Proceedings of the 55th ACM Technical Symposium on Computer Science Education v. 1 2024
DOI: 10.1145/3626252.3630958
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Use of AI-driven Code Generation Models in Teaching and Learning Programming: a Systematic Literature Review

Doga Cambaz,
Xiaoling Zhang

Abstract: The recent emergence of AI-driven code generation models can potentially transform programming education. To pinpoint the current state of research on using AI code generators to support learning and teaching programming, we conducted a systematic literature review with 21 papers published since 2018. The review presents the teaching and learning practices in programming education that utilize these models, the characteristics and performance indicators of the code generation models, and aspects to be consider… Show more

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Cited by 2 publications
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