was accounted for, considering the large number of variables 2 3 8 that were examined ini t i a l l y , is troublesome but not surprising. For example, in Astin's (1975) study, 53 of the original 110 predictor variables attained statistical significance and were subsequently entered in the multiple regression calculation. This number was again reduced to 31 when subgroups were formed from the total sample and analyzed separately. With the reduced number of variables, Astin (1975) states that "even though the final 20 or 25 predictors in each additional analysis add only a small amount of precision to the estimates, a l l variables that contribute anything of statistical significance (p < .05) have been included to exert the fullest possible control over i n i t i a l differences in characteristics among college entrants" (29). Astin's inclusion of a l l statistically significant variables and various subgroups of significant variables resulted in between 14.4 and 29.2 percent of the variance being accounted for. Therefore, a major portion of the variance is attributable to variables not included in his study. A similar situation existed in Sainty's (1971) study with only 17 of the original 43 predictor variables being included in the final regression analysis. Unlike Astin (1975), Sainty selected only the three variables yielding the highest R for inclusion in the development of the prediction formula. This approach resulted in 43.0 percent of the variance being accounted for. Considering the amount of variance accounted for in the present study, in Astin's (1975) stvlSy, and in other multivariate attrition studies employing similar methods (Astin, 1968; Boshier, 1973), Sainty's results seem high. As stated by Boshier (1973): "the multiple r of .79 [using a l l 17 rather than 239 only the three highest predictor variables] produced by Sainty is not in accord with these [Boshier's] findings but suspect (and unable to be generalized), since 'dropout' was not defined" (267). In addition, as mentioned previously, Sainty's study also fails to examine postentry factors which may further reduce the potential of his formula for predicting potential dropouts. The Dropout Prediction Formula To determine how effective the resulting five variables from the multiple regression calculation would be in predicting which male TRAC students dropout and which persist, the partial regression coefficients from the multiple regression analysis were used to construct a prediction formula: P/W Score = [1.770 - .620(Tests Passed/Tests Written) -.006(Combined Math Scores) + .117(Study Time Compared) - .013(Age) - .074(Perception of TRAC Friends' Gain from Common Core)] x 100 As discussed previously, the use of dummy variables for the dependent variable in regression analysis infers that persistence/withdrawal is continuous rather than dichotomous in nature. In essence what the P/W Score becomes is the propensity for TRAC students to persist or withdraw. The signs on each of the partial regression coefficients in the prediction formula indicate whether the relationship between the criterion variable (persistence/ withdrawal) and each of the predictor variables is direct (+) or inverse (-). In this equation, as the number of tests passed compared to the number of tests attempted increases, the tendency to withdraw decreases, i.e., an inverse relationship. Similarly, as students' scores on the CAT math tests or their 240 ages increase, the tendency to withdraw decreases. The perception of what their friends gained from Common Core is also inversely related to withdrawal: as the perception of the amount gained decreases the tendency to persist increases. Study time, on the other hand, is directly related to dropping out: the lower the student's estimate of the amount he studies compared to others, the more likely he is to withdraw. Substituting individual student's values for each of the five variables resulted in Persistence/Withdrawal (P/W) Scores for the research sample extending between a minimum value of .3 and a maximum value of 179.0 (due to the presence of outliers in the multiple regression calculation the theoretical maximum of 100 is exceeded). This score was related to the criterion variable in such a way that the larger the score, the greater the chance of dropping out. Therefore, a student's dropout potential is calculated by substituting his value on each of the predictor variables into the formula and the closer his score is to the maximum value, the more likely he is to drop out. To test the ability of the formula to differentiate between persisters and dropouts, the scores of both groups were compared by the percentage of persisters and dropouts included in intervals between the minimum and maximum values, and by the number of subjects included in each interval (Table 86). As calculated from the prediction formula, students' scores varied between .3 and 179.0—the higher the score, the greater the chance a student will drop out. In Table 86 "Prediction Score" represents these scores expressed using a range of 10 for each interval (e.g. 0 to 10, 50 to 59), except for the maximum Table 86 Comparing Persisters' and Dropouts' Scores Using the Dropout Prediction Formula  Prediction Persister Dropouts Score % #'s % #'s 100* 0 0 100 6 90 to 99 8 1 92 5 80 to 89 27 3 73 8 70 to 79 17 4 83 20 60 to 69 55 18 45 15 50 to 59 67 46 33 23 40 to 49 78 25 22 7 30 to 39 64 21 36 12 20 to 29 89 8 11 1 10 to 19 80 4 20 1 0 to 10 100 2 0 0 Total #' s 132 98 *Note: the inclusion of outliers in the multiple regression calculation resulted in scores in excess of the theoretical maximum. These scores have been collapsed into the final interval. score which, because no persisters scored higher than 93.8, goes to the theoretical maximum score of 100. Moving across the table, the fi r s t column after the prediction score represents the percentage of persisters who obtained a score in a particular interval, followed by the number of students whose scores f e l l in that interval. Similar information is given in the next two columns for dropouts. For example, for students whose scores f e l l in the 30 to 39 interval, 21 were persisters and 12 were dropouts. Of the 33 students who obtained scores in this range, 64 percent (21/33) were persisters and 36 percent (12/33) were dropouts. From this table i t can be seen that potential dropouts in the sample could have been identified with 100 percent accuracy i f their scores are greater than 100 and the same is true for potential persisters with scores of 10 or less. By grouping scores at the bottom (scores between 0 and 30) and top (scores 242 between 80 and 179) of the scale, i t can be said with 88 percent accuracy (14 persisters/16 persisters and dropouts) that persisters are sample students with scores of less than 30, and with 83 percent accuracy (39 dropouts/47 dropouts and persisters) that dropouts are sample students with scores of 70 or higher. Because the results in Table 86 are based upon calculations using the same students who were used in the identification of the variables for inclusion in the prediction formula, they verify the the data analysis. In terms of using the formula for predicting the dropout potential of new students, these results indicate which information needs to be collected before i t can be used for this purpose. Conclusion Five variables entered into the prediction formula: proportion of tests passed to tests written, combined CAT math scores, study time compared, age, and perception of friends' gain from Common Core. However, when combined, these variables account for only 16 percent of a l l that which resulted in male TRAC students' decisions to withdraw. In addition, these results do not justify any statement about whether pre-entry or postentry factors contribute more to these decisions. What these findings do is reveal which of the variables studied in this research are related to persistence/withdrawal for the research population. In general, this prediction formula should enable educational practitioners to reduce attrition by using either of two possible approaches. If dealing with an open access 243 philosophy to student entry, they can state with some confidence that i f entry level vocational students are provided with assistance with their math, have impressed upon them the importance of sufficient study prior to writing tests, are provided with i n i t i a l activities at which they can succeed, and are provided with content that is relevant, then their attrition can be reduced. A second approach would be to establish entrance criteria specifying high school graduation with a set grade on a particular level of mathematics. This would help ensure that students entered the program with the math and study skills indicated to facilitate early and continued success in their studies. In addition, the setting of an age requirement that reflects both the average age of persisters and the traditional high school leaving age would help ensure that students planning to enter the TRAC program have completed high school and are similar in age to those who persist. In the final analysis, much of what is related to persistence or withdrawal for male TRAC students