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Sex differences in mathematics in Scotland Kerr, Peter 1988

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SEX DIFFERENCES IN MATHEMATICS IN SCOTLAND by PETER  A THESIS S U B M I T T E D THE  KERR  IN P A R T I A L  REQUIREMENTS FOR MASTER  OF  FULFILMENT OF  T H E DEGREE OF ARTS  in THE  F A C U L T Y OF GRADUATE  Department  of Mathematics  and Science Education  We accept this thesis as to the required  THE  STUDIES  conforming  standard  U N I V E R S I T Y O F BRITISH 21 December  1988  ® Peter Kerr,  1988  COLUMBIA  In  presenting this  degree at the  thesis  in  University of  partial  fulfilment  of  of  department  this thesis for or  by  his  or  requirements  British Columbia, I agree that the  freely available for reference and study. I further copying  the  representatives.  an advanced  Library shall make  it  agree that permission for extensive  scholarly purposes may be her  for  It  is  granted  by the  understood  that  head of copying  my or  publication of this thesis for financial gain shall not be allowed without my written permission.  Department  of  l/VdXfo^*^^'  The University of British Columbia Vancouver, Canada  DE-6 (2/88)  Jbom-vc^  €^<-<^^U^'  ABSTRACT  This study examines sex differences in mathematics in Scotland. The study is based on longitudinal data from the 1985 Scottish School Leavers Surve3 of r  5726 students in one school district. It compares the distribution of scores for boys and girls on the 1984 Ordinary Grade (O-grade) Arithmetic examination, taken by the majority of Scottish students at the end of compulsory schooling, and matches these results with indicators of male and female ability, socioeconomic status (SES), previous arithmetic achievement in primary school, and destinations upon completion of compulson' schooling.  The findings suggest that boys slightly outperformed girls on the O-grade Arithmetic examination. Girls were more likely to present for this examination, but more girls than boys scored at the lower end of the distribution. These differences did not vary substantially for pupils at different levels of ability, SES, or prior achievement in arithmetic. The gender gap in mathematics favoring boys, however, did become significant after the period of compulsory  schooling. More  girls than boys stayed on at school, but fewer of them elected to take further training in mathematics. Boys took more advanced  mathematics courses in the  last two years of high school and performed better than girls on those courses. Policy implications of these findings and directions for research are discussed. Teachers and counsellors must become informed about the lack of female persistence in mathematics and take steps to alleviate it. Future research should examine why  girls in Scotland do not keep up with boys and the factors that  have enabled some girls to overcome this general tendency.  ii  T A B L E OF  CONTENTS  Abstract  ii  Table of Contents  iii  List of Tables  iv  List of Figures  v  Chapter I. The Problem A. The Scottish Setting B. The Problem Situation, Strengths, and Perceived Need C. Purpose of the Study  1 3 8 11  Chapter II. Review of Literature 13 A. Sex Differences in Mathematics 14 1. Sex differences in mathematics enrolment 15 2. Sex differences on mathematics achievement test scores. 16 3. Problems in measurement of sex differences in mathematics 19 4. Sex differences in the distribution of mathematics achievement 22 5. Current trends in sex differences in mathematics 22 B. Causation: Why Sex Differences Exist 24 1. Cognitive, ability, or biological variables 25 2. Affective variables 32 3. Educational and other societal variables. 34 4. Socioeconomic status 38 5. Conclusions about causation 44 C. Post-secondary destinations 45 Chapter III. Methodology A. Design B. Achieved Sample C. Dependent Variables D. Independent or Control Variables E. Data Set Construction F. Analyses  52 52 55 57 59 61 62  Chapter IV. Results  64  Chapter V. Summary and Conclusions A. Principal findings B. Policy implications C. Directions for Research Appendix  80 83 85 89 93  References  94 iii  LIST  OF  TABLES  Table 1. Parameter estimates and standard errors for regression of O-grade Arithmetic on sex, SES, and a SES-by-sex interaction  71  Table 2. Parameter estimates and standard errors for the regression of O-grade Arithmetic results on sex, Primary 3 arithmetic (P3ARIT), and a P3ARIT—by—sex interaction  72  Table 3. Parameter estimates and standard errors for the regression of O—grade Arithmetic results on sex, Primary 7 verbal reasoning (P7VRQ), and a P7VRQ-by-sex interaction  73  Table 4. Crosstabulations of O — grade Arithmetic results by destinations (Column percentages by sex)  77  Table 5. Highers Mathematics results in S5 and S6 by  iv  sex  post—compulsory 78  LIST  OF  FIGURES  Figure 1. Cumulative frequency distribution, O—grade Arithmetic scores  65  Figure 2. Cumulative frequency  distribution, P3 Arithmetic scores.  68  Figure 3. Cumulative frequency  distribution, P7 verbal reasoning scores  69  v  C H A P T E R I. T H E  PROBLEM  Research on sex differences in mathematics is a complex, fascinating field. Fennema and Petersen (1986), two leading writers in this area, admit that the more they study and analyze the problem of sex differences in mathematics, the more complex the problem becomes. As academic, government, and public awareness of the existence of these differences and their negative consequences for women has grown over the last two decades, so has the quantity and quality of research in this area. More powerful studies, many of national and international scope, with better databases and improved, more specific lines of inquiry have been completed. These improvements have helped researchers define the location and the extent of sex differences in mathematics with greater accuracy.  National and international studies conducted during the past decade have indicated that sex differences in mathematics still tend to favor males, but that the size of these differences and the age of subjects involved are smaller and more restricted in scope, respectively, than was previously believed. For instance, boys tend to take more elective mathematics courses than girls in the U.S. (NAEP, 1983), especially at advanced levels, but the difference is not great and has been declining. (Chip'man & Thomas, 1985). On tests of mathematics achievement, sex differences usually favor boys but performance gaps are not universally present at any age or grade level, never very large, and not regularly observable prior to Grade 10 (Fennema, 1984). In the last decade or  1  The Problem / 2 so, research has indicated a reduction in the size of the gap between boys' and girls' mathematics performance in the U.S. (Levine & Ornstein, 1983) and the U.K. (Marriott, 1986; Willms & Kerr, 1987) compared with the results of earlier studies.  Although the quantity and quality of research on sex differences in mathematics have both increased significantly over the last 10 or 15 years, there remain important areas of research where gaps of information exist or where valuable extensions to current research could be undertaken. If a nation's educational system is inconsistent in terms of instruction, curriculum, or evaluation across geographical boundaries, results of national research may not be readily generalizable. This problem affects research from the U.S., the main source of information on sex differences in mathematics. Because the onset of puberty is now acknowledged to be the approximate starting point for predictable sex differences in mathematics (Fennema, 1984), studies that examine only younger students are poorly targeted. Few studies have provided important background information on prior student achievement or ability (Ethington & Wolfle, 1984) or socioeconemic  status (Stanic & Reyes, 1986). Previous research  also has failed to examine adequately the distribution of sex differences across various levels of ability, previous achievement, or famity background. Finally, few studies have been able to tie sex differences in high school mathematics to subsequent student academic and occupational movement.  The  present study addresses some of the areas in the literature where  gaps exist or where extensions of current knowledge could be made. The study  The Problem / 3 outlines the distribution of achievement of boys and girls on the national government examination  in arithmetic, administered at the end of the fourth year  of secondarj' school in Scotland, the final year of compulsory schooling for most Scottish students. Sex differences are estimated across various levels of socioeconomic  background, ability, and early arithmetic achievement. The  also examine the relation between fourth year arithmetic examination the performance in higher level mathematics for those who  analyses  results and  stayed beyond the  minimun leaving age, or occupational directions for those who  left school after  S4. To avoid confusion, the author uses the term "sex differences" instead of "gender differences" throughout this study, although "gender" is often used in the literature and is appropriate in a context describing the social, cultural, or psychological aspects of male and female behavior.  The remainder of this chapter provides information about the problem setting: important characteristics of the Scottish educational system, including some pertinent historical developments. The problem situation is then explained, including the current status of sex differences outlined in the literature. Next the importance of this study and its perceived strengths are outlined and finalty, after the setting, background, and motivation for the study are in place, the formal statement of the problem concludes the chapter.  A. THE  SCOTTISH SETTING  The present study examines sex differences in mathematics achievement in the secondary schools of one of Scotland's educational authorities or school  The Problem / 4 districts. Scottish schools are administered by a total of nine mainland and three island Education Authorities. Appendix A describes the area examined by the present study.  Several important historical changes have influenced the development of the modern Scottish system of education and bear upon this study. Prior to the Scottish secondary program was  1962  designed around the norm of a five-year  course for most students. In the Fifth year, usually at age 17, students could sit either Lowers or Highers examinations (or some combination of the two) in a variety of subjects. The Highers examinations were the main qualification for entrance to higher education in Scotland. About half the fifth year students would then stay on for a sixth year to attempt more Highers or to re-sit old ones (Raffe, 1984a). However, the minimum school-leaving age prior to 1973  was  onty 15, so many students did not feel compelled to staj' until the fifth year and left without any official certification.  In  1962, in response to official worries about substantial early leaving  from the five-year academic high school course, Scotland introduced the Scottish Certificate of Education (SCE) Ordinary Grade (or O-grade) examinations for sixteen-year olds in academic programmes, at the end of their S4 year (Scottish Education Department, 1959). Pupils may fourth, fifth, or sixth years. They may  now  leave school at the end of their  take O-grade examinations in any of  these years and Highers examinations in their fifth and sixth years.  Students deemed capable may  sit O-grades in a selection of 48 different  The Problem / 5 subjects. English and mathematics ("arithmetic") are two core subjects taken by virtually all students! and about 80% of all students sit an O-grade examination in these two subjects. Highers examinations still retain their essential characteristic as the main qualification for higher education, undertaken voluntarily by students after completion of their compulsory years of schooling.  The second significant change occured in 1965. At that time the Scottish Education Department began to reorganize its secondary education system along comprehensive lines, by abolishing selective transfer to secondary school (Scottish Education Department, 1965). Previously, pupils had been streamed into separate schools according to their abilities and interests directly after primary school. Comprehensive reorganization meant that all schools were now  designed to serve  the needs of all pupils in a designated catchment area. Although catchment areas differed in socioeconomic makeup, and therefore provided differing populations of students for their local schools, comprehensive reorganization did open all secondary schools to a broader range of students (Willms, 1986). By the late 1970's, after comprehensive reorganization, the Scottish secondary system consisted of 470 secondary schools and virtually all pupils (95%) were being admitted to programmes with comprehensive intakes (McPherson and Willms, 1987).  Another important change was  the raising of the minimum school leaving  age to 16 in 1973. This meant that Scottish students, who  enter secondary  t"Arithmetic" and "Mathematics" are two separate O-level examinations offered by the Scottish Education Department. Mathematics is a more difficult examination aimed at a minority of very capable students. The Arithmetic O-grade examination, taken by the majority of students, is the main measure of achievement employed in this study.  The Problem / 6 school at age 12, would end their compulsory  education at or around the end of  fourth year. Finally, while enrolment in Scottish education authority secondary schools is declining, from a plateau of some 410,000 in 1978  and  1979 to a  projected trough of approximately 290,000 in 1991, youth unemployment has risen sharpty since 1979. This shift in employment patterns may  mitigate against  the effects of falling enrolment b3' motivating students to stay in school, but it also creates new  problems for schools. Students now  deciding to stay on past  fourth year are often non-academic pupils demanding a level of programming which has not previously been available in the post-compulsory  courses of most  Scottish schools (Burnhill, 1984).  One  of the net effects of the changes cited above has been a shift in the  role of the O-grade examination. The original intention had been that 30% of the 16-year age group should have a reasonable chance of passing the examination in three or more subjects. By  1976, with more students staying on past fourth  year and with most students enrolling original^ in comprehensive programmes, some 80% of the age group were attempting at least one O-grade examination and the O-grade had come to. be regarded as the end-of-compulsory-schooling certificate (Gray, McPherson, & and in 1973  Raffe, 1983). As a result, pass rates declined,  the original pass/fail distinction was  replaced by 5 bands, A to E,  with the A, B, C bands corresponding to the original pass grade. About half of the pupils taking O-grades remain in school for a fifth or sixth year, during which time the majority take SCE (Gray et al. 1983)  "Higher-grade examinations," or "Highers"  The Problem / 7 Beyond the Sex Discrimination Act of 1975, Section 22, which legally protects women's rights to equal access to education, there is little to be found in government policy or legislation in response to the issue of sex differences in education in general, or in mathematics in particular. For instance, the main goal of comprehensive reorganization was not to reduce sex inequality — class inequality being one more obvious target (McPherson & Willms, 1987). However, a report by Her Majesty's Inspectors of Schools (Scottish Education Department, 1975) stated: the process of secondary reorganization along comprehensive lines, frequently with mixed ability grouping — almost invariably coeducational — at the early stages of secondary education ha[d] encouraged reappraisal of the curricular arrangements (p. 37). It is easier normally for coeducational comprehensive schools to minimize differences in the provision for boys and girls, (p. 39)  Studies have shown that these changes in the organization of the Scottish school system were indeed accompanied by a general trend towards increased female educational achievement (Scottish Education Department, 1986) and participation in higher education (Burnhill & McPherson, 1984). Burnhill and McPherson showed that, in the earty 1980's, academically capable female students finished secondary school with occupational ambitions that surpassed their female counterparts in the early 1970's, and now more closely resembled those of male students. Both men and women also were more likely to view higher female ambitions as appropriate. Again, these changes seem to have been part of wider social changes and not the result of any major educational reform designed to  The Problem / 8 reduce sex differences.  B. THE  P R O B L E M SITUATION, STRENGTHS, AND  PERCEIVED NEED  This study covers a ten-year period. The data set provides information on a sample of 5726 students, most of whom were born in 1968, as they moved through primary and secondary school. The sample comprises nearly all (97%) the students in this age category in one Scottish school district. Examination results are described for a test of early arithmetic achievement at the Primary 3 (P3) level, a test of verbal reasoning ability at Primary 7 (P7), achievement in arithmetic at Secondary  4 (S4), and achievement in mathematics by students  continued beyond the age of compulsory  who  schooling to their fifth or sixth years of  secondary education. Also incorporated in the analyses is survey questionnaire information supplied by the students on such factors as family background and choices of direction once they had passed the minimal school-leaving age.  This study is strengthened by the consistent nature of the Scottish educational system across geographical boundaries, and the  comprehensive,  longitudinal nature of the data available. For instance, the O-grade data, the main achievement indicator and focus of this study, have some advantages over data describing pupil achievement in the U.S., such as the National Assessment of Educational Progress (NAEP) or the High School and Beyond (HSB) data. O-grade examinations, as described above, are national certificate examinations and success on these examinations is one of the major goals for students of secondary school programmes since the institution of comprehensive reorganization.  The Problem / 9 Because of the diversity of goals and curricula in U.S. high schools, the NAEP and HSB  achievement tests include some items that are insensitive to instruction  (Willms, 1985). The Scottish tests, however, are more likely to reflect school-related achievement uniformly across all schools of the district, and those scores will be comparable to those of students across the entire country. Also, the Scottish system has fewer transition points where students may  "leak out" of  the study of mathematics. In a typical U.S. high school, mathematics instruction beyond Grade 8 (age 13) progresses in a sequence of courses with options for withdrawal along the way:  Algebra I, Geometry, Algebra II, Trigonometry,  Pre-Calculus, and Calculus (Lee &  Ware, 1986). In Scotland, English and  arithmetic are considered core subjects for all students deemed capable until the end of S4. Thus the first major transition point in Scottish school mathematics occurs upon completion of the fourth year examinations  and with the subsequent  decision whether to continue study in the fifth year. The uniformity of Scottish system provides an advantage in the present study.  Fraser and Cormack (1987a) feel that this uniformity is reflected in other ways as well, in comparisons within the United Kingdom. In Scotland, mathematics at the "Highers" level (S5 and S6) can be taken along with several other subjects, but in England  and Wales students are restricted to only three  "A"-level subjects after O-Grades and this leaves no room for mathematics on the schedules of any but the most specialized students. Thus the lack of intense pressure to specialize at an early age (roughly 14 for English students)  may  encourage more Scottish girls to continue with mathematics. Fraser and Cormack note that almost 50% of recent mathematics graduates at Edinburgh University  The Problem / 10 were female, compared to the national average of 30%.  While these phenomena of uniformity and female persistence in mathematics in Scotland might engender a hypothesis of no sex differences in secondary mathematics achievement, there is little empirical evidence to support or disprove this claim. Almost no work has been done on sex differences in Scottish primary and secondary school mathematics or on longitudinal analysis of Scottish boys' and girls' progress in mathematics. In 1983 Achievement Programme (AAP)  the Assessment of  carried out a survey of P4, P7  and S2 students  and concluded that "at all three stages boys and girls performed equallj' well" (Assessment of Achievement Programme, 1983). Although  there were no further  details given, the Times Educational Supplement (1986) reported that these results "...showed once again that Scotland does not have the problem in this area experienced south of the border." It is generally acknowledged that boys often do better than girls at mathematics in secondary school (see Chapter 2). Could Scotland be an exception to this pattern? The present study provides much needed information on this situation.  Another area where previous research is inadequate  is the consideration of  family background along with mathematics achievement. Grant and Sleeter (1986) published a review of studies incorporating the variables of race, sex and socioeconomic  status (SES) in educational research. They concluded from their  review of 71 studies that few of the investigators had integrated the three factors in their designs and analyses. They argued that this lack of integration of race, sex, and SES  oversimplifies the analysis of student behavior in school  The Problem / 11 and could perpetuate biases. Such research provides too narrow a focus, treating individuals as if they were members of just one group, and ignores the joint contribution of each of the factors. Similar^, Stanic and Reyes (1986) concluded that, "there has been no definitive study of SES as it relates to mathematics achievement" (pp. 4-5). The present study incorporates data on student family SES  into the analysis of sex differences in mathematics.  Abilit3' and its effect on mathematics achievement continues to be a controversial issue (see Chapter 2). Ethington and Wolfle (1984) stated that the analysis of the interaction between sex and other important variables in the process of mathematics achievement is complex, and that questions about male-female differences in mathematics achievement "may have no meaning unless one asks the question in relation to specific values of variables that measure prior ability and educational experience" (p. 375). This studj provides some r  measure of prior ability.  