mlsanityData to 7 Oct 2026

A Survey Study on the State of the Art of Programming Exercise Generation using Large Language Models

arXiv 2405.20183 ↗First posted 30 May 2024cs.AI cs.SEcited by 1

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Abstract (arXiv)

This paper analyzes Large Language Models (LLMs) with regard to their programming exercise generation capabilities. Through a survey study, we defined the state of the art, extracted their strengths and weaknesses and finally proposed an evaluation matrix, helping researchers and educators to decide which LLM is the best fitting for the programming exercise generation use case. We also found that multiple LLMs are capable of producing useful programming exercises. Nevertheless, there exist challenges like the ease with which LLMs might solve exercises generated by LLMs. This paper contributes to the ongoing discourse on the integration of LLMs in education.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 19 of its 26 references that are in the map. First posted on arXiv 30 May 2024.

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19 of 26 references.

References · 19

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7 more
  1. 2023The Robots are Here: Navigating the Generative AI Revolution in Computing Educationcited by 85
  2. 2023Practical and Ethical Challenges of Large Language Models in Education: A Systematic Scoping Reviewcited by 83
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  7. 2024Iris: An AI-Driven Virtual Tutor For Computer Science Educationcited by 9

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