is not indicated in the results of this study. In considering a course of action which would result in attrition reduction i t is important that this be considered. These results recommend the identification of potential dropouts for inclusion in a retention program as the preferred strategy given the that only 16 percent of the attrition variance could be accounted for. 244 CHAPTER VII SUMMARY AND DISCUSSION The primary purpose of entry l e v e l vocational t r a i n i n g i s to provide i n d i v i d u a l s with the knowledge and s k i l l s needed to obtain entry l e v e l employment. In apprenticable trades t h i s t r a i n i n g improves graduates' chances of obtaining an apprenticeship which, i n turn, leads to journeyman status and a career as a s k i l l e d tradesman. As part of the postsecondary education system, these programs provide educational opportunities f o r i n d i v i d u a l s who do not q u a l i f y f o r , or do not desire, a two-year diploma or a u n i v e r s i t y degree. Because of the short-term nature of entry l e v e l vocational programs and the marketability of the graduates, these programs are seen by s o c i a l agencies as an e f f e c t i v e means of improving the employability of t h e i r c l i e n t s . As with any educational program, to have the desired e f f e c t i t i s important f o r students to remain i n the program u n t i l completion. E a r l y leaving has costs for the student, the i n s t i t u t e , and the sponsoring agency and i t i s these costs together with the considerable number of students who f a i l to graduate, which have le d to increasing demands to reduce a t t r i t i o n . The purpose of t h i s study was twofold: to devise a means of p r e d i c t i n g which students are most l i k e l y to withdraw and, to t e s t the u t i l i t y of a t t r i t i o n factors "borrowed" from high j&i&ool, adult, and higher education research when applied to students i n entry l e v e l vocational programs. Although v a l i d a t i o n of the i n c l u s i o n of factors used i n other a t t r i t i o n research i s a natural outcome of any study of why students withdraw, i t i s 245 of more importance when studying vocational students because they have been virtually ignored by attrition researchers. In addition, knowing what factors are related to withdrawal, and being able to predict who is most likely to dropout, gives educational administrators a basis for setting entrance requirements and/or designing retention programs to increase the likelihood of successful program completion. Restricting enrollment to those with the best chance for success or developing methods to retain potential dropouts both have similar objectives: reduced attrition. This, the final chapter, is a review of the major findings of the study centered around its two purposes: validation and prediction. The research design will be detailed including a description of the research site, population, and sample, followed by an explanation of how the data were gathered and analyzed. The significant findings will then be examined for meaning in the context of the program and the population, and, the prediction formula will be interpreted. Finally, the findings will be discussed in terms of their u t i l i t y for educational practitioners and the limitations of the study will be reviewed and recommendations made for future research. The Design of the Study In selecting a research site, population, and method, a number of factors were considered. First of a l l , the program had to be entry level vocational t-uining. Next, to facilitate generalization of the results to similar kinds of training programs, i t was necessary to choose a site where a variety of trade specialties were taught. The concern was that by looking 246 only at a small number of trades the applicability of the results may be affected by differences that were particular to, for example, construction or mechanical trades. Because data were to be gathered using a questionnaire, i t was important to choose a program with a large enough enrollment to ensure a response that would be adequate for purposes of analysis. A population heterogeneous with regard to academic background was also believed by the researcher to be important. Including students with a variety of educational backgrounds would be useful in clarifying the relationship between previous educational experience and persistence/withdrawal. The logistical concerns of cost and easy access to institute records were also considered, and finally, the program had to have an attrition level high enough to be of concern to program administrators. Site Selection The program which best met each of the requirements was the Training Access (TRAC) program at Pacific Vocational Institute in Burnaby, British Columbia. TRAC was a competency-based entry level trades program incorporating a continuous entry/exit, self-paced, and student-driven delivery method. It encompassed 22 different trade specialties and had an enrollment of between 1300 and 1500 students at any one time. Because there were no entrance requirements other than a minimum age, i t attracted studetitss with a wide variety of educational backgrounds. The fact that the researcher was employed by the Institute made access to students' records easier and kept the costs involved to a minimum. Finally, as reported in a province-wide evaluation 247 of the program, TRAC had an attrition rate between 40 and 60 percent (Russnell and Collins, 1985). Population and Sample Selection Because TRAC had gone through some dramatic changes during its i n i t i a l start up phase, the program itself was considered a factor with the potential to confound others such as early program performance and those related to students' perceptions of the value of TRAC. In the early phases of TRAC, learning materials were not a l l available, policies and procedures were changed as system "bugs" were encountered, and the recording of students' progress changed from a paper-based to a computer-based system. For these reasons the selection of the research population was designed to coincide with a period when the TRAC program began to run relatively smoothly: from September 1984 to when the last student enrolled in May of 1986. From this population (1473), including a l l male students (except those taking Horticulture) who began the program between September 19, 1984 and May 6, 1986, a cohort of students was selected to coincide with the beginning of basic s k i l l testing at PVI. Therefore, the sample included a l l male students who had begun TRAC during the six month period between April 24, 1985 and October 23, 1985 (N = 634). Because random selection was not used, students who enrolled prior to and after the sample students were compared to the selected cohort on age, as well as on Canadian Achievement Test scores for the postsample group. This was done to determine i f a l l students belonged to the same population. The results indicated that differences that did exist could be explained and 248 were of no practical significance and, therefore, that the sample could be thought of as representative. Data Collection For each hypothesized relationship between the criterion and predictor variables data were collected for analysis. These data were obtained from two sources: students* records and a mailed questionnaire. Information on age, enrollment status, and early program performance was obtained from the students' computer file s . In addition, the results of the Canadian Achievement Tests and scores on Rotter's I/E Scale (locus of control) were also obtained from the students' records following testing which was done routinely at PVI during the fi r s t two days of attendance. Information which was not available from Institute records was obtained from students using a mailed out questionnaire. Based upon the hypothesized relationships indicated in the attrition literature, decisions were made regarding the kinds of information that were required. Questionnaire items were then designed to obtain this information and the completed survey and letter of transmittal was reviewed by the researcher's colleagues at PVI. This material was then tried on a group of TRAC students attending the program at the time. Following this, the questionnaire was reviewed by the researcher's committee and, after incorporating the modifications recommended during the revief process, the instrument took on its final form. Prior to printing and distributing the questionnaire to the research sample, i t was pilot tested by mailing i t to a group of students not included in the research sample. This was done to 249 t e s t the a d m i n i s t r a t i o n procedure and t o g e t an i d e a o f what c o u l d be expected f o r a response r a t e . T h i s p r o c e s s a l s o p r o v i d e d a f i n a l check on the form and con t e n t o f the q u e s t i o n n a i r e . The q u e s t i o n n a i r e was m a i l e d t o the sample d u r i n g the S p r i n g o f 1986. T h i s f i r s t m a i l - o u t was f o l l o w e d by a reminder l e t t e r two weeks l a t e r and a l l nonrespondents r e c e i v e d a second copy of the q u e s t i o n n