Optimizing RAG in Programming Education: A Comparative Study of Models and Strategies

This study examines how Retrieval-Augmented Generation (RAG) enhances the effectiveness of generative artificial intelligence in programming education. This study compares commercial and open-source large language models within a RAG system, examining how retrieval design and prompt engineering affe...

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Veröffentlicht in:	IEEE access Jg. 13; S. 190890 - 190903
Hauptverfasser:	Yang, Christopher C. Y., Liu, Guan-Jie, Yu, Cheng-Jui
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Accuracy Adaptation models AI in education Artificial intelligence Biological system modeling Cognition Comparative studies Costs Education Effectiveness generative AI Generative artificial intelligence Large language models LLMs Machine learning Open source software Performance enhancement Programming programming education Programming profession Prompt engineering Recall Retrieval Retrieval augmented generation Retrieval-augmented generation (RAG) retrieval-augmented generation assessment (RAGAS)
ISSN:	2169-3536, 2169-3536
Online-Zugang:	Volltext
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