C. PURPOSE OF T H E STUDY  This study compares the achievement of boys and girls on the pivotal O-grade examination  in arithmetic, taken in the fourth year of secondary school,  for an entire Scottish school district in 1984. The first part of the stud3' examines SES, student achievement in arithmetic in P3, and student verbal reasoning ability in P7. The study considers the predictive value of each of these three measures on S4 O-grade Arithmetic achievement. The second part of the stud3' examines the relationship between these same O-grade results and the  The Problem / subsequent decision to leave school or stay beyond S4. The achievement of "stayers" on mathematics examinations in S5 and S6, and the various destinations of school leavers are related to previous achievement in O-grade Arithmetic.  C H A P T E R II. REVIEW OF L I T E R A T U R E  The research questions considered in this stud3' are: What are the size and distribution of sex differences in achievement on the O-grade Arithmetic examinations taken at the end of S4? How do these sex differences vary across levels of student ability and socioeconomic status? How are subsequent educational and employment destinations related to O-grade arithmetic performance? This chapter reviews important studies in the literature that relate to each of these research questions.  To begin, evidence from the literature on the size, age of occurrence, distribution, and changing patterns of sex differences in mathematics is presented. Then the literature on possible causes of these sex differences is reviewed. Although this study is designed to address the research questions above in a descriptive fashion, and is not intended to test any of the various theories about the causes of sex differences in mathematics, it may, with its information on student ability and family background, provide valuable information for later investigations of causation. This review of literature therefore includes a summary of research into the possible causes of sex differences in mathematics with special attention to the areas of ability and family background. The review concludes with an examination of the literature on the relationship between sex differences in mathematics and post-secondary destinations. Throughout this chapter, historical trends in research, when apparent, are indicated.  13  Review of Literature / 14  A. SEX D I F F E R E N C E S IN  MATHEMATICS  To survej' the literature on the size and age of occurence of sex differences in mathematics, it is important to distinguish between mathematics achievement and mathematics attainment or enrolment. This is often overlooked in the way  articles are presented in the literature. Erickson, Erickson, and Haggerty  (1980) felt that enrolment in school mathematics courses should be considered a form of achievement in mathematics, along with scores on tests. Although this study does not combine these two measures in this way, their mutual importance in the assessment of performance in mathematics is considered essential. While enrolment might be considered a less direct measure, it does indicate the level of school qualification achieved and these qualifications directly influence future student options. Also, course taking and achievement on mathematics achievement tests appear to be directly related.  Thus enrolment is a valid indicator of performance and receives consideration along with achievement in this review. Enrolment and achievement on tests comprise the first two parts of this five-part section. The third part examines problems and difficulties which may  occur in large studies and in  meta-analyses of research on sex differences in mathematics. The fourth part outlines research evidence on sex differences in the distribution of mathematics achievement, and the last part summarizes the current discernible directions or trends in sex differences in mathematics indicated in the literature.  Review of Literature / 15 1. Sex differences in mathematics enrolment.  Boys tend to take more elective mathematics courses in high school than girls and this proportion is greater for more advanced courses. The British Columbia Mathematics Assessment of 1977 (Robitaille & Sherrill, 1977) reported that 64 percent of Grade 12 students with no mathematics beyond Grade 10 were female, and that only 43 percent of Grade 12 mathematics students were female. Similar results have been reported in the U.S. (Fennema & Sherman, 1977, 1978; Armstrong, 1980; Lee & Ware, 1986; Leder, 1986) and internationally (Husen, 1967). The third NAEP report in mathematics (NAEP, 1983) showed the male-female course differential in the U.S. was not large at any time, but that the male advantage was largest in the advanced courses. Girls showed a consistent improvement in relative enrolment figures from 1978 to 1982 across courses. In the U.K., figures for 1984-85 for England and Wales show female enrolment still lagging considerabty behind in mathematics, chemistry, physics, and computer science for both O-level and A-level entries (Department of Education and Science, 1985). A comparison of England and Wales with Scotland (Fraser & Cormack, 1987b) shows that Scottish girls are enrolling for more mathematics than their English and Welsh counterparts, but are still not equivalent to boys in this respect.  In  general, the enrolment gap in secondary mathematics between boys and  girls in developed countries seems to be decreasing. Armstrong (1980) found only slight differences in participation. Chipman and Thomas (1985), in a recent review, reported that the difference is no longer as great as earlier research had  Review of Literature / 16 reported. Lee and Ware (1986) make the valuable point that overall lack of persistence in mathematics, regardless of sex, is considerable (p. 13) and this helps underscore the fact that, although some differences in enrolment may  still  exist, there is considerable overlap in enrolment patterns between the two  sex  groups.  2. Sex differences on mathematics achievement test scores.  The basic pattern to be noticed in the literature on test results is a narrowing or tightening of the size and age of occurrence of regularly observed sex differences. Fennema (1974) was  one of the first to question the accepted  view that male superiorhVy in mathematics achievement was  prevalent throughout  the school years, from kindergarten to high school leaving (e.g., Glennon  &  Callahan, 1968). Subsequent research supported this narrower definition of the usual age and grade levels where sex differences in mathematics tend to occur. Large-scale studies and reviews in the early 1970's concluded that sex differences in young children's mathematics achievement were inconsistent, but that male superiority became evident by upper elementary or junior high school and continued to grow (Maccoby &  Jacklin, 1974; Hilton &  Berglund, 1974). Also,  males were found to be superior in "higher-level", cognitive mathematics areas requiring understanding  and application (usually equated with "problem solving").  Fennema again sharpened perceptions (1977, 1978) when she pointed out that many of these large scale studies, such as the 1972-73 NAEP National Mathematics Assessment or the first mathematics study conducted by the  Review of Literature / 17 International Association for the Evaluation of Educational Achievement  (IEA)  (Husen, 1967), failed to control for history of courses taken. Because males often have studied more mathematics than females, the studies compared males and females with unequal mathematics backgrounds. Between 1974 this discrepancy in attainment was  and  1978,  when  taken into consideration, a number of studies  showed differences in achievement to be less than previously indicated. For example, Fennema and Sherman (1977, 1978) sometimes nonexistent when coursework was  found differences were small  and  controlled. Schonberger (1978)  observed male superiority in problem solving to be limited to the high ability range of students and  only to certain problem types, and  differences being eliminated when coursework was conclude that differential coursework was achievement differences and  Wise (1978) noted  held constant. This led some to  the major cause of sex-related  Fennema (1980) stated, "this author believes strongly  that if the amount of time spent learning mathematics were somehow equated for females and males, educationally significant sex-related differences in mathematics performance would disappear" (p. 82).  However, subsequent studies showed differences persisting even when controls were instituted for previous courses taken. Armstrong (1980) analyzed data from two  large U.S.  1977-78 (NAEP, 1978,  national studies, including the second NAEP in  1979)  and concluded that 13-year-old girls enter high  school mathematics on at least an equal footing with males in terms of ability and  grades but that by the end of high school males consistently outperformed  females, especially on higher level cognitive items. The  second international study  by the IEA, of 24 countries in 1981-82, supported these findings (Crosswhite,  Review of Literature / 18 Dossey, Swafford, McKnight &  Cooney, 1985; see also NAEP, 1983).  In light of these and other studies, Fennema (1984) partially rejected her earlier hypothesis that achievement differences might be eliminated if coursework were equalized. This, then, is the current state of affairs: consistent achievement differences favouring boys are not expected to emerge prior to Grade 10, are typically not very large, and are not found universally even in advanced high school years. Girls often excel in lower cognitive level, computational tasks, and boys on higher-order tasks.  The situation in the U.K.  fits this general pattern of differences in  achievement in mathematics. Shuard Performance  (1986) anatyzed the Assessment of  Unit (APU) data for all of England and Wales, 1980-82, and found  that 11-year-old girls performed better than boys in just one category: "computation: whole numbers and decimals." Boys, in contrast, did better in the categories of concepts with whole numbers, decimals, and fractions, and in applications with numbers, measurement, and geometr3'. Similarly, the Schools' Council Project (Ward, 1979) gives a number of examples of questions which call for understanding of number, where boys do better than girls. Computational questions, where girls had an advantage, were of about the same difficulty but could be done by rule alone (Shuard, 1986). Later work in mathematics, of course, builds on understanding, not on memorization of rules.  In an important series of studies with results that differed from the generall} small sex differences in mathematics found in the literature, Benbow 7  Review of Literature / 19 and  Stanley (1980, 1983)  of Grade 7 and advantage was  found boys exceeded girls, in a highly-gifted population  8 students, on the SAT-M examinations, and that the male quite large at the higher levels of SAT-M scores.  3. Problems in measurement of sex differences in mathematics.  Some of the potential problems that may  interfere with the measurement  of sex differences in mathematics have been indicated. Selection bias should be avoided: if males are more likely to drop out of school, then high school studies may  be comparing a more heterogeneous group of females with a more  homogeneous, intellectually-motivated group of males. Also, if males who  remain  in school are likely to take more advanced mathematics courses than females, another form of selection bias is introduced if course-taking experience is not controlled for in analyses of test results describing third or fourth year performance (Fennema &  Sherman, 1977). Not controlling for courses taken  a problem in national studies in the U.S.  prior to 1974.  usually controlled for course-taking but the problem may  was  Since then studies have still exist in a subtler  form: course titles at the secondary level are a questionnable indicator of content studied. Detailed definitions of courses and more surveys and research on what is actually taught, and how,  are needed (Raizen, 1986); for example, some studies  show boys often receive more hours of formal instruction time than girls (Eccles &  Jacobs, 1986). In Scotland, because all students are required to take  arithmetic through their compulsory years of schooling, and because the same O-grade examination, Arithmetic, is a point of destination for a majority of students across the countrj', the consistent nature of the educational system  Review of Literature / 20 overcomes these problems of course-taking and instruction.  Another area of difficultj^ in the literature is student family background or SES. Data have been collected in the vast majority of studies from white, middle-class North Americans, and very little cross-cultural data or even upper or lower-class data are available for comparison (Jacklin, 1979). Cross-cultural data would provide information about whether different types of family socialization affect male and female learning of mathematics differently and thereby help to support or disprove environmental  theories of causation of sex differences in  mathematics. The present study anatyzes data on student achievement across all socioeconomic  levels in one school district.  Often large-scale studies (meta-analyses and national or international studies), because of their large sample sizes, may find differences which are statistically significant but of questionable practical or substantive significance t (Willms, 1987). Also, the use of mean scores ma3 mask important differences r  between males and females in the distributions of their mathematics scores. This study, which employs a nationally standardized metric, and describes the cumulative distributions of male and female scores, is able to consider the substantive importance of observed differences as well their distributional qualities.  Meta-analyses may suffer from other problems as well. Maccob3 and r  tFeminists such as Bleier (1984) would go further to suggest that "by their very methods of reporting trivial differences in the mean scores of large groups or populations of boys and girls as sex differences [so-called 'scientific'] disciplines helped, along with other cultural forces, to create the entit3' (gender differences) that they claim to explain and measure scientifically" (pp. 108-109).  Review of Literature / 21 Jacklin (1974) published a review of some 1600 studies on sex differences, mostly from 1966 to 1973. Their review was  a significant contribution to the  literature and is one of the most cited of such reviews to this day. In their massive work are examples of some of the shortcomings of research on sex differences (Block, 1976). More than one third of the documented comparisons between the sexes were based on samples of 60 or less, and about one fifth involved 40 or less. The conceptual quality of psychological measures used often was  ignored, evaluations were based predominantly on studies of younger children  (75% on 12-year olds or younger, 40% on preschool) even though sex differences in mathematics are known to begin primarily in adolescence, and categories for grouping studies were inconsistently defined - sometimes conceptually disparate studies were combined. Finally, more flaws in documentation were found in the review than are acceptable in a reference volume (Block, 1976).  Age is a potentially confounding factor in a different sense. Puberty, the time when sex differences in mathematics most reliably appear, is also likely to be a critical time for intensification of socialization effects and thus for differences between the sexes. Also, there are differences in the physical maturation rates of males and females (Tanner, 1962). Therefore comparing males and females on tests at the same age may developmental ages may  be inappropriate because  be different. More information is needed about  maturation rates of behavioral characteristics (Wittig & Petersen, 1979). These problems are a limitation of the present study as well.  Review of Literature / 22 4. Sex differences in the distribution of mathematics achievement.  Two more important features of sex-related differences in achievement should be mentioned. First, with regard to differences in the distribution of test scores, boys appear to be more variable than girls; that is, they score more frequently at both ends of the spectrum. Male domination at the higher end of the distribution is widely acknowledged (Fox, Brody & Tobin, 1980; Benbow & Stanley, 1980), but their position at the low end is often overlooked. For example, in special programmes for pupils with learning disabilities, mild mental handicaps, or other educational disadvantages, boys typically outnumber girls by at least seven to one (Bentzen, 1966). Studies.such as those completed by Benbow and Stanley, which fail to consider the entire distribution of students across all levels of ability (or SES), are obviously limited in their application to more general populations. This study looks at the whole distribution of students.  5. Current trends in sex differences in mathematics.  The final feature to note in this section is that the achievement and attainment gaps in mathematics appear to be diminishing. In the U.K. for example, there has been a steady improvement in girls' performance in mathematics at both 'O' (Grade 10) and 'A' (Grade 12) levels (Marriott, 1986; Willms & Kerr, 1987). Levine and Ornstein (1983) noted similar trends in the NAEP reports between 1973 and 1978.  Stockard and Wood (1984) found that boys were generally underachieving  Review of Literature / 23 (receiving lower grades for equal abilitj') more often than girls in high school, although this difference was  much smaller for mathematics than for English or  total grades. They labelled female underachievement a myth, asserted that school grades appeared to be an appropriate place for females to exercise their valuing of achievement, and claimed that the focus for intervention and remediation might well shift to the poor transfer of achievement to occupational attainment.  Similarly, Walden and Walkerdine (1985) examined the classroom performance  of girls in mathematics in the U.K.  common belief, girls' performance  and found that, contrary to  did not decline as they progressed through  school. Walden and Walkerdine also found that there was  not a large difference  in examination performance between boys and girls but that the girls' success often came to be seen as failure in the classroom because of widely-held ideas about what constitutes "proper" learning, coupled with traditional notions of masculinity and femininity. Often pupils' actual attainments were not seen as reliable or simple indicators of success. According to Walden and  Walkerdine,  teachers want to encourage "real understanding," so they watch for and promote those characteristics which they consider to be related to this — confidence, flexibility, risk-taking, and rule-breaking. Because these behaviours are usually found more often in males, females who  have actually done well on examinations  are less likely to be stretched and challenged by their teachers and also less likely to be entered for O-level examinations (Walden & Walkerdine, 1985).  The changing role of women in society, the feminist movement, and the increased quantity and quality of research available to identify differences, their  Review of Literature / 24 causes and possible solutions all help to explain the reduction of the enrolment and achievement differentials between the sexes. Also relevant are new  legislation  and school programmes, instructional material and curricula adjusted to eliminate sexual bias, and new  programmes for intervention and prevention, including  in-service to help raise school staff and student awareness.  B. CAUSATION: WHY  SEX  DIFFERENCES EXIST  School mathematics involves the acquisition of mathematical knowledge and the attitudes, expectations, beliefs and values of students, peers, parents, and educators toward males and females as learners of mathematics. All these areas are intertwined and virtually inseparable so that it is basicalty impossible at present to study the totality of the causation of sex-related differences in mathematics. One  can, however, select important variables and look at their  developmental interrelationships and effects (Fennema, 1984). One  interpretation is  hopeful: since there are few clear cut indicators of cause and effect, there appears to be no major barrier to equit}' in mathematics education. Differentiation in learning appears largely dependent on the social environment and this can be changed. Research on causation is examined here in four categories: cognitive, ability, or biological variables; affective variables; educational and other societal variables; and socioeconomic  status, followed by a section of conclusions.  Review of Literature / 25 1. Cognitive, ability, or biological variables.  The chief distinction in the intellectual prowess of the two sexes is shown by man's attaining to a higher eminence, in whatever he takes up, than can women — whether requiring deep thought, reason, or imagination, or merely the use of the senses and hands. If two lists were made of the most eminent men and women in poetry, painting, history, science, and philosophy, with half-a-dozen names under each subject, the two lists would not bear comparison. We may also infer...that if men are capable of a decided preeminence over women in many subjects, the average of mental power in man must be above that in women... (Darwin, 1871, pp. 873-874)  With such sweeping condemnations, men of the last century relegated women to a situation of double jeopardy: they were tried twice for the offence of being female — once at birth when they were assigned to a life of mental ineptness and again at death when the lives thus lived were judged inadequate. Scientists of that era created such disciplines as craniology to support the theory of inherent physical differences between the sexes. Women were found to have "a head almost too small for intellect but just big enough for love" (Meigs, 1847). Later this obviously flawed discipline disappeared as a serious scientific field, replaced by the measurement of mental abilities through IQ testing or by other measures of physiological differences, and the scientific case for inherent or genetic differences between the sexes came under increasing scrutiny and attack.  