a i r e , l e t t e r o f t r a n s m i t t a l and s e l f - a d d r e s s e d , stamped, r e t u r n envelope t h r e e weeks a f t e r t h a t . Because the response r e c e i v e d from TRAC dropouts d i d not r e f l e c t t h e i r a c t u a l p r o p o r t i o n i n the sample, a t h i r d package was addressed t o a l l nonresponding dropouts s o l i c i t i n g t h e i r a s s i s t a n c e and o f f e r i n g them an i n c e n t i v e f o r completing and r e t u r n i n g the q u e s t i o n n a i r e . T h i s r e s u l t e d i n a s m a l l i n c r e a s e i n t h e number o f responses r e c e i v e d from t h i s group. Data A n a l y s i s As t h e completed q u e s t i o n n a i r e s were r e t u r n e d , the s t a t u s o f the s t u d e n t ( e i t h e r p e r s i s t e r o r dropout) was e s t a b l i s h e d and the q u e s t i o n n a i r e responses were t r a n s f e r r e d t o computer scannable s h e e t s . These sheets were then scanned t o c r e a t e a computer da t a f i l e . T h i s f i l e c o n s i s t e d o f both nominal or o r d i n a l , and i n t e r v a l o r r a t i o measures. The c r i t e r i o n v a r i a b l e , p e r s i s t e n c e o r withdrawal, was nominal i n nature. The form o f t h e data d i c t a t e d the s t a t i s t i c a l method used i n i t s a n a l y s i s . Where the p r e d i c t o r v a r i a b l e was nominal or o r d i n a l , a c o n t i n g e n c y t a b l e was produced and a c h i square c a l c u l a t i o n performed t o determine i f t h e d i f f e r e n c e s between the observed and expected f r e q u e n c i e s were s t a t i s t i c a l l y 250 s i g n i f i c a n t . In these c a l c u l a t i o n s the PRE ( p r o p o r t i o n a l r e d u c t i o n i n e r r o r ) measure "lambda" was used t o i n d i c a t e the s t r e n g t h of t h e r e l a t i o n s h i p between the v a r i a b l e s . In cases where the independent v a r i a b l e was an i n t e r v a l o r r a t i o measure, the c o r r e l a t i o n r a t i o (eta) was used t o g e t h e r w i t h the F r a t i o which t e s t s e t a f o r s t a t i s t i c a l s i g n i f i c a n c e . E t a c o u l d then be c o n v e r t e d t o a number i n d i c a t i n g t h e percentage of v a r i a n c e a t t r i b u t a b l e t o the p r e d i c t o r v a r i a b l e which, l i k e lambda, was a l s o a measure o f the s t r e n g t h o f t h e a s s o c i a t i o n . For each h y p o t h e s i z e d r e l a t i o n s h i p , a s t a t i s t i c a l t e s t was performed t o determine the s i g n i f i c a n c e o f t h e r e s u l t s and whether the n u l l h y p o t h e s i s was accepted o r r e j e c t e d . Once the s i g n i f i c a n t r e l a t i o n s h i p s had been i d e n t i f i e d , a second a n a l y s i s was done t o determine i f combinations o f t h e s e v a r i a b l e s c o u l d s e r v e as a b e t t e r p r e d i c t o r o f dropout. M u l t i p l e r e g r e s s i o n was used i n t h e s e c a l c u l a t i o n s which were performed on v a r i a b l e s d e f i n e d as " p r e - e n t r y " ( c h a r a c t e r i s t i c s t h a t t h e s tudent brought w i t h him t o h i s postsecondary experience) o r " p o s t e n t r y " ( f a c t o r s encountered a f t e r the student had e n r o l l e d ) . T h i s a n a l y s i s was performed a t h i r d time when both p r e - e n t r y and p o s t e n t r y f a c t o r s were combined t o produce an e q u a t i o n designed t o p r e d i c t dropout. Research F i n d i n g s The r e s u l t s o f the s t a t i s t i c a l a n a l y s e s were r e p o r t e d i n t h r e e d i f f e r ^ i a t ways. F i r s t , each of the hypotheses was t e s t e d u s i n g t h e s t a t i s t i c a l method d i c t a t e d by t h e measure d e f i n i n g t h e v a r i a b l e s . These a n a l y s e s were c a t e g o r i z e d as p r e - e n t r y and p o s t e n t r y . Based upon the r e s u l t s o f t h e s e c a l c u l a t i o n s each 251 hypothesis was either accepted or rejected. Next, those variables which produced statistically significant relationships when associated with persistence/withdrawal were entered into a multiple regression equation. Multiple regression analysis was used to determine i f groups of variables would produce results accounting for more attrition variance than did individual variables. These calculations were again categorized into pre-entry and postentry factors. Finally, a l l the statistically significant factors were combined, again using multiple regression, to provide a formula for predicting which students would persist and which would withdraw. Response Rate The result of the mail-out of the survey packages and subsequent follow-up was a 53.5 percent response rate. Seventy-two of the 629 survey packages sent out were returned by the Post Office. The response rate was, therefore, based on the number of responses received by the researcher compared to the number that actually reached the sample members. Of the 298 responses received, 61.4 percent were from TRAC persisters and 38.6 percent were sent by TRAC dropouts compared to 41.2 percent and 58.8 percent, the actual proportions of persisters and dropouts in the sample. Because the response rate was less than 100 percent, respondents and nonrespondents were compared by age, CAT scores, I/E Scale scores, the number of credits rec_ived for previous education or work experience, and the total number of tests on which the criteria for mastery was met, not met, or exceeded plus the total number of tests written during the student's f i r s t six weeks in the program. These factors were compared between responding and nonresponding persisters and dropouts. The results indicated that there were no significant differences between persisters who completed and returned the questionnaire and those who had not. Similar results were found for dropouts on a l l factors except tests passed, exceeded, and attempted. On each of these factors the means of the respondents exceeded the means of the nonrespondents with the differences between the means being statistically significant at the .05 level. These differences seemed to indicate that the respondents were more active during the f i r s t six weeks of their program, whereas nonrespondents may have left the program during that period. These differences were not seen by the researcher as an indication that the responding and nonresponding dropouts were members of two different populations; the remaining research was based on the assumption that this was not, in fact, the case. Pre-entry and Postentry Factors in Relation to Persistence/  Withdrawal Throughout the literature concerned with why postsecondary students withdraw from training, the student's previous experience is considered apart from what happens to him after he enrolls. The idea of pre-entry and postentry factors is followed in this study. Variables are considered in relation to when they were encountered by the student and then, in total, as to which cluster of variables, pre-entry or postentry, had the greatest possible impact on students' decisions to persist or withdraw. Although i t makes sense to follow this format in first organizing variables for examination, a more holistic approach 253 is then required to answer the question of why some TRAC students withdrew from training. Pre-entry factors are described as those that the student brings with him to his postsecondary schooling. In this research these are divided into a number of categories, each of which is subdivided into relationships selected for their relevance to PVI's TRAC students and stated in the form of a null hypothesis. Defined as pre-entry categories are: previous educational experience (11 hypotheses), academic factors (3 hypotheses), demographic factors (7 hypotheses), motivational factors (12 hypotheses), and learner self-confidence (2 hypotheses). The acceptance or rejection of each hypothesis was based upon the results of the statistical analysis. The conclusion drawn from the examination of the pre-entry factors is that "good" students are better able to successfully complete the TRAC program at PVI. In this study those characteristics which differentiate TRAC persisters, i.e., good students, from TRAC dropouts are high school graduation, higher levels of basic math and reading skills, higher socioeconomic status, a strong conviction that their choice of training was the right one, and the belief that they were responsible for their own success or failure. In terms of "raw material" these characteristics are what most teachers would desire for their students, regardless of subject or field. Although at first glance socioeconomic status seems unrelated V&_ the other factors, i t was believed to be related by the breadth of educational experience that the student enjoyed both in terms of what his parents could afford and their educational values. 