Exploring Generative AI for Postgraduate Research Supervision

Higher Education is at a crossroads. Large language models (LLMS) have changed universities irrevocably. In the context of graduate studies and post-graduate research outputs, the responsibility of research supervisors is ever more pertinent. Post-graduate students rely upon their supervisors to provide guidance along the supervisory journey. Supervisors are tasked with ensuring positive outcomes for graduates that are integral, values led and represent the university research philosophy. This culture is carried by graduates into their world of work, and their university guidance and experience will have consequences for society at large. Universities and post-graduate supervisors now stand at a critical juncture in the history of artificial intelligence (AI), looking for key signposts to ensure robust and ethical research outputs and impact. This current study explores critical challenges for post-graduate supervision and the ultimate research outputs in Higher Education. Universities must embed excellent research practices, placing societal concerns front and centre, to effect long-term change in all research disciplines. A post-positivism approach is applied for this empirical study where 103 research supervisors and 25 post-graduate research students contributed. Findings outline a critical need to standardise practice across all post-graduate study and supervisory practices as AI and GenAI move at a phenomenal pace in pursuit of profit for creators and developers. Universities must exercise their power to support ethically scalable processes that will secure the learning environment for all, providing unassailable guardrails for the future of AI, while protecting students, practitioners and society.