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Gender-related differences in technology education related to problem solving Langille, Lindsay B. 1993

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GENDER-RELATED DIFFERENCES IN TECHNOLOGY EDUCATION RELATED TO PROBLEM SOLVING by LINDSAY BLAKE LANGILLE B.Ed (Secondary) The University of British Columbia, 1988 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF ARTS in THE FACULTY OF GRADUATE STUDIES Department of Mathematics and Science Education Faculty of Education  We acce t this thesis as conforming to herquiredstandr  THE UNIVERSITY OF BRITISH COLUMBIA May 1993  © Lindsay B. Langille, 1993  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.  (Signature)  Department of The University of British Columbia Vancouver, Canada  Date  DE-6 (2/88)  ^301 1161-3  ABSTRACT:  The purpose of this study was to compare the achievement of girls and boys in the area of Technology Education, primarily in the area of problem solving. In today's society, particularly in the secondary school setting, the courses taught under the auspices of Technology Education are chosen primarily by males. This gender unbalanced enrollment, has been directly influenced by the way society has split up the labour force for centuries by deeming some tasks as those largely performed by males, and others as those performed by females. Although the feminist movement has helped change the perspective of "boys classes", "girls classes", "boys things", "girls things", the trend still remains that most girls tend to continue in the traditional line of Home Economics and Family Management courses, while the boys choose to enrol in courses of a Technological and Scientific nature. This study was carried out on an equal number of girls and boys at the grade 8 level at a large sub-urban secondary school. The primary focus of the study was to test the hypothesis that given a problem to solve in the area of Technology Education, there would be no differences between the achievement of boys or girls. The study showed that there was no significant difference in the achievement of boys or girls (p < 0.10).  TABLE OF CONTENTS  Abstract ^  ii  Table of Contents ^  iii  List of Tables ^  vi  List of Figures ^  vii  Dedication^  viii  Acknowledgements ^  ix  Chapter One: Introduction ^  1  Statement of the Problem ^  9  Justification for the Study ^  9  Hypothesis ^  10  Thesis Organization^  11  iii  Chapter Two:  Review of the Literature ^  12  Summary ^  30  Chapter Three:  Methodology ^  32  Background ^  33  Population ^  34  Instrumentation ^  34  Characteristics of the Instrument ^  38  Procedures ^  39  Scoring Procedures ^  42  Testing of Hypothesis^  47  Chapter Four:  Results of Testing ^  48  Variables where Girls are significantly better ^  54  Variables where Boys are significantly better ^  55  Variables showing no significance ^  55  v  Chapter Five: Summary, Conclusions, Discussion and Recommendations ^  66  Summary ^  66  Conclusions ^  67  Importance of the Study ^  68  Limitations ^  69  Recommendations ^  69  Bibliography^  70  Appendices  Appendix A ^  73  Appendix B ^  86  Appendix C ^  87  Appendix D ^  94  List of Tables  Table 1.1^1988/89 Provincial Enrollment in Industrial Education ^4 Table 1.2^1988/89 Provincial Enrollment in Physical and Applied Sciences ^ 5 Table 1.3^1988/89 Provincial Enrollment in Computer Education ^ 6 Table 1.4^1988/89 Provincial Enrollment in Mathematics ^ 7 Table 2.1^Percentage of Females in Different Career Programs ^ 16 Table 4.1^Variable Description Chart ^  50  Table 4.2^Developing Solutions Data ^  51  Table 4.3^Effects of Gender ^  51  Table 4.4^Statistical Data of Variables ^  53  Table 4.5^Comparison of Variables in the Conceptual Cluster ^ 58 Table 4.6^Comparison of Variables in the Communication Cluster^ 61 Table 4.7^Factor Analysis of Data ^  vi  63  Table of Figures  Figure 3.1^Variable Description Chart^  36  Figure 3.2^Test Score Descriptors ^  46  vii  DEDICATION  This thesis is dedicated to my wife Tammy Alissa May Langille, (BSc. Pharm, 1988. U.B.C.), who has supported my educational endeavours from the beginning. Thank you for believing in me and continually pushing me to completion. Without you, none of this would have become reality. Also, to my parents, who never had the educational opportunities in their lifetime, this is for you.  viii  ACKNOWLEDGEMENTS  While conducting my study, there were several key people to whom I am very grateful, without them my study would not have been possible. Firstly, I must thank Bill Logan (U.B.C.) for his assistance from day one of my undergraduate degree, for seeing the possibilities in me and continuing throughout the years to provide help, assurance, support and above all, a sense of feeling that always came through that he genuinely cared about you personally. This one man certainly has made the difference. I also am very grateful to Tony Wheeler (University of London) for allowing me to  stay with him and his family, in crowded quarters, for 2 weeks in London, England and to visit many of his colleagues, schools and APU team members. Also for providing me with the necessary tests in which to gather the results of my research. Appreciation is also extended to Dr. David John Bateson (U.B.C.) who through poor health continued to administer and guide me to completion. Also, to Dr. Jolie Mayer-Smith for her welcomed suggestions and comments, thankyou. Lastly, I thank my students who allowed me to impose upon them a test that took so much of their personal time. For those of you that continue on with your education, you will understand and appreciate what your time has meant to me. Thanks to all who have encouraged this procrastinator to completion.  ix  CHAPTER ONE  INTRODUCTION  Many teachers of Technology Education, have been intrigued by the fact that few female students ever continue on in the elective courses of Technology Education, since these same teachers believe that there are no reasons that females should not do well in this area of study. Technology Education is a rapidly developing area of the school curriculum concerned with encouraging students to become active participants in the human-made world of products, systems, and environments. This area of the curriculum is essentially procedural in nature; students use skills and knowledge as resources for action, rather than as ends in themselves. Technology Education courses generally dedicate a considerable amount of time to "hands on" type activities that usually require a problem solving approach. In British Columbia schools, a large majority of students at the grade eight level take a course called "Technology Education", formerly called Industrial Education. This course is not taught at all schools for different reasons, but has the support of many of the province's high schools. For schools that can not offer the course, an attempt is made to offer something similar. Some schools may offer a course called Life Skills, which makes an attempt at teaching some of the same things that Technology Education offers. However, when courses similar to Technology Education are offered, the length of the course is usually  1  shorter, course content is not the same, and the number of pupils attending will not be recorded as being enrolled in Technology Education in the British Columbia Ministry of Education School Data. It should be noted at this time that Technology Education does not have a provincially mandated curriculum, and therefore course content can differ from school to school based on the interpretation of the teacher. There are, however, guidelines that are set out by the Ministry of Education, describing what knowledge and skills should be gained by students who take this course. After the one introductory course at the grade 8 level, further study in this area is not compulsory. Technology Education courses involve working with materials such as wood, metal, and synthetic material, and include electronics, technical drafting, and design activities. One of the main learning objectives of the course is to allow students to 'problem solve' using different materials (B.C. Ministry of Education, Technology Education Curriculum). It is very important, as we look about our human-made world, that we understand that everything we see, everything we work with, and everything that makes our lives a little better and increases the quality of life, involves materials, tools, and an understanding of how to use these things in such a way as to make our world a better place in which to live. Thus, allowing students to use materials and tools to create and solve real life problems within a school setting very much prepares them to understand and fill an active role in this humanmade world of which they are a part. Technology Education should be a subject that involves both sexes. It is as important that girls as well as boys understand the technologies that are a large part of their every day lives. Taipan, (1992) explains "that the only way of profiting in the near future includes the  2  understanding of technologies" (p.5). Technologies such as "laser dentistry", "super seeds", "quake proof concretes" and more, are mentioned as some of the most promising job fields of the present and the future. (p.5) These jobs are not gender specific, but are open to both men and women. In order to be prepared for a prospective career involving technology, both girls and boys must be preparing themselves by enroling in technological courses within the school system. Technology Education is important for all, since the opportunities that grow from knowledge, processes, and skills developed in these courses are endless. If our country is to take a leadership role in the world market, we must not lose our technological edge. Technology Education is therefore an important area of study. The British Columbia Ministry of Education has recently recognized the value of Technology Education, and has included it in the Year 2000 document as curriculum that should be taught to all ages at all levels. This is a major step forward, since Technology Education previously had generally been found only in the secondary school environment, with the exception of a very few elementary schools. One of the very desirable characteristics of Technology Education is that it allows students to 'problem solve'. In today's careers, those that can think critically and use the skills they have learned to solve practical problems have a better chance to enjoy success. Johnson and Betts (1988) provide a description of the needs of problem solving: "In order to be a problem solver, one must be able to be creative, and to think on a broad spectrum, possibly have spatial abilities" (p.14.1). In technological activities, students are presented with a problem to which they must find a solution. Usually, the student works toward a solution, materials will be selected and used, scientific principles will be reviewed, and construction methods will be employed.  3  Thus, problem solving is an integral and important component of Technology Education. In order to better understand the enrolment patterns in Technology Education courses and related Science and Mathematics courses, one should consider the British Columbia Ministry of Education data on provincial enrolments. On examining the Ministry enrolment figures for the whole province for 1988/1989, a distinctive pattern in the numbers of girls and boys enroled in what was then called Industrial Education can be seen (see Table 1.1).  Table 1.1 1988/1989 Provincial Enrolment in Industrial Education  GRADE LEVEL:  BOYS  GIRLS  GRADE 8  13,965  8686  GRADE 11  18,468  1854  GRADE 12  10,359  433  MULTI-GRADE (9/10)  24,421  2577  TOTAL  67,213  13,550  4  One can see that in 1988/1989, even at the Grade 8 level, there are more boys than girls enroled in Industrial Education courses. However, as the grade level moves from Grade 8 to Grade 12, even fewer girls enrol in these courses, until by Grade 12, girls make up less than 5% of the total Industrial Education enrolment. The patterns of enrolment are similar in Physics, a course with similarities to Industrial Education because its content tends to lean towards activities that boys traditionally appear to find more interesting than do girls. The Ministry of Education data shown in Table 1.2 demonstrates this similar male/female imbalance.  Table 1.2 1988/1989 Provincial Enrolment in Physics  GRADE LEVEL  BOYS  PHYSICS 11  5696  GIRLS  3295  PHYSICS 12  2406  717  TOTAL  8102  4012  5  The data in Table 1.3 demonstrate similar enrolment patterns in the area of Computer Education, another traditionally male oriented course.  Table 1.3 1988/1989 Provincial Enrolment in Computer Education  GRADE LEVEL  BOYS  GIRLS  COMPUTER ED. 11  5031  3537  COMPUTER ED. 12  1421  617  TOTAL  6452  4154  Enrolment in Mathematics also portrays the same patterns of enrolment with the boys electing this subject more than the girls. Although the differences are not as great, the data shown in Table 1.4 still shows that more boys than girls choose mathematics as a subject of study.  6  Table 1.4 1988/1989 Provincial Enrolment in Mathematics  GRADE LEVEL  BOYS  GIRLS  MATHEMATICS 11  17511  16385  MATHEMATICS 12  7126  5615  TOTAL  24637  22000  In other subjects such as Business Education and Home Economics, the patterns of enrolment differ slightly. The enrolment data indicate that more girls than boys enrol in these subjects. These two subjects include areas of study that may traditionally have been seen as more beneficial to girls than boys, as they deal in part with secretarial and family management skills, unlike Physics, Mathematics, and Computer Education, that prepare boys for futures in fields of engineering and apprenticable trade-related careers It could be that enrolment patterns reflect our society's value system. Many parents and counsellors have seen, and continue to see various courses as 'boy courses, girl courses', and feel that girls should choose courses of a more domestic nature. The Illinois State Board of Education, (1989) stated that "in many schools, boys were regularly channelled into Industrial Education [Technology Education] while girls were enrolled in Home Economics (p.5). Until our 7  society's value system completely recognizes equality between sexes, educational decisions that are made by boys and girls will continue to be greatly influenced by these values and enrolment will remain unbalanced. The complete British Columbia Ministry of Education male-female breakdown of enrolment data for public schools is provided in Appendix A. The trend continues that technological courses are still widely chosen only by males. The available data only provides enrolment patterns by sex, and tells nothing of achievement, and there is no evidence to indicate that girls will not do as well as boys in courses of this subject nature. There are a myriad of reasons for girls' decisions not to further their studies in the area of Technology. One reason, undoubtedly, is that of social attitudes (Illinois State Board of Education, 1989). "Many writings have denounced the gross inequalities of education for girls and the loss of talent because girls do not develop the abilities they have." (Sutherland, 1981, p.5) There is a feeling that, as a society, we have suffered in not allowing females to develop in an equal way, including encouraging equal participation in the area of Technology Education. Based on personal observation, girls in Technology Education classes believe that they will not perform as well as boys in this area, and therefore that they will not do as well as the boys in the class. Most girls in Technology Education have entertained the thought, that as long as they pass, that is all that is required since they do not intend to continue on in this area of study. Boys, however, being brought up differently, view Technology Education as an area in which they are superior to girls.  8  Although there may be a societal belief that females will not achieve as well as males in Technology Education, there is no evidence to suggest that such a conjecture has any foundation.  Statement of the Problem: The problem of this thesis was to determine if there were any gender-related differences in Technology Education with relation to problem solving.  Justification for the Study: Very little has been done in the study of achievement relating to girls and boys in the area of Technology Education. In fact, only one large study has been conducted, and that was done in the United Kingdom (1985-1991). This study was carried out on 15,000 subjects, and examined the differences that existed between girls and boys in the area of Technology. As a result of this study, it was felt that a similar study on a smaller scale should be carried out here in British Columbia. This thesis is the result. The role that technology plays in our every day lives is becoming more apparent each day: new products, new processes, new ideas, loss of existing jobs to new technologies, the need for retraining, environmental impact as a result of new technologies, and the list goes on. Given the lack of research studies in Technology Education and the role it plays, this area should be one showing further research in the next few years. The intent of the present study is to provide information about gender-related differences in the area of problem solving, which is the focus of Technology Education. This study will provide information  9  that will allow educators, curriculum writers, educational researchers, counsellors, and administrators to better understand and prepare students for the future, and promote and encourage females to enrol in Technology Education courses.  