254 The concept of being in control of one's own success or failure stems from the discussion in Chapter II regarding learner self-confidence and the use of Rotter's I/E Scale (locus of control) as a measure of this construct. Self-confidence was described by Burke (1983) as consisting of two components: ability and effort. In an educational context this was interpreted by the researcher to mean that the effort expended would be dependent upon the student's evaluation of his ability. If the student's past educational experiences led him to guestion his abilities as a learner (i.e., lack of learner self-confidence), such as may be the case for a high school dropout, then he may see l i t t l e relationship between personal effort and success. This lack of effort would, upon subsequent attempts, result in lack of success thus confirming the relationship and leading to withdrawal. Failing to see ability as part of the equation for success, the student would assign the responsibility for his success or failure to forces outside his control. As a measure of whether one sees himself (i.e., internal control), or, external forces (i.e., external control) as responsible for the outcomes of his actions, Rotter's locus of control measure, the I/E Scale, was selected as a measure of learner self-confidence. The results of the examination of the relationships between Rotter's concept of locus of control and persistence/withdrawal in the TRAC program ,<.ifid in high school partially reinforced the outcomes anticipated by the researcher. A belief in personal control was related to persistence for TRAC students but to withdrawal for this group while in high school. 255 An additional conclusion stems from the pre-entry results when taken in total. While the skills the student brings with him to postsecondary schooling provide the tools necessary for his success, the impact of his feelings and perceptions surrounding what occurred in public school seems reduced once the student begins college. For example, skipping a grade and enjoying school, while both related to high school graduation, were also related to dropping out of TRAC. In a similar way, TRAC persisters believed they were instrumental in influencing their own futures, whereas high school dropouts also held this view. These seemingly conflicting results may signal a change that occurs between the time the student leaves high school and some point before he begins or at some point during his postsecondary education. The fact that high school dropouts and TRAC persisters saw themselves as responsible for their own learning outcomes could be a sign of increasing maturity which appears as the student leaves adolescence and moves towards l i f e as a young adult. This finding is reinforced by the fact that TRAC persisters were about 14 months older than TRAC dropouts. Such a change may also explain why " . . . researchers generally agree that what happens following entry is, in most cases, more important to the process of student departure than what occurs prior to entry" (Tinto, 1987: 47). Postentry factors are generally described as being related to what occurs after the student is enrolled in pos_S_condary school. In this study both categories, pre-entry and postentry, share similar variables. For example, academic and motivational factors, which are developed both before and after he enrolls, 256 are included in both categories. A process similar to that used for pre-entry factors was followed in determining the relationship between postentry factors and persistence/withdrawal. Variables relevant to TRAC students at PVI were selected from existing research and stated in terms of a null hypothesis, data were collected and analyzed, and, based on the analysis, a decision was made to accept or reject each hypothesis. Factors defined as postentry were academic (7 hypotheses), motivational (7 hypotheses), financial (4 hypotheses), institutional (9 factors), and whether or not a student was an attainer—ascribing to a personal rather than institutional definition of completion. Similar to conclusions extending from the findings for pre-entry factors, those characteristics or actions associated with being a good student were also related to persistence when postentry factors were examined. TRAC students who believed they spent enough time studying prior to writing a test, felt they spent more time studying than others, and those who spent more time at school each week were more likely to be persisters. The apparent belief that "hard work pays off" was substantiated as persisters required fewer attempts than dropouts to pass or exceed the criterion for test mastery. Persisters also gave the TRAC program more credit for the number of graduating students than did dropouts. In addition to hiding the academic and study skills characteristic of successful students, persisters seemed to be less concerned about money. Unlike the findings of higher education researchers (Lenning et al., 1980), this study 257 indicates that dropouts' concern about the adequacy of their financial resources is real because more of them turned concern into action by applying for student loans. Even among sponsored students, who are more likely to be persisters than dropouts, concern about having the money necessary to make ends meet was high. This relationship between increasing financial concern and dropping out would seem to indicate a problem may exist with the present student financial assistance programs. The findings that TRAC dropouts believed their friends gained something from Common Core, and that visiting a Training Consultant was more common for dropouts, while opposite to that anticipated, were explained by the kind of exposure TRAC dropouts had to the program. For example, because 80 percent of a l l dropouts left while in Common Core, they, unlike persisters who completed Occupational Core and Specialty, had nothing with which to compare their gains from Common Core. While persisters saw very l i t t l e benefit obtained from this part of the program by themselves or their friends, dropouts seemed to want to attribute some positive outcome to participation in the program, but would not go as far as indicating that i t was themselves who had benefitted. This negative perception regarding TRAC is also seen in the low estimate given by dropouts to TRAC's success in graduating participants. In a similar way, because only those who were falling behind in the program were required to vis i t a iraining Consultant, these visits were more common for dropouts than persisters. Dropping out, therefore, is not seen as directly related to visiting a Training Consultant, but is attributed again to an experience more common for dropouts than 258 persisters. In conclusion, these result indicate that students who are adequately prepared for the challenges of postsecondary schooling are more likely to successfully complete. Adequate preparation in this case can be narrowed down to graduation from high school—having the academic skills gained and the study skills developed and proven in this environment. In itself this is not a very novel or momentous discovery because i t exists now as a common and logical assumption. The term "assumption" is used because attrition research done with populations other than vocational students is often applied on an assumptive basis to vocational populations as well. Most college and university programs consider high school graduation as a "given"—it is required as a prerequisite. On the other hand, adult upgrading programs make no assumptions about the skills students bring to school. Only in vocational programs are high school graduates and nongraduates mixed on a regular basis. Accordingly, this study lends credence to the importance placed on graduation from high school and defines the components of graduation, such as competence in basic skills, that define its importance. Dropout Prediction As stated previously, knowing the relationships between variables which produce statistically significant results is important in validating the relevance of factors borrowed from adult and higher education research when they are applied to entry level vocational populations. In isolation, however, this knowledge has limited value for the practitioner attempting to deal with a high attrition rate. The value is increased when 2 5 9 these variables are combined to produce a formula with predictive power and using i t to identify which students are potential dropouts. This was the primary objective of this research. When considering pre-entry variables which, when compared to persistence/withdrawal, produce a statistically significant relationship, only two variables met the statistical requirements for inclusion in the stepwise multiple regression calculation: the combined CAT math score and the student's age. Together these two variables produced a result indicating that, combined, they account for 8 percent of the total dropout variance. This leaves the remaining 92 percent of the variance unaccounted for. Part of this unaccounted variance would logically be part of that included in variables described as postentry. The result from the multiple regression analysis using postentry variables accounted for 12 percent of the dropout variance. In this calculation three variables met the criteria for entry into the calculation: proportion of tests passed to tests written, the study time of the student compared to others, and the number of tests on which the criterion