Variables related to the academic success of women engineering students

Whigham, Myrna

doi:10.31274/rtd-180813-13396

Cited by 4 publications

(17 citation statements)

References 37 publications

(41 reference statements)

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“…As previously noted, women who attempt engineering and other technical majors tend to be multi-talented, with correspondingly strong English and social science achievement scores (Jagacinski & Lebold, 1981;Whigham, 1985). Thus, they may expect to be successfiil in other fields as well as in mathematics.…”

Section: Value Of Outcomementioning

confidence: 97%

“…Data are mixed in observed gender differences in persistence rates. Some studies reported higher persistence rates for men than women in college science and mathematics majors (Lovely, 1987;Ott, 1978;Sanders, Benbow, & Albright, 1992;Ware, Steckler & Lesserman, 1985;Whigham, 1985). Conversely, Hilton and Lee (1988) found that young women persisted in science at a higher rate than young men between high school and first year in college.…”

Section: Persistence In Scientific and Mathematical Fieldsmentioning

confidence: 99%

“…Thus, the majority of women (persisters and transfers) were dissatisfied with their academic performance, with higher rates of dissatisfaction for women who persisted in engineering. In another study, Whigham (1985) found that freshmen women were uncertain if they would continue in engineering if they could only maintain a "C" grade point average.…”

Section: Goal Setting and Social Learning Theorymentioning

confidence: 99%

“…Women who enter engineering tend to be multi-talented students, with high standardized test scores in mathematics, English, and social sciences (Jagacinski & Lebold, 1981;Whigham, 1985). They would be expected to excel in a number of fields outside of mathematics and the sciences.…”

Section: Goal Setting and Social Learning Theorymentioning

confidence: 99%

“…There is a perception that scientific or mathematical college majors are more demanding than majors in other fields, fi'om the perspective of time commitment and sacrifices. Whigham (1985) asked college women about the sacrifices that women engineers have to make in their personal and social lives. The women participated in a seminar designed to provide support and educate the women about engineering as a field.…”

Section: Value Of Outcomementioning

confidence: 99%

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Women in engineering: factors affecting persistence and attrition in college majors

Schaefers

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Model with ability block entered first 109 Model with ability block entered last 110 Examining the model for parsimony 110 Logistic Regression Analysis using Pre-Choice Measures RESULTS 113 Persistence Status 113 Sample Representativeness 114 Questionnaire Form 115 Preliminary Analyses 116 Scales with Experimental Items 116 Math Self-Efficacy Courses Subscale (MSE-COURSES) 116 Outcome Expectations (OE) 117 Classroom Environment Scale (CES) 118

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Section: Value Of Outcomementioning

confidence: 97%

Section: Persistence In Scientific and Mathematical Fieldsmentioning

confidence: 99%

Section: Goal Setting and Social Learning Theorymentioning

confidence: 99%

Section: Goal Setting and Social Learning Theorymentioning

confidence: 99%

Section: Value Of Outcomementioning

confidence: 99%

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Women in engineering: factors affecting persistence and attrition in college majors

Schaefers

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Gender differences in mathematics performance: A meta-analysis.

Hyde

Fennema²,

Lamon³

1990

Psychological Bulletin

1,338

951

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Reviewers have consistently concluded that males perform better on mathematics tests than females do. To make a refined assessment of the magnitude of gender differences in mathematics performance, we performed a meta-analysis of 100 studies. They yielded 254 independent effect sizes, representing the testing of 3,175,188 Ss. Averaged over all effect sizes based on samples of the general population, d was -0.05, indicating that females outperformed males by only a negligible amount. For computation, d was -0.14 (the negative value indicating superior performance by females). For understanding of mathematical concepts, d was -0.03; for complex problem solving, d was 0.08. An examination of age trends indicated that girls showed a slight superiority in computation in elementary school and middle school. There were no gender differences in problem solving in elementary or middle school; differences favoring men emerged in high school (d = 0.29) and in college (d = 0.32). Gender differences were smallest and actually favored females in samples of the general population, grew larger with increasingly selective samples, and were largest for highly selected samples and samples of highly precocious persons. The magnitude of the gender difference has declined over the years; for studies published in 1973 or earlier d was 0.31, whereas it was 0.14 for studies published in 1974 or later. We conclude that gender differences in mathematics performance are small. Nonetheless, the lower performance of women in problem solving that is evident in high school requires attention.

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Relationships among freshman background characteristic variables, misconceptions about major and satisfaction with major area of study

298

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Variables related to the academic success of women engineering students

Cited by 4 publications

References 37 publications

Women in engineering: factors affecting persistence and attrition in college majors

Women in engineering: factors affecting persistence and attrition in college majors

Gender differences in mathematics performance: A meta-analysis.

Relationships among freshman background characteristic variables, misconceptions about major and satisfaction with major area of study

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