Hypothesis: Specifically, there were two null hypotheses (Ho) tested in this study.  1. There will be no significant difference between the mean score for girls and the mean score for boys in their achievement in the area of problem solving in Technology Education using the Assessment Performance Unit (APU) test.  HO:  IA boys =^girls  14 boys^IL girls  2. There will be no significant difference between the standard deviation on the scores for girls and the standard deviation for boys in their achievement in the area of problem solving in Technology Education using the APU test.  HO: a boys = Cr girls H1: a- boys^girls  10  Thesis Organization: Chapter two contains a review of significant literature related to the study. Chapter three contains a description of the methodology and procedure of the study. In Chapter four, the results of the study are presented and analyses of the data collected are reported and discussed. A summary, conclusions, and recommendations made on the basis of relevant literature and the findings of this study are included in Chapter five.  11  CHAPTER TWO  REVIEW OF THE LITERATURE  Very few, if any, educational problems are straightforward enough to have simple answers. Problems that focus on female enrolment in Technology Education and females' ability to problem solve in the area of Technology Education also do not have straight forward answers, but there are some commonalities. This chapter presents a review of the literature which examines two aspects of the problem in relation to the stated hypotheses. The first section examines studies on female enrolment in non-traditional courses of study such as physics, mathematics, and other subjects that directly or indirectly relate to Technology Education. The second section reviews studies related to the ability of females to problem solve. Dr. Jane Gaskell (1984), in a study carried out in Vancouver, British Columbia, Canada, examined gender and course selection in three separate high schools. She said "one of the clearest ways that the school creates differences amongst students is by enroling them in different courses. This begins a process of differentiation that sets students on alternative paths towards adulthood" ( p.8). The courses students select, in most cases, shape adult life. By spending time in specific classes, friends are made, skills are learned, attitudes are formed, and an overall shaping of the individual begins. Many of us can look back to our own individual high school experiences, and although we may or may not be able to identify  12  the specific reason why we enrolled in a particular course, we will probably agree that our course selection programmed us in a certain direction. One would have to agree that the course selections that students choose shape and mould their future and sets them up for a certain style of adulthood. Each elected course is part of a larger picture, in that secondary school courses orient students toward future endeavours. Industrial Arts courses orient students towards blue collared work. Maths and Science allow them to enter technological fields. Business courses teach them what is involved in secretarial or sales jobs. Home Economics prepares them for domestic tasks. And so it goes (Gaskell, 1984, p.8). All courses are theoretically open to selection without discrimination for either sex. However, the question of why girls choose not to become involved in Technology Education courses is puzzling. Generally, boys still are selecting the courses that have traditionally been their mainstay: Industrial/Technological courses along with Mathematics and Science. The fact that girls generally do not elect to take these courses, does not suggest that girls will not do well in these courses; it mainly suggests that in our society females are more comfortable enroling in some courses rather than others. Traditionally, education has reflected the inequalities that exist within our society. Girls and boys have been encouraged and tracked into programs and classes assumed most appropriate to preparation for traditional adult male and female roles. "In many schools, boys were regularly channelled into Industrial Education [Technology Education] while girls were enroled in Home Economics" (Illinois State Board of Education, 1989, p.5). educational situation has set up huge inequalities within the work force, which, in turn,  13  offered females fewer economical and financial rewards. However, "Because women are becoming increasingly involved in the economy as producers and consumers, it is important that they acquire technological literacy and gain an understanding of our total economic system" (p.5). Another observation noted by the sex equity guide consultants in their report to the Illinois State Board of Education (1989) states that counsellors in the school setting are one of the causes of girls not being enroled into non-traditional courses, including Technology Education. Their report states; "Research studies indicate that counsellors have an important influence on women and men students in reinforcing their thinking about career decisions and also encouraging them to think more broadly about their decisions" (p.5). Gaskell (1984) in her study found that "neither parents nor counsellors were seen very often [by students] to have direct influence on course selection" (p.92). Counsellors were described by students as "coercive" (p.92). "I wanted to take academics but they wouldn't let me" (p.92). More often students' advice was discounted, if heard at all. "The counsellors we've got here are just completely terrible. They don't know what they are doing" (p.92). In another study, Gaskell (1986) states that: Counsellors are more likely to provide girls with information on traditionally female occupations than on non-traditional occupations both because the girls ask for this information and because the counsellor thinks of it. (p.35) In another study done in Canada (Gaskell & McLaren, 1987), lack of effective guidance counselling also was noticed. Girls in the study were quoted as saying: To tell you the truth, I think counsellors just don't get enough of whatever it takes to become a counsellor.. .There is not enough counsellors. They are having to take care of a whole grade of people. The're spending their time running through the papers and there is not much time for them to sit around 14  and rap. (p.156) When we consider the following dialogue, we grasp a sense of lack of guidance. The girls themselves said: I like to do the jobs men do. I think they are more interesting. I wish I had taken woodwork. I like working with wood. It would be exciting to be a truck driver. But I wouldn't know how to go about it. (p.163) Only new attitudes, and collaboration between counsellors, students, and parents might help to make sure that this process of differentiation ceases within the school setting, and that students are placed into courses based on their interests, rather than their gender. As stated by the Illinois State Board of Education (1989), "All individuals taking a role in recruitment activities must be committed to the principle that Industrial Education is for all segments of the population including those people non-traditional by sex, race, age, handicap and ethnic culture" (p.5). In 1948, the General Assembly of the United Nations stated to all member countries that "Everyone has the right to an education. It also stated that the rights of human beings shall not be subject to distinctions, such as race, colour, sex ..." (Sutherland, 1981, p.7). Although a statement of this nature promotes the idea that all should be educated, it does not mean that all will be educated equally. Sutherland (1981) states that "Although the number of years of compulsory education is the same for both sexes this does not mean that they have exactly the same education" (p.10). There is no prescription of subjects which must be learned by all. If one wants to ensure that girls and boys have the same subjects of study one would need a centralized curriculum. (p.11) In the United States, it was the legislating and passing of Title IX of the Educational 15  Amendments of 1972 (P.L. 92.318) that caused educators to make a more serious effort, on the whole, to reduce sex discrimination in education (see Appendix B). In effect, this legal mandate dictated equal access for both girls and boys to all classes. "Specifically, it ends the restrictions which prevented girls from participation in Industrial Education merely because they were female" (Illinois State Board of Education, 1989, p.5). Vetter and Hickey (1985), reported that ten years later, in 1982, women continued to enrol in great numbers in traditionally female programs. The percentages of women they found enroled in vocational programs in 1982 are found in Table 2.1. The content has been rearranged in terms of descending percentages.  Table 2.1 Percentage of Females in Different Career Programs in United States Middle (Diploma) Colleges in 1982  Program of Study:  Female  (non-traditional)  Enrollment  Program of Study: (traditional)  Female Enrollment  Architectural Technology  22.10 %  Dental Hygiene  96.40 %  Industrial Technology  15.60 %  Dental Assistants  95.50 %  Water Technology  14.80 %  Stenographer/Secretarial  93.50 %  Civil Technology  13.80 %  Guidance of Children  92.40 %  16  Mechanical Technology  11.90 %  Nursing  91.20 %  Electronics  11.70 %  Medical Assistant  90.20 %  Electrical Technology  7.80 %  Clothing Management  89.60 %  Construction  7.40 %  Home Furnishing  80.70 %  Agricultural Technology  5.30 %  Typing  79.60 %  Automotive Technology  5.10 %  * Table arranged in order of descending  percentages  (Vetter & Hickey, 1985,p.185)  Legislation alone, against discrimination in education, is not enough to cause females to enroll in male dominated courses. Change is a slow process, and traditions are not relinquished easily. One key factor that stands in the way of expanding educational options for girls and preparing them for participation in a technological world is the view held by society. When society begins to allow the workforce of this country to be decided upon by ability rather than gender, this, in turn, will provide easier access for boys and girls to select courses of every nature, and courses that are of interest to them. In the United Kingdom, it has long been the practise to divide classes so that girls do the needlework while boys work at crafts of various kinds. (Sutherland, 1981, p.11) In  17  British Columbia, both boys and girls at the grade eight level engage in technological courses as well as in home economics. However, very few boys continue to select courses in Home Economics and conversely, very few girls continue to select courses of a technical nature; most continue to choose courses in the traditional manner. A study conducted in the United Kingdom in 1976 found that 81,765 boys and only 1,501 girls were enrolled in technical drawing which is Technology Education based. (Sutherland, 1981, p.18) In subjects that lend themselves towards Technology Education, such as mathematics and science, the results were similar: Physics - 86,657 boys and 11,619 girls; and Chemistry - 43,009 boys and 20,418 girls. (p.18) In British Columbia, as in other geographical areas, the results follow the same pattern. Few girls elect courses of a mathematics, science, or technological nature. Bateson and Parsons-Chatman (1989) recommended that "female students need to be provided with more opportunities for in school, hands on experience in the physical and earth/space sciences beginning in the primary school" (p.383). Hoffman (1987), based on a study of 5200 students in France, maintained that:  ...For both boys and girls, preschool and out of school activities connected with physics and technology are significantly related to interest in physics, self concept, and the estimation in general and for the students' own later career. (p.101)  More effort must be made by all authorities to enforce equity. If equity does not exist, work will need to be done to accomplish it. Even though "women generally do well in school in comparison with men" (Gaskell, 1984, p.89) they will tend to stay out of the male orientated courses. " The girls, if they  18  thought of continuing their schooling, considered jobs like dental assistant, nurse, child care worker, interior designer, journalist, teacher or social worker" (p.95). In all of these humanity selections, an education in technological areas was not seen to be of benefit to girls. As one girl said" I considered engineering, pretty seriously, (but) ... if I'm going to get married, that's the most important thing I'm looking forward to" (p.95). During the course of Gaskell's work, the assumption of girls was that "paid work was a temporary phase in their lives to be replaced by a primary commitment to domestic work by the time they were 25..." (p.95). This observation is well supported by other researchers. Kenkel and Gage (1983) argue that "Girls aspire to a smaller number of occupations while boys choose from a wider variety of jobs ... four occupations, nurse, teacher, secretary, and social worker have been found to dominate the occupational choices of girls" (p. 130). Prediger, Roth, and North (1984), in their study of eleventh graders, found that "More than half of the girls chose jobs that fell into three categories: education and social services; nursing and human care; and clerical and secretarial" (p.'76). Martina Horner (1969) conducted a study to "explore the basis for sex differences in achievement motivation" (p.315). The results of her study are startling: "afraid of failure and success, women face a psychological barrier to achievement" (p319). Horner carried out her study on a sample of 90 girls and 88 boys, all undergraduates at the University of Michigan. She had each complete the following story. "After first term finals John (Anne) finds himself (herself) at the top of his (her) medical school class" (p.316). The girls wrote about Anne, the boys about John. The imagery fell into 3 categories. The most frequent response reflected fear of social rejection as a result of success. Girls showed anxiety of  19  becoming unpopular, unmarriageable, and lonely. In some cases, "the girls insisted that Anne give up her career for marriage" (p.323). The above study provides insight that it is not a lack of intelligence, abilities, or knowledge that keeps girls out of the technological courses of study. Courses that would open doors to careers in engineering, medical fields, architecture, and other vocational areas that would give women positions in well paying careers, are not their choice, frequently because of social stigma. The fear of the possibility of not being accepted, not being liked, and maybe never marrying, cause anxiety. This, in turn is reflected in females' course selections and their ability to perform. The females in Homer's study "who did not fear success, however, were aspiring to graduate degrees and careers in such scientific areas as maths, physics and chemistry" (p.335). As MacCarthy (1976) puts it: Employment needs currently and in the future are heavily concentrated in technological and service areas ... Women who continue to choose courses and programs which have no specific technological orientation are apt to find their employment in the low paying service areas ... (p.6)  Research has shown that the problems of gender segregation identified above are not based on any biological or physiological reasons, but mainly on reasons that are as a result of their socialization (Kenkel & Gage, 1983; Linn & Hyde, 1989). Kenkel and Gage identify one of the reasons as lack of female role models in non-traditional jobs or career preparation programs. In the U.S.A., one of the most developed countries in the world, MacCants (1984) identified socialization as a major factor in career choices. She proclaims:  20  As legal and biological barriers have been overcome, access to the technologies has become an option for women. The barriers that remain are psychological and sociological and these will not be overcome until women take advantage of the education and training available to them. (p.5) The influence of socialization was also identified by O'Brien (1987), and Tucker and Asser (1980). These authors found that parents respond positively, and even use rewards to encourage their children to fit into traditional careers, according to gender rather than ability. A report in the Toronto Globe