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Effects of Gender, Effort, and Spatial Visualization Abilities in an Engineering Graphics Class

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2019 ASEE Annual Conference & Exposition


Tampa, Florida

Publication Date

June 15, 2019

Start Date

June 15, 2019

End Date

June 19, 2019

Conference Session

Engineering Design Graphics Division Technical Session 3 - Spatial Visualization Topics

Tagged Division

Engineering Design Graphics

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Paper Authors


Hannah Budinoff University of California, Berkeley Orcid 16x16

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Hannah Budinoff is a PhD student studying mechanical engineering at the University of California, Berkeley. She is advised by Prof. Sara McMains and works on research related to additive manufacturing in the Computer Aided Design and Manufacturing Lab. She holds a B.S. in mechanical engineering from the University of Arizona and an M.S. in mechanical engineering from the University of California, Berkeley.

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Audrey Ford University of California, Berkeley

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Audrey Ford is a 5th year PhD candidate in mechanical engineering at the University of California Berkeley.

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Sara McMains University of California, Berkeley Orcid 16x16

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Professor McMains directs the Computer-Aided Design and Manufacturing Lab in the Department of Mechanical Engineering at the University of California, Berkeley. Her pedagogical research interests include engineering design visualization and auto-grading of engineering drawings. Her other research interests include Geometric DFM (Design for Manufacturing) feedback, computational geometry, geometric and solid modeling, CAD/CAM, GPU algorithms, computer aided process planning, additive manufacturing, computer vision, and machine learning. She received her A.B. from Harvard University in Computer Science, and her M.S. and Ph.D. from UC Berkeley in Computer Science with a minor in Mechanical Engineering. Her research has been recognized with various best paper awards (Usenix, ASME DETC, ACM Solid and Physical Modeling Symposium, NAMRC), the Audi Production Award, and the NSF CAREER Award.

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The objective of this study is to understand the interaction between gender, spatial visualization ability, effort, and course outcomes in an engineering graphics course. Within engineering, spatial visualization ability is essential to many applications, beginning with engineering graphics. Engineering graphics courses are commonly introductory-level classes in engineering programs, creating challenges for women, who on average score lower on tests of spatial visualization ability. Improved understanding of gender differences in engineering graphics classes could therefore help identify pedagogical areas to support women and increase their retention in engineering programs. Although a gender gap exists in spatial ability and performance in engineering graphics classes, female students still achieve positive course outcomes. We hypothesize that: 1) female students put more effort into engineering graphics courses; and 2) that this greater effort (measured as time spent on homework, homework scores, quiz scores and attendance) by female students reduces the gender gap in course and exam grades. By analyzing scores on homework, quizzes, exams, and attendance in addition to total course score, we can better assess differences between students and quantify the relative importance of different factors like effort and ability on student performance. We present data from three semesters of a freshman-level engineering graphics course at a large research university and analyze differences in spatial visualization ability and course outcomes of male students (n=232) and female students (n=76). Female students scored lower on spatial visualization tests and course exams but had higher performance in less time-restricted, effort-related outcomes, such as attendance and homework scores, compared to male students. However, on average, female students had lower overall course grades. After accounting for the spatial ability gender gap by comparing students in groups of similar visualization ability, we found that female students with high spatial visualization abilities tended to have better performance on less time-restricted, effort-related outcomes and took more time on homework, but still had lower exam and course scores than their male counterparts. It appears that the gender gap in performance may not be explained fully by spatial visualization, but could be related to gender differences in testing. Better understanding of the differences between male and female students of similar visualization ability could help educators identify opportunities to leverage these differences in developing pedagogical strategies to support women in introductory engineering graphics courses and further engineering pursuits.

Budinoff, H., & Ford, A., & McMains, S. (2019, June), Effects of Gender, Effort, and Spatial Visualization Abilities in an Engineering Graphics Class Paper presented at 2019 ASEE Annual Conference & Exposition , Tampa, Florida. 10.18260/1-2--32695

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