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Decoding Logic Errors: A Comparative Study on Bug Detection by Students and Large Language Models., , , , , , , and . CoRR, (2023)"Like a Nesting Doll": Analyzing Recursion Analogies Generated by CS Students Using Large Language Models., , , , , , , and . ITiCSE (1), ACM, (2024)Comparing Code Explanations Created by Students and Large Language Models., , , , , , , and . ITiCSE (1), page 124-130. ACM, (2023)The Implications of Large Language Models for CS Teachers and Students., , , , , , , , , and 2 other author(s). SIGCSE (2), page 1255. ACM, (2023)Automatically Generating CS Learning Materials with Large Language Models., , , , , , , and . SIGCSE (2), page 1176. ACM, (2023)Experiences from Using Code Explanations Generated by Large Language Models in a Web Software Development E-Book., , , , , , , and . SIGCSE (1), page 931-937. ACM, (2023)Decoding Logic Errors: A Comparative Study on Bug Detection by Students and Large Language Models., , , , , , , and . ACE, page 11-18. ACM, (2024)Analyzing Students' Preferences for LLM-Generated Analogies., , , , , and . ITiCSE (2), ACM, (2024)Generating Diverse Code Explanations using the GPT-3 Large Language Model, , , , , and . Proceedings of the 2022 ACM Conference on International Computing Education Research - Volume 2, volume 2 of ICER '22, page 37–39. New York, NY, USA, Association for Computing Machinery, (Aug 7, 2022)