and Mail, October 15, 1990 states: "It seems that a mother doesn't dream of 'My daughter the welder" (p.32). More recently, a similar report by Carol Roberts, parallels the same thought. Roberts' article in the Vancouver Province newspaper of December 15, 1992, exposed parents as those most responsible for the reasons that girls do not choose courses that will see them studying in technological areas. When Carol Roberts told school children, particularly girls, about the rewards of engineering, she ran into some surprising barriers, their parents. I still don't think they believe engineering is a legitimate choice for girls, and they're teaching their children that. Parents still perceive math not being feminine and engineering as not being a caring profession. The kids are usually enthusiastic, but talking with parents later, they didn't believe the engineer in the classroom was a woman. (Province, 1992, p. 64 ) Rather than specific training, Technology Education must be seen more as an area in which to learn to be creative, and to use materials to solve problems with real life applications; all things that relate to getting through life successfully. The social stigma that has firmly attached itself to Technology Education as a subject area to be dominated by  21  males must be dismissed. Women have missed out on many opportunities because of the prevailing belief. For females like those in Homer's (1969) study who have not feared success, they have gone on to successful careers in the male dominated areas of society's workforce. While the focus of this chapter to this point has been on events that limit female enrolment in non-traditional courses, it is important now to look at the achievement of those females that do enrol in the male dominated areas, and compare their achievements to those of males.. So much has restricted females participation in these areas, that one wonders how they will measure up in their ability to perform in the mathematics, science, and technology based exercises. Technology Education can briefly be defined as: "using materials with the understanding of scientific principles to solve problems and find solutions for human need" (Langill, 1992). Because of the direct link that bonds Technology Education with mathematics and sciences, one should also look to gender-related differences in these areas to provide indications of possible differences. There are some studies, though few in number, which show that girls out-perform boys in mathematics and science. One such study, done in Hawaii, examined mathematics achievement for children of grades 4,6,8, and 10, and its relationship to gender, ethnic group, grade, and year. (Brandon,1981) The findings were put this way: ...contrasted with most studies, the study reported here shows girls with higher mathematics achievement levels than boys. That the Hawaii data show differences in Mathematics achievement favouring girls is not surprising: previous Hawaii studies give clues about Hawaii girls' superiority over boys in Mathematics and the differences increase as the grade level 22  increases. (p.22) It should be noted that there were extenuating factors which could have accounted for the results obtained. One of these factors has to do with the definition of mathematics achievement used by the study. The test that was used divided the skills tested into mathematical reasoning, mathematical computation, and mathematical application. The study found that boys perform at a higher level in mathematical applications, and girls scored higher in computation problems. A possible explanation for this may be found in the Bateson and Parsons-Chatman (1989) study that suggested that boys do better because they draw on out of school experiences when answering, more than do girls. This would explain why the boys in this study did better than girls in applications of mathematics. In comparison, computation is more mechanical in nature, and achievement here is more reliant on what was taught. Therefore, girls being given an equal starting point with boys, proved to do not only as good, but better than the boys tested in this study. Another factor has to do with role models. As the study puts it, "because of the high proportion of female Japanese-American Public School teachers in Hawaii, girls may have powerful female sex role models showing them that academic achievement is possible and desirable" (Brandon, 1981, p.28). Another study which seems to argue for girls' higher achievement in Mathematics and Science was conducted in Rhode Island by Sharon and Sharon (1986). These authors found that: in addition to choosing as many high level courses as their male classmates, young women in the sample tended to receive higher grades for their work in maths and science classes than their male counterparts. Sixty percent of all A's awarded in maths and science classes were earned by females... Female 23  students also received more B's awarded in maths and science classes (52%). (p.8) Like the Hawaiian study, role models were hypothesized to have played a large part. Sharon and Sharon (1986) found that in Rhode Island there were more female mathematics teachers than male, which acted as positive role models for the girls. One point to note in this study is that achievement was obtained from teachers' grades, not from standardized tests. There was no significant correlation between these grades and the scores obtained by the same students on the federal standardized test, where boys outperformed girls. This leads to questions about the reliability and validity of teachers grades as measures of achievement. Sharon and Sharon (1986) saw this possibility of error: "Do maths and science teachers in this state inflate the grades of young women?" (p.23). However, the possibility could exist whereby the teacher's grades were valid and the standardized tests, while being reliable, may not have been valid for this group, based on their curriculum. Gaskel and McLaren (1987) shed some light on the issue of the difference in girls' performance as reflected in teacher grades and grades from standardized tests. They suggest that: ...when women receive lower scores on standardized mathematics achievement tests it may be primarily a result of the fact that they have taken fewer courses. Most studies do not match females and males on number of courses taken. However, the ones that do, usually find that sex-related differences in mathematics achievement become smaller or disappear on some or all of the tests that are used. (p.134) Technology Education involves problem solving. Zaner (1989) describes the "claim to fame" (p.87) of Technology Education as its potential for developing problem solving  24  abilities. Johnson and Betts (1988) speak out about Technology Education and say, "It is very important that students learn to think critically, and problem solving has been the belief reflected in the goals of Technology Education for a number of years"... (p.32). "In order to be a problem solver, one must be able to be creative, and to think on a broad spectrum, possibly using spatial abilities" (Johnson and Betts, 1988, p.141). Creativity testing has received more attention in the last two decades (Sutherland, 1969). The definition of creativity reflects an ability to produce new and unforeseen solutions to problems (Getzels & Jackson, 1985). It frequently has been found that sex differences in creativity do appear (Sutherland, 1969, p.82). Using a creativity test in Britain, Dyer (1974) found the following: ...school children were invited to draw a machine that be convenient and keep Britain tidy' (sic) boys tended to produce technical drawings (or at least drawings of machines that might conceivably be mechanically workable) while girls tended to respond by drawing fantastic animals which had aesthetic appeal, but which were perhaps not true machines (p.98) Boys proved to be more creative than did girls according to the results of Dyers testing. As a result of his testing, Dyer found that girls' responses did not provide complete solutions to the stated problems. A more recent study done by Erickson and Erickson (1984), in examining the British Columbia Science Assessment results, notes that boys do better than girls on items that deal with objects and events drawn from their sphere of experience. They emphasize that this is most clearly illustrated in the physical sciences (p.63). Farkas (1986) found that where males outperformed females, males tended to draw on 'out of school' experiences to answer questions to a much greater extent than did females. Bateson and  25  Parsons-Chatman (1989) proclaimed in their study, that "Males continue to show much better achievement than females in the knowledge and application areas at all grade levels, particularly in the physical and earth/space sciences" (p.376). They continue on to say that "In the critical and rational thinking area, males and females are very equal at grade 4 but by grade 10, males significantly outperform females" (p.377). However, they attribute these differences to two factors. The first is that boys have been provided with many more 'out of school' experiences than girls in this area that they can draw upon when answering. The second is that many of the questions were predominantly gender biassed in favour of the males. They state: Thus it is possible, however unwittingly, to construct items that will 'a priori' show a sex-related bias by extracting the items from a male or a female sphere of experience or by putting the item in a male or female context (p.381). They also conclude "that researchers should not assume the gender content of items to be obvious and that researchers should take greater pains to determine items' gender orientation" (p.383). Even though many studies show that boys predominantly out perform girls in most areas of mathematics, science, and technology, a study by Linn and Hyde (1989) showed that this gap is narrowing. They found that "cognitive gender differences have declined in all areas studied and no longer exist for verbal ability, spatial visualization, and mathematics computation and concepts." (p.22) One factor they attribute this decline to is that "there have been declines in gender differences consistent with changing educational opportunities, changing social roles, and the changing demands of the workplace." (p.24) Another 26  contributing factor is the increased "awareness of societal expectations of roles for males and females". (p.24) Like Bateson and Parsons-Chatman (1989), Linn and Hyde (1989) maintained that, although differences in cognitive skills have declined, those that remain are largely explained by differences in experiences. In the area of Technology Education, little research has been done in relation to gender-related differences and the effect they have on achievement. In fact, the Assessment of Performance Unit (APU) team in submitting their final report (1991) on Design and Technology in the United Kingdom, describe their survey in this way: "Whatever their judgement there is no doubting it is a first of its kind in design and technology" (Assessment of Performance Unit, 1991, p.239). "...and because of the desperate lack of research evidence, we feel obligated to report the findings as we see them..." (p.211). The Assessment of Performance Unit (APU) team when beginning to set the test items for fifteen thousand subjects, were extremely aware of gender content, and tried as much as possible to set their questions in a totally neutral setting.  It is almost impossible - not to mention misleading - to attempt to isolate individual influences on performance as there are so many and they are generally closely interrelated. When looking (for example) at gender effects on holistic capability, it is very difficult to isolate it from the test structure effect, context effect, and task effect, not to mention the effects of ability and curriculum experience...( APU, 1992, p.205)  In order to keep the test questions as gender balanced as possible, many different abilities were measured, and the tests were set into many different domains. The test structures were  27  balanced to produce tests that measured the "reflective and the active" domains. (APU, 1992, p.106) Tests were also structured in the amount of "tightness and looseness" that they had. (APU, 1992, p.107) The students then were tested, and were divided into three groups based on holistic or general ability. These groups were broken into categories of high ability, mid ability, and low ability students based on their overall school grades. Based on this structuring method, the results were as follows:  Generally, girls do far better on the more reflective test than boys, and boys do somewhat better than girls in the more active tests... Girls appear to be better at identifying tasks, investigating and appraising ideas, whilst boys seem to be better at generating and developing ideas (APU, 1992, p.205).  In addition to testing reflective and active domains, the tests also tested for communication ability. Here girls outperform boys on the Starting Points and Evaluating Products tests, essentially tests where the dominant domains are reflective, and boys outperform girls on the Early Ideas, Developing Solutions and Modelling tests - those which we have described as the developmental heartland of design and technology, and where there is a strong focus on the active domains. (APU, 1992, p.219)  In general terms, girls demonstrate strengths in the reflective domain, and boys in the active. These strengths are mirrored in the strengths that students are able to demonstrate in their associated communication styles. The APU team also tested conceptual ability. They decided to split this knowledge  28  and understanding into four areas - Materials, Enemy Systems, Aesthetics, and People. The testing provided the following conclusions. In the understanding of itnaterials they write. In very general terms, there is not much difference (when using materials) between boys and girls. Where there is a significant difference, boys tend to demonstrate more understanding than girls, especially where the task requires the active development of a solution (APU, 1992, p.221).  The results of the Energy Systems testing provided slightly different results. The complete dominance of boys in this conceptual area is the most straight forward of all our findings ... no matter which way the sample is split, boys demonstrate more understanding than girls in every instance (APU, 1992, p.221). The report continued with Aesthetics and stated: But boys do not have everything their own way! In the area of aesthetics, girls show more understanding than boys in almost all tests.. interestingly, whilst the girls generally outperform boys in aesthetics for the vast majority of tests, the boys who are good holistically at design and technology are more likely to keep pace with equivalent girls (APU, 1992, p.221). Finally, in the area of People, the report concludes that: In general terms, girls dominate this area in a way that is strikingly similar to the way that they dominate aesthetics. If the sample is split by ability, girls in general are good at dealing with people issues - and high and mid ability girls are very good at these issues (APU, 1992, p.222).  As a result of the APU tests, the performance of gender groups was found to correspond with the test designs as being reflective/active and tightly/loosely structured. The 29  girls outperformed boys in the tight and reflective tests, and the boys outperformed girls in looser, more active tests. When examining communicative ability, gender was not a significant factor. Overall, the APU report indicates that both boys and girls scored equally well, with boys doing better in some things, and girls in others, thus equalizing the differences. However, when conceptual understanding was examined in terms of materials, energy systems, aesthetics, and people, (typically users) the understanding of materials showed no significant gender effect, whereas the other three did. As a result of the study, it would appear to be possible to design activities that largely eliminate, or at least balance one sort of bias with another, thus providing a more equitable activity for both sexes.  SUMMARY Throughout the literature, several explanations of why girls may not choose courses of a technological nature have been postulated. Most studies indicate that social influences have a strong effect. Those who help students make career choices, and future decisions are also affected by sociological pressures. This, in turn, causes beliefs that some career paths and school courses are more suitable to boys than girls, and these beliefs are passed from generation to generation. The literature provides strong evidence that gender-related differences exist for certain abilities, but, in some cases, it is the females who out-perform the males. More recent studies by Linn and Hyde (1989) and Feingold (1988) show that if there are differences in levels of achievement between boys and girls, that there is a trend developing  30  whereby the gap is narrowing. As social attitudes change, it is hoped that females will achieve the equity that they much deserve. Finally, to encourage persistence in mathematics, science, and technological careers, learning and earning environments must be altered to promote success for all.  31  CHAFFER THREE Methodology  The objective of this thesis was to determine if there were any significant differences related to gender that affect the ability to perform in the area of Technology Education. The two null hypotheses (Ho) tested in this study were:  1. There will be no significant difference between the mean score for girls and the mean score for boys in their achievement in the area of problem solving in Technology Education using the Assessment Performance Unit (APU) test.  