My Learnings from Allowing Large Language Models in Introductory Computer Science Classes

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Abstract

Many instructors want to allow their students to use large language models (LLMs) in their introductory computer science courses, but they first want to see other instructors' results from doing so before taking on the risk in their own courses. Presented here are the results from allowing students to use LLMs in the second course in a sequence of intensive introductory courses designed to prepare students with a non-computational background for entry into a masters' degree program. We allowed students to use the internet and LLMs (such as ChatGPT or Github Copilot) to help with assignments, with guidelines to avoid plagiarism and encourage learning. We then surveyed students to ask about how they used LLMs, whether they saw others cheating, how they generally used internet-based resources on assignments and exams, and their feedback on the policies. We found that students are overwhelmingly using LLMs (and the internet generally) to learn and code "better"rather than cheat. These results are intended to be a starting point to spark discussion on the adoption of new technologies in introductory computer science courses. The authors themselves will continue teaching courses with the policy that students should interact with an LLM the way they interact with a person: students are encouraged to discuss and collaborate with it, but copying code from it is considered plagiarism.

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APA

Bhalerao, R. (2024). My Learnings from Allowing Large Language Models in Introductory Computer Science Classes. In SIGCSE 2024 - Proceedings of the 55th ACM Technical Symposium on Computer Science Education (Vol. 2, pp. 1574–1575). Association for Computing Machinery, Inc. https://doi.org/10.1145/3626253.3635511

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