Investigating the Division of Labour in Student-AI-Collaboration on Critical Thinking Tasks
Journal
2025 IEEE International Conference on Advanced Learning Technologies (ICALT)
ISSN
2161-3761
Type
conference paper
Date Issued
2025
Author(s)
Abstract
This study investigates the division of labor between students and generative AI in solving tasks addressing critical thinking. Three key research interests guide the study: (1) the extent of ChatGPT usage by students, (2) the division of labour between student and AI as perceived by students, ChatGPT, and an expert, and (3) if these ratings align with each other. An experiment involving 20 undergraduate students who completed 11 tasks using ChatGPT was carried out. Findings demonstrated substantial variation in the extent of ChatGPT usage among students. The division of labour analysis revealed that ChatGPT is used most heavily for reasoning tasks, and that students consistently rated the AI's contribution to their task solutions as slightly lower than both ChatGPT and the expert. Correlations of the ratings indicated strong alignment between students and ChatGPT, but weaker alignment with the expert perspective, particularly in the metacognition domain. These results highlight the need for enhanced integration of AI in educational practices, focusing on fostering students' understanding of AI capabilities while promoting critical engagement. Future research should explore diverse populations, a broader range of task types, and the long-term impact of AI integration to enhance the effective use of generative AI in education.
Language
English
Keywords
Artificial Intelligence (AI
Generative AI
ChatGPT
Critical Thinking (CT)
Division of Labour
Publisher
IEEE
Start page
249
End page
253
Event Title
2025 IEEE International Conference on Advanced Learning Technologies (ICALT)
Event Location
Changhua, Taiwan
Event Date
14-17 July 2025
Subject(s)
Division(s)