Review of Literature / 26 Today it is generally acknowledged that sex differences in general academic ability or intelligence are non-existent or inconsequential  (Stockard,  1980). In fact, although females tend to excel in general verbal ability (Macc'oby &  Jacklin, 1974), average differences are actually quite small and by high school  males are approximately equal on the verbal skills needed for mathematics learning (Fennema, 1984). The  current study provides a measure of "verbal  reasoning ability" which will permit a re-examination of these conclusions with a population of Scottish high school students.  Sex differences in a subset of spatial ability, spatial visualization, are often associated with sex differences in mathematics (Maccoby &  Jacklin, 1974),  but here again recent research indicates a modification of an earlier viewpoint. Spatial visualization involves the visual imagery of three-dimensional two-dimensional representations of three-dimensional  objects, or  objects, and the mental  manipulation of these objects. In mathematical terms, it requires objects to be rotated, reflected or translated. One  popular test used to measure this ability is  the Space Relations sub-test of the Differential Aptitude Test (Connor & 1980;  Serbin,  Wattanawaha, 1977). Maccoby and Jacklin (1974) and Harris (1978)  described consistent and increasing mean differences in spatial visualization in favour of males, beginning at adolescence. However, in the Fennema and Sherman studies (1977, 1978)  few sex-related differences in spatial visualization  were found and the data did not support the theory that these differences explain sex differences in achievement, although the two  were highly correlated  (see also Fennema, 1983). Armstrong (1980) found no sex differences in spatial ability for Grade 12; among 13-year-olds, females actually did better on the  Review of Literature / 27 spatial tasks. Thus, at the very least, a broad causal relationship between mathematics achievement and spatial ability is not indicated. In fact spatial visualization may be a .by-product of mathematics learning and perhaps, as enrolments equalize, any existing sex differences in spatial visualization will be reduced. Research has not yet indicated whether teaching spatial visualization directly improves mathematical performance (Jacklin, 1979).  Although neither general intelligence nor spatial ability appear central to an explanation of sex-related differences in mathematics, this by no means has meant the end of efforts to establish the existence of an inherent biological aspect of these differences. Benbow and Benbow (1984) examined data on about 65 000 highly-gifted Grade 7 and 8 students. These students took the College Board Scholastic Aptitude Test — mathematics section (SAT-M), a test designed for above-average 12th graders. Boys outscored girls on these tests, especially in the higher range of scores; for example, there were 14 times as many boys as girls who scored above 660. t Because course-taking differences were not a factor for this sample (the school years of elective mathematics courses were still in the future for these students) and high school mathematics experience was minimal, a biological component to male superiority in "mathematics reasoning ability" was hypothesized. These studies caused a sensation in the U.S. media at the time: Benbow was quoted as saying that many women "can't bring themselves to accept sexual differences in aptitude. But the difference in math is -  a fact. The best way to help girls is accept it and go from there" ("Gender factor", 1980) Newsweek  of the same date asked in its story headline, "Do Males  IThe mean and standard deviation for the SAT-M examination 475 and 110, respectively (Waters, 1981).  are approximately  Review of Literature / 28 Have a Math Gene?" ("Do  males", 1980).  Pallas and Alexander (1983) represent critics of these studies. They point out first that the sample was  limited to very able and motivated students and  results might not be generalizable; other studies are cited with more regular cohorts that do not show achievement differences at such an early age. Also, it would have been preferable to test the effect of course background directly with students who  differed on that variable, otherwise its effect remains uncertain.  Furthermore, differential coursework is not the only possible "environmental" explanation of sex-related mathematics differences (see below), and  even equivalent  course work (everyone had completed Grade 6) does not necessarily indicate equivalent mathematical experience. Eccles and Jacobs (1986) cited studies that showed that boys often receive more hours of formal instruction than do girls in primary mathematics classes and also may mathematically-related  have more informal  experiences outside the classroom (p. 369).  Benbow and Benbow (1984) based their hypothesis for a biological difference in mathematical reasoning ability between the sexes on acceptance of a biological base for sex-related differences in spatial abilities. They assume that spatial ability may that the two  positively influence mathematical reasoning ability, or at least  mental abilities 'may  involve similar cognitive processes, and that  sex differences in spatial ability and their biological explanations  also will apply  to mathematical reasoning. As reported earlier, sex differences in spatial ability is not as clear-cut an issue as was  formerly believed. Also the biological aspect of  spatial differences which do exist has not been proven (Keating, 1976;  Serbin,  Review of Literature / 29 1980, 1983) and the proposed link between spatial and mathematical reasoning abilities is still just an hypothesis.  Large SAT-M sex differences favouring boys are not unique to populations of the highly-gifted. For example, Lee and Ware (1986) looked at the 1982 HSB data on 8321 high school graduates with at least one academic course in mathematics. They found girls had higher overall GPA's and higher grades in mathematics, but lagged behind boys on the SAT-M by an average of 45 points and they were at a loss to explain the contradictory results. Benbow and Stanley's assumption (1980, 1983) that the SAT-M measures mathematical aptitude belies girls' in-class performances. Jackson (1980) asserts that the SAT-M instead measures acquired intellectual skills and is only described as an aptitude test "because, unlike a traditional achievement test, it is not tied to a particular course of study, and because it is designed to assist in predicting future academic performance" (p. 383). Similarly Schafer and Gray (1981) quote a member of the Educational Testing Service (producers of the SAT tests) to the effect that "the developers of the SAT do not view it as a measure of fixed capacities" but instead, "the test is intended to measure aspects of developed ability." Chipman of the National Institute of Education wrote (1981) that the mathematics SAT samples "performance in a domain of learned knowledge and skill...In a fundamental sense, we do not yet know what mathematical ability is...". Kifer (1986), in looking at the Second International Mathematics Stud}', concurred, questioning the existence of mathematical ability and applauding the Japanese teachers who, unlike their North American counterparts, do not blame poor student performance on lack of ability but on their own failure to motivate.  Review of Literature / 30 Sherman (1977) examined several suggested biological causes of mathematical ability sex differences, including hereditary differences linked to the X-chromosome, sex differences in serum uric acid, hormone differences, and difference in brain lateralization and cerebral organization. She concluded that only sex differences in brain lateralization had reasonable support. Petersen (1980) felt hormones might also prove important but research in both these areas is extremely difficult (Shepherd-Look, 1982; Bryden, 1979). For example, different metabolic forms of the same family of hormones — say estrogens or androgens —  have different behavioural effects as do different dosages or the timing of the  injections. Different species of laboratory animals or even particular strains within a species vary in their hormonal profiles and respond differently to hormonal manipulations. Because of these and other fundamental differences in the biological and behavioural responses among different species of laboratory animals it is difficult to extrapolate findings from rat to guinea pig or monkey and, certainly, to human. Then, of course, laboratory circumstances may not have relevance to natural environments where the influence of learning and environmental factors is unavoidable and inseparable from the basic biological mechanisms and structures.  Research on the differential rate of brain lateralization, or hemispheric specialization between the sexes has produced inconclusive results. One group of theorists (Levi-Agresti & Sperry, 1968) has maintained that man's superior spatial performance is the result of a stronger lateralization of brain functions while another group (Buffery & Gray, 1972) has argued that man's superior spatial ability stems from a lesser degree of specialization. (For reviews see  Review of Literature / 31 McGlone, 1980). There is also a general difficult}' with trying to connect sex differences in brain lateralization and sex differences in behaviour: the way skills are assumed to be divided between the two halves of the brain is not the same way that skills are divided between women and men. For example, the left half of the brain is thought to be more specialized for verbal skills, at which women are better, and for analytical and logical skills, at which men are widely held to be superior. The right hemisphere appears to be more specialized for spatial-visual abilities, a male-dominated area, and intuitive thinking, a trait usually assigned to women (Hubbard, Hanifin & Fried, 1982).  "Knowledge of basic biological mechanisms has less and less predictive value about the behaviours of animals the more complicated, flexible, and unpredictable  the animals' behaviours are and the more complex and  heterogeneous their environment and culture are"' (Bleier, 1984, p. 106). Most research and theory today does not favour a strictly biological explanation of cognitive differences (Shepherd-Look, 1982; Bryden, 1979). While sex-related differences in cognitive functioning may turn out to have some biological component (more research is needed), such influences would not limit any cognitive ability to one sex or another and would produce small differences at most (Jacklin, 1983). Social and psychological factors are now favoured in the literature as explanations 1985;  of sex differences in mathematics (Linn & Peterson,  Petersen, 1979; Fox, Tobin, & Brody, 1979).  Review of Literature / 32 2. Affective variables.  The  affective domain involves feelings, beliefs, and attitudes; it is  complicated, as the list of variables is long and the possible interactions are, in practical terms, limitless over time and age. Confidence in learning mathematics, for instance, is related to general self-esteem, causal attributions, and mathematics anxiety among other factors. Fennema and Sherman (1978) found that, in grades 6 through  11, males were consistently more confident than  females at equal achievement levels. For females this can lead to a cycle of failure, with reduced expectations and achievement following reduced effort. Wolleat, Pedro, Becker and Fennema (1980) found that females at all achievement levels more strongly attributed failure to lack of ability, and success to effort or circumstance. For males, the situation is reversed; that is, they tend to attribute success to ability and failure to lack of effort or circumstance. Thus females feel less in control of their mathematical learning and are less apt to persist. Confidence is more highly related to achievement than any other affective variable (Fennema, 1984). However much is unknown about the true effect of confidence or how  such feelings are developed.  The perceived usefulness of mathematics for future goal attainment also shows a significant positive correlation with mathematics achievement and attainment (Fennema &  Sherman, 1977,  1978; Meece, Parsons, Kaczala, Goff, &  Futterman, 1982) and high school girls generally tend to consider mathematics as less essential to their plans and possibilities than boys (Fox, 1977; Fennema Sherman, 1977,  &  1978). Fox (1977) also looked at students' general enjoyment of  Review of Literature / 33 mathematics. She found sex differences were small, with a low but significant correlation with achievement. Similarlj', as girls tend to enjoy mathematics less, they also rate it as more difficult than boys (Eccles-Parsons, Adler, Futterman, Goff, Kaczala, Meece, & Midgley, 1983). However the direction of causation for both enjoyment and perceived difficulty of mathematics remains uncertain; for example, students may  enjoy subjects in which they perform well or vice versa.  Another area where the relationship with achievement is not clearly understood  is sex-typing of mathematics. When mathematics is stereotyped it is  seen as a male achievement domain by both male and female students. Males, however, have this perception to a greater extent than females; females surprisingly do not regularly characterize participation or competence in mathematics as unfeminine (Eccles-Parsons, 1984) and mathematics perceived as a male domain might not be important as a predictor of later achievement (Meyer &  Fennema, 1986). A closely-related concept, perceived congruency between  engaging in mathematics and one's own  sex role can, on the other hand,  influence performance negatively for females (Fennema & girls may  Sherman, 1977). Thus  experience conflict between academic pursuit and popularity. In general  one should keep in mind that "sex role" is not a set of specific behaviours but a concept, the perceptions of which differ not only between persons but also within a person depending on situations and personal development. Value attached to mathematics is a function of both the perceived qualities of the task and  an  individual's needs, goals and self-perceptions. Past experiences, social stereotypes, and information from parents, teachers and peers all influence mathematical choices and performance.  Review of Literature / 34 3. Educational and  other societal variables.  While the entire social milieu influences how how  well one learns as well as  one feels about mathematics, the most important influences occur within the  classrooms where mathematics is taught. Learning environments for boys and girls within classrooms, while appearing to be the same, differ a great deal; the differences today are just more subtle than in the past. Fennema (1984) has stated categorically that the "causation of sex-related differences in mathematics rests within the schools" (p. 161).  Classroom experiences can contribute to sex differences in mathematics in two  wa3's: the differential treatment of boj'S and girls within class or the  differential impact of similar treatment. Often, instead of altering traditional sex stereotypes, schooling tends to reinforce the sex-role lessons of infancy and early childhood (Frazier &  Sadker, 1973). In theory most teachers believe education  should be a liberating and democratic influence (Skolnick, Langbort, &  Day,  1982), but in practise mathematics teachers are still seen to reinforce traditional behaviour and  occupational plans for both boys and girls independent of where  student interests or talents may  lie (Eccles &  Hoffman, 1984), and  at times  even to actively discourage nontraditional (mathematical) female interests (Fox, Brody, & Tobin, 1980). Mathematics teachers also tend to interact more with boys (Sadker &  Sadker, 1979). Boys receive more criticism for behaviour and  more praise for work and behaviour (Fennema, 1984). The  hidden curricular  message for boys reads, "if you would only behave yourself and try, you would succeed". Boys' behavior captures adult attention and implicitly protects the male  Review of Literature / 35 intellectual ego (Slolnick, Langbort, & Day,  1982). While boys are usually praised  for intellectual works, girls are mostly praised for behaving properly and rules of form, and criticized primarily for intellectual reasons. They  obejdng  learn they  are pleasing but not necessarily capable, and teacher praise for compliant behavior pressures girls to adhere to this role (Skolnick, Langbort, &  Day, 1982).  Positive interactions which build self-confidence and mathematics interest are especially favourable to boys among high ability students (Brophy, 1985). Differential treatment may inconclusive here. One  be due to differential expectations but the literature is  study found no differences in teacher expectations of  mathematics success (Parsons, Heller, Meece &  Kaczala, 1979) while others have  shown greater expectations for boys (Ernest, 1976; Levine, 1976). Higher expectations for males result in teachers helping girls but encouraging boys to persist on their own, calling on boys more often for high-level questions (Fennema, 1984), and different teacher 'wait-times' (the pause for student response) which could affect achievement (Fennema &  Sherman, 1978). Reyes  (1982) found tremendous variation in the behaviour of grade 12 teachers, and overall the effect of student-teacher interactions on mathematics achievements remains unclear (Erickson, Erickson, & Haggerty, 1980).  Fennema and Peterson (1986) found boys and girls were engaged in the same activities during mathematics class and were  equals  engaged in those  activities. However, Brush (1980) noted the competitive climate of many mathematics classes and apparently girls are less likely to thrive in such an environment. Research suggests girls' preparation for continuation in mathematics  Review of Literature I 36 could be most favorably affected by a non-competitive learning atmosphere, active encouragement, exposure to positive role models, sincere praise, and explicit advice regarding the value of mathematics studies; the so-called 'girl-friendly classroom' (Eccles, Miller, Reumann, Feldhauffer, Jacobs, Midgley, & Wigfield, 1986). These factors are often neglected, and students who  come to high school mathematics  classes with well-learned sex-role stereotypes leave the same way. Perhaps equal treatment of males and females is not enough and teachers must play an active role in creating a confident, positive female attitude towards the learning of mathematics.  Adolescence is the time when the clash between principles and realities, between achievement and social fulfilment, makes its first major impact on the lives of young women (Skolnick, Langbort, & Day, 1982). Peers are important 'socializers' in a student's life. Girls may  experience intense peer pressure against  achievement in mathematics in high school (Nash, 1979; Fox, Tobin, & Brody, 1979; Fennema &  Sherman, 1977; Ernest, 1976). Gifted girls are often judged  less favorably by peers than gifted boys (Solano, 1976). In more advanced mathematics courses, female registration may  fall short of a 'critical mass'  necessary for same-sex support.  The adolescent years are fraught with insecurities and pressures. Strong support and guidance to pursue mathematics is required but instead North American students are given their first option to drop mathematics in Grade 9 and do not receive adequate information about the possible consequences of this decision. Counsellors operating under sex-biased assumptions report reacting  Review of Literature / 37 differently to a girl who  wishes to drop back to a less advanced mathematics  class than to a boy who  "is more apt to need the math" (Skolnick, Langbort,  &  Day, 1982).  Textbooks, test design, school materials, and the media have all been shown to reinforce traditional sex-role stereotypes (Delgaty, Getty, lies, & 1980; Sadker &  Pointon,  Sadker,1979; Tobias, 1978; Kepner & Koehn, 1977;  Saflios-Rothschild, 1979). Their long-term impact on sex-related differences in mathematics would appear likely but these effects are difficult to measure in the short run (Fox, Tobin, & Brody, 1979).  Finally, parents, family, and other adults may  influence student  achievement and participation in mathematics; by their own  attitudes and  behaviors towards mathematics, their expectations and goals for their children, and the activities they provide or encourage. Several studies have discovered sex differences in these areas (see Eccles-Parsons, 1984; Eccles et al., 1986) but few have assessed the causal impact of these socialization experiences. Encouragement from parents appears to influence girls' decisions to continue in advanced mathematics (Armstrong,  1980; Fennema &  Sherman, 1977,  Adler, & Kaczala, 1982). A strong relationship was  1978;  Parsons,  shown between parents'  judgement about their child's ability in mathematics and the child's estimates of her own  ability, plans for more mathematics courses, and actual achievement  (Parsons et al., 1982). Also, student beliefs about their parents' perceptions of them as mathematics learners can predict enrolment intentions (Fennema & Sherman, 1977). In general, however, the direction of causality with the parent  Review of Literature / 38 variable is still open to debate; for example, expectations may arise from previous achievement or vice versa.  4. Socioeconomic status.  Although socioeconomic status (SES) is another social variable which could conceivably influence the level of sex-related differences in mathematics, it has been noted above that SES has generally been inadequately  considered in the  literature to date. The combination of sex, mathematics, and SES in the literature is extremely rare and in general the consideration of sex in studies of SES  (and vice versa) has been inadequate.  Willms (1983) defined SES as "the relative position of a family or individual on an hierarchial social stratification structure, based on their access to, or control over, wealth, prestige, and power" (p. 40). SES is often operationally defined as comprising  the income, education, and occupation of  household heads (White, 1982), but there is often considerable variation from this basic premise. The traditional definition is often supplemented or replaced by an assortment of variables including size of family, educational aspirations, ethnicity, mobility, presence of reading materials in the home, and amount of travel, as well as such school level variables as teachers' salary, pupil/teacher ratio, per capita expense, and staff turnover. White (1982) found over 70 different variables used (either alone or in some combination) as indicators of SES in the studies he reviewed. The educational significance of the SES of a student's family is considered in different studies via the possible effect of SES on educational  Review of Literature / 39 aspiration (how  far you would ideally like to go), expectation (how  far you  realistically think you can go, given your particular set of circumstances), attainment, and achievement.  