HO: boys = /4 girls  HI:^boys^girls  2. There will be no significant difference between the standard deviation on the scores for girls and the standard deviation for boys in their achievement in the area of problem solving in Technology Education using the APU test.  110: a boy, = Cr girl, 111: Cr boys^a gins  32  Because this study was exploratory in nature, and no other study like this has been done in Canada, the statistical significance level used was 0.10. This level was selected in order to as much as possible reduce the risk of Type 2 as opposed to Type 1 errors. This chapter describes the testing methodology and procedures that were used to achieve the results presented in Chapter Four.  Background: The setting for the study was carried out at Aldergrove Secondary School, Aldergrove, British Columbia, Canada. Aldergrove Secondary is one of eight secondary schools in the Langley School District (#35). Langley is a sub-urban area, located close to the Vancouver metropolitan area. Traditionally a farming community, it is changing to become a "bedroom community" for Vancouver. Located in the eastern, and more rural section of the district, the school is of medium size with an overall population of 850 students from Grades 8 through 12. The school boasts a very strong technology department, with five full-time teachers instructing in the area of Technology Education. Students in the school's catchment area come from a varied background. Many of the students live in a country setting either on farms or small acreages. However, there is a significant portion of students who live in single-family dwellings and multi-family dwellings within the city limits. Students come from a wide range of socio-economic classes ranging from upper middle class to the very lowest class. This study was carried out in June of 1992.  33  Population: The subjects who participated in this study were a group of 90 Grade 8 girls and boys from four intact classes at Aldergrove Secondary School, with an approximately equal representation of both sexes. All the students participating in the study had previously completed a five month course in Home Economics, and had also recently completed a five month course in Technology Education. The mean age of the students was approximately 14 years. None of these students had any formal technical training prior to their Grade 8 year, since, in the British Columbia school system, courses of a technical nature begin at this level. Although, for convenience, the students came from intact classes under the control of the researcher, there was nothing in their nature that would make them obviously different from the usual student in this situation. As such, they might be considered typical of sub-urban, mid to low socio-economic class students in Grade 8.  Instrumentation: In order to measure students' abilities to solve problems in Technology Education, the instrument chosen was a focused test that was created and used extensively in the United Kingdom between 1985 and 1991. A copy of this test can be found in Appendix C. This instrument was designed to measure both the reflective and the active abilities of the students, thus making it a test that was believed to be relatively 'gender neutral' overall for both sexes. Reflective ability is the capability to reflect on the issues. Reflection is thoughts and ideas that are brought to bear on the problem at hand. The active ability is the capability to act on the issues. This ability is demonstrated in the instrument through having  34  the students make drawings and describe construction procedures. In addition to reflective and active abilities, abilities of communication and conceptual knowledge were also measured. Each of these abilities were again sub-divided in order that differing aspects of the ability being measured were being included in the testing. The ability of communication included aspects of its degree of complexity, clarity of message, confidence demonstrated, and skill in presentation. Conceptual knowledge was sub-divided into the aspects of materials, energy systems, aesthetic/sensory, and people (both users of the product and manufacturers). In order to measure all of these abilities and aspects, the instrument finally selected was a focused 90 minute test dealing with a specific theme, "Developing Solutions". This test can be considered technological in nature because it required students to demonstrate the following knowledge and processes which are included in the goals of Technology Education: problem solving, logic, understanding materials, comprehension of energy systems, discernment on how technology impacts people, manufacturing, products, aesthetics, design, communication, and creativity. The above were all aspects that the instrument proported to measure. The instrument used was a test entitled "Developin  Solutions", and had a reliability index of 0.82. The instrument was designed to measure thirteen areas of technological achievement as shown in Figure 3.1  35  Variable #1  Developing Solutions  Variable #2  Reflections on Issues  Variable #3  Active for the User  Variable #4  Active for the Manufacturer  Variable #5  Reflective Appraisal  Variable #6  Complexity  Variable #7  Clarity  Variable #8  Confidence  Variable #9  Skill in Presentation  Variable #10  Materials  Variable #11  Energy Systems  Variable #12  Aesthetics  Variable #13  People  figure 3.1. Variable description chart.  36  The focused test had five structured questions. Each question was designed in such a way as to differentiate the different abilities from the student response and the questions were designed to deal with specific abilities. For example, questions #2, #4, and #5 were designed to measure reflective abilities, while questions #1 and #3 measured active abilities. For consistency in administration, an administrators script was used (see Appendix D). Each group tested was given the instructions, using the same words, so that no one group was given advantage through language, explanation, or example. Time, intonation, and other language association variables were also consistent for all groups to the greatest extent possible. In conjunction with the focused test, a seven minute video was used. The title of the video was Quantity with Quality, and was explicitly concerned with mass production. The video showed a complete, factory-based, mass production system for producing electrical plug sockets, from drawing board to distribution. The video followed the theme of the test  Developing Solutions, and included all the characteristics which were intended to be measured by the test. The video demonstrated the logic in the manufacturing process, the problems that arise, and how the problems are solved. It covered the myriad of materials needed to develop a product and the energy systems involved. People were a major part of the video, both the user of the product and those that built the product. This demonstrated to students the importance of the human element in technological activities. Aesthetics, design, communication, and creativity were also presented in the video. The final stages of the video displayed, for the pupils, a visual summary (through a series of flashbacks) of all key issued raised, thus preparing them for the test that was to follow.  37  The video was carefully constructed to create a scenario to which pupils could relate. The video "became a launch pad" (APU, 1992, p.102) for the focused test. The video ended by presenting the task that was to be carried out in the test booklets. For all testees, the test was completed under the direction of the researcher.  Characteristics of the Instrument:  As the test designers explain, the Developing Solutions test is regarded as the "heartland" (APU, 1992, p.205) of technology, because it strongly represents the characteristics of a technology activity. (p.205) This test contained a realistic balance of questions in both the reflective (3 items) and active (2 items) domains. This testing instrument was very tightly structured and thus did not provide room for generalization in answers, but kept students' responses very focused on each specific question. Answers from these types of questions provide very focused but often divergent answers, as there is no liberty within the question to answer in general terms. Due to the nature of task tightness, the test proved to be reliable when measuring the achievements in confidence, complexity, clarity and skill being demonstrated in pupils' work. The reliability coefficient  for the overall test was 0.82. (APU, 1992, p.258) The instrument was also structured in such a way as to promote consistency in marking. The Assessment of Performance Unit stated that: "before we would be justified in making any claims about the data resulting from the survey, it was clearly important to establish the reliability of the markers." (APU, 1992, p.132) They found that the correlation between markers proved to be better than 0.74, (p.132) thus making the test one that could be marked with considerable reliably by others. 38  This statement was important to the APU team, because their study was carried out on 15,000 students representing many geographical areas of the United Kingdom, Wales and Ireland, and required many trained markers. Unlike the APU study, the Langill study required only one marker. The overall structure and format of the instrument also made it easy to categorize responses in both facets of capability: active and reflective. Although the test purports to measure both capabilities, a complete separation of active and reflective facets would be a distortion of theory in the area of Technology Education. All too often, curriculum is subject to Cartesian dualism (separation of mind and body), but such a separation is contrary to the theory of Technology Education; both capabilities should be simultaneously present, as Technology Education involves both the head and the hands, as well as the heart. The benefit of looking at each capability in testing is it allows us to identify the relative strengths and weaknesses of pupils in relation to these two dimensions, a task which is purported to be accomplished with the use of this instrument.  Procedures:  Prior to each group of students' arrival for testing, the room was set up to accommodate the requirements of the instrument. Test forms and response sheets were set out about the room, and the video machine was prepared for immediate use. Students came into the room, took their seats according to their previously arranged seating order, and did not open the test booklets until instructed to do so. Students were then asked to enter their date of birth on the front of the test in the box provided, and were also given an identification number to enter on the front page of their test booklet. This was done to render subsequent marking  39  anonymous and thus reduce bias based on pre-conceived notions of particular students. Following entry of these preliminary data, students were asked to focus their attention to the front of the room where the video machine was centrally located for all to easily see. The previously described seven minute video titled Quality with Quantity was shown to the test group. The purpose of the video was to set the scene for the test and give all students a common platform from which to begin. Following the video, the students were instructed to open their booklets and the administrator presented starting instructions. The instructions were read to all students from the administrators script, clearly and carefully. It was explained to the students prior to the test that the work in which they were about to engage would not be graded for use on their report cards and the test scores would not affect their course grades, but, that they were participating in a national survey, a survey that had been used in the United Kingdom, and now was being used in British Columbia. All students were supplied with a test kit containing a pencil, pencil sharpener, blue and red pen, and a pack of coloured felt pens. The students were told that during the test they could use anything from the kit that would be helpful to them. Students then were instructed to open the booklet and begin at question one. During the testing period, the majority of the students worked feverishly and were on task. It should be noted that on all questions, students previously judged to be of high ability, generally worked constantly until they were instructed to stop. This, however, was not the case with students who were previously judged to be of the mid and lower ability levels. In their cases, as certain questions would slow them down and ideas would not come quickly to them, they could be seen picking up the colouring pens and spending time  40  colouring in shapes, rather than further exploring an idea in other ways. However, it must be mentioned, that this observation in no way biased the marker's judgement when evaluating the final papers, as marking of student response sheets were identifiable only by gender and student identification number. Because of the length of the test, 90 minutes, the administration of test had to be spread over two periods since the school timetable operates on 50 minute periods of instruction. Students were instructed to only do questions #1, #2, and #3 during the first period. These questions were easily completed during the allowed 45 minutes of this first period. Upon their return in the following period, students were given 5 minutes to review the questions and their answers from the last period. Having done this, the students were then instructed by the researcher to begin the last two questions of the test; questions #4 and #5. Because of the amount of work that was to be completed in these last two questions, students felt that it was more important to finish the entire test so that it was a complete work, rather than go back and add more to the previous day's first three questions and maybe not finish. Also, the very nature of the test provided to the testees a satisfaction of completing the last two questions, thus showing that their first three responses were very good solutions to the questions asked on the test instrument. By administrating the 90 minute test over two periods, the students' were able to remain focused on the questions more so than if they had completed the entire test in one 90 minute sitting. The two periods allowed students the required 90 minutes in which to complete the entire test.  41  Scoring Procedures: Prior to testing, the researcher had gathered all the school Grade Point Average (GPA) scores for each of the testees. These scores were used so that the tests could be sorted according to the achievement levels of the students. Any students with a school GPA falling between 4.00 - 3.00 were classified as high ability students. Those students who had a GPA falling between 2.9 - 2.0, were categorized as mid ability students, and any students with a GPA between 1.9 - 1.0, were rated as low ability students. The researcher then sorted the tests into three piles according to ability level: high ability, mid ability, and low ability. This method of categorizing tests by student ability level prior to assessment was recommended by Tony Wheeler, senior researcher from Goldsmith's College, University of London, and an APU team member. The main reason for categorizing by pre-assigned levels of ability was for ease of marking. This method of categorizing is an accepted practice within the European community. This again did not bias the marker's judgement, as work was solely being graded on what was present. The APU holistic marking sheet was used to record the evaluation of student response data (see Appendix C). First, under the topic heading "Developing Solutions", a holistic score was given on a five point scale based on the overall work completed during the 90 minute focused test. The test consisted of five questions, each question being set into a task box. This task box gave the student a work area in which to provide their response to the question. The purpose of the task box, was to help the student focus as much as possible on the question being asked. As a developmental tool, this holistic question "Developing Solutions", focused on the descriptive aspects of the assessment framework: what students were doing and how they