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"With Great Power Comes Great Responsibility!": Student and Instructor Perspectives on the influence of LLMs on Undergraduate Engineering Education

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arxiv 2309.10694 v2 pith:CFGQUK2X submitted 2023-09-19 cs.HC cs.AIcs.CYcs.ET

classification cs.HCcs.AIcs.CYcs.ET
keywords llmsstudentsinstructorsengineeringinterviewsundergraduateacademiceducation
verification ladder T0 review T1 audit T2 compute T3 formal
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The rise in popularity of Large Language Models (LLMs) has prompted discussions in academic circles, with students exploring LLM-based tools for coursework inquiries and instructors exploring them for teaching and research. Even though a lot of work is underway to create LLM-based tools tailored for students and instructors, there is a lack of comprehensive user studies that capture the perspectives of students and instructors regarding LLMs. This paper addresses this gap by conducting surveys and interviews within undergraduate engineering universities in India. Using 1306 survey responses among students, 112 student interviews, and 27 instructor interviews around the academic usage of ChatGPT (a popular LLM), this paper offers insights into the current usage patterns, perceived benefits, threats, and challenges, as well as recommendations for enhancing the adoption of LLMs among students and instructors. These insights are further utilized to discuss the practical implications of LLMs in undergraduate engineering education and beyond.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Insights from the Frontline: GenAI Utilization Among Software Engineering Students

    cs.HC 2024-12 accept novelty 6.0 of 10

    Students found generative AI helpful for incremental learning and initial implementation, but challenging for first-time concept learning and advanced implementation, with causes traced to intrinsic AI faults and gaps.

  2. Howzat? Appealing to Expert Judgement for Evaluating Human and AI Next-Step Hints for Novice Programmers

    cs.CY 2024-11 conditional novelty 6.0 of 10

    With a carefully designed multi-stage prompt, GPT-4 generated next-step hints that Java educators ranked higher than hints written by experienced human educators.

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