It is widely believed that SES  is strongly, and positively, correlated with  academic achievement. In the Equality of Educational Opportunity Survey (Coleman et al., 1966) the authors concluded that SES  had a major influence on  achievement, and that schools did little to alter this effect. Other studies also have found a strong relationship between SES  and academic achievement (Klein,  1971; Levine, Stephenson, & Mares, 1973; Baker, Shutz, & Hinze, 1961;  and  Thomas, 1962). Oakes (1987) found SES  differences in achievement and  participation in her analysis of the HSB  data and other studies. Poor children do  less well than their more affluent peers overall, especiallj' on measures of higher level skills and problem solving (National Center for Educational Statistics, 1985). SES  differences in achievement are evident at age 9, clearly in place at age  13,  and continue to increase during senior high school (Carpenter, Matthews, Lindquist, &  Silver, 1984). In the HSB  data, with other school and home factors  controlled, students' socioeconomic status (defined by educational levels of parents, father's occupation, family income, and household possessions) accounted for a substantial amount of the differences in students' mathematics achievement (Rock, 1984).  This strong relationship between SES  and academic achievement is in fact  often referred to in the literature as an indisputable fact and is not accompanied by further reference or supporting evidence.  Review of Literature / 40 The  family characteristic that is the most powerful predictor of school  performance is socioeconomic status (SES): the higher the SES  of the  student's family, the higher his academic achievement. This relationship has been documented in countless studies and seems to hold no matter what measure of status is used (occupation of principal breadwinner, family income, parents' education, or some combination of these). (Boocock, 1972, p. 32) To characterize youth according to the social class position of their parents is to order them on the extent of their participation and degree of success in the American Educational System. This has been so consistentlj' confirmed by research that it can now empirical law ... SES  be regarded  as  predicts grades, achievement, and intelligence  scores, retentions at grade level, course failures, truancy, suspensions from school, high school dropouts, plans for college attendance, and total amounts of formal schooling. (Charters, 1963, pp. 739-740)  However, numerous other studies have reported moderate-to-weak relations between SES  and academic achievement (Lambert, 1970;  Fetters, 1975; Hennesy, 1976; correlations between SES from 0.100  and Wright &  Bean, 1974)  Stroud,  1959;  and the obtained  and various measures of academic achievement range  to 0.800 without adequate explanation for this wide variation (White,  1982). White (1982) examined almost 200 between SES  Knief &  studies that considered the relationship  and academic achievement. Results of his meta-analysis indicated  that: ...as it is most frequentlj' used (with the student as the unit of  Review of Literature / 41 analysis) and traditionally defined (using one or more indicators of parents' income, educational attainment, or occupational level), SES is positively but only weakly correlated with measures of academic achievement, (p.474)  White offers explanations  for his observations: The relation between SES  and academic achievement is generally weak and appears to be declining in more recent studies because of the increased availability to all people of television, movies, community groups and organizations, and preschool, and also because of increased efforts at equalization of educational opportunities. The achievement of older students is observed to be less affected by SES, perhaps partial^ because of a disproportionately high dropout rate among low achievers toward the end of high school.  Studies that use aggregated units of analysis for the study of SES (for example, school or district) instead of individual student units, produce much higher correlations between SES and academic achievement and this may account in part for the frequent but misleading  conclusion of a strong relationship  between SES and academic achievement (White, 1982). Also, "some measures that are used as indicators of SES, such as 'home atmosphere', are much more strongly correlated with academic achievement than are the traditional indicators of SES" (White, 1982, p. 474). These discrepancies in the units of analysis used in different studies also help explain the wide variation in correlations across studies. Finally, academic achievement variables (grade level, year of study, type of achievement measure) can influence the correlations of achievement with SES.  Review of Literature / 42 In a three-year study of grades 6 and 9 students and a one-year study of grade 12 students, Brush (1980) reported that SES  was  an important  influence on mathematics attainment among high school students but not among younger students. Younger students were influenced by their feelings about mathematics and were more open to changing their course planning; their socio-economic background was  not a restricting factor in these plans. For high  school students, ability and, to a lesser extent, socio-economic status were the main predictors of attainment. The effect of SES  was  stronger for girls than for  boys. Brush suggested that one reason for this difference may  be that many  low-SES girls choose clerical work as their goal and drop mathematics when it becomes optional, but low-SES boys take additional mathematics because it is required for certain career options (for example, carpentry and drafting) or because these boys lack clearly-defined goals. High-SES high school girls will take more mathematics than their low-SES counterparts because they are planning to attend university.  Studies by Sewell, Hauser, and Featherman (1976), Marini and Greenberger  (1978), and Rehberg and Rosenthal (1978) suggest that any male  advantage in educational attainment is greatest amongst low-SES pupils. Marini and Greenberger  (1978) cited a number of studies of students who  school between 1955  and  1960 that showed the direct effect of SES  attended high on  educational aspirations to be greater than the effect of academic ability for both sexes. Marini and Greenberger's study (1978) of some 2500 Grade 11 students in Penns3dvania  reversed this conclusion; academic achievement (their measure of  ability) had a stronger effect than SES  on educational ambition for both sexes,  Review of Literature / 43 although the difference between the size of the two effects was greater for girls than boys. In between-sex comparisons, a greater effect on the ambitions of boys than girls was found for SES. Thus boj^s' educational aspirations and expectations were shown to be more strongly tied to their social class origins than those of girls. Difficulties in comparing the Marini and Greenberger study with previous studies were cited and more research was called for to confirm this apparent shift in the relative importance of SES and ability. The reduction in the sex differentiation of adult roles since the late 50's, the increase in participation of married women in the labour force, the decline in fertility rates (Ferriss, 1971), and efforts to achieve greater equalitj' of educational opportunity were all listed as possible explanations for the increased role of academic achievement relative to SES  in the determination of educational goals (Marini & Greenberger, 1978).  Rehberg and Rosenthal (1978) reached the conclusion that " in total effect neither ability nor social class predict college entry as strongly for women as men"  (p. 244). These researchers also found the power of social class to predict  attainment and achievement for both sexes to be modest and diminishing. "Social class is no longer the dominant force in schooling; merit has emerged as the larger determinant  of the individual's progress through the school and of his or  her ultimate schooling attainment" (pp. 261-262). There are, of course, still social and therefore "class" elements attached to the ways in which merit is distributed; for instance, in the way parents who have reached high levels of occupational attainment socialize their children. Lee and Ware (1986) did not find social class to be a contributing factor to step-by-step analysis of U.S.  students'  participation in high school mathematics courses. Stockard and Wood (1984) found  Review of Literature / 44 the influence of SES to differ little between males and females. Both of these studies found ability to exert a stronger influence over achievement  outcomes  than social class for both males and females.  5. Conclusions about causation.  Some of the factors that may cause sex-related differences in mathematics have been discussed. Obviously, getting to the roots of sex differences in mathematics is a very difficult, complex task. Within the category of causation research and theory most of the current emphasis is on environmental or experiential, as opposed to biological, factors. Why environmentally-based theories of causation —  is this? Perhaps  proponents of  educational psychologists, sociologists,  mathematics educators, etc., have an emotional investment in eradicating sex differences in mathematics which impairs their receptivity to apparently unchangeable  biological explanations. Many current writers in this area are, after  all, women. Perhaps  too these erstwhile crusaders lack the scientific  background  necessary for a proper understanding of the biological theories and are forced to try and ignore these ideas in the hope they will atrophy through neglect. In general, I think not. The evidence cited above indicates an ever-strengthening body of support for the environmental, experiential, and attitudinal approaches to understanding sex differences in mathematics. beyond the question of "Why  aren't women  people behave as they do?". This approach  One can and should now look more like men?" to ask "Why do  legitimizes the behavior of both males  and females, permitting the examination of sex differences from perspective rather than from  a choice  a deficit perspective, and greatly increases the  Review of Literature / 45 possibilities for successful intervention and prevention  of sex differences in  mathematics. Many such programs are alreadj' producing positive results — final testimony to the validity of this approach (Grayson, 1987; Jump, Heid, & Harris, 1987).  Finally, although the current emphasis is on environmental and experiential explanations  of sex differences in mathematics, it should also be made clear that  further work on possible biological or genetic correlates of these differences remains a necessary and worthwhile component of the effort to improve female performance. Arch (1987) argued that "what must be avoided is a simple causal dichotomy which says that either sex differentiation of behavior precedes differential socialization and thus is biologically set, or it follows such socialization and  thus can be altered at will by environmental change. What is missing is  the possibility that there are biological potentialities and limits which influence how socialization practices or environmental factors in general come to have differential effects" (p. 7). The current research, with its indicators of prior student ability and famity background, provides valuable information for this investigation.  C. POST-SECONDARY DESTINATIONS  Schonberger and Holden (1984) state that sex-related differences in mathematics participation and performance have been of considerable interest to researchers  since Sells (1978) identified high school mathematics as the 'critical  filter' which confined female students to a few, traditionally female college majors at the University of California at Berkeley in 1972. Sells' work and other  Review of Literature / 46 related studies will be examined in this final section of the literature review. The problem of mathematics avoidance and the extent to which it can limit career choices will be placed in a sociological context by considering the literature on the career and academic choices of young people enrolment patterns in post-secondary  (and especially young women),  education, and the current status of women  in the labor force.  In 1972, Sells, a Berkeley applicants seeking admission  sociologist, found  to the University of California, 5 7 % of the males,  but only 8% of the females, had taken (Sells, 1978). Sells concluded  that of a sample of  four years of high school mathematics  that without  the four years of high school  mathematics almost all of these women would be ineligible for the introductory courses in such disciplines as economics, mathematics, chemistry, physics, engineering sciences, statistics, and computer science; and that without courses they  these  would be unable to major in 5 0 % of the fields offered at the  university. These women would be confined in their choices to five main areas: the humanities,  music, social work, elementary education, and guidance and  counselling.  Sells' description of restricted patterns of female enrolment and subsequent career choices have been well documented in both 1976;  the U.S. and Canada (Ernest,  Armstrong, 1980; Ontario Ministry of Labor, 1983). Schonberger and  Holden (1984) cited several recent studies that have supported that successful completion  Sells' hypothesis  of high school mathematics is critical to women's  chances for matching the educational and occupational attainment  of men after  Review of Literature / 47 graduation. For example, Hacker (1983) has  documented the increased emphasis  on mathematics, especially calculus, in U.S.  baccalaureate programs in engineering  over the last century and  that this has  for women and  has  hypothesized  minorities in these programs. Elkins and  constituted a barrier Leutkemeyer (1974)  found that the mathematics portion of the Scholastic Aptitude Test (SAT-M) differentiated between persisting and  non-persisting engineering students at the  University of Maryland, while the verbal portion (SAT-V) did not. High school mathematics is the most critical factor in the completion or mathematics (McNamara & found  that personal values and  than education  Scherrei, 1982). On  of a degree in science  the other hand, Arnold (1987)  perceived social constraints were more  (or ability) in determining  important  the future vocational achievement of top  female high school mathematics students.  Many girls continue to show a preference for traditional careers, are uninformed about the labor market and  available careers, and  seem to be  generally unprepared for a long stay in the work force (Toronto Board of Education, females  1983). Studies have shown that the vast majority of males  usually aspire to "traditional" occupational roles held by  (Sayer, 1980;  Looft, 1971;  Vondracek &  Kirchner, 1974;  and  their own  sex  Iglitzin, 1972; Tibbetts,  1975). Sex-typing of occupations by young people appears to be declining, especially with regards to female occupations; that is, both males and  females  now'more readily accept female aspiration to non-traditional jobs (White Ouellette, 1980;  Gregg &  &  Dobson, 1980). However, actual expectations of  employment, as opposed to aspirations, tend to adhere to traditional lines (Larter &  FitzGerald, 1979). Of  1350  students randomly selected from Houston, Texas  Review of Literature / 48 high schools, 2-year colleges, and 4-year colleges, 9 0 % of males aspired to male-dominated occupations and 80%; expected contrast 6 4 % of female  to attain their aspiration. By  high school seniors aspired to non-traditional occupations  with only 4 0 % expecting to attain them. Of all females  surveyed, 7 0 % expected  to enter a female-dominated occupation (Derryberrj', Davis, & Rosen and Aneshensel  (1978) surveyed  Wright,  1979).  3200 students in New York State and  reported that the number of girls who think that they will have a non-traditional feminine occupation decreases with age; the percentage  with professional or  executive expectations in Grades 7-8 was twice as large as that in Grades 11-12.  A  great majority of young women plan to combine careers with  (Glaze, 1979; Sayer,  1980). One effect of this is reduced  marriage  or moderate "career  salience". Almquist and Angrist (1970) define a career-salient woman as one who places career above all other priorities. Skolnick, Langbort, and Day (1982) tell us that: Making room for family considerations tends to orient girls toward jobs rather than careers; that is, toward occupations which thej' imagine involve less training and less single-minded devotion to professional development. Stereotypically, math and science occupations are thought to fit the career mold, perhaps precisely because they have traditionally been male domains. Although  it sways girls away  math and science fields, the notion that traditionally female  from  occupations  are more conducive to family life is questionable. Many times these occupations are merely  lower-paying, (p.43)  Review of Literature / 49 The  Glaze (1979) studies also showed inadequacies in young women's  awareness of the current status of women in the labor force. For example, the majority of respondents grossly underestimated the marriage rate of college graduates. The implications are significant considering the above-mentionned marital plans of most of these girls. The majority (80%) also mistakenly believed that divorce was more common among career women than among housewives and were poorly informed about the size of the female workforce, the average number of  years females work outside outside the home (underestimating both of these),  and  about reasonable approaches to making career decisions. Larter and  FitzGerald (1979), and Sayer (1980) concurred with this finding of low female occupational awareness and expectation and posited that such attitudes were well-entrenched and would be slow to change in future.  Over of  the last two decades women have comprised an increasing percentage  the total enrolment in programs at universities and colleges. In the U.S. in  1981, women earned about 4 8 % of the B.A.'s, 5 0 % of the Master's degrees, and 31%  of the Ph.D's; up 6, 10, and 18 percent respectively from  1970 (O'Neill,  1984). In Canada, the Ontario Ministry of Labour Women's Bureau  (1983)  reports that between 1970 and 1980 female enrolment in full-time undergraduate programs increased from  3 6 % to 46%, in M.A. programs from  in  16% to 32%. However, despite these increases women  Ph.D. programs from  2 4 % to 40%, and  are  still not represented in university programs in the same proportion as they  are  in the general population and those women enrolled in university still are  clustered in the Arts programs and in other traditionally female areas. In Ontario universities women represent only 1 0 % of the total enrolment in  Review of Literature / 50 engineering and applied sciences and 3 1 % of enrolment in mathematics and the physical sciences. Enrolment in the health sciences is high ( 5 6 % female) but concentrated  in traditional areas such as nursing instead of dentistry (17%),  optometry (34%), or medicine (31%). Women have made some inroads into these and  other traditionally male programs such as architecture, commerce, law, and  business administration (Gaskell, 1980). In graduate school, women are not as well represented  as in the undergraduate years. Part-time enrolment and  enrolment in Colleges of Applied Arts and Technology are also up for women (Ontario Ministry of Labour Women's Bureau, 1983). However female representation in such college programs as clerical and retailing ( 9 9 % and 9 1 % respectively) indicates an unfortunate remunerative  concentration in areas which are not  and which are not projected to grow in the future (Menzies,  1981).  Women in this century have dramatically increased their participation in the labour force. During  the period 1947 to 1980, the number of women in the  labour force in the U.S. increased 173%, compared to an increase of 4 3 % for males. Statistics Canada (1982) reports that from 64%  1972 to 1982 there was a  increase in the number of women in Ontario's labour force. The majority of  married  women now work outside the home and it is predicted that married  women with children can expect to spend at least 25 years in the workforce while single women can count on as many as 45 years. ...by  the year  2000, 65-78% of all Canadian women are expected to  be in the labour force. The majority of these women will spend from 25  to 48 years working outside the home. (Toronto Board of  Education,  1983, pp.35-36)  Review of Literature / 51 However, although  women's work has changed greatly, its status has not.  Townson (1980) suggests that "women have exchanged one work ghetto for another". A t the beginning of the century, 3 4 % of all Canadian women in the paid labour force were maids or servants. In 1982, about one third of the 4.9 million workers were in clerical positions and 7 1 % were restricted to four occupations: clerical (33%), service jobs (19%), sales (10%), and medicine and health (9%) (Toronto Board of Education, 1983).  Within this broad position of mathematically  sociological perspective one need hardly point out the related fields of study  and employment; these  areas  remain in the category of traditionally male-dominated endeavour. Paradoxically mathematics has expanded its sphere  of influence in recent times; it is no longer  used only in the fields of physics, chemistry, engineering, and astronomy but is also increasingly called for in industry, computer technology, business, government, nursing, home economics, and education. This situation, when considered with the current trends in post-secondary underscore society.  destinations outlined above can only serve to  the continuing role of mathematics as a "critical filter" in our modern  CHAPTER  III.  METHODOLOGY  This chapter outlines the methodology used performance  in mathematics in Scotland and  levels of family background,  to analyze male and  to compare these results across  ability, primary arithmetic achievement,  destinations beyond the compulsory  female  level of secondary  schooling. The  and chapter  describes five areas of the study: the research design, the achieved sample, independent or control variables, dependent or outcome variables, data set construction, and analyses.  A.  