of mastery was exceeded compared to the number of tests written. Although accounting for a greater percentage of the dropout variance, the difference between pre-entry and postentry variables is not gr#&t enough to say with confidence that what occurs after tn_ student enrolls is more closely related to his decisions to persist or withdraw than what he brings to the postsecondary experience with him. When pre-entry and postentry variables were combined, five were included in the multiple regression analysis. Tests passed to tests attempted, combined CAT math scores, the student's study time compared to others, age, and the student's perception of how much his friends gained from Common Core, were entered into the calculation in a stepwise fashion and produced a result accounting for 16 percent of the dropout variance. Although accounting for a relatively small percentage of the variance, these results are not unlike those produced in other attrition studies (Astin, 1975; Boshier, 1973; Sainty, 1971; Astin, 1968). Essentially, what these results and those of other researchers indicated is that much of what enters into a student's decision to withdraw or persist has yet to be discovered. To determine the effectiveness of the five variables included in the combined pre-/postentry calculation in predicting dropout, partial regression coefficients from the multiple regression analysis were used to produce a prediction formula: P/W Score = [1.770 - .620(Tests Passed/Tests Written) -.006(Combined Math Scores) + .117(Study Time Compared) - .013(Age) - .074(Perception of TRAC Friends' Gain from Common Core)] x 100 By substituting individual student's data for each variable into the formula a P/W (persistence/withdrawal) Score was calculated. These scores had a potential range from a minimum of .3 to a maximum of 179.0 for the research sample. The relation between these scores and persistence/withdrawal is such that the larger the score, the greater the chance that a student will dropout. For example, in comparing sample students' scores to their 261 status in the TRAC program (i.e., persister or dropout), persisters were identified with 100 percent accuracy i f their score was less than 10 and, similarly, dropouts with scores larger than 100 were identified with similar accuracy. Theoretically, by selecting a desired level of discrimination, entrance criteria could have been specified for the sample or potential dropouts could have been identified for inclusion in a retention program. The development of a prediction formula provides educators with two possible courses of action. First, i t provides a tool for use by administrators to set admission criteria to restrict entry to only those students who are likely to succeed, and, second, i t gives a means of identifying students likely to withdraw while providing an indication of target areas which would provide the greatest return on resources dedicated to a student retention program. Either choice would be expected to have the effect of reducing program attrition. Conclusions Validation and prediction, as stated in the introduction to Chapter VII, were the primary objectives of this study. The validation of attrition factors "borrowed" from other populations when applied to the research population, and the prediction of dropout for male students from entry level vocational programs were the anticipated outcomes. In both cases certain Conclusions can be drawn from the results of the study. Validation of Borrowed Factors In terms of expanding the frontiers of knowledge in adult or higher education, the examination and testing of that which 262 other researchers have already discovered may seem like a redundant activity. This criticism is not unjustified unless the population under study has been overlooked by other researchers and has resulted in the application of untested assumptions to this group. As stated by Dennison and Gallagher (1986), Canadian community colleges do not see research as one of their functions, and, as further pointed out by Gates and Creamer (1984), even when two-year institutions do conduct research, vocational students are virtually ignored as a research population. Therefore, upon selecting the study of attrition in entry level vocational programs, the researcher had attrition factors from adult and higher education to use as a starting point, but, unfortunately, very few had been applied to the population of interest. Previous studies provide an i n i t i a l direction for research in an unexplored area, but they may have also resulted in important factors being overlooked. Of the 63 relationships tested, only 22 were statistically significant. In other words, a third of the factors borrowed from adult and higher education research produced similar results when applied to entry level vocational students. Furthermore, only 5 of these 22 variables were identified as a result of the analysis for entry into the multiple regression calculation which ultimately produced the dropout prediction formula. Combi:;__, these five variables accounted for only 16 percent of the total dropout variance. A variety of reasons for the unaccounted dropout variance are possible. It may be that important factors were not selected for inclusion in the research. Also, certain factors, such as the TRAC program itself, may account for a portion of the undiscovered attrition variance. It is also possible that the measures used in defining the variables lacked precision, resulting in a number of Type II errors. It is believed by the researcher, however, that the major reason why the variables examined in this study accounted for only a small portion of the total variance is because the populations from which they were borrowed and, to which they were then applied, were different from one another. An important factor which distinguishes entry level vocational programs from other postsecondary programs is their short length. This, together with the close relation between the vocational program chosen and the student's occupational goal, makes participation in an entry level vocational program different from participation in diploma or degree programs. Because vocational programs are usually between 6 and 12 months in duration, compared to two years for a diploma and four years for a degree, students do not have to endure withdrawal related factors for a long period of time. For example, even though financial concern was indicated to be a significant factor, for vocational students i t is a short-term problem. Similar statements can be made about the support that students felt from their family and friends, how well they f i t within the social structure of the institute, and the effort required to keep up with their studies. Over the short-term students may be better able to deal with a lack of support from their family and friends, feelings that they do not belong, or even attend school 264 and hold down a part-time job. Compared to college or university students, the length of time that vocational students have to endure the pressures of participation is short. Time may also play a part from a motivational perspective. Vocational students take training presumably to obtain employment. The relationship between their educational and occupational aspirations is direct and clearly visible. For students in a four-year degree program this may not be the case. The lack of a clearly defined "end" may influence the way these students look at the "means." Factors such as deferment of gratification and commitment, although having meaning for students in programs of different lengths may, however, differ in the way they are related to persistence/withdrawal. Although providing a guide for the i n i t i a l examination of factors related to attrition in the research population, the borrowed factors only partially explained the relationships between them and dropping out. Further research is s t i l l required and the focus needs to be shifted to factors not yet examined. For example, attrition research tends to examine the characteristics of the student, the institution, the interaction between them, and factors external to both but fails to focus on the program of study. Even though program evaluation is an integral part of the program planning process, seldom is the program itself mentioned as related to student withdrawal. This aspect of students' decisions to wichdraw seem to be inferred from responses regarding their satisfaction or dissatisfaction with the program. But, similar to "previous educational experience", perhaps satisfaction needs to be broken into its 265 operating variables and examined more closely. Variables such as the student's orientation to the program, the placement of practical experiences in relation to the completion of the related theory, and expectations regarding the student's prerequisite knowledge and experience may have an impact on decisions to persist or withdraw beyond a general feeling of satisfaction. The Prediction of Dropout The prediction formula is the distillation of the results of this research into a usable form. Determining which variables are the best predictors of dropout, and the combination producing the most effective