were doing  42  it, and how completely they answered the entire test. This holistic score looked at the whole test, without breaking it down into smaller variables: To understand how the scoring for this question is decided upon, one must understand that the interpretation of this question includes looking at both the reflective and active capabilities expressed by the students in the work that they have produced. To gain a clear understanding of the interaction of these two abilities, one needs to refer to Chapter 12 of the APU text where an in depth discussion can be found. (APU, 1992, p.153) To discern between scale points the following guidelines were followed (also see Figure 3.2): A scale factor of one was only given if there was no work present. A scale factor of two was given to student work when the issues described were so general that they could apply to almost any product. The proposals here are static (lead nowhere) and lack detail, and show no attempt by the student to place value judgement on any of the ideas and proposals. All the elements that are present are fairly weak and there is no evidence to suggest any significant integration of issues (reflective capability) and proposals (active  capability). Student responses were given a scale factor of three when the following work was present. The work here presented issues that were very superficial and do not help to clarify the task. Importantly, the student sees the product outcome as priority, neglecting consideration of the overall purpose of the product. Although there is considerable evidence of the ability to take action to make something work, there is no evidence to show that this is in response to any of the important issues, such as safety, which would need to be considered if this product was to be successful. Nevertheless, there is a detailed focus on how the product will work in principle. A scale factor of four was used when good holistic  43  performance was achieved with a balanced combination of elements. The elements themselves may not have been outstanding, but the crucial feature here is the way the elements work together, feeding off one another and pushing the work forward. The issues here are broad ranging, from safety, to aesthetics, to people, to technical working, and extend well beyond the introductory material identified in the video. An example of issues described by the student here would be: safety, no sharp edges, small pieces that could be swallowed etc. In terms of the active capability, there is evidence of consideration of how the products will be used and how they might work. Again, these ideas go beyond the video and demonstrate that the student is clearly working divergently, and the ideas presented strongly show originality in this work. Finally, there is evidence of appraisal at each stage of the development which appears to be pushing this work forward, allowing deeper thought and further consideration of already mentioned proposals. To obtain a five, the student had to provide without any doubt that the work presented was a classic example of highly developed design and technological capability. With work in this range, it becomes more difficult to isolate issues from proposals, and one can expect to see high level examples of both reflective and active capabilities. It would be difficult to say which capability is better. However, it is possible to make judgements on which capability is leading and see the proposals that are constantly made as a result of the identification of important issues. In this student work, the issues are sophisticated, deep, and broad ranging, and go far beyond the video and task box description. The issues focus not only on the general parameters of the task, but also on the resolution. An example of a student response to this could be: "I'm not sure if wood is a suitable material for the wheel, because its properties may change due  44  to moisture content, and thus make it unsuitable in certain areas". High level proposals that result from this detailed consideration of issues, focus mainly on how the system would work, although where it would work and aesthetics are also considered. Each idea is explained and detailed and there is evidence of originality in some of the solutions suggested. There is evidence of growth; each new proposal is a synthesis of all previous ideas. The work is very dynamic, with ideas branching in many different directions. The student's appraisal of the work is intuitive, identifying strengths and weaknesses from the moment s/he starts work. It is this high level of appraisal and evaluation that drives the work forward. A complete description of this marking system along with examples can be found in chapters 12 to 14 in the APU text (APU, 1992, p. 153-202)  45  Test Score Descriptors Descriptors  Score 1  -  no work present  2  - issues described are very general and could apply to any product. - proposals lack detail and are static. - no attempt made by student to cast value judgements on any issues. - little to no integration of issues (reflective) and proposals (active).  3  - issues are superficial and do not clarify the task. - product is seen as priority rather than the purpose of the product. - evidence of action to make something work, but important issues such as safety are neglected. - detailed focus on how product will work in principle. good holistic performance achieved. - balance of active and reflective issues described. - many issues described; eg.^safety, aesthetics, etc. - issues described go beyond the focus of the video.  4  -  highly developed design and technology capability described. - high level examples given for both capabilities. (reflective & active) - sophisticated ideas that go way beyond the video. - issues focus not only on general parameters, but also resolution. - each idea is explained in great detail. - work is very dynamic. - student appraisal and evaluation of work is well documented.  5  -  figure 3.2 Succinctly put, the holistic score was based on the question, "Do the students' proposals grow towards a solution that would work and be good to use?". After reviewing the students' work sheets, the work sheets were marked according to the specific capabilities being observed. In the case of the test used, Developing Solutions, the data from the student work sheets was recorded on an assessment form. Since this form is generic, and was set up to be used for many different tests produced by the APU, only assessment items 46  numbered 10, 11, and 12, and 17 to 24 on the form were used for this test. Each of these specific items can be found on the marks sheet in the Appendix C. The student work sheets were evaluated and scores on the following capabilities were recorded on the assessment form: Developing Solutions, Reflective capability on issues,  Active capability in manukcturing processes, Active capability for users ofa manukctured product, Reflective appraisal, Complexity, Clarity, Confidence, Skill of presentation, Understanding materials, Understanding energy systems, Aesthetics, Affects of technology on people. Each of these capabilities were scored and recorded based on student's work on the response sheets. In evaluating each student's work, these specific capabilities or achievements were looked at separately and assessed. A complete, highly detailed breakdown of the marking procedure can be found in the "Assessment of Performance Unit in Design and Technology ", report (APU, 1992, pp 58-100).  Testing of Hypothesis: After all students' response sheets were scored, the data were then transferred from the holistic marks sheet into a computerized data file. The file also contained data for identification of sex: 1 = male, 0 = female. The SPSS:PC analysis program was used to provide basic statistics (mean, standard deviation, range, and distribution) for all 13 scores, and analysis of variance was used to detect any overall significant gender differences. A factor analysis of the 13 scores was also performed to determine if the observed variable structure agreed with the theoretical structure of the test. The results of this testing can be found in chapter four.  47  CHAPTER FOUR  Results of Testing  The objective of this thesis was to determine if there were any significant differences related to gender that affect the ability to perform in the area of Technology Education. The two null hypotheses (Ho) tested in this study were:  1. There will be no significant difference between the mean score for girls and the mean score for boys in their achievement in the area of problem solving in Technology Education using the Assessment Performance Unit (APU) test.  Ho:^boys =^girls Hl:^boys^girls  2. There will be no significant difference between the standard deviation on the scores for girls and the standard deviation for boys in their achievement in the area of problem solving in Technology Education using the APU test.  Ho: o- boy. = a girls 111:  a boy,^a girls  48  Because this study was exploratory in nature, and no other study like this has been done in Canada, the statistical significance level used was 0.10. This level was selected in order to as much as possible reduce the risk of Type 2 as opposed to Type 1 errors. Included in this chapter are the results found in the study. Variable #1, Developing Solutions, was a holistic score designed to give an indication of overall achievement. It was designed to measure how the student was able to handle the overall problem of the test. This variable was scored using a five point scale as previously described in Chapter 3. These data portray a picture that the students tested found this test to be both challenging and difficult. Table 4.1 presents the overall results for this variable.  49  Table 4.1 Summary Data for Variable # 1, Developing Solutions n = 90  Score  Frequency  Percent  1  10  11  2  34  38  3  37  41  4  9  10  5  0  0  Mean  2.5  Standard Deviation  0.82  Differences between male and female ratings are presented in Table 4.2 and the analysis of variance between males and females are displayed in Table 4.3.  50  Table 4.2 Male and Female results for Variable # 1, Developing Solutions  Labels  N  Mean  Standard Deviation  Males  45  2.67  0.77  Females  45  2.33  0.85  Table 4.3 Analysis of Variance for Male and Female responses to Variable # 1, Developing Solutions  Source  DF  SS  Mean Square  F  Sig.  Between Groups  1  2.50  2.50  3.7931  0.0547  Within Groups  88  58.00  0.6591  51  By examining Table 4.3 it is evident that there is a significant difference between the means of males and females in overall achievement (p < 0.10). The difference between the standard deviations is 0.08, which is not significant (p < 0.10). Although males performed significantly better than females (2.67 versus 2.33), the difference is so small that there is probably no educational or practical difference between the achievement of boys and girls. Table 4.4 provides summary information regarding the performance of males and females on the specific sub-scores. This table displays the mean and the standard deviation for both males and females, according to each of the twelve variables tested.  52  Table 4.4 Summary of Performance Standard Deviation  Mean Variable  Descriptor  Males  Females  Males  Females  V2 *  Reflection on Issues  1.96  2.31  0.88  0.79  V3  Active for the User  1.87  1.93  0.82  0.69  V4  Active for Manti&ct.  2.20  2.11  0.94  0.69  V5  Reflective Appraisal  2.02  2.20  0.92  0.89  V6  Complexity  2.20  2.24  1.02  0.93  V7 *  Clarity  2.09  2.36  0.95  0.83  V8  Confidence  2.36  2.47  1.05  0.99  1/9*  Skill in Presentation  2.02  2.38  0.99  0.96  V10  Materials  1.76  1.69  0.86  0.76  V11*  Energy Systems  1.53  1.67  0.79  0.88  V12 *  Aesthetics  1.49  2.20  0.76  0.76  V13 **  People  1.53  1.22  0.63  0.74  * indicates significance (p < 0.10) for IL and Ho, where girls scored significantly better. ** indicates significance (p < 0.10) for 11„, and H, where boys scored significantly better.  53  Variables where girls are significantly better: Based on the information in table 4.4, the following conclusions can be drawn. Variable #2 examined Reflections on Issues. The difference between the means is 0.35, while the difference between the standard deviations is 0.09. Females achieved significantly better than their male counterparts in this category. In this case, both null hypotheses will be rejected, as this variable is significant (p <0.10). Variable #7 measured Clarity. One would almost expect girls to do better than boys in this area as girls tend to be a little neater and more careful than do boys, and that was the case. The difference in mean scores is 0.27, while the difference in the standard deviations is 0.12. Both null hypothesis will be rejected here, as girls significantly outperformed the boys and girl's scores were less variable than those of boys. Variable #9 considered Skill in Presentation. This variable examined how well the entire test was presented. The difference in mean scores is 0.36. Girls appear to do better than boys when comparing mean scores and null hypotheses #1 will be rejected. However, the difference between the standard deviations is only 0.03, leading to acceptance of null hypothesis #2 for this variable. Variable #11 surveyed Energy Systems. In this category, girls scored higher than boys. The difference in mean scores is 0.16, significantly favouring the girls, while the difference in standard deviations of 0.09 is not significant. It appeared that girls considered energy systems and noted this in the test, while the boys took energy systems for granted and failed to note this as part of their response. For this variable, the first null hypothesis will be rejected, and the second null hypothesis will be accepted.  54  Variable #12 considered Aesthetics. The difference between the mean scores is 0.29, while the difference between the standard deviations is 0.00. Girls display better aesthetics than boys do, based on the results of the mean score, but no significant difference was shown for the standard deviations. For this variable, null hypotheses #1 will be rejected while null hypothesis #2 is accepted.  Variables where boys are significantly better: Variable #13, People, is a very important in the area of Technology Education. This variable focused on the impact that technology has on people. Based on common knowledge, one would expect girls to do better than boys in this area as girls generally show more consideration, understanding, and feeling towards people than do boys, but this was not necessarily true here. The difference between the mean scores is 0.31, with boys doing significantly better than girls. Therefore, null hypotheses #1 will be rejected. However, the difference in the standard deviations of 0.09 was not significant leading to acceptance of null hypothesis #2.  Variables where there were no significant differences: Variable #3, Active for User, gave mixed results. Difference between the means is 0.06 while difference between the standard deviation is 0.13. In this case, the null hypothesis stating there will be no significant difference between the mean score for girls and the mean score for boys must be accepted. However, the second null hypothesis stating there will be no significant difference between the standard deviation of the scores for girls and the standard deviation for boys must be rejected. Therefore, girls proved to be more  55  variable in performance in this area than did the boys that were tested. Looking at variable #4, Active for Manufacturer, the difference in the mean scores is 0.09, while the difference in the standard deviation is 0.25. For this tested variable, both null hypothesis will be accepted. For Variable #5, Reflective Appraisal, the difference in the mean scores is 0.04, while the difference in the standard deviation is 0.02. For this tested variable, again both null hypothesis will be accepted. Variable #6, Complexity, provided information on how well developed student responses were. The difference in the mean scores is 0.04, while the difference in the standard deviation is 0.09. Again, both null hypothesis will be accepted. Variable #8 looked at Confidence. This test provided information on how strongly the person presented their argument. The difference in the mean scores is 0.11, while the difference in the standard deviation is 0.57. For this variable, null hypothesis #1 will be rejected, but null hypothesis #2 will be accepted. Variable #10 examined Materials. It might be assumed that girls would fall behind the boys in their knowledge of materials, but that was not the case. The difference between the means was 0.07 which was not significant. Girls were able to make value laden decisions here, and, with both null hypotheses being accepted leading one to conclude that there is not significant difference between the two genders as a result of this tested variable. Overall, based on the results of this test, there is not much difference between girls and boys in the area problem solving in Technology Education. Girls did significantly better (p <0.10) on variables #2, #7, #9, #11, and #12. These areas dealt with the reflection on  56  issues, clarity, skill in presentation, energy systems, and aesthetics. These variables also measure the reflective capabilities more strongly than the active. The APU team also concluded the following. "Girls generally outperform boys in reflective aspects of capability, though where they are set in a more active test structure, boys' performance is much improved." (APU, 1992, p.225) Boys only outperformed girls (p <0.10) on one variable, Variable #13. This variable dealt with the impact of technology on people, and boys significantly out scored females. This provides evidence that boys focus on the effects of technology and the interaction that takes place between it and people more so than do girls. Many of the variables tested, #3, #4, #5, #6, #8, and #10, showed non-significant differences (p <0.10). While these variables measured mostly active capabilities, gender proved not to be a factor. This, may be the result of the gender-neutral effects of this test. However, it does indicate that gender is not the element of influence that has always been suspected. When the APU analyzed these thirteen test variables, they combined them into two categories of abilities; communication and conceptual. Variables found under the heading of conceptual were materials, energy systems, aesthetics, and people. Variables in the communication category included complexity, clarity, confidence, and skill in presentation.  