Conference paper 2025

Understanding the Use Behaviour of Gen AI Among Full Time Students and Apprenticeship Trainees in Higher Education

2025 13th International Conference on Information and Education Technology, ICIET 2025
Conference · pp. 18-25
Abstract

As we reach the second anniversary since the announcement of ChatGPT to the world in Nov 2022, the education sector, especially in the institutes of higher learning (IHLs) has seen an exponential growth in the use of Generative AI (Gen AI). The use of Gen AI in IHLs is warranted as it commits to preparing students for the workforce and is obliged in duty to embrace Gen AI in its classrooms. But the use of Gen AI in classrooms are not without challenges. A survey conducted in the US states that 85 % of undergraduates feel more comfortable using GenAI tools if they were vetted by academic sources, and a further 65 % agreed that AI will improve their learning. However, there are many factors that led to the student's agreement in the use of AI, in particular Gen AI. Among others, the student's own (i) performance expectation, in that using Gen AI will help improve their academic performance; (ii) or their social influence, in that people close to them encourage their use of AI for their academic work, (iii) or their perceived anthropomorphism of the AI tool, in that they find that they have a 'buddy' that is close to them and that they can confide in their buddy for any queries they have of their course contents, or (iv) that the institution policy encourages their use of Gen AI in their school work. This study reports on the use behaviour of two groups of students - full time versus part time students. The findings suggests that the full-time students' Gen AI use is driven by social influence and perceived anthropomorphism, while apprenticeship students are more driven by institutional policy. Both groups of students are equally driven by the use of Gen AI to improve their academic outcome. © 2025 IEEE.

Keywords

Author Keywords

Generative AI Apprenticeship training social influence Full-Time Study Institutional Policy Perceived Anthropomorphism Performance Expectation Use Behaviour

Index Keywords

Curricula High educations Personnel training Apprentices Education computing Students artificial intelligence social influence Apprenticeship training Behavioral research Economic and social effects Higher learning Generative AI Full-time study Institutional policies Perceived anthropomorphism Performance expectations Use behavior
Author Affiliations
Institute of Technical Education, Singapore City, Singapore
Funding & Acknowledgements
No funding information
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