results is a valuable concept that can be used by educational practitioners. But in addition to the development of a "tool," other results of a more general nature were also produced. Statements about what promotes persistence, what appears not to influence i t , and possible reasons for each, are also relevant to other populations and educational programs. From the results of this research i t seems reasonable, though hardly surprising, to say that the better prepared a student is prior to enrolling in a postsecondary program, the better are his chances for completion. Certain factors lend credence to this general statement. Factors such as high school graduation, basic reading and mathematics ski l l s , and study skills are related to a student's pre-entry preparation, and also to pers i s tence . Students who have graduated from high school are generally better prepared to handle the demands of a postsecondary education. This is true only i f the functional components of graduation include a basic level of competence in reading and mathematics skills and these skills are necessary tools for learning in the new situation. In addition, competence does not come without the development of certain strategies for dealing with the transfer of information into knowledge, and the application of this knowledge to specific tasks. These strategies, commonly called "study skills , " are a part of being a competent student and are also related to persistence. However, in terms of the certification of competence, high school graduation is no guarantee that graduates possess these prerequisite skil l s . If, as indicated from this study, these skills are important in retaining students, a strong case can be made for the functional testing of basic skills as an entrance requirement for a l l . Also attached to the relationship between being prepared for and persisting in postsecondary schooling is socioeconomic status (SES). in this study SES was directly related to persistence. This finding is similar to that found by other researchers (Lenning, et al. 1980), but the results of this study are more direct. Similar to high school graduation's relationship to persistence, i t is the components of SES which are most likely related to students' decisions to persist or withdraw. The ranking scale used in this study (McRoberts, 1976) defines SES according to education, salary, and occupational prestige. Because salary and occupational prestige are commonly a product of education, i t seems reasonable to make the connection between a parent's level of education and the influence this exerts on the children. The connection between 2 6 7 education and the benefits i t has brought to the parent would probably not go unnoticed by the child. This could be reinforced further by the educational opportunities afforded the child by the parent such as access to books, educational television, travel, and even private school. It is possible that these components of higher socioeconomic status could influence high school performance, thereby preparing a student to successfully cope with postsecondary schooling. The Study's Contribution to the Knowledge Base Beyond the validation of borrowed factors and the prediction of dropout, the question may be asked about what this study contributes to the knowledge about postsecondary attrition. The review of the research from adult and higher education previously described the search for knowledge about attrition as evolutionary. Starting with "how many" and "who" drop out, moving towards the "why" of withdrawal, the evolution gradually moved towards the development of theories attempting to explain this behavior. In neither case did researchers jump immediately to the explanation of the phenomenon without fi r s t understanding its components. Explaining the theoretical basis for withdrawal from entry level vocational programs by adopting that which applies to other postsecondary populations is inappropriate. The wholesale adoption of factors related to dropout for adult basic education or university populations for the development of a prediction forsala would have similarly been inappropriate. Therefore, in the final analysis, what this study adds to what is already known about why students drop out is empirical evidence about the important factors for a specific 268 postsecondary population. Had the research population consisted of students enrolled in adult or higher education programs, Darkenwald's (1981) criticisms of the redundancy of empirical, atheoretical research would be well-deserved. However, considering the lack of attrition research which targets entry level vocational programs, theory building is only appropriate as a future activity. Vocational education at the postsecondary level is as different from its counterparts as they are from each other. From the populations served to the outcomes, each has carved out its own niche in the broad field of education. Because of the nature of vocational education, progress towards answering the relevant questions has been slow. The findings of this study, therefore, contribute only to the "why" of vocational program attrition. To attempt to advance a theoretical description of the dropout behaviour of vocational students would be conjectural and inappropriate given the stage in the development of vocational attrition research. As an interim step in the move towards theory building, a research emphasis directed at how the populations and programs associated with postsecondary vocational education differ from other postsecondary education may prove to be an effective strategy. For example, the relationship between motivation and course length, motivation and the specificity of the occupational goal, competence in specific academic skills (i.e. mathematics versus reading) and success in learning practical skills, and the financial sponsorship of students and their financial concerns, are a l l research questions for which answers can help further define 269 vocational populations and speed the move towards the development and application of theory. Limitations and Implications for Further Study A review of the research indicates that studies which have similarly attempted to predict dropout have been unable to account for other than small portions of the variance related to withdrawal. An inherent danger in attempting to predict who will persist and who will withdraw is the credence this lends to prediction in other than research related activities. As indicated in Dennison and Gallagher's (1986) study, the perceived research needs of educators in Canadian community colleges regarding attrition are directed at the selection of students most likely to succeed. To infer that such selection is possible provides a rationale for throwing up a variety of barriers to participation in postsecondary education and makes i t difficult to justify the maintenance of an open access philosophy. In most cases this stems from a confusion on the part of administrators and admissions officers with regard to equating persistence with success and withdrawal with failure. Even though i t is legitimate to outline and require the skills necessary for success in new learning, i t is not valid to tie directly together relationships between variables and causation. The possibility that the prediction equation developed from this research could be used as a means for selecting students for admission to vocational programs is, therefore, a potential limitation. This study was handicapped by a condition shared by every study which bases its findings on information collected from 270 human subjects: an inability to get " a l l " the facts. More than not getting a one hundred percent response rate on a questionnaire, or not having the same data available from each student's institute records, i t also involves the use of subjective measures. A number of examples in the present study exist where the results of the analyses do not agree with the findings of other researchers. Although in terms of statistical significance i t is not safe to reject the hypothesis based on these results, i t leaves the researcher questioning whether the results would have been significant had a more rigorous measuring stick been available. Specific cases in the present study include the relationship between the size of students' loans or their high school grades, and persistence/withdrawal. Because actual details regarding how much a student borrowed were confidential, requiring a reliance on the information volunteered by the respondents, i t is possible that the results of the analysis were not a true indication of the actual relationship. Similarly, relying on a student's recollection in stating whether he was an "A," "B," "C," "D," or "F" student in high school makes assumptions regarding his accuracy of memory, truthfulness of response, and ability to "average" the meaning of letter grades into a single response. Ultimately, the researcher has to make do with the information that is accessible. A similar and related limitation of this research had to do with the methods used and the content of the data collected by the institute. At PVI data were generated at four points in a student's