Table 4.5 provides comparative data from the APU tests results, and the Langille study. This comparison shows that the girls in the Langille test scored closer to the boys that did the girls in the APU study.  57  Table 4.5 Comparison of Variables in the "Conceptual Cluster"  APU Test Results^(U.K.)  Variables  Present Study Test Results  Mean  Mean  Difference  Mean  Mean  Difference  Scores  Scores  of Means  Scores  Scores  of Means  of Boys  of Girls  (B - G)  of Boys  of Girls  (B - G)  Materials  1.19  0.92  0.27  0.86  0.76  0.10  Energy Systems  0.94  0.66  0.28  0.78  0.88  -0.09  ft^  Aesthetics  0.96  0.77  0.19  0.76  0.76  0  People  0.96  0.77  0.19  0.63  0.74  -0.11  Total Conceptual  4.05  3.12  0.93  3.03  3.14  0.20  When comparing the data from the APU test and the Langille test, differences can be noted. Primarily, the complete dominance by the boys in the APU study. In the Langill study, the results differ some what. In the area of Materials, boys did significantly better than girls, in a statistical sense, but the difference is so small that it is probably not educationally significant. Girls scored significantly better that boys in the area of People,  58  but again, the actual difference is so small that it can probably be ignored in an educational sense. The other two variables, Energy Systems and Aesthetics show non-significant differences. However, the APU reports that "girls show more understanding than boys in almost all the tests" in Aesthetics. (APU, 1992, p.221) As the APU used many different tests to measure these variables they concluded the following:  " The exception to this rule is in the Developing Solutions tests in the industry context, where boys do better no matter which way the sample is split, and this (as far as we have seen previously) is yet another feature of the context effect." (APU, 1992, p.221) Therefore, in the Langille test, the girls proved to do very well in showing no significant difference whatsoever, their performance as equal to that of boys in this very difficult area of aesthetics. This result of no difference provides evidence of the overall strength of the girls tested, in the Langille study. The APU team also reported the following of the conceptual cluster:  In the understanding and use of materials, it is interesting that it is only in a comparatively small number of tests that statistically significant differences occur between the performance of girls and boys. In very general terms, there is not very much difference (when using materials) between boys and girls. Where there is a significance difference, boys tend to demonstrate more understanding than girls, especially where the task requires the active development of a solution (APU, p.221)  59  The APU also found that girls dominated in the area of "People". These two conceptual area results hold a striking resemblance to the present study in that the girls performed better than the boys in the area of "People", and the boys performed better than the girls in the area of "Materials". Lastly, in the area of conceptual ability, the overall total differences (total conceptual) of the mean in the APU study are much larger (0.93) in comparison to the Langille study (0.20). This again provides evidence that the girls in the present study performed much better in comparison to the boys, than did the girls in the APU study. Table 4.6 presents data for the variables of communication abilities. Each of the four variables in communication were looked as in the following way: the complexity a student is able to handle in their communication, the clarity with which ideas are expressed, the  confidence with which they are communicated, and the skill that students demonstrate in their presentation. Together, these communication variables describe student ability to communicate their technological understanding. As was shown earlier in the data presented, in general terms girls demonstrate strengths in the reflective domain, and boys in the active domain, and these strengths are mirrored in the strengths they are able to demonstrate in their associated communication styles.  60  Table 4.6 Comparison of Variables in the "Communication Cluster"  APU Test Results^(U.K.) Variables  Present Study Test Results  Mean  Mean  Difference  mean  Mean  Difference  Scores  Scores  of Means  Scores  Scores  of Means  of Boys  of Girls  (B - G)  of Boys  of Girls  Complexity  2.28  1.96  0.32  2.16  2.24  -0.08  Clarity  2.56  2.23  0.33  2.09  2.36  -0.27  Confidence  2.67  2.58  0.10  2.36  2.47  -0.11  Skill  2.36  2.23  0.13  2.38  2.40  -0.02  Total Communication  9.87  9.00  0.88  8.99  9.47  -0.48  (B - G)  The above data shows that in the APU test, boys scored significantly higher in all areas of communication. However, results of the present study show that this is not the case. In the present study, means of the raw scores of girls were higher than the boys. However, these differences were significant (p <0.10) for only Clarity (0.11) and Confidence (0.27). The APU  61  researchers state the following with regard to the communication cluster: "whilst not being a very helpful diagnostic tool, therefore, it does at least confirm common sense ... if you can't express yourself clearly, you can't do well." (APU, 1992, p.219) In comparison to the APU test, girls in the present study showed to be much closer to the boys in scoring when the overall cluster differences were reviewed. The last analysis performed on these data was a principal components factor analysis followed by varimax rotation. Since theoretically there were different components to the scoring of the test instrument used (conceptual and communication), a principal components factor analysis of the data was performed to indicate which variables where contributing factors, and in what way were they contributing, thus providing evidence to support the theoretical structure of the instrument. Using the rule of eigenvalues greater than one, the analysis showed that there were two contributing factors. As defined, these factors were assumed to be latent traits or reflective abilities, and secondly, components or conceptual abilities. The first factor is defined by test variables # 1 to # 10. These factors all load strongly, and almost equally on the first factor (reflective) and together account for 58.5 % of the variance among students' total scores. The second factor is defined by variables # 11, # 12, and # 13. These variables all load strongly and almost equally on the second factor (conceptual abilities) and all have weak loadings on the first factor. These three variables as a group account for an additional 17.4 % of the total variance. Together the two factors account for almost 76 % of the variance. The interpretation of the principal components factor analysis is that some support for the theoretical structure of the test is provided. The results of this principal components factor analysis show very good results for a test instrument. Table 4.7 shows the loading of the variables on the rotated factors.  62  Table 4.7 Rotated Principal Components Factor Analysis for Test Variables # 1 to # 13  Variables  Factor # 1  Factor # 2  V1  0.81  -0.13  V2  0.87  -0.07  V3  0.85  -0.08  V4  0.85  0.03  V5  0.85  0.02  V6  0.91  -0.08  V7  0.92  -0.08  V8  0.92  -0.03  V9  0.94  -0.07  V10  0.74  -0.02  V11  -0.01  0.83  V12  -0.12  0.88  V13  -0.03  0.90  63  While the factor analysis defines two factors within the test, the theoretical structure suggests that there are three distinct areas. Variables 1 - 5, even though they are measuring both reflective and active capability, theoretically define how well the student is able to communicate. As pointed out earlier, if the student cannot communicate, then their ideas, will be not easily understood. Therefore, Variables 1 - 5 are intended to measure the student's ability to communicate. Variables 6 through 9 specifically deal with particular areas of communication. Since the two sets of Variables, 1 to 5 and 6 to 9 both deal with different aspects of communication, then Variables 1 through 9 readily fit into the category of reflective abilities or latent traits as defined by factor one. Factor two appears to be made up of items measuring components, or conceptual traits, and Variables 11 to 13 deal directly with this type of knowledge. The only variable that cannot be theoretically explained in this factor analysis is Variable 10, which. The intent of this variable is to measure conceptual knowledge about student understanding of materials. This variable should theoretically, be a part of factor two. However, as the data shows, the loading of this variable is among the weakest of all variables contributing to factor one. Generally, however, the theoretical structure of this instrument is supported. In conclusion to this chapter, it was found that in the area of Technology Education, girls outperform boys in some areas, and boys outperform girls in others. When each variable is examined as a separate identity, the differences between the performance of boys and the performance of girls in the area of Technology Education proved to be very minimal. Holistically, although the null hypotheses were rejected, the overall differences are so small that there is little, if any practical difference between the overall achievement of boys and girls  64  related to problem solving as measured in this study.  65  CHAPTER FIVE Summary, Conclusions, Discussion, and Recommendations  Summary:  The objective of this thesis was to determine if there were any significant differences related to gender that affect the ability to perform in the area of Technology Education. The two null hypotheses (Ho) tested in this study were:  1. There will be no significant difference between the mean score for girls and the mean score for boys in their achievement in the area of problem solving in Technology Education using the Assessment Performance Unit (APU) test.  HO:^boys = IgirIs H1 P• boys^girls  2. There will be no significant difference between the standard deviation on the scores for girls and the standard deviation for boys in their achievement in the area of problem solving in Technology Education using the APU test.  110: 0- boy, =^girls  H1: a  ,5^gbis  66  Because this study was exploratory in nature, and no other study like this has been done in Canada, the statistical significance level used was 0.10. The subjects who participated in this study were a group of 90 Grade 8 girls and boys from four intact classes at Aldergrove Secondary School, with an approximately equal representation of both sexes. All the students participating in the study, had previously completed a five month course in Home Economics and had also recently completed a five month course in Technology Education. The mean age of the students was approximately 14 years. None of these students had any formal technical training prior to their Grade 8 year, since, in the British Columbia school system, courses of a technical nature begin at this level. Although, for convenience, the students came from intact classes under the control of the researcher, there was nothing in their nature that would make them obviously different from the usual student in this situation. As such, they might be considered typical of sub-urban, mid to low socio-economic class students in Grade 8.  CONCLUSIONS: As a result of this unique study, it can be concluded that in the area of Technology Education, boys do not demonstrate significantly better problem solving performance than girls. Even though schools enrol more boys in Technology Education than they do girls, boys do not dominate in achievement. This study has provided evidence, that both boys and girls have certain strengths and weaknesses. In some of the variables tested boys proved to perform better than girls did, and in other variables, girls proved to be stronger than boys, while in some cases, there were no significant differences (p <0.10).  67  As Linn & Hyde (1989) have reported, the gap between boys and girls is narrowing, and the differences between them that formerly were observed, especially in areas of Mathematics, Science, and Technology are considerably less than they once were. This observation is confirmed by the findings of this study. It is very possible, if observed trends continue, that this gap will become narrower in the next few years, until there will be little or no differences at all. This developing trend is probably supported partly by the acceptance of women into nontraditional areas of the work force, and also by the changing roles that men and women play within our society.  IMPORTANCE OF THE STUDY:  This study has explored issues of educational principal and pedagogy, and, moreover, has sought to reflect these issues in the presentation and analysis of the resulting survey data. It is hoped that administrators, counsellors, teachers, parents, and others who make educational decisions in the best interests of students will see this study as a curriculum research and development project, as much as it is an achievement study. Whatever their judgement, there is no doubt that this study is the first of its kind in British Columbia and Canada. It is hoped that the results of this study will be seen in terms of informing the nature of teaching and learning in Technology Education as well as in providing base-line data on pupil performance. Therefore, this study is important in that it provides evidence that girls can do as well, or better than boys do in many areas of Technology Education. It suggests that, if girls are not selecting to enrol in Technology Education, it should not be for the reason that they will not  68  achieve as well as the boys do.  LIMITATIONS:  This study has provided considerable information about the performance of boys and girls in the area of Technology Education. However, the study was very exploratory in nature, and it was carried out on a select group of students. The group as previously described, was one grade level of students in one school in the Langley School District. Generalization beyond that group may not be valid.  RECOMMENDATIONS:  This study has shed new light on the area of Technology Education in British Columbia, especially in terms of gender as related to achievement. It is hoped that, as a result of this study, others will step forward and continue to do further research on the issue of gender differences in Technology Education. Although this research has provided some answers, it has also provided many questions that can act as catalysts for new enquiries. Results of this study suggest that girls can do as well as, or better than boys in most areas of Technology. However, much more research in this area is needed to determine whether the findings can be generalized. It is therefore recommended that a study of this nature be continued on a much larger scale, possibly province wide, to provide a greater range of data from a larger cross section of students, thus adding evidence for the generalizability of the findings.  