Learning to Program: Gender Differences and Interactive Effects of Students' Motivation, Goals, and Self-Efficacy on Performance
Abstract
Previous research in computer science education has demonstrated the importance of motivation for success in introductory programming. Theoretical constructs from self-regulated learning theory (SRL), which integrates several different types of metacognitive processes, as well as motivational constructs, have proved to be important predictors of success in most academic disciplines. These individual components of self-regulated learning (e.g., self-efficacy, metacognitive strategies) interact in complex ways to influence students' affective states and behaviors, which in turn influence learning outcomes. These elements have been previously examined individually in novice programmers, but we do not have a comprehensive understanding of how SRL constructs interact to influence learning to program. This paper reports on a study that examined the interaction of self-efficacy, intrinsic and extrinsic goal orientations, and metacognitive strategies and their impact on student performance in a CS1 course. We also report on significant gender differences in the relationships between SRL constructs and learning outcomes. We found that student performance had the expected motivational and SRL precursors, but the interactions between these constructs revealed some unexpected relationships. Furthermore, we found that females' self-efficacy had a different connection to programming performance than that of their male peers. Further research on success in introductory programming should ta…
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Self-efficacy can affect performance via goal orientation, and performance impacts self-efficacy again.
“Interestingly, Self-efficacy can affect performance via goal orientation, and performance impacts self-efficacy again (Nazari, 2020; Lishinski et al., 2016).”
From Application of Artificial Intelligence powered digital writing assistant in higher education: randomized controlled trial (2021) · cites this paper as Lishinski et al., 2016
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- Authors
- Lishinski, A., Yadav, A., Good, J., & Enbody, R.
- Affiliations
- Michigan State University, East Lansing, MI, USA
- Venue
- Proceedings of the 2016 ACM Conference on International Computing Education Research
- Publisher
- ACM
- Published
- 2016-08-25
- Pages
- 211-220
- Cited by
- 166
- References
- 10
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