Minneapolis, MN
August 23, 2022
June 26, 2022
June 29, 2022
18
10.18260/1-2--41778
https://strategy.asee.org/41778
257
Becky Matz is a Research Scientist on the Research & Development team at the Center for Academic Innovation at the University of Michigan. She directs and supports research projects across CAI’s portfolio of educational technologies. Becky has research experience in assessing the efficacy of software tools that support student learning and success, analyzing quantitative equity disparities in STEM courses across institutions, and developing interdisciplinary activities for introductory chemistry and biology courses.
Mark Mills is a Data Scientist on the Research & Development team at the Center for Academic Innovation at the University of Michigan. He directs and supports data analytics across CAI’s portfolio of educational technologies. Mark has experience in assessing the efficacy of software tools that support student learning and success, analyzing equity disparities in STEM courses across colleges, and developing actionable insights for instructors, departments, and colleges.
Caitlin Hayward is the Associate Director for Research & Development at the University of Michigan Center for Academic Innovation. She is responsible for managing the educational research portfolio, with a focus on ensuring that our projects are taking advantage of the vast amount of data available to them to inform prioritization, design, and iteration. Caitlin's work focuses on translational research, learning analytics, educational motivation, and gameful pedagogy.
Madison Jeffrey is a graduate candidate in the University of Michigan's Masters in Higher Education program. With a focus on Management and Organizations, she's interested in ways in which the system of higher education can adapt to become more accessible and equitable to students. She's a research assistant at the University of Michigan's Center of Academic Innovation, where she works with a team of researchers responsible for Tandem, a software that monitors team performance to link students and instructors.
Andrew Moffat is a postdoctoral research fellow at the Engineering Education Research unit at the University of Michigan, exploring ways to evaluate the effectiveness of Tandem, an in-house software platform designed to help undergraduate students develop teamwork skills. Andrew has experience in education research and evaluation, having previously worked in the Leeds Institute for Teaching Excellence at the University of Leeds in the UK. His interests in learning and technology stem from a background in English language teaching.
Gendered differences in academic confidence and self-efficacy between men and women are well-documented. In STEM fields and specifically in engineering, such differences have important consequences in that students low on these constructs are often more prone to leave their degree programs. While this evidence base is fairly established, less is known about the extent to which men and women show differences in confidence of team success, or collective efficacy, which may also be consequential in decisions to join and persist in design team experiences, or even to stay in or leave an engineering major, especially for first-year students. In this analysis, we quantitatively investigated gendered differences in confidence of team success and collective efficacy among first-year engineering students working on semester-long design projects in stable teams. Using a software tool built to support equitable teamwork, survey data on team confidence and collective efficacy was collected for these engineering students as well as for students in other courses for the sake of comparison. Three hierarchical linear models were fit to the data from 1,806 students across 31 unique course/term combinations. The results were mixed. In two of these analyses, we identified significant interactions between gender and team confidence. Specifically, men generally reported higher team confidence scores than women throughout the term with women eventually catching up, and team confidence ratings increased for men but not women following a lesson on imposter syndrome. No gendered differences were observed with respect to a collective efficacy scale administered near the middle and end of the term, however. In all cases, the results were consistent across course type (engineering, business, and others).
Keywords: collective efficacy, engineering, first-year students, gender, team confidence, team success
Matz, R., & Mills, M., & Fowler, R., & Hayward, C., & Jeffrey, M., & Moffat, A. (2022, August), Mixed results for gendered patterns in confidence of team success and collective efficacy Paper presented at 2022 ASEE Annual Conference & Exposition, Minneapolis, MN. 10.18260/1-2--41778
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