Self-Regulation, Self-Efficacy, and Fear of Failure Interactions with How Novices Use LLMs to Solve Programming Problems
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A4 Artikkeli konferenssijulkaisussa
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Date
2024-07-03
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Language
en
Pages
7
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Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE ; Volume 1
Abstract
We explored how undergraduate introductory programming students naturalistically used generative AI to solve programming problems. We focused on the relationship between their use of AI to their self-regulation strategies, self-efficacy, and fear of failure in programming. In this repeated-measures, mixed-methods research, we examined students' patterns of using generative AI with qualitative student reflections and their self-regulation, self-efficacy, and fear of failure with quantitative instruments at multiple times throughout the semester. We also explored the relationships among these variables to learner characteristics, perceived usefulness of AI, and performance. Overall, our results suggest that student factors affect their baseline use of AI. In particular, students with higher self-efficacy, lower fear of failure, or higher prior grades tended to use AI less or later in the problem-solving process and rated it as less useful than others. Interestingly, we found no relationship between students' self-regulation strategies and their use of AI. Students who used AI less or later in problem-solving also had higher grades in the course, but this is most likely due to prior characteristics as our data do not suggest that this is a causal relationship.Description
Publisher Copyright: © 2024 Owner/Author.
Keywords
artificial intelligence, copilot, CS1, fear of failure, generative ai, introductory programming, large language models, LLMs, metacognition, self-efficacy, self-regulated learning, self-regulation
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Citation
Margulieux, L E, Prather, J, Reeves, B N, Becker, B A, Cetin Uzun, G, Loksa, D, Leinonen, J & Denny, P 2024, Self-Regulation, Self-Efficacy, and Fear of Failure Interactions with How Novices Use LLMs to Solve Programming Problems . in ITiCSE 2024 - Proceedings of the 2024 Conference Innovation and Technology in Computer Science Education . Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE, vol. 1, ACM, pp. 276-282, Annual Conference on Innovation and Technology in Computer Science Education, Milan, Italy, 08/07/2024 . https://doi.org/10.1145/3649217.3653621