DESIGN  Careful scruthry of education requires a regular sampling of leavers from secondary  schools. The  1985  Scottish Young Peoples Survey  the present study provides such a sampling frame. It was  (SYPS) utilized in conducted  by the  Centre for Educational Sociology (CES), University of Edinburgh, with funding from  the Scottish Education Department (SED). The  series of biennial surveys conducted by  CES.  1985  survey forms part of a  These surveys are made more  effective by the availability of the powerful government appartus for constructing as complete  a sampling frame as possible: for example, through information  available to the central government such as the record of examination presentations. Also, the surveys are strengthened because by  a non-government agency (the CES). The  government's need to manage and  they are administered  potential conflict between  defend its policies and  social research's need  for open-minded, critical inquir}' is therebj' avoided (Burnhill, McPherson, Raffe, &  52  Methodology / 53 Tomes, 1987).  The  1985  SYPS survej'ed all pupils in Scotland who  an original sampling  frame of 10%.  The  S4  with  target population consisted of two  overlapping groups: a school-year group of students who 1983-1984, and  completed  a school-leaver group who  in the same session (Lamb, 1986). The  had 1985  were in S4 in  left school from SYPS was  any  school year  a large-scale  multipurpose  postal survey. Questionnaires were mailed to home addresses in  April, 1985,  thus reaching respondents  school-leaving dates. The  some nine or more months after their  range of topics covered in the questionnaire included the  student's educational histor}- (number of primary the examined and examinations  and  non-examined school curriculum (special tutoring received,  taken, work experience programs, special college-level "link" courses  taken in high school, subjects taken in third and  fourth years), affective factors  (feelings about school, attitudes of parents, peers, and friends), a record of post-secondary parents' job status, and  became available from  teachers, destinations of  destinations; reasons for leaving school,  parents' education.  When student achievement and  ability data from  the school district used  research possibilities presented themselves, nature. To  secondarj' schools attended),  primary  in the present study, many  additional 8 7 %  sample from  new  including studies of a longitudinal  have as complete a data set as possible, the CES  augment the original 10%  school records  decided to  this district (the "main survey") with  an  sample (the "regional survey"), bringing the final survey fraction  for the district to 97%.  The  remaining  3%  of the population had  been previously  Methodology / 54 committed to another  survey and was therefore unavailable. Finallj', the local  authority also provided results for O-grade Arithmetic, O-grade Mathematics, and Highers Mathematics examinations  taken by students in the present study in  their fourth, fifth, and sixth years of secondary  The  school.  present study examines O-grade Arithmetic results for all students  who completed  their fourth year of secondary  school in one Scottish school  district in 1984. Analysis is done to establish whether there are male-female differences in achievement in O-grade Arithmetic, and to measure the size of these differences. Often when the achievement scores of two or more groups are considered, only mean scores are compared. Mean scores, like other statistics such as the standard deviation and the range, are summary measures that may mask important characteristics of the groups. In this study, however, the whole distribution of scores is available which allows a comparison of the cumulative distributions of male and female scores.  To  begin the analysis of O-grade Arithmetic results in relation to previous  student behavior and background, the relationship between results on a test of acquired arithmetic knowledge administered to these students eight years previous to their S4 examinations, in Primary  3 (P3ARIT), and their O-grade Arithmetic  scores is examined. Next, the relationship between results on a test of verbal reasoning ability administered in Primary  7 (P7VRQ) and the S4 O-grade  Arithmetic scores are analyzed, followed by socioeconomic  the relationship between the students'  status (SES) and their performance on O-grade arithmetic. Finally,  to conclude this section of analysis, the study uses multiple regression to examine  Methodology / 55 possible interactions between sex and between sex and  The  P3ARIT, between sex and  P7VRQ, and  SES.  second  set of analyses examines how  is related to subsequent  O-grade Arithmetic achievement  student destinations. To  this end  the study relates the  S4  arithmetic results to the critical choice between leaving secondary  S4  or staying on for S5  and  perhaps  school after  S6. School leavers' destinations are then  further categorized into areas such as employment, further education, and unemployment, and  each of these areas is compared according to O-grade  Arithmetic performance.  Students who  stayed on may  a number of different courses. They may, Arithmetic examination  in S5  and  have taken mathematics in  for instance, have retaken the O-grade  even once more in S6. They also may  elected to take O-grade Mathematics or Highers Mathematics in S5  have  or S6. All  these categories can be related to the O-grade Arithmetic scores to see, for instance, what fraction of girls go on to mathematics Highers and do compared with boys, given their levels of S4  B. A C H I E V E D  The The  how  well girls  O-grade Arithmetic.  SAMPLE  achieved sample is, of course, rarely  major problem  with coverage  in the 1985  100%  of the target population.  survej' was  due  to non-contact:  not all sample members' addresses were current or accurate, causing a loss of coverage. This non-contact rate was address, through  reduced through contact with the original  an intermediary, or through  processing, the remaining non-coverage was  an agency. Excluding errors of  due  to response to the questionnaire  Methodology / 56 itself, either as a whole or to particular items within the questionnaire. Response to the questionnaire was boosted by readministration and reminders. Final coverage takes all of these elements into account and is calculated as a percentage of valid returns over the original target sample (Burnhill et al., 1987, p. 119).  Figures for the achieved sample in this study are as follows: a questionnaire was  sent to 5726 individuals from a total S4 population in the  school district of 5869. Questionnaires were returned by 4519 people; a response rate of nearly 80%. Of this group who  returned questionnaires, 80% were  successfully matched with test information from their Primarj' 3 year, 89% were matched with P7 information, and 82% had O-grade examination information available (70% wrote the Arithmetic O-grade examination). Students with both P3 and O-grade information totalled 66%, and those in both P7 and O-grade databases  74%.  The data are the best available in the U.K.  to date for the purpose of  estimating the size and distribution of sex differences in mathematics along lines of ability and social class. For example, what may  become a comparable  sampling arrangement for England and Wales did not appear until 1985. Prior data on pupils were based on Department of Education and Science (DES) questionnaires sent to head teachers and Department of Employment (DE) surveys of labor-market entrants. Both of these inquiries were conducted without contacting the young people themselves and also with little attention to previous education. The SYPS, on the other hand, provides data that describe school  Methodology / 57 leavers' own  accounts of their experience, and  officers believe  not what teachers or career  about them. Also the SYPS education data may  be analyzed in  the light of data on the school leavers' transitions to the labor market or to post-school education, and the DES  vice versa (Burnhill et al., 1987). Even in recent years  has been obliged to use SSLS datat because there were no  data available for England  and  Wales (see for example DES,  comparable  1984).  Looking beyond the school district examined in this study, the consistent, uniform nature of the Scottish school sj'stem (for example, the same O-grade examinations  are written and  prepared  for across the country) makes the results  generalizable to Scotland as a whole. Furthermore,  the comprehensive nature of  the data base heightens the descriptive power of the results and potential interest to researchers, educators, and  makes them of  policy-makers outside the U.K.  as  well.  C. DEPENDENT VARIABLES  The  present study presents an outcome measure of achievement describing  pupils' O-grade Arithmetic examination they fall within each of six percentage 69; C  - 50  to 59; D  - 40  to 49; E  results. These results are described as categories: A - 30  - 70 to 100%;  to 39; and  No  B  - 60 to  Award - below  30%.  (For some analyses these categories will be separated further into a total of 14 bands.) Categories A levels at O-grade. As  tThe  to C  are nominally considered to represent the passing  in previous years, the 1984  Scottish School Leavers  O-grade Arithmetic examination  Survey, the predecessor to the SYPS.  Methodology / 58 was  available to students along with the O-grade Mathematics examination.  O-grade Mathematics is designed to be undertaken  While  by more advanced students,  O-grade Arithmetic should not be considered a routine computational exercise. In fact, a cursor.y examination reveals a preponderance  of the items on the 1984  O-grade Arithmetic test  of higher cognitive level problem-solving questions; these  more difficult items outnumber the straight-forward computational questions by approximately  2 to 1.  In an earlier study, Willms  (1986) described how  outcome variables. This same method of scaling was  he had  scaled the  utilized in the present  study: Each outcome measure was  scaled on a logit distribution using a  technique for re-expressing grades described by Mosteller and (1977). Any  scaling, including a simple numbering of ordered categories  (in this case from and  one to fourteen for O-grade bands) is arbitrary,  different methods of scaling can produce  1983;  Tukey  Willms, 1986). The  different results (Spencer,  logit technique assumes that each  attainment category represents a score on an underlying distribution (similar to a normal distribution but with fatter tails), and  divides the  distribution into pieces according to the percentage of pupils in each attainment category. The  scaled score is then the centre of gravit}^ of  each piece. Because the two  covariates VRQ  and  SES  are  approximately normally distributed, the logit scaling of the outcome variables provides a slightly better fit to the data than simply numbering the categories, (p. 229)  Methodology / 59 For the post-S4 analyses, subjects were categorized as having school beyond S4  or as having  left. Questionnaire  information was  stayed in  then used  again to assign each school leaver to 1 of 3 areas: Full-time employment, the Youth Training Scheme (YTS)t, and students who  stayed in school past S4  O-grade Mathematics, and  D. INDEPENDENT OR  The  Regional  (school district) was  CONTROL  the Regional  VARIABLES  1984  Scottish Educational Authority  Council Education  administered  3, or P3). This is an  a maximum  Council and  school leavers surveyed  no  in this  study.  the Educational Authority are of particular interest  first is the Regional  school (known as Primary 17 items and  for O-grade Arithmetic,  able to provide background test information from the  Survey in Mathematics, which was  with  are presented  Council (school board) for one  tests provided by  to this study. The  Unemployed. Examination results for  Highers Mathematics.  elementary years for most of the  Two  On  score of 50. The  information on  Committee  in the third year  Screening  of elementary  untimed, two-part group test test was  developed locally  validity or reliability is available.  by The  second test is the Moray House Verbal Reasoning Test (Godfrej' Thomson Unit, 1971)  administered  in the final year of elementary school (P7). This timed group  tThe Youth Training Scheme (YTS). was instituted in 1981 (replacing the Youth Opportunities Program) to provide twelve months of work experience, training, and education for 16 and 17 year olds who have recently left secondary school. Although the scheme welcomes the unemployed, it is also intended to be an integral part of the whole economy and to this end firms are encouraged to place their young, first-year employees in the program for a year of consistent, well-rounded preparation. Trainees are paid a nominal salary while on the YTS (Raffe, 1984b).  Methodology / 60 test (45 minutes) includes 100 calculated from  the Kuder-Richardson  the effects of age. The Test (MHE  items. The  coefficient of internal consistency,  formula  20, was  0.968 after allowing for  test correlated positively with the Moray House English  40) (0.902), and  the Moray House Mathematics Test (MHM  4A)  (0.888). This test provides a measure of previous student ability (verbal reasoning quotient or VRQ)  The  SES  in the present study.  of the pupils is an independent  variable derived from  questionnaire information. This is a standardized SES three indicators of SES:  after examining and  variable calculated  father's occupation, mother's education, and  siblings. In previous research with SES, several combinations  father's education. He  Willms  the  SYPS  from  number of  (1986) selected these variables  of variables, including mother's occupation  found father's occupation, mother's education, and  number of siblings to be the best of the SES-related predictors of achievement in O-grade arithmetic used  in his study. Mother's occupation and  father's education  were tested in preliminary analyses in Willms' study but were dropped from  the  model because they did not contribute substantially to the explained variance of the outcome variable after father's occupation, mother's education, and  number of  siblings were included.  The  occupations of pupils' fathers are classified using the Registrar  General's "Social Class" index (Office of Population Censuses and  Surveys,  1970),  which contains 7 employment categories (see below). Father's occupation is scaled for each individual using the Hope-Goldthorpe Scale (Goldthorpe & The  average  Hope, 1974).  Hope-Goldthorpe value is then computed for all pupils within each  Methodology / 61 of the Registrar General's e m p ^ m e n t categories. These average  prestige ratings  constitute the scaled values for each category of the Registrar General's index. The  Office of Population Censuses and  Surveys  employment categories and  scaled  values are as follows: 1. Professional  72.85  2. Intermediate  59.82  3. Skilled Non-Manual  45.94  4. Skilled Manual  40.17  5. Partly Skilled  32.13  6. Unskilled  20.17  7. No  Job or Unclassified  34.53  Mother's education is classified as a dummy variable: 0 represents education up beyond. Sex  to 15 years of age, and was  E. D A T A SET  To  coded  0 for males and  1 for females.  compile the final data base for this study several steps were  of any  two  S4  (O-grade) data were matched. Approximately  sets of data were matched via information in computer files  (i.e., surname, initials, birthdate, and visual inspections and main and  16 or  CONSTRUCTION  necessary. First the P3, P7, and 80%  1 represents education at age  school) but the remaining 2 0 % required  independent judgements. Next the common variables of  regional survey data were merged and  Variable and  matched to the P3-P7-S4 data.  value labels were then set; a descriptive label was  attached to each  Methodology / 62 variable in the combined data (some 150 variables) and the labels were set for each value of each variable, including different types of missing data (for example, "did not answer" or "not part of survey"). The proportions or frequencies of pupils having each value of each with missing data, was determined  variable, including the proportion  and validated. Finally, as described above,  some variables had to be scaled for analysis purposes.  F. A N A L Y S E S  For the purpose  of analysis, the goals of the present study can be stated  as eight specific questions, with accompanying analytical techniques: Question  1: Do the distributions of results in O-grade Arithmetic differ between  the sexes? For this analysis, separate cumulative frequency distributions for males and  females chart the cumulative percentages, from  of 14 O-grade "bands": A B  (65-69), B  (90-100), A  (85-89), A  (60-64), C (55-59), C (50-55), D  0 to 100, at or below each (80-84), A  (45-49), D  (75-79), A  (70-74),  (40-44), E (35-39), E  (30-34), and No Award (0-29). Questions 2 and 3: Do the distributions of results on the earlier achievement tests of primary school arithmetic and of verbal reasoning ability differ between the sexes? Cumulative  frequency distributions are again employed for these  analyses to chart the cumulative percentages of males and females at or below each Primary  3 arithmetic score and each Primary  ranging from  70 to 140. With such a wide spread of scores to be included,  cumulative frequenc3  ?  point to be analyzed.  7 verbal reasoning score,  distributions provide the advantage of allowing every data  Methodology / 63 Question 4: How  do  sex  differences on  O-grade Arithmetic vary  socioeconomic status; that is, what is the role of SES and  what is the interaction between sex  Arithmetic  results on  (father's occupation, analysis, an  sex  and  and  interaction term for sex by  Questions 5 and  6: How  The  analysis regresses  Primary 3 arithmetic test and and  on  several indicators of  SES  number of siblings) In a second  SES  is added to the model.  well do early student achievement in arithmetic  early student ability in verbal reasoning Arithmetic?  in arithmetic achievement,  SES? Analyses regress O-grade  (dummy variable) and  mother's education,  across levels of  and  predict later achievement in O-grade  O-grade Arithmetic  the Primary  examines the interactions between sex  results on  7 verbal reasoning and  these two  scores on  the  test, respectively,  tests.  Question 7: Does the relationship between achievement in O-grade Arithmetic  and  students' destinations following completion of their compulsory schooling differ by sex? Cross-tabulations  compare O-grade Arithmetic results in six letter-grade  categories (A to E, and after S4  'No  Award') with student destinations if they left school  (3 categories: Full-time employment, YTS,  or Unemployed), or if they  remained in school (4 categories: Repeated O-Grade Arithmetic, O-Grade Mathematics, Highers Mathematics, or No Question 8: How  do results in Highers Mathematics compare with  achievement in O-Grade Arithmetic again  mathematics.  employed for these  analyses.  for males and  previous  females? Cross-tabulations  are  C H A P T E R IV. RESULTS  This chapter reports findings for each of the questions asked at the end of Chapter 3. Question 1 asked whether the distributions of scores on the O-grade Arithmetic examination, taken in S4, differed between the sexes. Figure 1 displays the cumulative frequency distributions of these O—grade results for males and females. Data were available for 5726 students overall, 2937 boys and 2789 girls. Achievement is presented in 15 categories, including students who did not write the O-grade Arithmetic examination ("Did Not Present") and O-grade "bands": A l (90-100), A2 Bl  (65-69), B2  (85-89), A3  (80-84), A4  14  (75-79), A5 (70-74),  (60-64), C l (55-59), C2 (50-54), D l (45-49), D2  (40-44), E l  (35-39), E2 (30 34), and No Award (0-29). Scores of C or higher are considered a passing grade for these examinations.  Figure 1 indicates that sex differences on the O-grade Arithmetic examination were small. Boys did slightly better at the higher end of the distribution; that is, boys gained more on girls within the higher categories of results. Results were approximately equally distributed in the middle grades, and girls scored more often than boys at the lower levels. Overall 72% of the girls in the present study presented for the O-grade Arithmetic examination compared with 67% of the boys. Although this difference is not large, it is statistically significant because the sample was  large and comprised nearly the entire  population of students for that cohort. Thus girls were more likely to attempt O-grade Arithmetic but less likely to perform well. For example, girls received more failing grades (D, E, or No Award) than boys.  64  30-| JO  e o  Sex 20 o Female 10  a Male  0 &  E2  E l D2 Dl  C2  CI  B2  Bl  A5  A4  A3  A2 Al  70 tn C  rt 0)  S4 Arithmetic O-grade S c o r e s Figure 1 Cumulative Irequency distribution, Arithmetic O-grade scores  Results / 66 Scores on O—grade Arithmetic were quite evenly distributed various scoring bands for the student group  across the  as a whole. Nine percent of all  presenting students scored from  30 to 39  (letter-grades E l and E2), 9%  to 49  50  ( C l and  and  ( D l and  B2), 1 1 %  D2), 12% from  from  70 to 79  to 59  (A4 and A5), and  C2), 10% 12%  from  A3). Four percent of students scored at each of the two Award) and  from  from . 60 to 69 ( B l 80 to 89  (A2  extremes, 0-29  and  (No  90-100 (Al). However, more than twice as many females (167) as  males (79) placed at the lowest scoring level of "No  Award". Thus, although  more girls took the examination, 6%  wrote  scored from  E2  of all girls who  0 to 29, compared with only 3%  frequently represented, usually by from  (30-34) up  to B2  of boys. Girls were also more  a small margin, in all the lower categories  of girls, and  of the 2 6 %  (80—84). Again, differences were  of boys scored 70 or higher, compared with  of students who  did show a considerable advantage  A,  70 to 100, boys were more frequently  represented than girls at each level except A3 generally small. Overall, 2 8 %  O-grade Arithmetic  (60-64). For the five grade levels designated as  comprising examination scores from  62%  40  scored an A, 54%  were males.  24% Males  in representation at the highest level of A l :  of the students in this categor}' were male ( 5 % of males versus 3%  of  females).  The the  separate lines for males and  proportion of students scoring at or below a given level. For example,  of the males and  28%  33%  of the females in the sample did not write the O-grade  Arithmetic examination; 4 3 % up  females in Figure 1 show at each point  of both males and  females attained a grade level  to E l (or did not present). Figure 1 shows how  the female majorities at the  Results / 67 lowest levels of achievement overcame the initial male advantage in cumulative percentage the two  for the "Did Not  distributions from  Question  Present" category, and  then on  how  were small (lines roughly parallel).  