program: during admission, during the delivery of the 271 program, upon completion, and after the student left the Institute. Unfortunately, even though a considerable amount of data were gathered, departments were responsible only for that which directly affected them and data were not combined into one data base. For example, Admissions and Records utilized the Student Record System (SRS), whereas TRAC had its own computer system on which the students' progress was tracked. Furthermore, follow-up information on what the student did after either graduating or withdrawing was never gathered on a consistent basis. This is not a criticism leveled specifically at PVI but, considering the limited role that research appears to play in the college system (Dennison & Gallagher, 1986), i t is likely that the collection of data for purposes beyond the immediate needs of the college is not a common activity. Unfortunately, once the student leaves school, much of the data which could answer questions regarding why he completed or withdrew leaves with him. A third limitation of this study concerns the lack of research directed specifically at postsecondary vocational students. Rather than approach the reasons for student withdrawal by establishing a causal link between a factor and its outcomes, i t was necessary to take a shotgun-like approach to f i r s t establish where the relationships were. At best this indicates that there exists, for example, a relationship between higher levels of basic mathematics skills and TRAC persistence. It does not, however, mean that improving the mathematics skills of potential dropouts will result in more of them successfully completing the program. Nor does i t indicate why or how mathematics skills are important in a program which by nature deals with practical and "hands-on" skills rather than those which are primarily theoretical and academic. Had the field of possible factors been already defined, an different approach may have been possible. Each of the above is related to limitations which are of obvious concern when examining a phenomenon from an quantitative perspective. However this is only one possible vantage point from which to examine why some students persist while others withdraw. Given the inability of this and other researchers to account for the majority of factors which are related to attrition, i t may be appropriate to recommend methods other than identifying, measuring, and counting that which is believed to be related to the act of dropping out. Academic abilities are indicated to be related to the act of persisting or withdrawing, however many student, especially those who withdraw voluntarily (Tinto, 1987), have more than enough academic power to successfully complete the tasks. It may in future prove to be more fruitful to examine the decision making process of students contemplating dropping out rather than that which is believed to influence this decision. Recent attempts to interview both completers and dropouts have provided some qualitative insights into the decision making process. Persisters seem to have a better understanding of their selected trade. This understanding may have come through their family's involvement with that trade, a part- or full-time job previous to returning to school, a hobby, a talent recognized through participation in high school Industrial Education, the 273 process of occupational elimination, or a combination of these. Dropouts, on the other hand, seem less aware of what the outcome of their training will be.. Not having a clear vision or well defined goal, they seem more easily deterred by the difficulties encountered by any adult going to school. This method of investigation seems to provide a gestalten view of attrition which gets lost in attempts to quantify and examine the phenomenon in groups. Similar to that found to be an early problem in the study of higher education populations, a failure to adequately define terms may have narrowed the field of findings in this study. To simply examine attrition as an either/or alternative dismisses the possibility that there exists a typology of withdrawal types. Even though they were described as a separated and distinct class of dropouts, attainers could not be said to be typical of persisters or dropouts in terms of their characteristics. In a similar way, TRAC students who stopped out, transferred, changed programs, withdrew early or late, registered but failed to show up, withdrew for disciplinary reasons, failed, or withdrew for positive reasons, were not set apart in this study. It is possible that different factors affect different types of dropouts. In retrospect, and based upon day-to-day contact with vocational students, the researcher has observed the results of the decision to withdraw imt s t i l l feels unable to adequately explain i t . Much seems to revolve around the type of students who choose a trades career and the environment they enter to prepare for i t . Intuitively i t appears that those who select a 2 7 4 trade are amenable to the rather rigid structure imposed while in training and subsequently encountered as workers. It is not obvious whether this is part of the socialization process which exists as part of the training environment or is brought to training by the students. Thus the concept of f i t or congruence seems to be an appropriate factor in studying vocational students' experiences, however i t would seem more related to how the students interacts with the training, occupational, and work environments rather than how they interact with their fellow students, instructors, and the institute. 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Certain questions refer to C o m m o n Core . If you are now in Occupat iona l or Specialty please try to answer the questions according to the way you felt when you were in Common Core. By complet -ing this quest ionnaire you will be helping us find ways to improve the T R A C program. For each quest ion s imply put a check • by your answer or fill in the blank as required. GENERAL INFORMATION Student ID # 1. Age (on the day you started the TRAC program): years 2. Place of Birth: City Province/State Country 3. Marital Status: • single • married (including common-law relationships) • separated • divorced 4. Number of Children: 5. Parent's occupation (or previous occupation if now retired or unemployed) Father's Occupation: — — Mother's Occupation: ——— 6. Which of the following statements best describes your present enrolment status in the TRAC program? 1 • Active full-time — you are at PVI at least 30 hours per week on a regular basis • Active part-time — you are at PVI less than 30 hours per week on a regular basis • Inactive—you have told the Control Center staff that you are working, will not be at PVI for a period of one month or longer, and plan to return in (month), 198 • Inactive—you have told the Control Center staff that you are taking time off, will not be at PVI for a period of one month or longer, and plan to return in (month), 198 • Withdrawn — you have officially withdrawn because you have found full-time employment • Withdrawn — you have officially withdrawn for other reasons • Completed — you have completed all course requirements and have been told by the Control Center staff that your PVI certificate wi(f be sent by mail - . • Temporarily Inactive—you have told the Control Center staff that you will not be at PVI for a period of less than one month and plan to return in (month), 198 285 7. If you withdrew because you have found full-time employment is that employment related to your TRAC specialty (e.g., Heavy Duty, Joinery,.etc.)? • Yes • No 8. If you withdrew for reasons other than employment which of the following describes why you withdrew? • family responsibilities • illness (family or personal) • personal problems • I changed my goals • not enough money • course was not what I expected Q other: PREVIOUS EDUCATION 9. What was the last grade you completed and when did you complete? Grade When 19 10. Do you have a high school diploma? • Yes • No . 11. If you attended high school what were the courses you took designed to prepare you for: • university entrance • vocational institute entrance • apprenticeship • business careers • employment 12. During elementary school did you ever repeat a grade? d Yes • No 13. During elementary school did you ever skip a grade? • Yes d No 14. Based on your marks in secondary school were you: d an "A" student d a "-"Student d a "C" student • a "D" student d an "F" student 15. If your former teachers were asked about your behaviour as a student, which of the following statements do you think would be closest to their responses: • he was a perfect student, never caused any problems • he was an average student, I don't remember him as causing problems d if there were problems he was usually involved d if there were problems he usually started them 16. In looking back on your school experience, would you say you:, • enjoyed it very much O enjoyed It most of the time > : d disliked it most Of the time f_ disliked it very much 286 17. Other than TRAC. have you attended any other education or training program since you left secondary school? • Yes • No (If NO go to 18) Name of college or school attended: : Name of program taken: Did you complete the program? • Yes • Still attending • No What year did you complete or leave the program? 