Abstract Book of the 10th International Conference on Advanced Research in Education, Teaching and Learning
Year: 2025
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University Research Supervisors’ Responses to Generative AI in the context of Institutional Policy Lag
Prof. Suriamurthee Moonsamy Maistry
ABSTRACT:
Universities across the world have been affected by the advent of Generative AI. Its human-like responses, a product of advanced natural language processing capabilities, will likely appeal significantly to the higher education fraternity. The academic research community whose enterprise constitutes knowledge production is also likely to be profoundly impacted by this technological advancement. Given the speed at which generative AI has moved in the recent twelve months, it is not unusual that bureaucracies like large comprehensive universities would experience some degree of inertia in reviewing and updating existing research, ethics and plagiarism policy guidelines. In the context of this policy lag, this paper reports on a qualitative study of university academics’ research supervision dispositions concerning the use of AI in Master’s and doctoral supervision. Theoretically, the paper draws on the Unified Theory of Acceptance and Use of Technology (UTAUT). The study sample comprised thirty university research supervisors and was drawn from a research-led university in South Africa. Data for this study was generated using an open-ended survey questionnaire, and a thematic analysis protocol was applied to establish the key findings. The study revealed diverse perspectives on using AI language models like ChatGPT in academic research, particularly regarding its role in academic writing and ethics. Many participants viewed ChatGPT as a valuable tool for enhancing students’ writing skills, highlighting its ability to assist with idea generation and editing, and serving as a benchmark for quality. However, concerns were raised about the risk of students violating plagiarism policies, compromising their writing abilities and critical thinking. The paper offers insights into higher education research supervision with AI as an enabler, especially regarding the competencies expected of doctoral candidates.
Keywords: artificial intelligence, research supervision, academic writing, ethics, plagiarism