Artificial Intelligence Use in Honours Research: Implications for Supervision Relationships, Knowledge Development, and Research Quality

Abstract

The increasing use of artificial intelligence (AI) tools in higher education has reshaped how students engage with academic research, particularly at Honours level, where students transition from structured undergraduate learning to independent postgraduate research. Guided by Self‑Regulated Learning (SRL) theory, this study examines how reliance on AI by Honours research students influences the supervisor-supervisee relationship, the quality of research produced, and the extent of knowledge gained through the research process. SRL theory emphasises learners’ ability to plan, monitor, and reflect on their own learning, which is central to successful postgraduate research development. This study adopts a conceptual and literature‑based review methodology, drawing on peer‑reviewed studies on AI use in higher education, literature on postgraduate supervision, and academic integrity and research skills development frameworks, with specific attention to Honours‑level contexts. The documents were analysed using thematic content analysis, focusing on self‑regulatory behaviours, supervisory interaction, research skill development, and learning depth. The findings suggest that limited and transparent use of AI can support honours students by reducing surface‑level cognitive load and assisting with language clarity. However, excessive reliance on AI may undermine key self‑regulation processes, weaken critical thinking, and reduce meaningful engagement with supervisors. Supervisors may struggle to accurately assess students’ understanding, potentially straining trust and feedback processes. The review further indicates that over‑reliance on AI risks producing research that is technically adequate but conceptually shallow, with reduced long‑term knowledge acquisition. The study concludes that clear supervision practices and explicit guidance on responsible AI use are necessary to ensure that AI supports, rather than replaces, the self‑regulated learning essential for high‑quality Honours‑level research.

Keywords: {'name': 'Artificial intelligence'}, {'name': 'Honours Research'}, {'name': 'Research supervision'}, {'name': 'Research quality'}, {'name': 'Self-regulated learning'}

Authors & affiliations

Sympathy Luyanda Mncube
University of Venda

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