2 asked whether the distributions of scores on the arithmetic  achievement test administered to students in Primary shows the cumulative from  the differences between  70 to 140, by  this test of Primary  3 differed by  frequency distributions of the P3 sex. Male and  female  means of the male and  female  arithmetic scores, ranging  students had  arithmetic. Further analysis  for males and  similar distributions on  confirms this  scores were 98.88 and  the standard deviations were 14.25  sex. Figure 2  conclusion. The  99.45 respectively, and  13.74  for females.  The  differences between these values were not statistically significant at the 0.05  level  (t=1.38).  Question  3 asked  how  the distributions of scores on the test of verbal  reasoning ability administered to students in Primary displays the cumulative frequency scores, from  70  to 140, by  7 differed by  distributions of the Primary  sex. Figure 3  7 verbal reasoning  sex. Males scored more frequently in the lower  range, 70 to 84. Males accounted the middle range of scores, 85  for 6 2 %  of the pupils within this range. In  to 119, which accounts for 9 0 %  of the sample,  results were evenly distributed between the sexes. Males were also overrepresented in the higher range: 5 5 % were male.  of those scoring between  120  and  140  Primary 7 Verbal Reasoning S c o r e s Figure 3.Cumulative frequency distribution, P7 verbal reasoning scores.  Results / 70 The and  means of male and  female  scores were 95.96 and  the standard deviations were 11.10  for males and  differences between the sexes, therefore, was which was  statistically  10.26  about 15%  significant at the 0.05  indicates that the distributions for males and  97.52 respectively, for females.  of a standard deviation,  level (t=5.18). However, Figure 3 females  were nearly identical for  the major group of students in the middle range of scores, and statistically  significant difference in average  more males at the lower end  Question  4 asked  on  sex, SES,  estimates and  and  scores stemmed from  that the the presence of  of the distribution.  whether sex differences on  across levels of socioeconomic  The  O-grade Arithmetic varied  status. O-grade Arithmetic results were regressed  the interaction of sex with SES.  Table  1 shows the parameter  standard errors for this regression. In all analyses, sex was  0 for males and  1 for females. SES  was  scaled to have a mean of 0 and  coded a  standard deviation of 1 for the entire school district. Therefore, the intercept is an SES  estimate of the expected score that is average  in one  attainment, or O-grade score, for a male with for the population under consideration (all S4  school district in 1984). The  estimates of the female  an  students  parameter estimates for the sex effect are  advantage for O-grade Arithmetic. Similarly, the  parameter estimates for SES  are estimates of the Arithmetic/SES  slope for  males, while the parameter estimates for the SES-by-sex interaction are estimates of the differences between the male and  female  Parameter estimates are statistically approximate!}' two  Arithmetic/SES slopes.  significant (p<0.05) if they are  times their standard errors. Table  1 indicates a male  Results / 71 advantage ("Sex" =  —0.036) for O-grade Arithmetic, after taking account of  SES, but this difference was not statistically significant. The interaction effect of sex b}' SES is the difference between the slopes of the regression lines for males and females. This parameter estimate statistically  significant. Overall, only  ("SES by Sex") was also not  14% of the variance  in O-grade Arithmetic  achievement was explained by the variables sex, SES, and sex-by-SES interaction.  Table 1 Parameter estimates  and standard  errors for regression of O—grade Arithmetic on  sex, SES, and a S E S — b y — s e x interaction.  Intercept (Expected O-grade Arithmetic score of average male) Sex (Difference between females and males for the average pupil) Socioeconomic Status (SES slope for males) SES by sex (Difference between female and male S E S slopes)  Parameter Estimate  Standard Error  0.018  0.017  -0.036  0.024  0.395  0.017  -0.034  0.024  Results / 72 Question 5 asked how  well student  achievement on a Primary 3  arithmetic test predicted later achievement on O-grade Arithmetic these predictions differed by sex. O-grade results were regressed 3 arithmetic (P3ARIT), and the interaction of sex with the parameter estimates  and standard  and whether on sex, Primary  P3ARIT. Table  2 shows  errors for these regressions. For the sex  effect, there were no statistically significant differences between males and females in O-grade Arithmetic, after taking account of P3ARIT Parameter estimates  for P3ARIT  are estimates  slope for males. The parameter estimates estimates  of the O-grade Arithmetic/P3ARIT  for the P3ARIT-by-sex interaction are  of the differences between males and females in their 0-grade/P3  slopes. In this case the male slope was —  ("Sex" = -0.022).  0.047 and the female slope 0.043 (0.047  0.004). Thus the interaction effect, although statistical^ significant, was not  large; statistical significance is attributable to the large sample size.  Table Parameter estimates  and standard  2  errors for the regression of O—grade  Arithmetic results on sex, Primary 3 arithmetic (P3ARIT), and a P 3 A R I T — b y — s e x interaction. Parameter Estimates  Standard Error  Constant  0.020  0.016  Sex (Difference between females and males for the average pupil)  0.022  0.023  P3 Arithmetic  0.047  0.001  0.004  0.002  (P3ARIT slope for males)  P3 Arithmetic by Sex (Difference between female and male P3ARIT slopes)  Results / 73 Question  6 asked  whether sex differences on O-grade Arithmetic varied  across levels of student ability as measured by  a test of verbal reasoning  administered in Primarj' 7. O-grade Arithmetic results were regressed on Primary  7 verbal reasoning ability (P7VRQ), and  the interaction of sex with  P7VRQ. Table 3 shows the parameter estimates and regressions. For the sex effect, males had  an  sex,  standard errors for these  advantage in O-grade Arithmetic  after taking account of P 7 V R Q ("Sex" = -0.118). Parameter estimates for P 7 V R Q are estimates of the O-grade Arithmetic/P7VRQ slope for males. Parameter estimates for the P7VRQ-by-sex interaction are estimates of the differences between males and slope for males was As  in Question  females  in their 0-grade/P7VRQ slopes. In this case, the  0.070 and  the slope for females  5, the interaction effect was  significance derived from  was  0.066 (0.070 - 0.004).  not large and  its statistical  the large sample size. Table 3  Parameter estimates and  standard errors for the regression of O—grade  Arithmetic results on sex, Primary  7 verbal reasoning (P7VRQ), and  P7VRQ—by—sex  interaction. Parameter Estimate  Constant Sex and  (Difference between females males for the average pupil)  P7VRQ (Verbal reasoning slope for males) P7VRQ by Sex (Difference between female and male P7VRQ slopes)  a  Standard Error  0.080  0.013  -0.118  0.019  0.070  0.001  -0.004  0.002  Results / 74 Question 7 asked whether the relationship between achievement in O-grade Arithmetic and  students' destinations following completion of their  schooling differed by  sex. Table 4 presents results of crosstabulations matching  O-grade Arithmetic examination  results in six categories (A - 70  to  69; C  to 49; E  or  missing)t with post-compulsor}' destinations in seven  YTS,  - 50  to 59; D  - 40  - 30  to 39; and  No  O-grade Mathematics, and  Passed  to 100; B  Award  - 60  - 0 to 29  categories (Unemployed,  Working, School without further mathematics, Repeated and  Arithemetic, Passed  compulsory  passed O-grade  Highers Mathematics), t  Table 4 displays the destinations of school leavers nine months after completion of S4  (April, 1985)  in S5  to Highers Mathematics, for those students who  or S6, up  school for one  or two  percentages of each  and  the highest level of mathematics achievement  additional years. The  figures in Table 4 show the  sex group for each destination category, for each of the  various levels of previous O-grade Arithmetic performance. the males who  scored an A  later, compared with Arithmetic and  remained in  1.1%  For example, 1.3%  of  in O-grade Arithmetic were unemployed nine months of females. Information was  post-compulsory  available for both O-grade  destinations for 5445 of the students in the  tThe letter grade of A is acknowledged to include a large range of possible scores, larger than that usually accepted as the highest level of achievement in North America. However, it was felt that a more accurate picture of the Scottish grading system and its relationship to subsequent student movement would be provided if the letter-grade system was presented as it is used in Scotland, instead of breaking the A level into smaller groups. tin Scotland, students may take O-grade examinations at the end of their fourth, fifth, and sixth years and Highers examinations in their fifth and sixth years. These examinations may also be repeated if students are returning to school and wish to improve their marks. Therefore, the post-compulsory categories involving the study of mathematics are totals for fifth and sixth year examinations results achieved by students in each of O-grade Arithmetic, O-grade Mathematics, and Highers Mathematics.  Results / 75 present study (95%). This group was 2805 males and respond  quite evenly divided between the sexes:  2639 females. Five percent of the original sample did not  to the question on destinations in their questionnaires.  Overall, students with higher grades likely to stay in school beyond S4 pronounced among females marks; that is, from 60%  A  in O-grade Arithmetic were more  than low  achievers. This tendency  was  more  than males. For the letter-grades considered as passing  through  C, 7 6 %  of females  stayed on, compared  with  of the males. However, females with these fair-to-excellent O-grade results  did not persist in mathematics education as frequently as their male counterparts. In fact, only about one-half of the female categories successfully completed compared with 64%  end  of secondary  another mathematics course in S5  female  achieved an A  or  to C S6,  in O-grade Arithmetic, almost half of  groups were able to pass Highers Mathematics by  school. Another 3 0 %  of females stayed in school but did not  continue with mathematics at all, compared to 2 0 % leavers with an A  the A  of the male "stayers".  Among students who both the male and  "stayers" (51%) from  of males. Among school  at O-grade, males (62%) were more likely to find full-time  employment within nine months than females (42%).  the  Results / 76 Table 4 Crosstabulations of O-grade Arithmetic results by post-compulsory destinations (Column percentages by sex). S4  O-grade Arithmetic  B  Post-S4 Destinations  Pupils who Unemployed Males Females  Results  D  E  NA  ;|  left school  1.3 1.1  7.4 7.6  10.7 6.8  10.7 7.8  9.1 10.0  23.2 23.4  Males Females  5.7 4.3  21.5 11.9  27.7 23.7  41.7 26.4  37.0 35.0  43.4 40.3  Working Males Females  11.2 3.9  17.8 9.5  23.8 16.2  19.5 10.8  30.5 19.4  23.5 18.7  28.4 41.8  15.9 32.8  20.8 24.7  9.3 16.7  1.3  7.1 16.7  2.6 10.4  0.1 0.1  5.1 5.5  0.5  0.1 0.1  YTS  Pupils who No  more mathematics Males Females  stayed 20.4 30.3  in school 26.1 49.9  O-grade Arithmetic Males Females O-grade Mathematics Males Females  14.2 14.3  21.0 15.8  8.3 9.5  Highers Mathematics Males Females  47.2 46.1  6.2 5.3  1.1 0.7  737 615  290 259  328 325  Total Number Males Females ;:  NA=  No  Award  0.4 0.4  220 271  195 236  1035 933  Results / 77 Students with a B in O-grade Arithmetic who  persisted in mathematics  usually went no further than O-grade Mathematics, with males holding a slight advantage within this category. Females (71%) stayed in school more often than males (53%), but more male "stayers" pursued the study of mathematics.  "C"  students displayed a similar pattern. Sixty percent of males left school, compared with 47% of females, but over 75% of the female "stayers" dropped mathematics, a greater proportion than males. For each level of O-grade achievement, males subsequently held a greater percentage of full-time jobs and placements on the YTS. The female tendency to remain in school more often than males maj' partially account for the male advantage in these two non-school categories, but it also should be noted that patterns of unemployment were similar for the two sexes and therefore males who  left school appear to have  been more successful in finding productive activities.  Question 8 asked whether achievement in Highers Mathematics differed between males and females across various levels of O-grade Arithmetic achievement. This question was the  select group of students who  included to consider possible sex differences within went on to advanced mathematics study in  secondary school. Overall, data on both O-grade Arithmetic and Highers Mathematics  were available for 1114 students, 636 males (57%) and 478 females  (43%). Because the original sample was divided almost evenly (51% to 49% for males and females, respectively) it is apparent that a greater percentage of males sat Highers examinations in S5 or S6.  Table 4 showed that 47% of the males and 46% of the females  who  Results / 78 scored an A  in O-grade Arithmetic in S4 were able to pass Highers Mathematics  in S5 or S6. In terms of Question 8, this meant that the overwhelming majority (93%) of Highers Mathematics passes were achieved by students with an O-grade Arithmetic score of A  in S4. Therefore a cell-by cell matching of O-grade results  with Highers results was  deemed unnecessary. Instead, the figures in Table 5  simply show the number of males and females who  placed in each of the  Highers Mathematics letter-grade categories.  Table 5 Highers Mathematics results in S5 and S6 by sex. Highers Mathematics A A A A A B B C C D D E E F  (90-100) (85-89) (80-84) (75-79) (70-74) (65-69) (60-64) (55-59) (50-54) (45-49) (40-44) (35-39) (30-34) (00-29)  Males 3 9 5 17 35 60 55 70 89 73 92 77 44 6  Females  — 5 10 17 40 49 68 95 53 69 45 25 • 2  Although females did not sit Highers examinations as frequently as males, those who A  did present were somewhat more likely to achieve a passing grade of  to C. Fifty-nine percent of females passed Highers mathematics compared to  5 4 % of males. Among passers, males had an advantage (20% of passing males  Results / 79 versus 11% advantage  of passing females) within the A  within the B category (34% of passing males versus 3 1 %  females). The advantage  letter-grade category, and  female advantage  in overall  at the lowest passing level, C  a slight  of passing  passes is explained by the female (57% of female passes versus 4 6 % of  male passes). Males dominated both extremes of Highers Mathematics performance; all of the twelve students who and  46%  scored from 85 to 100  were male  of the males received a failing grade (below 50) compared with 4 1 % of  the females.  C H A P T E R V. SUMMARY  This study has addressed  AND  CONCLUSIONS  several questions concerning sex differences in  mathematics. The study is based  on longitudinal data from  about 6000 students  in one school district of Scotland.  The  first chapter outlined the purpose of this study: to examine sex  differences in achievement on the O-grade Arithmetic examination these results with indicators of male and female performance, and destinations upon completion to  and to match  ability, SES, previous arithmetic  of compulsory schooling. The need  include such factors as SES, ability, prior performance, and subsequent  academic and career behaviors in a well-informed description of sex differences, and  the frequent failure of previous research to do so, helped explain the  rationale for undertaking the present study.  In  the first chapter also contained a description of the unique  Scottish  background and setting for the study, highlighting those features which strengthened  the project's potential for contributing to the existing body of  knowledge in this area. The reorganization of Scottish secondary  schools along  comprehensive lines, the raising of the minimum school leaving age to 16, and increased enrolment  at all levels of secondarj' school have combined to give the  O-grade Arithmetic examination This is an examination  a pivotal role in the Scottish education system.  for a "core subject", taken by  80  a majority of students,  Summary and  it helps to mark a vital transition point at the end  Although the size and  the current study is based  across a ten-year period) and  100%  of one  Conclusions / 81  of compulsory schooling.  upon data from  scope of the data base (almost  and  one age  school district, group documented  the consistent nature, of the Scottish education  system across geographic boundaries  give the results a relevance and strength  that goes beyond their immediate frame of reference.  In the second  chapter a review of the literature on each of the areas of  interest in the present study was  presented, and  several important observations  emerged. In general, when results of the most recent studies are compared with earlier analyses, sex differences in mathematics achievement and  enrolment  appear  to be declining. Consistent achievement differences favoring boys are not expected to appear until adolescence, are never very large, and any  are not always present at  grade level. When differences do appear, girls often do better on straight  computation  or one-step  word problems, but boys do better on multiple-step word  problems, applications, spatial relationships, more advanced logical reasoning, statistics and  graphs (California State Department of Education, 1979;  Commission of the States, 1978;  National Council of Teachers  Education  of Mathematics,  1980). Boys tend to score more frequently than girls at both the high and  low  extremes of the achievement distribution.  A  review  of the literature on the causation of sex-related differences in  mathematics showed an ever-strengthening body of work to support  environmental  theories of causation. Studies to date have not shown general intelligence, spatial  Summary  and Conclusions / 82  visualization, innate mathematics ability, or other biological explanations to have a sound basis in scientific fact. On the other hand, such "environmental" factors as confidence and the perceived usefulness of mathematics are highly correlated with mathematics achievement  and enrolment. The classroom environment  is also very  important. The role of socioeconomic status in predicting mathematics  performance  appears to be important but diminishing.  The  second chapter also included a review of the literature on  post-secondary destinations. The review described the increasing importance of mathematics in many people's lives after secondary participation and performance  school and the improved  of women in mathematics-related fields of work and  study. However, the review also indicated that the majority of women still adhere to the restricting path of traditional occupational roles and aspirations and fail to understand the possible consequences  The  of these decisions.  review of literature includes, whenever possible, examples of studies  done in the U . K . , especially Scotland, to match the more prominent information from  North America. Data from  the U . K . usually indicated situations  similar in strength and direction to those of North American also provided in-depth documentation  body of  studies. The review  of the perceived need for, and strengths of,  the current study when its design was compared with the existing literature.  Summary A.  PRINCIPAL  Conclusions  / 83  FINDINGS  Chapters 3 and study. The  and  4 described the methodology and  principal findings for the study  results for the  present  were as follows:  1. Overall, sex differences on the O-grade Arithmetic examination, taken at the end  of compulsory schooling by  a majority of students, were small. However, a  consistent pattern to the differences was levels from C I  (55-59) to A l  scores than female scores was represented  apparent. For each of the eight band  (90-100), a greater percentage of overall male present. Conversely,  in each of the six band levels from No  However, a higher percentage of boys (37%)  girls were more frequently Award  (0-29) to C2  than girls (28%)  in our  (50-54).  sample did  not present for the O-grade Arithmetic examination.  Thus boys showed a slight advantage across the spectrum of passing grades and  the cumulative  male advantage for all these categories combined  indicates a definite sex difference in mathematics favoring males that is consistent with the literature. Because the male advantages were consistently small in each category, there was  considerable overlap between the sexes, and  many females in Scotland are doing well in high school mathematics up to O-grade Arithmetic.  2. Girls and  boys performed equally well in the early years of primary school  arithmetic, and end  had  of elemental  about the same overall ability in verbal reasoning  at the  school. Thus the later male advantage in O-grade Arithmetic  Summary indicates a shift from the status quo  in elementary  and  Conclusions / 84  school. Females are not  realizing their potential in mathematics as well as males. These findings are again consistent with the literature on sex differences in mathematics:  these  differences are not expected to appear before adolescence.  3. The  relationship between SES  and  achievement  1982). In an earlier study, Willms and socioeconomic status was  (White,  Kerr (1987) observed that, although  related to students' performance  Arithmetic examination, there was The  is well established  on the 1984  O-grade  no significant interaction between SES. and  present study also found that sex differences in achievement  sex.  did not vary  for different levels of SES.  4. Females lagged behind males in their rate of persistence in advanced mathematics in secondary school. The end of compulsory students. The performance  O-grade Arithmetic examination marks the  schooling in the "core" subject of mathematics for most  study of mathematics beyond S4  is predicated upon satisfactory  on the O-grade examination. Thus, the O-grade examination  an important transition point for Scottish high school students. The present study indicated sex differences in the way It appears  marks  results of the  this transition was negotiated.  that many females are managing to compete reasonably well with  their male counterparts in mathematics up S4. Also, females who  to the end of compulsory  schooling in  passed the O-grade Arithmetic examination chose to staj'  in school more often than males. However, amongst students who greater percentage of males than females participated and  stayed on, a  were successful in  optional, higher-level mathematics courses. Female ability and  potential in  Summary  and Conclusions / 85  mathematics are not being translated into training in this subject area as readily as for males.  