69  References  Ashton-Jones, E. & Olson, A., (1991). The Gender Reader. Needham Heights, Mass.: Allyn and Bacon. Assessment of Performance Unit (APU). (1992). The Assessment of Performance in Design andTechnology. London, England: School Examinations and Assessment Council. Bateson, D.J. & Parsons-Chatman, S. (1989). Sex-related differences in science achievement: A possible testing artifact. International Journal of Science Education, 11 (4), 371-385. Brandon, P.R. (1981). The Superiority of Girls over Boys in Hawaii. Paper presented at Annual Meeting of American Education Research Association, Chicago, April 1981. Dyer, R. (1974). Scoring Procedures, External Criteria and the Effects of Some Variables on Divergent Thinking Tests. Unpublished M.Phil. thesis, University of Leeds. Erickson, G. & Erickson, L. (1984). Females and science achievement. Science Education, 68, 63-89. Farkas, S. (1986). Gender differences in science tests. Unpublished MA thesis, University of British Columbia. Feingold, A. (1988). Cognitive gender differences are dissapearing. American Pyschologist, 43, (2), 95-103. Gaskel, J. & McLaren, A. (1987). Women and Education: A Canadian Perspective. Calgary: Detseling Enterprises Ltd. Gaskell, J. (1981). Sex Inequities in Education for Work: The case of business education. Canadian Journal of Education 6, (2), 54-72. Gaskell, J, (1984). Gender and course choice: The orientation of male and female students. Journal of Education, 166, (1). Boston: Trustees of Boston University. 89-102.  70  Horner, Martina. (1969). Fail: Bright women, reprinted with permission from Psychology Today, The Gender Reader. Allyn and Bacon Publishers, Needham Heights, Mass. 1991. 319-327. Illinois State Board of Education. (1989). Sex Equity Guide For Industrial Education Programs. A paper to the International Technology Association. Reston, Virginia. Kenkel, W.F. & Gage, B.A. (1983). The restricted and gender typed occupational aspirations of young women: Can they be modified?, Family Relations Vol 31, 129-138. Langille, L.B. (Speaker). (1992). Career Education: [TV]. Surrey: Roger's Cablenet Productions. Linn, M. & Hyde, J. (1989). Gender, Mathematics, and Science. Educational Researcher, 18, (8), pp. 17-19, 22-27. Marshall. K. (1985). Women in Male dominated professions. Canadian Social Trends. Winter, 7-11. Motherwell, Cathryn. (1990, Oct.15). More studying technology at community colleges, Toronto Globe and Mail„ p. A-7. McCants, L. (1985). Breaking the barriers: Women in the technologies, Vocational Education Journal, October, 4-9. McCarthy, K.A. (1976). Sex Bias in Tests of Mathematical Aptitude. Unpublished doctoral dissertation, City University of New York. (University Microfilms No. 76-11, 629) O'Brien, M. (1987). Sexism in Education. R. In Gosh, & D. Ray, (Eds), Social Change and Education in Canada. Toronto: Harcourt Brace Jovanovich. Prediger, M., Roth, L., & North, F., (1988). Gender differences in Matematics Performance. Boston: Houghton Mifflin Company. Sutherland, Margaret, B. (1981). Sex Bias in Education, Oxford, England: Basil Blackwell. Taipan, (September, 1992), Profit Opportunities Today. , Fort Erie, Ontario: William Bonner, p-pgs 5-7.  71  Towns, D. (1985). The Responsibility to Educate Girls for a Technologically Oriented Society. , Victoria, Australia: Deakin University. Vetter, L.& Hickey, D.R. (1985). Vocational Education Journal. October, 26-29.  72  APPENDIX A  PROVINCE OF BRITISH COLUMBIA MINISTRY OF EDUCATION PUBLIC SCHOOL DATA INFORMATION MANAGEMENT BRANCH VICTORIA, B.C.  SCHOOL YEAR 1990/1991  73  PUBLIC SCHOOLS DATA •  Province of^Ministry of Education British Columbia FEB 15, 1989  DATA SYSTEMS ADM INISTRAT I ON BRANCH PARLIAMENT BUILDINGS VICTORIA, B.C. V8V 2M4  REPORT 2069 - 1988/1989 SCHOOL YEAR ^• . • SECONDARY COURSE ENROLMENT BY SUBJECT, COURSE LEVEL AND SCHOtil:.DISTR/CT  PAGE 1  SEPTEMBER 30, 1988 ACTUALS  • 1988/1989 TOTAL YEAR ESTIMATE ^ MULTI MULTI ^ ^ a 10^11^12^GRADE^TOTAL 10^11^12^GRADE^TOTAL^8 PROVINCE AGRICULTURE AGRICULTURE  58 11 69  184 156 340  51 59 110  352 293 645  15  23  7  45  15  23  7  45  59 67 126  73 11 84  207 156 363  58 59 117  397 293 690  4260 3669 7929  2608 2353 4961  2386 2367 4753  1114 1257 2371  18183 16005 34188  190 272 462  190 272 462  59 67 126  AGRICULTURE MECHANICS SUBJECT^TOTAL  . 173  • 173  75  417  137  802  15  23  7  45  90  440  144  847  5849  5604  2935  41128  580  580  ART ART  M F T  7815 6359 14174  ART CAREERS VISUAL ART 2D VISUAL ART 3D 7815 6359 14174  SUBJECT^TOTAL  4260 3669 7929  2608 2353 4961  17786  !...8954. .  2013 2062 4075  695 744 1439  1080 887 1967  3788 3693 7481  4620  2008  2207  8835  458 795 1253  207 311 518  469 456 925  1134 1562 2696  1443  662  1046  3151  4857 5224 10081  2206 2584 4790  1549 1343 2892  23295 21532 44827  11667  6185  3253  53694  17786 ..::8954  5849  BUSINESS ED. ACCOUNTING  M F T  971 1554 2525  971 1554 2525  ...  3268  3268  V8V 2M4  FEB^15,^1989  REPORT 2069 - 1988/1989 SCHOOL YEAR SECONDARY COURSE ENROLMENT BY SUBJECT, COURSE LEVEL AND SCHOOL DISTRICT ..  SEPTEMBER 30,^1988 ACTUALS 9^10^11  MULTI 12^GRADE  TOTAL^8  PAGE 2  1988/1989 TOTAL YEAR ESTIMATE 'MULTI 9^10.^11^12^GRADE  TOTAL  PROVINCE BUSINESS ED. ADVANCED ACCOUNTING BUSINESS COMMUNICATIONS CAREER TYPEWRITING 'GENERW-BUSINESS INTRO. DATA PROCESSING INTRODUCTION TO ACCOUNTING MACHINE CALC. & PROCEDURES MARKETING  NI  F T  m F T  ORGANIZATION & MANAGEMtNT  253 269 522  779  779  381 1139 1520  381 1139 1520  1671  1671  F T  262 1627 1889  262 1627 1889  2202  2202  M F T  137 156 293  137 156 293  316  316  NI  F T  2218 4118 6336  2218 4118 6336  7324  7324  M F T  4102 5661 9763  4102 5661 9763  11278  11278  NI  M F T  549 1423 1972  549 1423 1972  1723 1817  342 437 779  2065  2254 4319  107  21 833 854  128 2816 2944  M  233  233  T  515  M  3540  OFFICE PROCEDURES  253 269 522  IA  F T F  1983 2090  282  282 515  2349  2349  4109  964  5073  2459  1201  3660  676  676  Province of British Columbia FEB 15, 1989  Ministry of Education^PUBLIC SCHOOLS DATA  DATA SYSTEMS ADMINISTRATION BRANCH PARLIAMENT BUILDINGS VICTORIA, B.C. V8V 2M4  REPORT 2069 - 1988/1989 SCHOOL YEAR SECONDARY COURSE ENROLMENT BY SUBJECT, COURSE LEVEL AND SCHOOL DISTRICT  PAGE 3  SEPTEMBER 30, 1988 CTUALS  - 1988/1989 TOTAL YEAR ESTIMATE ^ MULTI MULTI ^ ^ 8 10^11^12^GRADE^TOTAL^8 10^11^12^GRADE^TOTAL PROVINCE BUSINESS ED. PERSONAL & BUSINESS RECORDS PERSONAL TYPEWRITING SHORTHAND TYPEWRITING  M  391 498 889  391 498 889  ni  1459 2425 3884  F T  ni  3 58 61  F T  NI  F T  SUBJECT^TOTAL  6990 11792 18782  826 2997 3823  7381 12290 19671  826 2997 3823  10011 17845 27856  2 75 77  2752 6012 8764  31 367 398  31 367 398  SUBJECT^TOTAL  972  1459 2425 3884  4626  36 500 536  61  7816 14789 22605  :20822  4357  21001 39511 60512  .^ • .^21794  4357  4626 90  425  576 25179  32375  10998  425  69949  '.  COMPUTER ED. COMPUTER STUDIES  972  NI F T  5031 3537 8568  1421 617 2038  6452 4154 10606  10204  2540  12744  5031 3537 8568  1421 617 2038  6452 4154 10606  10204  2540  12744  CONSUMER ED. CONSUMER EDUCATION SUBJECT^TOTAL  4753 4340 9093  10265 10321 20586  15018 14661 29679  10479  22905  33384  4753 4340 9093  10265 10321 20586  15018 14661 29679  10479  22905  33384  V8V 2M4  FEB 15, 1989  REPORT 2069 - 1988/1989 SCHOOL YEAR^• % SECONDARY COURSE ENROLMENT BY SUBJECT, COURSE LEVEL AND SCHOOL DISTRICT  PAGE 4  •  „ 1988/1989 TOTAL YEAR EST/MATE '^  SEPTEMBER 30, 1988 ACTUALS  MULTI MULTI 8^9^10^11^12^GRADE^TOTAL^8^9^10^11^12^GRADE^TOTAL PROVINCE ENGLISH COMMUNICATIONS COMPOSITION ENGLISH ENGLISH LITERATURE JOURNALISM WRITING  M F T  3169 1877 5046  M  986 1087 2073  2933 1977 4910  6102 3854 9956 986 1087 2073  10882 11805 22687  76604 75789 152413  M F T  840 2349 3189  840 2349 3189  M F T  292 542 834  M F T  M F T  18638 17825 36468  18638 17825  SUBJECT^TOTAL  17715 16895 34620  17715 16895  16910 16107 33022  16910 16107  36468  34620  33022  5660  4320  3992  12459 13157 25616  16614 16121  32735  5640 • . ^. '• 37506^36644  5868  2189  2189 27466  168495  3914  3914  292 542 834  926  926  749 1392 2141  749 1392 2141  2477  2477  15696  85573  40651  189509  18065 33761  85013 170606  35944  30935  11508  ...f .  1*  37506^36644  35944  38764  12010 ': 9143  8083  29236  12010% .9143 ••^•  8083  29236  GUIDANCE GUIDANCE  M F  T  SUBJECT^TOTAL  5388 11048  5660 5388 11048  4322 8642  4320 4322 8642  13972  3664 7656  13374 27346  3992 3664 7656  13972 13374 27346  1,4•,..  Province of British Columbia  Ministry of Education^PUBLIC SCHOOLS DATA..  DATA SYSTEMS ADMINISTRATION BRANCH PARLIAMENT BUILDINGS VICTORIA, B.C. V8V 2M4  PAGE 5  REPORT 2069 - 198B/1989 SCHOOL YEAR SECONDARY COURSE ENROLMENT BY SUBJECT, COURSE LEVEL AND SCHOOL, DISTRICT  FEB 15, 1989  1988/1989 TOTAL YEAR ESTIMATE ^ MULTI MULTI ^ 10^11^12^GRADE^TOTAL^8 10^11^12^GRADE^TOTAL  SEPTEMBER 30, 1988 ACTUALS  PROVINCE HOME ECONOMICS CAFETERIA  M F T  CLOTHING & TEXTILES  1926  15 1196 1211  M  969 4731 6700  196 1904  1957  F T  M F T  FAMILY STUDIES  FOODS & NUTRITION  M F T  INTRO. CLOTHING & TEXTILES  INTRO. FOODS & NUTRITION !  600 838 1438 226 4926 5152  2100  141 1311 1465  M F T  HOME ECONOMICS  SUBJECT^TOTAL  31  F I  M  FAMILY MANAGEMENT  TEXTILE ARTS & CRAFTS  600 838 1438  4402 5561 9963  1724 2437 4212  2327  3702 6029  857 1933 2790 466 811 1277  9000 12615 21615  1712  272 8048 8320  2228  1475  1165 6635 7800  6561  3011  141 1311 1465  1555  9310 13633 22994  4748  9466 13426 22892  1712  5629  9332  9572  1555  7307  3679  25832  26923  1355  27187  M F T  22 645  22 645 667  727  727  M  842  842 942 1784  1981  1981  293  303  596  6596  19107  667  F T  942 1784  M F T 9000 12615 21615  4402 5561 9963  13 274 287  4  252  1878 4022 5964  4195 12194 16389  17 522 539  248 1668 5871  7539  692 5737 6429  21835 46000 67899  25832  11189  9877  6984  79585  FEB 15, 1989  REPORT 2069 - 1988/1989 SCHOOL YEAR SECONDARY COURSE ENROLMENT BY SUBJECT, COURSE LEVEL AND same* DISTRICT .^. ., SEPTEMBER 30, 1988 ACTUALS^  PAGE 6  • • 198811989 TOTAL YEAR ESTIMATE  MULTI^ 8^9^10^11^12^GRADE^TOTAL^  MULTI 10^11^12^GRADE^TOTAL  PROVINCE INDUSTRIAL ED, CONSTRUCTION DRAFTING ELECTRONICS INDUSTRIAL EDUCATION MECHANICS METAL TECHNOLOGY  M F T  4709 336 5045  3043  109 3152  445 8197  5851  3786  9637  M F T  2917 657 3574  1102 184 1286  4019 841 4860  4079  1680  5759  M F T  1273 47 1320  631 9 640  1904 56 1960  1486  785  2271  M F T  13965 8686 22651  7752  24421 2577 26998  38386 11263 49649  5929 614 6545  3816 98 3914  9745 712 10459  M F T  2822 98 2920  1617 13 1630  4439 111 4550  M F T  818 102 920  150 20 170  968 122 1090  M F T  SUBJECT^TOTAL  13965 8686 22651  18468 0 10359 1854 433 20324 10792  24421 2577 26998  67213 13550 80765  ..,'-•  26513^•  0  26513,....  30073  56586  7714  4896  12610  3390  1980  5370  1027  240  1267  23547  13367  30073  93500  LANGUAGES BEGINNERS GERMAN BEGINNERS'^ITALIAN  M F T  449 481 930  449 481 930  1082  1062  25 25 50  25 25 50  50  50  Province of British Columbia FEB 15, 1989  Ministry of Education^PUBLIC SCHOOLS DATA  DATA SYSTEMS ADMINISTRATION BRANCH PARLIAMENT BUILDINGS VICTORIA, B.C. '^V8V 2M4  REPORT 2069 - 198871989 SCHOOL YEAR^•^• SECONDARY COURSE ENROLMENT BY SUBJECT, COURSE LEVEL AND SCHOOL/DISTRICT SEPTEMBER 30, 1988 ACTUALS  PAGE 7  1988/1989 TOTAL YEAR ESTIMATE  MULTI MULTI 10^11^12^GRADE^TOTAL^8^•^10^11^12^GRADE^TOTAL  8 PROVINCE LANGUAGES BEGINNERS' JAPANESE BEGINNERS' LATIN BEGINNERS' MANDARIN BEGINNERS' SPANISH FRANCAIS LANGUE FRANCAIS LITT. ET COMM. FRENCH GERMAN JAPANESE LATIN  M F T  192 201 393  192 201 393  M F T  4 11 15  M F T M F T  415  415  4 11 15  15  15  25 32 57  25 32 57  65  65  737 1041 1778  737 1041 1778  2036  2036  M F T  448 540 988  279 455 734  173 255 428  112 182 294  29 53 82  1041 1485 2526  M F 1  313 428 741  200 323 523  78 103 181  58 74 132  13 14  1  650 941 1591  M F T  15000 14946 29946  9763 11926 21689  7700 9640 17340  6122 7974 14096  1487 3305 4792  40072 47791 87863  324 302 626  200 209 409  247 283 530  57 61 118  828 855 1683  153 154 307  32 23 55  58 63 121  10  253 240 493  48 38 86  27 21 48  N F T  S  10  75 59 134  .•  :,..8.71  542  335  150  3069  775 .^597  '^181  194  55  1802  /3515 •.,  19234  16820  5935  97611  .667  409  764  192  2032  317  61  197  ..^141  48  40  1171  32107  •  32.  607 229  vex/ 244  FEB 15, 1989  PAGE 8  REPORT 2069 — 1988/1989 SCHOOL YEAR SECONDARY COURSE ENROLMENT BY SUBJECT, COURSE LEVEL AND SCHOOL DISTRICT SEPTEMBER 30, 1988 ACTUALS  ^  —1988/1989 TOTAL YEAR ESTIMATE  MULTI MULTI 8^9^10^11^12^GRADE^TOTAL^8 ,^10^11^12^GRADE^TOTAL PROVINCE LANGUAGES MANDARIN SPANISH  M F T  62 86 148  11 2 13  32 32 64  3 6 9  108 126 234  M F T  174 200 374  139 131 270  220 303 523  29 35 64  562 669 1231  11003 13484 24487  8360 10384 18744  8281 10702 18983  1616 3473 5089  45021 53957 98978  10688 10716 21404  6136 5024 11160  15761 15914 31675  SUBJECT^TOTAL  .^148 ..  13  75  28  264  411 .^. :'.^.  310  1008  111  1940  20798  23096  6503  111117  16824 15740 32564  26300  12895  39195  2162 2704 4866  6073  34053  26667  '°""-^---- — MATHEMATICS ALGEBRA  M  2162 2704 4866  CONSUMER MATHEMATICS GEOMETRY INTRODUCTORY ALGEBRA MATHEMATICS PROBABILITY & STATISTIC§  764 419 1183  M F T M F T M F T  17702 17115 34827  53472 51383 104875  17198 16329 33532  M  226 172 398  F  T TRADE MATHEMATICS  M  2369' 645 3014  1371  2292 2320 4612  2292 2320 4612 18572 17939 36516  764 419 1183  37922- 37402  1371 5071  5071 36361  111685  226 172 398 2369 645 3014  6073  562 3611  562 3611  Province of British Columbia  PUBLIC SCHOOLS DATA  Ministry of Education  DATA SYSTEMS ADMINISTRATION BRANCH  PARLIAMENT BUILDINGS VICTORIA, B.C. V8V 2M4 PAGE 9  REPORT 2069 - 1988/1989 SCHOOL YEAR SECONDARY COURSE ENROLMENT BY SUBJECT, COURSE LEVEL AND SCHOUL DISTRICT  FEB 15, 1989  -.1888/1989 TOTAL YEAR ESTIMATE ^ MULTI MULTI ^ ^ 10^11^12^GRADE^TOTAL 10^11^12^GRADE^TOTAL^8 8 SEPTEMBER 30, 1988 ACTUALS  PROVINCE MATHEMATICS  .  18572 17939 36516  SUBJECT^TOTAL  17702 17115 34827  17198 16329 33532  17511 16385 33896  7126 5615 12741  78109 73383 151512  2692 3313 6005  1941 2390 4331  1088 1568 2656  858 1004 1862  181 880 1061  119 780 899  326 1246 1572  198 674 872  • 37922  • .•  37402  36361  41055  14828  167568  6579 8275 14854  i6156  4439  2749  1951  15295  824 3580 4404  ,1126  985  1707  944  4762  MUSIC  m  BAND  F T  ni  CHORAL MUSIC  F T  M F T  MUSIC  4490 5227 9717  4490 5227 9717  ri  MUSIC COMPOSITION  F T  SUBJECT^TOTAL  159 106 265  459 342 801  297 190 487  188 90 278  360 166 526  124 62 186  969 508 1477  4490 5227 9717  3170 4383 7553  2248 3260 5508  2074 3216 5290  1339 1846 3185  13321 17932 31253  18615 18098 36713  17852 17085 34937  17040 15746 32786  7986 4508 12494  5173 2645 7818  18615 18098 36713  17852 17085 34937  17040 15746 32786  7986 4508 12494  5173 2645 7818  M  STRINGS  300 236 536  10792  10792 580  271  851  ..495  296  560  212  1563  ..7777  5720  5596  3378  33263  66666 58082 124748  37856 .36747  35241  14816  9691  134351  66666 58082 124748  37856  35241  14816  9691  134351  10792  tt. PHYSICAL ED. PHYSICAL EDUCATION SUBJECT^TOTAL  M F T  '3647  '....  VBV 2M4  FEB 15. 1989  REPORT 2069 - 1988/1989 SCHOOL YEAR SECONDARY COURSE ENROLMENT BY SUBJECT, COURSE LEVEL AND SCHOOL *DISTRICT  PAGE 10  1988/1989 TOTAL YEAR ESTIMATE • ^ MULTI MULTI a^9^10^11^12^GRADE^TOTAL^6^9^10^11^12^GRADE^TOTAL SEPTEMBER 30, 1988 ACTUALS  PROVINCE SCIENCE BIOLOGY CHEMISTRY EARTH SCIENCE GEOLOGY PHYSICS SCIENCE SCIENCE & TECHNOLOGY  M F T  7268 9833 17101  5036 8282  10514 14869 25383  20529  10220  30749  M F T.  6085 6053 12138  3407 2656 6063  9492 8709 18201  14559  7264  21823  M F T  1470 1151 2621  1470 1151 2621  3261  377 244 621  M F T M F T M F T  3246  5696 3295 8991 18417 17690 36112  17496 16858 34364  2406^. 717 3123  8102 4012 12114 52568 50446 103034  16655 15898 32558  M  377 244 621  86281 82501 168802  M F T  592 423 1015  M F T  3962 3167 7129  18417 17690 36112  17496 16858 34364  16655 15898 32558  24277 23402 47679  • 38129..:36823  758  758  4106  15061  35896  3758 3070 6828  3758 3070 6828 9436 8653 18089  SUBJECT^TOTAL  10955  3261  110848 8277  .^. 38129^ 36823  35896  57581  8277 22348  190777  592 423 1015  1348  1348  3962 3167 7129  8393  8393  SOCIAL STUDIES ECONOMICS GEOGRAPHY  (10  Province of British Columbia  Ministry of Education^PUBLIC. SCHOOLS DATA:'::  DATA SYSTEMS ADMINISTRATION BRANCH PARLIAMENT BUILDINGS VICTORIA, B.C. • V8V 2M4  REPORT 2069 - 1988/1989 SCHOOL YEAR ^1, SECONDARY COURSE ENROLMENT BY SUBJECT, COURSE LEVEL AND SCHOOCJ5ISTRICT  FEB 15. 1989  PAGE 11  • 1988/1989 TOTAL YEAR ESTIMATE ^ MULTI MULTI ^ 8 10^11^12^GRADE^TOTAL^8 .^10^11^12^GRADE^TOTAL SEPTEMBER 30, 1988 ACTUALS  PROVINCE SOCIAL STUDIES HISTORY LAW  M F T  3343 3364 6707  3343 3364 6707  m  4782 5070 9852  4782 5070 9852  F T  SOCIAL STUDIES  M F T  18275 17650 35930  17523 16835 34368  16790 16152 32947  m  WESTERN CIVILIZATION  1973 2701 4674  1973 2701 4674  14952 14596 29548  14652 14725 29377  82192 79958 162170  1499 2322 3821  631 1013 1644  2130 3335 5465  167 190 357  167 190 357  F T  SUBJECT^TOTAL  18275 17650 35930  17523 16835 34368  16790 16152 32947  67540 65233 132793  14952 14596 29548  '....  37807  37807  36784  36784  36082  36082  8023  8023  12018  12018  35953  146626 6051  6051  35953  35833  182459  4312  1988  6300  423  423  THEATRE  m  ACTING  F T  DIRECTING & SCRIPTWRITING  DRAMA  STAGECRAFT SUBJECT^TOTAL  t.  M F T M F T  4747 5702 10449  3170 4258 7428  M F T  4747 5702 10449  3170 4258 7428  9761 12384 22145  1844 2424 4268  1844 2424 4268  421 417 838  123  104 227  1920 2739 4659  1307  921  2228  544 521 1065 12602 16430 29032  ........ • . . -. 13435.. 