Evaluating the Quality of LLM-Generated Explanations for Logical Errors in CS1 Student Programs-Reference-Cited by-同舟云学术

Evaluating the Quality of LLM-Generated Explanations for Logical Errors in CS1 Student Programs

Published:2023-12-09 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 16th Annual ACM India Compute Conference
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Author:

Balse Rishabh¹^ORCID,Kumar Viraj²^ORCID,Prasad Prajish³^ORCID,Warriem Jayakrishnan Madathil⁴^ORCID

Affiliation:

1. BS Programme in Data Science and Applications, Indian Institute of Technology Madras, India

2. Indian Institute of Science, India

3. School of Computing and Data Sciences, FLAME University, India

4. National Programme on Technology Enhanced Learning (NPTEL), Indian Institute of Technology Madras, India and BS Programme in Data Science and Applications, Indian Institute of Technology Madras, India

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3627217.3627233

Reference26 articles.

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4. Julio C Caiza and Jose M Del Alamo . 2013 . Programming assignments automatic grading: review of tools and implementations . INTED2013 Proceedings (2013), 5691–5700. Julio C Caiza and Jose M Del Alamo. 2013. Programming assignments automatic grading: review of tools and implementations. INTED2013 Proceedings (2013), 5691–5700.

5. Mark Chen , Jerry Tworek , Heewoo Jun , Qiming Yuan , Henrique Ponde de Oliveira Pinto , Jared Kaplan, Harri Edwards, Yuri Burda , Nicholas Joseph, Greg Brockman , 2021 . Evaluating large language models trained on code. arXiv preprint arXiv:2107.03374 (2021). Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde de Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, 2021. Evaluating large language models trained on code. arXiv preprint arXiv:2107.03374 (2021).

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