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.
"With Great Power Comes Great Responsibility!": Student and Instructor Perspectives on the influence of LLMs on Undergraduate Engineering Education
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
abstract
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.
citation-role summary
background 1
citation-polarity summary
fields
cs.HC 1years
2024 1verdicts
ACCEPT 1roles
background 1polarities
unclear 1representative citing papers
citing papers explorer
-
Insights from the Frontline: GenAI Utilization Among Software Engineering Students
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.