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Title: Computing Self-Efficacy in Undergraduate Students: A Multi-Institutional and Intersectional Analysis
Computing self-efficacy is an important factor in shaping students' motivation, performance, and persistence in computer science (CS) courses. Therefore, investigating computing self-efficacy may help to improve the persistence of students from historically underrepresented groups in computing. Previous research has shown that computing self-efficacy is positively correlated with prior computing experience, but negatively correlated with some demographic identities (e.g., identifying as a woman). However, existing research has not demonstrated these patterns on a large scale while controlling for confounding variables and institutional context. In addition, there is a need to study the experiences of students with multiple marginalized identities through the lens of intersectionality. Our goal is to investigate the relationship between students' computing self-efficacy and their prior experience in computing, demographic identities, and institutional policies. We conduct this investigation using a large, recent, and multi-institutional dataset with survey responses from 31,425 students. Our findings confirm that more computing experience positively predicts computing self-efficacy. However, identifying as Asian, Black, Native, Hispanic, non-binary, and/or a woman were statistically significantly associated with lower computing self-efficacy. The results of our work point to several future avenues for self-efficacy research in computing.  more » « less
Award ID(s):
2229612 1821136
PAR ID:
10496747
Author(s) / Creator(s):
; ;
Publisher / Repository:
ACM
Date Published:
Journal Name:
Proceedings of the 55th ACM Technical Symposium on Computer Science Education V.1
ISBN:
9798400704239
Page Range / eLocation ID:
993 to 999
Format(s):
Medium: X
Location:
Portland OR USA
Sponsoring Org:
National Science Foundation
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