Exploring students' adoption of ChatGPT as a mentor for undergraduate computing projects: PLS-SEM analysis

• Main Authors: GOTTIPATI Swapna, SHIM, Kyong Jin, SHANKARARAMAN, Venky
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2023
• Subjects: Artificial Intelligence; ChatGPT; computing projects; mentorship; PLS-SEM analysis; Artificial Intelligence and Robotics; Databases and Information Systems; Educational Assessment, Evaluation, and Research; Higher Education
• Online Access: https://ink.library.smu.edu.sg/sis_research/8503; https://ink.library.smu.edu.sg/context/sis_research/article/9506/viewcontent/ICCE_2023_ChatGPT_Camera_V1.0.pdf
• Institution: Singapore Management University

As computing projects increasingly become a core component of undergraduate courses, effective mentorship is crucial for supporting students' learning and development. Our study examines the adoption of ChatGPT as a mentor for undergraduate computing projects. It explores the impact of ChatGPT mentorship, specifically, skills development, and mentor responsiveness, i.e., ChatGPT's responsiveness to students' needs and requests. We utilize PLS-SEM to investigate the interrelationships between different factors and develop a model that captures their contribution to the effectiveness of ChatGPT as a mentor. The findings suggest that mentor responsiveness and technical/design support are key factors for the adoption of AI tools like ChatGPT. The study provides practical implications for educators seeking to incorporate AI as a mentor to support students doing computing projects and contributes to the broader understanding of the use of AI in education.