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ChatGPT in the Classroom: an Analysis of Its Strengths and Weaknesses for Solving Undergraduate Computer Science Questions

Ishika Joshi,Ritvik Budhiraja,Harshal Dev, Jahnvi Kadia, M. Osama Ataullah, Sayan Mitra,Dhruv Kumar,Harshal D. Akolekar

arXiv (Cornell University)(2023)

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摘要
ChatGPT is an AI language model developed by OpenAI that can understand and generate human-like text. It can be used for a variety of use cases such as language generation, question answering, text summarization, chatbot development, language translation, sentiment analysis, content creation, personalization, text completion, and storytelling. While ChatGPT has garnered significant positive attention, it has also generated a sense of apprehension and uncertainty in academic circles. There is concern that students may leverage ChatGPT to complete take-home assignments and exams and obtain favorable grades without genuinely acquiring knowledge. This paper adopts a quantitative approach to demonstrate ChatGPT's high degree of unreliability in answering a diverse range of questions pertaining to topics in undergraduate computer science. Our analysis shows that students may risk self-sabotage by blindly depending on ChatGPT to complete assignments and exams. We build upon this analysis to provide constructive recommendations to both students and instructors.
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Student Performance Prediction,Topic Modeling
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