8132 . -^•^•  13435 • Ef,132  4691  4691  26258 899  300  1199  5211  2711  34180  V81/ 2M4  FEB 15, 1989  ^  REPORT 2069 - 1988/1989 SCHOOL YEAR  ^  SECONDARY COURSE ENROLMENT BY SUBJECT, COURSE LEVEL AND SCHOOL DISTRICT SEPTEMBER 30, 1988 ACIUALS MULTI^  PAGE 12  1988/1989 TOTAL YEAR ESTIMATE MULTI  a^9^10^11^12^GRADE^TOTAL^8^9^10^11^12^GRADE^TOTAL  PROVINCE THEATRE PROVINCE TOTAL  ^  153955 126053 106422 136384 79176 36958 638948 149093 132822 109347 132479 76245 20345 620331 303068 258915 215853 268865 155421 57303 1259425 329641 278229 235708 319412 189533 63640 1416163  APPENDIX B Education Amendment P.L. 92-318  "No persons - shall on the basis of sex, be excluded from participation in, be denied the benefits of, or be subjected to discrimination under any education program or activity receiving Federal financial assistance."  86  APPENDIX C APU DESIGN AND TECHNOLOGY TEST  TITLE: Products and Systems for Industry Quantity with Quality  Developing Solutions Test: 3iiE  87  Pupil Number  APU  32030  1988^  Design and Technology Products and Systems for Industry  Quantity with Quality Activity three: Developing solutions Date of Birth  Day month year 0713/0717/071810505/0504  Test 311E  Al>  :14  TASK The team has decided that it would be a good idea to design the wheel system so that it will make a "clip clopping" sound when the children "ride" it. They have decided that the redesigned wheel system must be able to do the things shown here. YOUR TASK TODAY is to take this idea and develop it as far as you can in the time available.  Can it assern6kd &sib ?  Design a wheel system for the hobby horse that; a) makes a "clip-clop" sound as the youngster "rides" along on the horse b) can be produced quickly in large numbers.  Put down all your design ideas for developing a successful solution.  2.  3.  List all the things the product or system will have to do if it is to be successful.  Jot down all the design problems that still need to be sorted out.  •  5.  List all the things you would need to find out or learn about if you were going to develop your ideas through to a successful solution.  How do your ideas measure up?  92  ASSESSMENT  School No.  Marker No.  ^  Pupil No.  Level 1  APU  1988 DESIGN AND TECHNOLOGY  193 583 573 563 553 543  GOLDSMITHS' COLLEGE  533  523 [13  UNIVERSITY OF LONDON^  593 (7, 563 [53  (93 583 573  593 57,  573  573  I6 [51  563  '63  [53  r43 [33  543 533  553 54, 533  563 553 543 531  553 543 533  523 513 50,  523  c23  '23  523  513  03  cl  [03  [03  [03  5O, 583 c'73  59,  c93  563  [83  583  583  c73  73  573  573  58, 573  563  561  [63  [53  '53  t53  56: '5' c43 531  563 553 t43 i33  cs3  565  543 533  [43  543  c43  [33  c33  533  t23 r13 503  52, 513 i0,  c23  523  523  513  513  c13  '23 t13  503  503  503  [03  311 o 4 o  5A3^[133^cC3^c03^cE3^c F3  Early ideas:  m=  1:03 cl, 52, c3, c41  513 523  Can they focus on what needs to be achieved, what they need to  7  1 o 2 o 31 o 3110 4= ^ cA3^5133^'Cr^'Dr 5E3^cF3  1,0,  Starting points:  Are they able to perceive and plan for intervention in a way that gives space and a framework for development? Can they get started?  EPW ==,  Ey, ER)  Test No.  Test No. 1 = 2 = 3i =  HOLISTIC MARK  503  ta  rft]  [33 [41  503 [13 [23 (33 [43 (53  cyit-FAIL achieve it and how logo about It? Developing solutions:  [23 [33  54:  [53  )503 513 523 533 c43^[53  c03 513 523 533  54:  (63  '01 cl 3 523 c33 543 [53  c0 3^[13  0o proposals grow towards a solution that would weekend be good to use? Evaluating products:  Can they appraise products with a sound. critical eye that sees opportunity for improvement?  look mainly in boxes  Starting points:..  Ability to locus and expand on one task.^ 2.47 7 Ability to identify sub tasks. Ability to speculate on overview of resolution of whole task. ^5, d Active grip on mit:tiering/dew/0,3mq early Ideas^3 5.^Ability to appraise for value and consequenr.e.^including red pen  1. 2. 3. 4.  Early ideas:^,, 8. Odeon issues that expand and dated the task^1, (3), 4 '7.^Abili* to plart'ahoed and nisounie thopirag40:41.^(3), 5, 8. 7. (8) 8. Active griped developing the product^a) for the user •^25 5 b) for manufacitme 2. (3) s^ ^ ,^. 9. Ability to appraise tor value end consequence^including red pen 7^Developing solutions: (^10. Passive gap on task issues.  2. 4, 6 11 Active grip on developing the product^a)^for the user^1.3 b) for manufacture^1. 3 including red pert 12 And ^to appraise for value and consequence  51  52,  53:  54:  ri  i23  [33  L43  [13  c2t  c33  c43  [13  513  [21  [33  [43  [13  [23  [33  54  51  52,  c3,  54,  513 513 rl,  523 52, 523 (23  53, 533 533 c33  c43 543 i43 54,  [13  [ 23  [33  '1.3  cl,  c2,  533  54  [13  [23  [33  c 1]  c23  533  .43  533 53,  513  r23  r3 3  543  t1r  52, 52,  543 54, (45  el  r 23  533  ,43  515  513  523  533  [43  [23  c33  543  53, [33 r3,  r4r 54,  [33  [43  cli  52'  53:  54:  0  c13  c23  533  543  0  r13  52,  r3,  [43  :1  c13  523  c33  543  Li,  52, c2, r2, r23  3  [43  Evaluating products: 1  511  c23  c35  54,  513  52,  r3,  [43  2a, 26  513  523  533  c43  [13  c23  c33  c43  13. Passive grip on identifying relevant criteria, 14. Critical appraisal^re.^users re. manufacture  2a, 26  rl,  c23  c33  [43  517  r 23  53,  4  03  [23  [33  r43  c13  c23  533  543  3, 5, 6  c13  523  533  543  [13  523  c33  543  513  15. Active response as a designer. 16. Grip on strategies for testing.  r4  • Quality of communication when handling the task 17. Complexity of the message canted 18. Clarity of that message. 19. Confidence demonstrated 20. Stoll in presentation.  52:  53:  54:  rl,  c2,  :3,  :43  513  '23  c33  c43  c13  523  533  5N]  513  rry,  cl,  'FP  523  533  c43  523  c33  54,  rl  523  i3,  543  543  c13  c23  c33  54,  523  533  [NJ  c13  523  533  523  53,  5FP  513  523  533  c13  523  5h13  513  '23  533  r1,  r2,  i3, c3  cN3  el 3  C23  Conceptual platform in operation in the task. In terms of: 21. Materials. 22.  Energy systems.  23. Aesthetic/sensory. 24.  People.  Characteristic forms of response to the tests: ED, cE,  EF,  5G,  cAl  510  003 cN3  5H3  clJ  5,11  cK,  5L]  00=  EN,  ET,  cOE  ERE  cQ,  ER1 ES,  ET]  EU,  5b,  EV3  6.4E,^rX3  ,y,  5Z,  Ei,  tc,  cd,^ce,  513  tv  cL,  ER3 cR3 EZ,  ca,  5f, cg,  5h3  EY,  EU,  583 cC3  50] 5E3 5F3  5G,  ca)  cb,  chE  r■)  DRS DATA & RESEARCH SERVICES PLC/H18411288  93  APPENDIX D Administrators Script  94  ^  —^  e  ,^1 /cm^tv■  ADMINISTRATOR'S INSTRUCTIONS TEST:^3iiE ACTIVITY: Developing solutions. CONTEXT: Products and systems for industry. THEME:^Quantity with Quality. A. Before the pupils enter the room: i)  Make sure that the ^room is suitably arranged for four pupils to share one resource pack, and that each pupil has sufficient space to work on a booklet when opened out.  Run the opening sequence of the video to check that it's OK, and set the sound level (there is a lead time of 40^about^20 seconds before the video V\^starts). Make sure it will be visible to all pupils. Rewind to the start.  iii) Have a look through the resource pack so you can see what is available. You may use any of the resources at any time. iv)  If at any stage you do not understand what you have been asked to do, ask for help.  v)  You will be given your own booklet to work in.^If you run out of space, ask for more paper.  vi)  You can use sketches,^drawings or diagrams at any time in the activity where you feel it would be helpful, even if you have not specifically been asked to.  ii)  B. When the pupils are admitted to the room SAY TO THEM: i)  Please sit at a workspace.  ii)  You are going to be involved in an activity^to do with designing and making things for people - which is called DESIGN and TECHNOLOGY. The task you will be undertaking today is part of an important national programme to build up a picture of what can be achieved in this area by young people of your age. Your contribution will be extremely valuable so please try to do the best you can.  vii) Throughout the task your thoughts and ideas are the things that are most important. GIVE OUT THE PUPIL BOOKLETS (making sure that each pupil receives the one with their allocated pupil number on it) AND THE PICTURE SHEET. ASK THEM NOT TO OPEN THE BOOKLET YET.  Time  Running the Activity.  1.  SAY TO THEM: To start with today you are going to watch a short video programme that looks at the business of manufacturing a product in large numbers. After you have seen the programme you will be asked to undertake a design task in relation to large scale manufacturing.  2. SHOW VIDEO PROGRAMME.  •4) (1^This^will  last about 7 minutes. When the music has faded out at the end STOP THE TAPE AND REWIND IT TO THE BEGINNING:  3.^SAY TO THEM: As you were told in the video programme, you are working today as if you are a member of a design and development team - working on one part of a project. The team has already found out that young children like playing with the hobby horse they have designed and made. To see if it would sell well, they took the prototype to the school fete and could have sold it ten times over. There was clearly a market for the hobby horse. Already they have been given orders for over 100. They have decided to make and sell as many as they can - starting with a production run of 200.  ^Comments  2  3  Time  To make them quickly they decided to set up a rapid^production^system.^The original design was for a 'one off' product, so the team decided to re-design some of the main parts to make it suitable for a small batch to be produced using rapid production techniques. Your job is to take responsibility for the re-design for manufacture of ONE part of the product. Outline details of the design of the hobby horse are shown on the picture sheet you have been given. Your task today is to do with the design of •the wheel system to make it suitable for producing in numbers. It is not your job to redesign the whole product. First of all study the basic design of the hobby horse. You have a few minutes to do this.  4.  5.  TIME THREE MINUTES  SAY TO THEM: Open your pupil booklets now so that you can see the details of your task today. As it tells you,^the team have also decided that it  would be a good idea to design the wheel system so that it will make a 'clip clopping' sound when the children 'ride' it. Your task today is to design a wheel system for the hobby horse that:  Comments  4  Comments  Time a) makes a 'clip clop' sound as the youngster 'rides' along on the horse,  0  f3c.o\de-k lead,^Snm.k uPt>cd Crt.f ■.,>or  c\ar)  ct^v.  •  b) can be produced quickly in large numbers. Your job is to take this idea and develop it as far as you can in the time available. Open the top flap of the booklet and find BOX 1. To start with you have About twenty minutes to put down ALL your early ideas for developing a successful wheel system that would create a 'clip clop' sound. Think of as many aspects of the design as you can. You will have more time later to explore and develop your ideas so use this first twenty minutes to get down AS MANY DIFFERENT ideas as you have. You can draw in any way that you think suitable and use notes to explain your thinking. Do this in box 1. 6. TIME 20 MINUTES  7, SAY TO THEM: Stop what you are doing please. Open the bottom flap of your test booklet and find box 2. It is important now to think about all the things that make products and systems successful. For example, if you were designing an overcoat for production in quantity, one thing that would help with its success would be that the fabric could be cut easily with little wastage - and there would be many other requirements.  tpis3cols(ti" e^Ao,C  c  ceP eccl. 4,.1,Az^th( ore  -^  Ir.  -C■rs-k 2  5  Time Bearing in mind all your thoughts and ideas up to now, list in box 2, ALL the things that the wheel system you are working on would have to do - and be like - to be successful. You have about 5 minutes for this.  8.  TIME 5 MINUTES  9.  SAY TO THEM: Stop what you are doing please. Look at the list you have made, and decide which you think are the THREE MOST IMPORTANT things on your list. Please put a STAR against each of them.  10. SAY TO THEM: The next stage is to look back at your ideas so far and decide how good they might be. ?Ev, Using a RED pencil from your pack, GO BACK OVER ALL YOUR EARLY IDEAS and say what is GOOD about them and WHY - and what is WEAK about them - and WHY. You can either do this by writing beside your early ideas, or you can use the 'notes' column. You have about 5 minutes for this. Remember to use a RED pencil.  Comments  Comments  Time 11.  TIME 5 MINUTES  3t 12.  6  SAY TO THEM: Stop what you are doing please. You now have about half an hour to EXPLORE AND DEVELOP your ideas for the wheel design. Think about the difficulties raised by your ideas and try to develop a solution that could be quickly produced in quantity and that would work well.  c.s11ovd 4 b e. ho/c'\ 1,110.3e.1-.41  of 444  S et ec,f, fs.e.efrAs 40 c-c  You may want to concentrate on one particular aspect of the design or try to develop the whole wheel system.  faxij  You can use any sketching, drawing, or designing techniques that you think suitable using any of the equipment provided.  CL-4-cct.)  A-dcc..%)  Do this in the space remaining in the lower half of box No 1. If you need more paper please ask for it. A  ,S43C Ere0^rid 0-.0,4c.)  13.  TIME 25 MINUTES.  o /Z icct^ $9,A)-  14.  SAY TO THEM: Stop what you are doing please. Turn down the top flap of your test booklet so that you can see box 3 whilst still being able to see your work in the lower half of box 1. You are nearing the end of the test and have a few minutes to think about any aspects of the design that you may not have already covered, or fully detailed and explained.  ,  Time  Look back through your ideas and jot down ALL the design problems that still need to be sorted out. Spend a couple of minutes doing this in the left hand side of box 3 and then spend the remaining time trying to sort some of them out. You have about ten minutes altogether for this.  •44,.  o  15.  TIME 10 MINUTES.  16.  SAY TO THEM: Stop what you are doing please. Fold the bottom flap of the booklet up and close it so that you can turn to the back page. You have^now^finished your designing, but in the process of working on your ideas, you will have thought about a variety of things that you don't know enough about in order to design a finished solution. In box 4, list ALL the things you would NEED TO FIND OUT, OR LEARN MORE ABOUT - if you were going to take your ideas further. You have about 5 minutes to do this.  17.^TIME 5 MINUTES.  ^Comments  7  8  Time  Stop what you are doing please. Your final task is to look at how well your design ideas measure up to the original task you were given. Open the booklet again and re-read the task. In box 5 explain how well you think your ideas measure up to this. What is GOOD about them - and WHY? What is WEAK about them - and WHY? You have about 5 minutes to do this.  19. TIME 5 MINUTES.  10.^SAY TO THEM: You can stop work now. You have finished the activity, but can you just make sure you have put your pupil number and test number onto any extra pieces of paper you may have had and put them inside your booklet.  CONTINUED OVERLEAF ...  Comments  9  Filling in the Data Sheet. (Pupil Information)  When you have done this, put a circle round the one that is your favourite and a star against the one you think you are best at.  1.  c) If you think any of these subjects have helped you in this test today, write these down in the space at c. Explain why, and in what way, you think the subject has helped.  Give out a data sheet to each pupil. SAY TO THEM: There are a few further details needed from you. First, can you put your date of birth in the boxes on the front of your BOOKLET. Next, copy your pupil number onto the DATA SHEET you have been given, and fill in your date of birth and the male or female box.  2. The following questions relate to the pupils' school^subjects.^It^is important that^the subject names are the actual course names. If the pupils are used to using abbreviations (eg PSE for Personal and Social Education), or alternative subjects names (eg Ceramics, in place of Art and Design: 3D Studies), could you ensure that they use full course names on this sheet. Could you allow the pupils time to fill in each question before moving on to the next. SAY TO THEM: a) If you take a CDT subject tick the box or boxes for any you do. b) In the space at b. write a list of all the other subjects you do at school.  d) If you have any out of school interests that you feel have helped, put these in the space at d.^Again, explain how they have helped. e) Are there any subjects that you did in earlier years and now no longer study, but which you think have helped? Put these in the space at e. and explain how they have helped you today.  3.^When they have all^finished, collect in the data sheets and pupil booklets in two separate piles. We are very grateful to you for running this activity,^and^to^your^pupils for their cooperation in taking part.^Please accept our thanks and extend them to the pupils involved.  

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