5. Males performed in S5  better than females on the Highers Mathematics  examinations  or S6. First, a greater percentage of males than females sat these  Highers examinations. Also, males and scores (almost always the more advanced Highers results, and  "A")  females with good O-grade Arithmetic  did not achieve similar results when they  Highers course. Males dominated the male advantage  was  scoring levels (all of the students scoring 85  the A  and  more pronounced to 100  B  attempted  categories of  at the highest  were males).  B. POLICY IMPLICATIONS  How  can schools ensure that girls with the ability to perform  as well as  males on the O-grade Arithmetic examination realize their potential by achieving good results on this important evaluation? How  can they ensure that girls  who  perform creditably on this examination do not limit their future options by failing to persist in mathematics beyond the O-grade level? Given good results on the O-grade examination, how examination be improved in mathematics,  can female performance  on the Highers Mathematics  relative to males? If girls are to produce better results  to persist in upper-level mathematics courses, and  greater inroads into traditionally male-dominated areas of work and educational policies must incorporate an around  to make study, public  awareness of the inequities centred  the transition point between compulsory  schooling and  optional mathematics  study documented in this study. In this section some suggestions are given for  Summary and Conclusions / 86 policies which address these concerns at the student, classroom, school, and school-district levels. These suggestions are based on the review of literature undertaken  as part of the present study.  Female mathematics students, including those in elemental school, should be made aware of the need for, and the usefulness of, mathematics in their lives, and of the importance of mathematics as a key to many future career options. Female students should be encouraged to continue their high school mathematics studies for at least four years at a level compatible with their interests and abilities. Female students should learn of the tendency of girls in previous years to sometimes leave their full potential in school mathematics unrealized and should be encouraged to discuss this phenomenon. All students should have ample opportunity for success and personal satisfaction in mathematics.  At the class level, teachers should create a positive and supportive environment for female mathematics students. Mathematics can be presented as fun, valuable, historic, even beautiful, and not as difficult as is often imagined. Classes should provide a sound fundamental mathematics program that enables students to grasp new  concepts and ideas, solve problems, and think critically  and creatively. Working through mathematics problems often involves much more than skills application. Students are asked to' take risks, make mistakes without becoming upset, tolerate ambiguity, persist in independent work, and trust in their abilities to find solutions and to effect changes in their environment (Tobias, 1978). Females often lack confidence in their intellectual abilities and feel  Summary inadequate  and  Conclusions / 87  at problem solving (Deaux, 1976).  Group work, cooperative learning, an experimental approach, deemphasis on right and  wrong (and on neatness  possibilities for improving  this situation. To  mathematics, girls need to practice and should be used who  may  than one guess, and  a  for girls) are some classroom  dissolve the threatening mystique of  to experience success. Manipulatives  at all levels of mathematics instruction, especially for females,  have had  males. Students  and  less experience with manipulative play and  exploration than  should experience problems with more than one  solution or more  possible approach. They should be encouraged to take chances, to to use estimation. These activities, when completed  build confidence and  Students  flexibility as well as problem—solving  successfully, can  skills.  should have an opportunity to meet women working in all kinds  of occupations that involve mathematics, including those in what has been considered the male domain. The  relevance of mathematics to life beyond the  classroom should always be emphasized, and  the conception of mathematics should  be. expanded to include technology, science, and traditionally considered the female  business, as well as areas  domain.  At the school level, the progress of female  students in mathematics should  be carefully monitored. Special classes, sections, or courses for girls should be provided when appropriate to foster achievement, to overcome mathematics anxiety, and  to address the special needs of females. Students  and  staff should  be made aware of the conflicts in modern womens' lives: the traditional vision of  Summary and Conclusions / 88 the full-time wife and mother versus economic realities which dictate that most women must work; child-rearing duties, still seen primarily as a woman's responsibility, versus demands of career; traditional notions of femininity versus competition with males; and a new ethic of independence and competence which goes beyond what many women suspect is really acceptable or even possible.  Teacher education programs should be implemented to increase teacher effectiveness with female students. For example, teacher expectations for female students should be high. Teachers should be given evidence from the realms of work, school, and research to support such raised expectations. Examples of intervention programs that have improved teacher awareness and subsequent female performance could be provided. Next, teachers should not interact with females in a stereotypical way. For example, female students would benefit from an equalization in the number of direct, open-ended, and abstract questions, more detailed instructions, and longer "wait-times" after questioning. High schools should hire more female mathematics teachers and inservice should be provided for all women teachers, especially those in elementary  school, so that they might present  themselves as comfortable and confident users of mathematics.  Counsellors and teachers should be kept abreast of changes in society and of career opportunities for mathematics students. Teachers and department heads should be given leave to visit business and industry for varying lengths of time. "Career education" should be a responsibility shared by all school staff including teachers and should present new perspectives on nontraditional careers as well as help both boys and girls to envision a new shared role within the family  Summary  and Conclusions / 89  (Skolnick, Longbort, and Day, 1982). Counsellors and teachers should give special attention to guiding female where many  students across the compulsory/optional transition point  "leak" out of mathematics.  At the district level, materials, textbooks, and examinations of sexual bias. School districts should monitor  female enrolment  should be free  and achievement  in mathematics. Proven intervention programs should be implemented where necessarj', including elementary  schools. Innovations and trends in the labor  market should be reflected in the mathematics curriculum.  C. D I R E C T I O N S F O R  RESEARCH  This final section presents some suggestions for future research. Some of the projects mentioned would continue or extend  the directions of the present  study, whereas others would consider questions that were off limits to the present study because of its design. For example, the present study was observational in nature and several of the recommendations to follow incorporate more controlled, experimental settings for analysis.  In Scotland, research should consider the course-taking patterns of girls who stay in secondary females  school beyond S4. The present shuty has indicated that  are not persisting in mathematics to the same extent as males. A  natural hypothesis would be that those girls who remain in school but do not persist in the study of mathematics despite encouraging  results in O-grade  Arithmetic would probably not study physics or chemistry either; instead they  Summary would choose more traditional courses for females  such  and Conclusions / 90  as English, history, other  languages, etc. This hypothesis requires confirmation. If this scenario exists, intervention programs to expand female patterns away from  perspectives and to adjust course-taking  traditional lines should be instituted and research should  document the effects of these programs from  their onset.  Reseach should continue to examine sex differences at the transition point between O-grade Arithmetic and more advanced mathematics by investigating  why  girls do not take more mathematics at the higher levels. Comparative studies of the design and inherent difficult}' of the O-grade Arithmetic, O-grade Mathematics, and  Highers Mathematics courses and their examinations  should be undertaken to  ascertain if these courses require noticeably different student skills. Perhaps many girls lack the necessary skills to successfully complete the more advanced mathematics courses. Questionnaire data should also be collected to decide if, consistent with the literature from  North  America,  Scottish girls lack confidence  in their abilities at higher levels of of mathematics, perceive these courses as more difficult than boys do, or don't see optional mathematics courses in S5 and S6 as necessary to their future wants and needs.  In  this study boys did not present as frequently as girls for O-grade  Arithmetic, but those who  did performed  generally better than girls. A t the  Highers level, boys presented more often than girls and achieved better results. Questionnaires and within-school studies should also examine how  boys and girls  make their decisions about persistence in mathematics; perhaps boys are not more skilled but are making better, more-informed decisions with the help of  Summary  and Conclusions / 91  teachers, parents, counsellors and peers, at both the O-grade Arithmetic and Highers Mathematics levels.  In  applied settings, attempts  to remediate  or intervene could be conducted  under experimental conditions. Studies could consider questions such as the following: What are the effects of short and long term How  exposures  to role models?  are teacher attitudes about women and mathematics related to their  mathematics teaching and what effect would training to heighten their awareness have? What would be an effective way to teach about  mathematics-related  careers? Would compulsory four-year mathematics programs be effective? Would greater emphasis on mathematics problems in the social sciences motivate  females  to study more mathematics? What is the best time for intervention (Fennema, 1983)? Better instruments to measure teacher attitudes should be developed (Grayson,  1987).  More affirmative research is needed (Stage, 1986). Studies should examine why  some women have succeeded  in mathematical  programs and careers. Deficit  models have less to offer intervention programs than do models of what is required for success. For instance, case studies of females mathematics and performed  who persisted in  well in advanced courses should be undertaken.  Similarly, more case studies of mathematically  gifted students and their  backgrounds (parents, families, teachers) should be conducted. How do the attitudes of gifted boys and girls compare? Do gifted children have different backgrounds of play and parental expectations? What are the characteristics of those teachers, male and female, who positively influence highly able girls  Summary (Fennema,  and Conclusions / 92  1983)? More evaluation research is also needed. (Stage, 1986). Enough  successful models are now in place that much valuable information could be gathered  on their most important  components  for dissemination to a more general  audience.  Finally, longitudinal research that considers broader  social, economic and  political conditions beyond schools and families, at various times  and in different  locations, is required. Research should be done to relate sex differences in mathematics to the changing state of the economy, to the range of jobs available, to incentives and training programs offered to women, and to political priorities which in turn dictate social support care programs.  services for women such as child  APPENDIX  The  School District  The  district encompasses a land area of some 505  a population of roughly 345 135  000. Although  000,  square  miles and  with a total work force of approximately  the land area includes just 1.7%  Scotland the population of the district exceeds 6%  of the total area of  of the county's  total  population. Employment can be categorized roughly as follows: primary 7.3% The  ; construction 7.2%  has  ; manufacturing  32.3%  ; and  industries  the service sector  majority of the population is concentrated in five main towns and  53%.  the  lifestyle of much of the remaining minority is best characterized as rural (Regional Council Publications, 1987).  Secondary education in this district was system as early as  1967.  described as a fully comprehensive  There are presently 21  secondary  schools. Most of  these have a policy of forming remedial groups where needed and  then dividing  all other pupils into classes of mixed ability; usually this is a planned, instead of a random, mix. From  Secondary 3 onward there are roughly two  broad  groupings: those students following courses that lead to certification on the Scottish Certificate of Education examination, and  those following non-certificate  courses. Recently the distinction between the two  has become less clear; that is,  less able pupils are allowed to present for the Scottish Certificate of Education in some subjects.  93  REFERENCES Almquist, E. M.. &  Angrist, S. S. (1970). Career salience and atypicality of  occupational choice among college women. Journal Family,  32,  and  the  242-249.  Arch, E. C. (1987). A practice.  of Marriage  biosocial perspective  on sex differences  and  educational  Paper presented at the annual meeting of the American Educational  Research Association, Washington,  DC.  Armstrong, J. M. (1980).Achievement and participation  of women  in  mathematics.  Education Commission of the States: Denver, CO.  Arnold, K. D. (1987). Values gifted  females  and  vocations:  in the first five years  annual meeting of the American Washington,  Assessment  The  career aspirations  after high  school.  Paper  of  academically  presented at the  Educational Research Association.  DC.  of Achievement  Programme.  (1983). Report published by the Scottish  Education Department.  Baker, R. L., Shutz, R. E., & ability on achievement Experimental  Benbow, C. P., &  Education,  Hinze, R. H. (1961). The influence of mental  when socioeconomic status is controlled. Journal 30,  of  155-158.  Benbow, R. M. (1984). Biological correlates of high  mathematical reasoning ability. In G. J. De Vries et al (Eds.), Progress Brain  Research,  Benbow, C. P., &  61,  469-490. Amsterdam: Elsevier Science Publishers B.V.  Stanlej', J. C. (1980). Sex differences in mathematical  Fact or artifact? Science,  Benbow, C. P., &  in  210,  1262-1264.  Stanley, J. C. (1983). Sex differences in mathematical  reasoning ability: More facts. Science,  94  222,  1029-1031.  ability:  / 95 Bentzen, F. (1966). Sex ratios in learning and behavior Elementary  Principal,  46,  13-17.  Bleier. R. (1984). Science  and  gender:  women.  New  A  critique  disorders. The  of biology  and  National  its theories  on  York: Pergamon Press.  Block, J. H. (1976, August). Debatable conclusions about sex differences. Contemporary  Psychology,  Boocock, S. S. (1972). An  21,  517-522.  introduction  to the sociology  of learning.  Boston:  Houghton-Mifflin.  Brophy, J. (1985). Interactions of male and female students female teachers. In L. C. Wilkinson, differences  in the classroom.  Brush, L. R. (1980). Encouraging solution.  New  girls  with  male and  C. B. Marett (Eds.), Gender  &  related  York: Academic Press.  in mathematics:  The problem  and  the  Boston: Abt Associates.  Bryden, M. P. (1979). Evidence for sex-related differences in cerebral organization. In M. A. Whittig, & cognitive  functioning:  A. C. Petersen Developmental  (Eds.), Sex-related  issues  differences  (pp. 121-143). New  in  York: Academic  Press.  Buffery, A., & and  Gray, J. (1972). Sex differences in the development of spatial  linguistic skills. In C. Ounsted, &  differences:  Their  ontogeny and  significance.  Burnhill, P. (1984). The 1981 Scottish School Fourteen  to eighteen:The  D. C. Taylor (Eds.),  changing  pattern  Baltimore: Williams  Gender and Wilkins.  Leavers Survey. In D. Raffe (Ed.), of schooling  in Scotland.  Aberdeen:  Aberdeen University Press.  Burnhill, P., &  McPherson, A. F. (1884). Careers and gender: The expectations  of the Scottish school leavers in 1971 and 1981. In S. Acker, & Warren (Eds.), Is higher  education  fair  D.  to women? London: Society for  / 96 Research in Higher Education.  Burnhill, P., McPherson, A., Raff'e, D., &  Tomes, N. (1987). Constructing a  public account of an education system. In G. Walford (Ed.), Doing of education.  Lewes, LTK: Falmer.  California State Department of Education (1979). Student schools,  sociology  1977-1978  Annual  Report,  Sex  differences  achievement  in  in mathematics  California achievement.  Sacramento, CA: California State Department of Education.  Carpenter, T. P., Matthews, W., Achievement Elementary  Charters, W.  in mathematics: School  W.,  Lindquist, M. M., &  Journal,  of research  84,  485-495.  on teaching  of teaching. In N. L. Gage  (Ch. 14). Chicago: Rand  Chipman, S. (1981). Letter to the editor. Science,  Chipman, S. F., &  The  Results from the national assessment.  Jr. (1963). The social background  (Ed.), Handbook  Silver, E. A. (1984).  212,  McNally.  229.  Thomas, V. G. (1985). Women's participation in mathematics:  Outlining the problem. In S. F. Chipman, L.R. Brush, & (Eds.), Women and  mathematics:  Lawrence Erlbaum  Associates.  Balancing  the equation.  D. M. Wilson  1-24. Hillsdale, NJ:  Coleman, J. S., Campbell, E. Q., Hobson, C. J., McPartland, J., Mood, A. M., Weinfeld, F. D., &  York, R. L. (1966). Equality  survey.  D.C.: National Center for Educational Statistics.  Washington,  Connor, J., &  Serbin, L. (1980). Mathematics,  Report to the U S  of educational  visual-spatial  ability  T. J. (1985, May) Second United  and  sex  roles.  National Institute of Education.  Crosswhite, F. J., Dossey, J. A., Swafford, J. O., McKnight,  for the  opportunity  States.  International  Mathematics  Champaign, IL: Stipes.  C. C , &  Study:  Summary  Cooney, report  / '97 Darwin,  C. (1871). The origin  of species and  the descent of man.  New  York:  Modern Library Edition.  Deaux, K. (1976). The behavior of women and men. Monterey,  Pointon, T. (1980). A  Delgaty, P., Getty, R., lies, J., & and  sexual  Ministry  bias in mathematics  of Education  and  textbooks  listed  in other widely  CA: Brooks/Cole.  report on the  in Circular  racialletnic  14 of the  used mathematics  textual  Ontario  materials.  Toronto: Board of Education for the City of Toronto.  Department of Education and Science (DES) (1984). Technical appendix to DES Report  on Education  Number  Derryberry, C , Davis, P., & recruitment  100,  Department of Education and Science.  Wright, M. (1979). Exemplary  into non-traditional  careers: Summary  program  for  report. Houston:  Houston  Community College.  Do males have a math gene? (1980). Newsweek,  Eccles, J. G., &  Hoffman, L. W.  in child  development  , p.73.  (1984). Socialization and maintenance  sex-segregated labor market. In H. W. Research  46,  and  Stevenson &  social policy:  Vol.1.  of a  A. E. Siegel (Eds.), Chicago, IL:  University of Chicago Press.  Eccles, J., & Jacobs, J. E- (1986). Social forces shape math attitudes and performance. Signs:  Journal  of Women  in Culture  and  Society,  11(2),  367-380.  Eccles, J. G., Miller, C , Reuman, D., Feldlaufer, H., Jacobs, J., Midgley, C , Wigfield, A. (1986). Transition intensification.  to junior  high  school and  &  gender  Paper presented at the annual meeting of the American  Educational Research Association, San Francisco.  Eccles-Parsons, J. (1984). Sex differences in mathematics participation. In M. L. Maehr (Ed.), Advances  in Motivation  and Achievement,  Vol.2,  93-137.  / 98 Greenwich, CT: J A I Press Inc.  Eccles-Parsons, J., Adler, T.F., Futterman, R., Goff, S. B., Kaczala, C. M., Meece, J. L., &  Midgley,  C. (1983). Expectations, values and academic  behaviors. In J. T. Spence (Ed.), Achievement San  Francisco: W.  Education  and  achievement  motivation.  II. Freeman.  Commission of the States (1978). National  assessment,  1977-1978.  Washington, D.C..  Elkins, R. L., &  Luetkemeyer, J. F. (1974). Characteristics of successful  freshmen engineering students. Engineering  Erickson, G., Erickson, L., & science  education  Education,  72(2),  Haggerty, S. (1980). Gender  in elementary  and  secondary  schools.  and  180-182.  mathematics  I  Discussion Paper 08/80.  Province of British Columbia: Ministry of Education.  Ernest, J. (1976). Mathematics  and  sex.  Santa Barbara:  University of California  Press. Ethington, C. A., &  Wolfle, L. M. (1984). Sex differences in a causal model of  mathematics achievement. Journal 15(5),  for Research  in Mathematics  Education,  361-377.  Fennema, E. (1974). Mathematics learning and the sexes: A Research  in Mathematics  Education,  review. Journal  for  5(3), 126-139.  Fennema, E. (1977). Influences of selected cognitive, affective, and educational variables on sex-related differences in mathematics learning and study. In L. H. Fox &  E. Fennema (Eds.), Women and  mathematics:  Research  for change.  Washington, DC: National Institute of Education.  perspectives  Fennema, E. (1978). Sex-related differences in mathematics achievement: Where and  how? In J. Jacobs (Ed.), Perspectives  Columbus, Ohio: ERIC Information  on women and  Analysis Centre  mathematics.  for Science, Mathematics,  / 99 and Environmental Education.  Fennema, E. (1980). Sex-related differences in mathematics achievement: and  D. Tobin (Eds.), Women and  why. In L. H. Fox, L. Brody, &  mathematical  mystique.  Baltimore, MD:  The Johns  Fennema, E. (1983). Success in mathematics. differentiation  and  schooling.  Hopkins  the  University Press. (Ed.), Sex  In M. Marland  London: Heinemann Educational Books.  Fennema, E. (1984). Girls, women and mathematics. Ayers (Eds.), Women and  Where  education:  Equity  In E. Fennema &  or equality?  