19 Name of college or school attended: . : Name of program taken: Did you complete the program? • Yes • Still attending • No What year did you complete or leave the program? 19 WORK EXPERIENCE 18. Were you employed at anytime during the 12 months before beginning the TRAC program at PVI? • Yes • No (If NO go to 22) • Part-time or • Full-time Type of employment: 19. How many times during that 12 month period did you change jobs? times 20. Was this work related to your chosen TRAC specialty (e.g., Heavy Duty, Joinery, etc.)? • Yes • No 21. What was the hourly rate of pay in your last job (this could include a job that you started before beginning TRAC and still have): • more than $14 • $ 1 1 — $ 1 4 • $8 —$11 O $5 — $8 • less than $5 22. Were you employed while doing Common Core? • Yes • N o (If N O go to 24) How many hours per week did you work on average? hours/week 23. Was this work related to your TRAC specialty (e.g.. Heavy Duty, Joinery, etc.)? • Yes • N o REASON FOR CHOICE OF SPECIALTY 24. When you began TRAC did you intend to complete: • all of the program • only part of the program 25. What was your main reason for taking this program? O to get a job • to gain some knowledge and skills that will be useful to me even if I don't get a job in that trade O to improve my chances of getting an apprenticeship • other (please give your reason): 287 2 6 . D i d y o u a l r e a d y h a v e a S p e c i a l t y ( e .g . , H e a v y D u t y , J o i n e r y , e tc . ) c h o s e n w h e n y o u f i rs t b e g a n t h e p r o g r a m ? • Y e s • N o (If N O g o to 29) W h i c h one: 27. H o w certain were y o u that the Special ty y o u chose was the one you wanted to complete? • very certain • quite certain • uncerta in • very uncertain 28. W h i c h of the fol lowing reasons explains why y o u chose that Special ty? (If more than o n e reason is true please n u m b e r e a c h c h o i c e to indicate w h i c h was: most important (1), next important (2), and so on.) • I have always wanted to work in this trade. • T h e c h a n c e s of getting a job in this trade look g o o d . • T h e wages in this trade are h igh. • I have friends who work in this trade. • I have relatives who work in this trade. • I have already worked in this trade an d want to get a certificate to prove I've got s o m e training. • I a lready have s o m e training in this trade and want to get a certificate. • O t h e r (please give y o u r reason): 29. C o n s i d e r i n g your reason for taking the T R A C program, which one of the following would be most important to y o u ? • comple t ing T R A C a n d getting the certificate • having s o m e skills that I c a n use 30. While in C o m m o n C o r e d id y o u c h a n g e your specialty? • Yes • N o (If N O go to 32) T o what: 31. W h i c h of the fol lowing reasons indicates why y o u c h a n g e d your cho ice of Special ty? (If more than o n e reason is true p lease n u m b e r e a c h c h o i c e to indicate which was: most important (1), next important (2), a n d s o on.) • I have always wanted to work in this trade. • T h e c h a n c e s for e m p l o y m e n t in this trade appeared better. • T h e wages in this trade are higher. • I have friends w h o work in this trade. ( • I have relatives who work in this trade. • I have already w o r k e d in this trade an d want to get a certificate to prove I've got s o m e training. • I a lready have s o m e training in this trade a n d want to get a certificate. • O t h e r (please give y o u r reason): 32. W h i c h of the fol lowing statements best descr ibes how your family feels about y o u r dec i s ion to return to s c h o o l ? • very m u c h for it : • for it . • against it • very m u c h against it 288 33. How m u c h do you value your family's opin ion in this case? • very m u c h • quite a bit • not very m u c h • not at all 34. W h i c h of the fol lowing statements best descr ibes how your friends who are not in the T R A C program feel about your dec i s ion to return to s choo l? • very m u c h for it • for it • against it • very m u c h against it 35. H o w m u c h d o you value your friends' opin ions in this case? • very m u c h • quite a bit • not very m u c h • not at all 36. Dur ing C o m m o n C o r e how m u c h did y o u feel y o u were getting from the program? • a great deal • quite a bit • a bit • not very m u c h • noth ing at all 37. Whi le they were in C o m m o n C o r e how m u c h d i d your friends, who are also T R A C students, feel they were getting from the program? • a great deal • quite a bit • a bit • not very m u c h • nothing at all 38. Whi le in C o m m o n C o r e d id y o u have definite p lans to get more training in this trade after y o u had comple ted the T R A C p r o g r a m ? • Y e s • N o 39. H a s any other m e m b e r of y o u r family attended PVI? • Yes • Is still attending • N o (If N O g o to 41) 40. D i d he o r she success fu l ly complete a program at PVI? • Yes • Is still attending • N o 41. H a s a friend attended PVI? • Yes • Is still attending • N o (If N O g o to 43) 42. D i d he or she success fu l ly complete a p r o g r a m ? • Yes • Is still attending • N o 43. Whi le y o u were in C o m m o n C o r e , if s o m e o n e interested in getting trades training asked for y o u r advice , would y o u r e c o m m e n d T R A C ? • Y e s • N o 44. W o u l d y o u have r e c o m m e n d e d PVI for training if s o m e o n e wished to take s o m e program other than T R A C ? • Y e s • N o 289 F I N A N C I A L F A C T O R S 45. A s a student in C o m m o n C o r e how m u c h of a concern was money? • It s eemed I was always worried about not having enough money to make ends meet. • M o n e y was a c o n c e r n ; but not a major c o n c e r n . • M o n e y was never a c o n c e r n ; I always felt I had enough to get by. 46. Did y o u apply for a student loan while in C o m m o n C o r e ? • Yes • N o (If N O g o to 47) Did y o u get it? • Yes • N o (If N O go to 47) What was the total value of that loan (approximately)? $ 47. D i d y o u receive a n y grant(s) or scholarship(s) for your school ing? • Yes • N o (If N O go to 48) What was the total value of the grant(s) or scholarship(s)? $ 48. While in C o m m o n C o r e were y o u s p o n s o r e d by s o m e agency or association? • Yes • N o (If N O go to 46) Please indicate who s p o n s o r e d y o u r training. • C a n a d i a n E m p l o y m e n t a n d Immigration C o m m i s s i o n (CEIC) • S p o n s o r e d ( C E I C pays y o u to g o to school ) • Sec t ion 39 (you pay y o u r tuition but y o u r Unemployment Insurance cheques keep c o m i n g while y o u are in school . ) • Ministry of H u m a n R e s o u r c e s • Workers ' C o m p e n s a t i o n B o a r d • Native B a n d o r C o u n c i l • Other (please explain): ACCOMMODATION & STUDENT SERVICES 49. D i d y o u have to c h a n g e y o u r p lace of res idence in order to take training at PVI? • Yes • N o 50. i/Vhere did y o u live while d o i n g C o m m o n C o r e ? • with my parent(s) • with my relative(s) • with my s p o u s e or s p o u s e a n d chi ldren • on my o w n • with friend(s) • at Redford H o u s e • other (please explain): 51. W h i c h of the fol lowing student services were available when you were taking C o m m o n C o r e ? • student counse l l ing services (for personal problems o r career planning) • career advisors (for information o n p r o g r a m s at PVI) • job placement • the Deve lopment Studies C e n t e r for extra help in basic math, sc ience and Engl i sh skills • student health services • student f inance • T R A C training consul tants 52. H o w often d i d y o u g o to the C o m m o n C o r e instructors for individual assistance while y o u were in C o m m o n C o r e ? • never • o n c e • more than o n c e 290 53. D o you feel C o m m o n C o r e students s p e n d enough time studying before writing a theory challenge? • Yes • N o 54. Which of the following study skills d id you use before writing a Common Core theory challenge? (If you. use more than one, check off those that you use.) • read the Learning Guide over a few times • read the questions in the Learning Guide before I began reading the Learning G u i d e • underlined the important parts as I read the Learning Guide • made notes as I read the Learning Guide • did the questions after reading the Learning Guide • had someone ask me questions on the material to test my knowledge • completed the shop first 55. While in Common Core where did you. do most of your studying? • in the Learning Resource Center • in the "quiet room" in the Learning Besqurce Center • in a lounge or cafeteria area • at home • at work 56. On the average approximately how many hours per day did you spend at P\/l whHe you were working on Common Core? • more than 8 hours • more than 6 hours but less than 8 hours • more than 4 hours but less than 6 hours • more than 2 hours but less than 4 hours • less than 2 hours 57. On the average approximately how many days per week did you spend at PVI while