Gender differences in predictors of college mathematics performance and in college mathematics course grades.

Abstract

Grades of men and women in lst-year mathematics courses were obtained from a sample of 9 universities. In addition, placement test scores were available from 4 of the institutions. This information was combined with Scholastic Aptitude Test (SAT) scores and self-reported information on mathematics courses taken in high school, grades in those courses, and overall high school grade point average. College courses were divided into three categories (algebra, precalculus, and calculus). Within a given college mathematics course, the average grades of women were about equal to or slightly higher than men's average grades, but men's average scores on the mathematical scale of the SAT were above women's average scores by a third of a standard deviation or more.Several recent meta-analyses of gender differences in mathematical ability suggest that simple generalizations about the superiority of either gender are impossible (Feingold, 1988;Friedman, 1989;Hyde, Fennema, & Lamon, 1990). The size and even the direction of gender differences depend on a number of factors. The comprehensive review by Hyde et al. (1990) indicated that age, type of task (e.g., computation or problem solving), and selectivity of the sample all appear to be important determiners of gender differences. On computational tasks, female students seem to be slightly superior before high school, with little or no gender difference in high school. On problem-solving tasks, moderate-sized differences favoring male students start to appear in high school. These differences favoring male students in problem solving are larger in more select samples; as Hyde (1981) notes, relatively large differences may be expected in the tails of distributions that differ only slightly when the entire distribution is considered.Because college admissions tests focus (a) on older students (those enrolled in the later years of high school), (b) on problem-solving skills, and (c) on a relatively select sample, superior performance by boys would be expected from the trends summarized above. However, the degree of male advantage on these tests, especially on the Mathematics subscale (M) of the Scholastic Aptitude Test (SAT) has caused some reviewers to characterize the gender difference as "anomalous" (Linn & Hyde, 1989) or "discrepant" (Hyde etal., 1990). On the Scholastic Aptitude Test-Mathematics subscale (SAT-M), which ranges from 200 to 800 points, the gender difference is about 46 points, or 0.39 d (in which d represents the difference between the two means divided by the pooled standard deviation; College Board, 1989). On the American College Testing Program (ACT) Mathematics Usage scale, This research was funded in part by the College Board. The conclusions and opinions expressed are those of Brent Bridgeman and Cathy Wendler.

College Major and Gender Differences in the Prediction of College Grades

“…In contrast, differences between the actual and predicted grades for females in these groups using the HSGPA-only model were closer to zero (0.014 and -0.032, respectively). These results are consistent with those of Bridgeman and Wendler (1991), who found that SAT-M underpredieted female students' grades in individual mathematics courses. Thus, SAT·M underpredicted the academic achievement of female students in mathematics and in the broad spectrum of courses taken by science and nonscience majors.…”

The role of motivation in gendered educational and occupational trajectories related to maths

“…This has prompted research emphases directed at understanding boys' and girls' mathematical participation, such as within the ExpectancyValue framework of Eccles and colleagues (e.g., Eccles (Parsons) et al, 1983;Wigfield & Eccles, 2000). Since Lucy Sells voiced social concerns about female ''underparticipation'' in maths courses by identifying maths as a ''critical filter'' which limits access to many high-status high-income careers (Sells, 1980), other researchers have also argued that many females prematurely restrict their educational and career options by discontinuing their mathematical training in high school or soon after (Heller & Parsons, 1981;Meece, Wigfield, & Eccles, 1990), with fewer females electing to study maths in post-secondary education (Bridgeman & Wendler, 1991;Lips, 1992). In the Australian context, the plethora of government policy documents and reports targeting girls' maths education also testifies to a general concern with girls' lower mathematical participation at school (see Leder & Forgasz, 1992, for a review of these curricular and professional development initiatives).…”

The Quantitative Reasoning for College Science (QuaRCS) Assessment 2: Demographic, Academic and Attitudinal Variables as Predictors of Quantitative Ability

“…Still, large-scale studies have reported a small but significant "female advantage" in course achievement across all subjects, including mathematics (Bridgeman and Wendler 1991;Correll 2001;Voyer and Voyer 2014). A "male advantage" remains on performance of standardized tests of mathematics, though this has been consistently tied to persistent attitudinal and psychosocial factors, rather than ability (Bridgeman and Wendler 1991;Correll 2001;Voyer and Voyer 2014).…”