M. J.  Berkeley, CA:  McCutcham Publishing Corporation, 137-164.  Fennema, E., &  Peterson, P. (1986). Autonomous  environments.  Paper  learning  behaviors  and  classroom  presented at the annual meeting of the American  Educational Research Association, San Francisco.  Fennema, E., &  Sherman, J. (1977). Sex-related differences in mathematics spatial visualization and affective factors. American  achievement, Research  Journal,  Fennema, E., &  Educational  14(1), 51-71.  Sherman, J. (1978). Sex-related differences in mathematics  achievement  and related factors: A  Mathematics  Education,  further study. Journal  for Research  in  9(3), 189-203.  Ferriss, A. L. (1971). Indicators  of trends  in the status of American  women.  New  York: Russell Sage Foundation.  Fetters, W. 1972:  B. (1975). National Questionnaires  category,  and  father's  and  longitudinal test results  education.  study of the by sex,  (No. H E  high  high  school class of  school program,  19.308:L86). Washington,  ethnic D.C.:  U.S. Government Printing Office.  Fox, L. H. (1977). The effects of sex-role socialization on mathematics participation and achievement. In L. H. Fox, E. Fennema, &  J. Sherman  / 100 (Eds.), Women and  mathematics:  Research  perspectives  for change.  Washington.  DC: National Institute of Education.  Fox, L. H., Brody, L., & mystique.  Tobin, D. (Eds.) (1980). Women and  Baltimore, MD:  Fox, L. H., Tobin, D., & in mathematics. differences  The Johns Hopkins  the  mathematical  University Press.  Brody, L. (1979). Sex-role socialization and achievement  In M. A. Wittig &  in cognitive  functioning:  A. C. Petersen (Eds.),  Developmental  issues  Sex-related  (pp. 303-332). New  York: Academic Press.  Fraser, E., &  Cormack, S. (1987a, January  mathematics.  p. 17.  Cormack, S. (1987b). The gender factor  Fraser, E., & report.  The Scotsman,  20). Female figures to the fore in  in mathematics:  Interim  Edinburgh: Edinburgh Centre for Mathematical Education, University  of Edinburgh.  Sadker, M. (1973). Sexism  Frazier, N., & Harper  &  The  gender  and  economic  returns.  and job  New  Implications  which  opportunities  York:  for women:  Paper presented at the SSHRC  factor in math. (1980). Time,  Glaze, A. (1979). Factors females:  society.  Row.  Gaskell, J. (1980, October). Education enrollment  in school and  influence  116,  of  Conference.  p. 57.  career choice and future  for career education,  Patterns  orientations  of  published doctoral dissertion,  Toronto: O.I.S.E.  Glennon, V. J., & Elementary and  Callahan, L. G. (1968). A guide  school mathematics.  Washington,  to current  research:  DC: Association for Supervision  Curriculum Development.  Goldthorpe, J. H., &  Hope, K. (1974). The social grading  of occupations:  A  new  / 101 approach  and  scale.  London: Oxford University Press.  Godfrey Thomson Unit. (1971). Moray  House  Verbal  Reasoning  Test  88.  Edinburgh: University of London Press.  Grant, C. A., &  Sleeter, C. E. (1986, Summer). Race, class, and gender in  education research: A n argument for integrative analysis. Review Educational  Research,  Gray, J., McPKsrson, education:  56  (2), 195-211. Raffe, D. (1983). Reconstructions  A. F., &  Theory,  of  myth and practice  since  the war.  of  secondary  London: Routledge  &  Kegan Paul.  Grayson, D. G. (1987). Evaluating Student  Achievement  (GESA)  meeting of the American  Gregg, C. H., &  the impact Program.  of the Gender  and  Paper presented at the annual  Educational Research Association, Washington,  D.G.  Dobson, K. (1980). Occupational sex-role stereotyping and  occupational interest in children. Elementary 15(1),  Expectations  School  Guidance  and  Counselling,  66-75.  Hacker, S. L. (1983). Mathematization of engineering: Limits on women and the field. In J. Rothschild (Ed.), Machina  ex dea  (pp. 38-58). New  York:  Permagon Press.  Harris, L. J. (1978). Sex differences in spatial ability: Possible environmental, Asymmetrical  genetic and neurological factors. In M. Kinsbourne (Ed.), functions  of the  brain.  Hennesy, J. J. (1976). The abilities  Cambridge:  relations  in a late adolescent  of the American  Hilton, T. L., &  University Press.  between socioeconomic  group.  status  and  mental  Paper presented at the annual meeting  Educational Research Association, San Francisco.  Berglund, G. W.  achievement: A  Cambridge  (1974). Sex differences in mathematical  longitudinal sUKry. Journal  of Educational  Research,  67,  / 102 231-237. Hubbard, R., Henifin, M. S., & Fried, B. (Eds.), (1982). Biological convenient  myth: A  collection  biography.  Cambridge, MA:  Husen, T. (1967). International  of twelve countries,  of feminist  essays and  a  woman  - the  comprehensive  Schenkman Publishing Companj'. study of achievement  2 volumes. New  in  mathematics:  A  comparison  York: John Witley.  Iglitzin, A. B. (1972). A child's-eye view of sex roles. Today's  Education,  61,  23-25. Jacklin, C. (1979). Epilogue. In M. Wittig & A. Petersen (Eds.), differences  in  cognitive  functioning:  Developmental  issues.  New  Sex-related York: Academic  Press. Jacklin, C. N. (1983). Boys and girls entering school. In M. Marland (Ed.), Sex differentiation  and  schooling.  London: Heinemann Educational Books.  Jackson, R. (1980, August). The Scholastic Aptitude Test: A response to Slack and Porter's "critical appraisal". Harvard  Educational  Review,  Jump, T. L., Heid, C. A., & Harris, J. J. (1987). Project equitable  attributes  attitudes  towards  in  mathematics  and  the  sciences):  50(3), 382-391.  TEAMS  An  (training  assessment  for  of  sex equity. Paper presented at the annual meeting of the  American Educational Research Association, Washington, D.C. Keating, D. P. (Ed.), (1976). Intellectual  Baltimore, MD:  talent: Research  and  development.  The Johns Hopkins Univershty Press.  Kepner, H., Jr., & Koehn, L. A. (1977). Sex roles in mathematics: A stud} of 7  the  status of sex stereotypes in elementary mathematics texts.  Teacher,  24(5),  Arithmetic  379-385.  Kifer, E. (1986). What opportunities  are  available  and  who  participates  when  / 103 curriculum American  is differentiated.  Paper  presented at the annual meeting of the  Educational Research Association, San Francisco.  Klein, C. A. (1971). Differences in science concepts held by children from three social-economic levels. School  Kneif, L. M., &  Science  and Mathematics,  71,  550-558.  Stroud, J. B. (1959). Intercorrelations among various intelligence,  achievement,  and social class scores. Journal  of Educational  Psychology,  50,  117-120.  Lamb, J. (1986). Scottish  Young  Peoples  Survey  1985:  Technical  report, p . l .  Edinburgh: Centre for Educational Sociology, University of Edinburgh.  Lambert, N. M. (1970). Paired associate learning, social status and tests of logical concrete behavior as univariate and multivariate predictions of first grade reading achievement. American  Educational  Research  Journal,  1,  511-528.  Larter, S., & Part  III,  FitzGerald, J. (1979). Students' the open-ended  and  true-false  attitudes  questions.  to work  and  unemployment:  Toronto: The Board of  Education for the City of Toronto, Research Department (#153).  Leder, G. C. (1986). Gender-linked explanations.  differences  64th Annual  Ware, N. C. (1986). When  school mathematics: the American  Levi-Agresti, J., &  A  closer look.  and  Further  Meeting, Washington,  why girls  "leak"  out of  DC.  high  Paper presented at the annual meeting of  Educational Research Association, San Francisco.  Sperry, R. (1968). Differential perceptual capacities in the  major and minor hemispheres. Proceedings Science,  learning:  Paper presented at the Research Pre-session to the National  Council of Teachers of Mathematics  Lee, V. E., &  in mathematics  of the National  Academy  of  61.  Levine, M. (1976, August). Identification  of reasons  why  women do not  pursue  / 104 mathematical  careers.  Report to the National Science Foundation: N S F  Grant  No. GYE-11411.  Levine, D. U., &  Ornstein, A. C. (1983). Sex differences in ability and  achievement. Journal  of Research  and  Development  in Education,  16(2),  66- 72.  Levine, D. U., Stephenson, R. S., & use of socioeconomic  census data  effects of concentrated Washington,  Mares, K. R. (1973). An  urban  to predict  poverty  among  achievement  and  elementary  schools  Petersen, A. C. (1985). Facts and assumptions  of sex differences. In S. S. Klien (Ed.), Handbook through  evaluate  of the the  in a big city.  D.C.: National center for Educational Research and Development  (DHEW/OE), (ERIC Document Reproduction Service No. E D  Linn, M. C , &  exploration  education.  Baltimore, MD:  The Johns  082 384).  about the nature  for achieving  Hopkins  sex equity  University Press,  (pp.53-77).  Looft, W.  R. (1971). Sex differences in the expression of vocational aspirations  by elementary school children. Developmental  Maccoby, E. E., &  Psychology,  Jacklin, C. N. (1974). The psychology  5,  of sex  366(a).  differences.  Stanford, CA: The Stanford University Press.  Marini, M. M., &  Greenberger, E. (1978). Sex differences in educational  aspirations and expectations. American  Educational  Research  Journal,  15,  67- 69.  Marriott, A. (1986, February 2). More equal. The  Times Educational  Supplement,  p.21.  McGlone, J. (1980). Sex differences in human survey. The Behavioral  McNamara, P. P., &  and  Brain  Sciences,  brain asymmetry: A  critical  3, 215-263.  Scherrei, R. A. (1982). College  women pursuing  careers  in  / 105 science,  mathematics,  and  engineering  in  the  1970's.  (NSF  Report No.  FGK  57295). Washington, DC: National Science Foundation. ERIC Document Reproduction Service No. ED  217-778.  McPherson, A. F., & Willms, J. D. (1986). The socio-historical construction of school contexts and their effects on contemporary pupil attainment in Scotland. In A. C. Kerckoff (Ed.), Research socialization.  in sociology  of education  and  (Vol.6, pp.227-302). Greenwich, CT: JAI Press.  McPherson, A. F., & Willms, J. D. (1987). Equalisation and improvement: Some effects of comprehensive reorganization in Scotland. Sociology,  21,(A),  509-539. Meece, J. L., Parsons, J. E., Kaczala, C. M., Goff, S. B., & Futterman, R. (1982). Sex differences in math achievement: Towards a model of academic choice. Psychological  Bulletin,  (1847). Lecture  Meigs, C. D.  on  91, 324-348. some of the  distinctive  characteristics  of the  female.  Paper delivered at the Jefferson Medical College, Philadelphia, PA. Menzies, H.  (1981). Women and  employment  in Canada.  the  chip:  Case  studies  of information  on  Montreal: The Instituite for Research on Public  Policy. Meyer, M. R., & Fennema, E. (1986). Gender between affective  variables  and  mathematics  differences  in the  achievement.  relationship  Paper presented  at  the annual meeting of the American Educational Research Association, San Francisco. Mosteller, F., & Tukey, J. W.  (1977). Data  analysis  and  regression.  Reading,  MA:  Addison-Wesley. Nash, C. (1979). Sex role as a mediator of intelluctual functioning. In M. A. Wittig &  New  A. C. Peterson  (Eds.), Sex-related  York: Academic Press.  differences  in  cognitive  functioning.  / 106 National Assessment Objectives:  The second  National Assessment 1977-78  of Educational Progress (NAEP), (1978).  mathematics  1977-1978.  Denver,CO: NAEP.  of Educational Progress (1979). Mathematical  assessment.  National Assessment  assessment,  Mathematics  application,  Denver, CO: NAEP.  of Educational Progress (1983). The  assessment:  Results,  trends  and  issues.  third  national  Report No. 13-MA.01.  Denver, CO: NAEP.  National Center for Educational Statistics (1985). The condition edition.  Washington,  for school mathematics  (1980). An if the 1980's.  agenda  for  action:  Reston, VA: NCTM.  Oakes, J. (1987). Tracking in mathematics and science education: A contribution to unequal schooling. In L. Weiss (Ed.), Race, in  U.S.  education.  1985  DC: U S Department of Education.  National Council of Teachers of Mathematics Recommendations  of education,  Buffalo, NY: State University of New  Office of Population Censuses  structural  class,  and  gender  York Press.  and Surveys. (1970). Classification  of  occupations.  London: HMSO.  O'Neill, J. (1984). The trend of the male-female Journal  of Labor  Economics  2, 4 (2).  Ontario Ministry of Labour, Women's Bureau EducationToronto,  Pallas, A. M., &  (1983). Women  force:  Alexander, K. L. (1983). Sex differences in quantitative S A T  Educational  evidence on the differential coursework hypothesis. Research  Journal,  20(2),  Parsons, J. E., Heller, K. A., Meece, J. L., & teachers'  in the labour  Ontario.  performance: New American  wage gap in the United States.  experiences  and  attributions  165-182.  Kaczala, C. (1979). The effects of  on students'  expectations  for success  in  / 107 mathematics.  Paper presented  at the annual meeting of the American  Educational Research Association, Boston.  Parsons, J. E., Adler, T. F., &  Kaczala, C. (1982). Socialization of achievement  attitudes and beliefs: Parental influences. Child  Development,  53,  310-321.  Petersen, A. C. (1979). Hormones and cognitive functioning in normal development. In M. A. Wittig & in cognitive Academic  functioning:  (Eds.), Sex-related  A. C. Petersen  Developmental  issues  (pp. 189-214). New  York:  Press.  Petersen, A. C. (1980). Biopsychosocial processes  in the development of sex-related  differences. In J. E. Parsons (Ed.), The psychobiology sex roles. New  York: Hemisphere Publishing  of sex differences  pattern  of schooling  in Scotland.  and  Corporation.  Raffe, D. (Ed.) (1984a). Introduction. In D. Raffe (Ed.), Fourteen changing  differences  to eighteen:  The  Aberdeen: Aberdeen University  Press.  Raffe, D. (1984b) Y O P eighteen:  The changing  University  Raizen,  and the future of YTS. In D. Raffe (Ed,), Fourteen pattern  in Scotland.  Aberdeen: Aberdeen  Press.  S. A. (1986). Report  pre-college  of schooling  to  education  of the work  in science and  of the committee mathematics.  on indicators  Paper rpesented  of  at the  annual meeting of the American Educational Research Association, San Francisco.  Rehberg, R. A., & high  school.  Rosenthal, New  E. R. (1978). Class  and  merit  in the  American  York: Longman.  Reyes, L. H. (1980). Attitudes and mathematics. In  Regional  Publications. (1987). Results  Lindquist (Ed.), Selected  in business.  issues in mathematics  Glenrothes, education.  Scotland. M. Berkeley,  M.  CA:  / 108 McCutchan Publishing.  Sherrill, J. (1977). The  Robitaille, D., & the Ministry  of Education,  Province  B.C.  mathematics  of British  assessment:  Columbia.  A  report to  Victoria, B.C.:  Queen's Printer.  Rock, D. A. (1984). Excellence 1972-1980,  final  Rosen, B. C , &  in high  school education:  study,  report. Princeton, NJ: Educational Testing Service.  Aneshensel, C. S. (1978). Sex differences in the  educational-occupational expectation process. Social Sadker, D. (1979). Between  Sadker, M., &  Cross-sectional  bias in classroom  interaction.  teacher and  Forces,  57(1), 164-186.  student:  Overcoming  sex  Newton, Mass.: Educational Development  Center.  Safilios-Rothschild, C. (1979). Sex synthesis  and  critique  role socialization  of the literature.  and  sex  discrimination:  A  Washington D.C.: National Institute of  Education, U.S. G.P.O..  Sayer, L. (1980). An  evaluation  of career  awareness  in Grade  Nine  girls.  Published  doctoral dissertation, O.I.S.E., Toronto, Ontario.  Schafer, A., &  Gray, M.  Science,  (1981). Sex and mathematics.  Schonberger, A. K. (1978). Are mathematics problems girls? In J. E. Jacobs (Ed.), Perspectives  211,  a problem  on women and  229.  for women and  mathematics.  Columbus, Ohio: ERIC Information Analysis Centre for Science, Mathematics, and Environmental Education.  Schonberger, A. K., &  Holden, C. C. (1984). Women as  science and  What helps them stick  technology:  with  university  students  it? Paper presented at  the annual meeting of the National Women's Studies Association, Brunswick, NJ.  in  New  / 109 Scottish Education Department (1959). Report curriculum  of senior  secondary  Leaving  Certificate.  the Scottish  of the working  school: Introduction  lines  of the Ordinary  Grade of  of secondary  education  on  boys and  girls  (Circular No. 600). Edinburgh: HMSO.  Scottish Education Department (1975). Differences in Scottish  on the  Edinburgh, HMSO.  Scottish Education Department (1965). Reorganisation comprehensive  party  secondary  schools:  A  report  of provision  by H.  for  M. Inspectors  of  Schools.  Edinburgh: HMSO.  Scottish Education Department (1986). School  leavers'  qualifications.  (Statistical  Bulletin NO. 1/E2). Edinburgh: Government Statistical Service.  Sells, L. (1978). Mathematics  Serbin, L. (1980). Teacher the  - a critical filter. The Science  expectations  and pupil  Teacher,  expectations.  Paper  45,,  28-29.  presented at  Organization in Schools Conference, Cambridge, England.  Serbin, L. (1983). The hidden curriculum: Academic consequences expectations. In M. Marland  (Ed.), Sex  differentiation  and  of teacher  schooling.  London:  Heinnemann Educational Books.  Sewell, W. and  H., Hauser, R. M., & achievement  in American  Featherman, D. L. (Eds.), (1976). society.  New  Schooling  York: Academic Press.  Sherman, J. (1977). Effects of biological factors on sex-related differences in mathematics achievement. In L. H. Fox & mathematics:  Research  perspectives  for change.  E. Fennema (Eds), Women Washington,  and  DC: National  Institute of Education.  Shepherd-Look, D. L. (1982). Sex differentiation and the development roles. In B. Wolman (Ed.), Handbook Cliffs, NJ: Prentice Hall.  of developmental  psychology.  of sex Englewood  /. 110 Shuard, H. (1986). The relative attainment of girls and boys in mathematics in the primary years. In L. Burton (Ed.), Girls  into mathematics  can  go.  London: Holt, Rinehart, and Winston.  Day, L. (1982). How  Skolnick, J., Langbort, C , & and  science.  to encourage  girls  in  math  Palo Alto, CA: Dale Seymour Publications.  Solano, C. (1976). Teacher and  student stereotypes  of gifted  presented at the annual meeting of the American  boys and girls.  Paper  Psychological Association.  Spencer, B. D. (1983). On interpreting test scores as social indicators: Statistical considerations. Journal  of Educational  Measurement,  20,  317-333.  Stage, E. K. (1986). Keeping young women in the talent pool: The effectiveness of precollege intervention programs. Paper presented the American  Stanic,  G. M., A  Educational  & Reyes,  case study  meeting  Research  L. H.  (1986).  of a seventh-grade  of the American  at the annual  Association,  San  Gender  race differences  and  classroom.  Paper  meeting  of  Francisco.  in  mathematics:  presented at the annual  Educational Research Association, San Francisco.  Statistics Canada, (1982). The labour force: Annual  averages,  1972-1982.  Ottawa:  Government of Canada.  Stockard, J. (1980). Sex inequities in the experience of students. In J. Stockard et al (Eds.), Sex  Stockard, J., &  equity  Wood, J. W.  in education.  New  York: Academic Press.  (1984). The myth of female underachievement:  reexamination of sex differences in academic Educational  Research  Journal,  Tanner, J. M. (1962). Growth  underachievement.  11,  1-4.  American  21(4), 825-838.  at adolescence.  Springfield IL: Thomas.  Thomas, J. A. (1962). Efficiency in education: A n empirical study. Notebook,  A  Administrator's  / 111 Tibbets, S. L. (1975). Sex-roie stereotyping in the lower grades: Part of the pollution. Journal  Times  Educational  of Vocational  Supplement  Behaviour,  6, 225-261.  (1986, October).  Tobias, S. (1978). Overcoming  math anxiety.  New  York: W.  W.  Norton  &  Company.  Toronto Board of Education (1983). Mathematics:  The  invisible  Ontario: Toronto Board of Education, Mathematics  Townson, M.  filter.Toronto,  Department.  (1980, Spring). Riding a treadmill to poverty. Canadian  Business  I.,  early  Review.  Vondracek,  S.  childhood:  & Kirchner, An  aspirations.  Walden, R., & secondary  E.  examination  Journal  P.  (1974).  of young  of Vocational  children's  Behaviour,  Walkerdine, V. (1985). Girls schooling.  Bedford Way  University of London: Turnaround  Ward, M. (1979). Mathematics Evans/Methuen  Vocational  and  development  expressions  of  in  vocational  5, 251-260.  mathematics:  From  primary  to  Papers, 24. Institute of Education, Distribution Ltd.  and the 10-year old: Schools Council,  UK.  Educational.  Waters, B. K. (1981). The  test score decline:  A  review and  annotated  Alexandria, VA: Human Resources Organization. (ERIC  bibliography.  Document  Reproduction Service No. 207 995)  Wattanawaha, N. (1977). Spatial spatial  tasks.  White, K. M., &  ability  and  sex  in performance  on  M.Ed, thesis, Monash University.  Ouellette, P. L. (1980). Occupational preferences: Children's  projections for self and opposite sex. Journal 37-43.  differences  of Genetic  Psychology,  136,  / 112 White, K. R. (1982). The relation between socioeconomic status and academic achievement. Psychological  Bulletin,  Willms, J. D. (1983). Achievement  91(3),  461-481.  outcomes in public  and  private  high  schools.  Unpublished doctoral dissertation, Stanford University, Palo Alto, CA.  Willms, J. D. (1985). Catholic schooling effects on academic achievement: evidence from the High School and Beyond Follow-up Education,  58(2),  New  Study. Sociology  of  98-114.  Willms, J. D. (1986, April). Social class segregation and its relationship to pupils' examination results in Scotland. American  Sociological  Review,  51,  224-241.  Willms, J. D. (1987). Differences between Scottish education authorities in their examination  attainment. Oxford  Willms, J. D., &  Review  of Education,  13(2),  211-232.  Kerr, P. D. (1987, Spring). Changes in sex differences in  Scottish examination results since 1976. Journal  of Early  Adolescence, 7(1),  85-105. Wise, L. L. (1978). The  role of mathematics  presented at the annual meeting  in women's career development:  of the American  Paper  Psychological Association,  Toronto.  Petersen, A. C. (Eds.) (1979). Sex-related  Wittig, M. A., & functioning:  Developmental  Wright, R. J., &  issues.  New  differences  in  cognitive  York: Academic Press.  Bean, A. G. (1974). The influence of socioeconomic status on  the predictability of college performance. Journal  of Educational  Measurement,  11, 277-284.  Wolleat, P. L., Pedro, J. D., Becker, A. D., &  Fennema, E. (1980). Sex  differences in high school students' causal attributions of performances in mathematics.  Journal  for Research  in Mathematics  Education,  11(5),  356-366.  


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