Artificial intelligence as a reflexive collaborator in graduate studies supervision

Oct 15, 2026

Uploaded by Margaret

The incorporation of generative artificial intelligence in doctoral supervision marks a transformative development in higher education, especially in emotionally complex fields such as sexuality studies. This reflective, collaborative autoethnographic study examines a doctoral student’s and supervisor’s experiences with AI generative tools to improve research processes, supervision quality, and intellectual inquiry. Grounded in Kolb’s Experiential Learning Theory and an augmented experiential learning framework, the study shows AI supports critical thinking, methodological innovation, ethical reflexivity, writing, and emotional resilience while addressing challenges such as bias, overreliance, and contextual insensitivity.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages8

Reading Time20 min

AccessFree to download

Introduction

Background and opportunities for AI in supervision

Research focus and approach

Transformation in Higher Education ISSN: (Online) 2519-5638,(Print) 2415-0991 ~~ ~~ Page 1 of 8 Origina~~l Research ~~ Artificial intelligence as a reflexive collaborator in graduate studies supervision Authors: Anthony Brown1 Jane Rossouw2 Affiliations: 1School of Interdisciplinary Research and Graduate Studies, College of Graduate Studies, University of South Africa, Pretoria, South Africa 2Department of Psychology of Education, College of Education, University of South Africa, Pretoria, South Africa Corresponding author: Anthony Brown, [browna@unisa.ac.za](browna@unisa.ac.za) Dates: Received: 27 July 2025 Accepted: 19 Nov. 2025 Published: 07 Feb. 2026 How to cite this article: Brown, A. & Rossouw, J., 2026, ‘Artificial intelligence asa reflexive collaborator in graduate studies supervision’, Transformation in Higher Education 11(0), a657 . [https://doi.org/10.4102/](https://doi.org/10.4102/)[ ](https://doi.org/10.4102/)[the.v11i0.657](the.v11i0.657) Copyright: © 2026. The Authors. Licensee: AOSIS. This work is licensed under the Creative Commons Attribution 4.0 International (CC BY 4 .0) license ([https://creativecommons](https://creativecommons). org/licenses/by/4 .0/) . Read online: Scan this QR code with your smart phone or mobile device to read online. The incorporation of generative artificial intelligence (AI) in doctoral supervision signifies a transformative evolution in higher education. This has been significant, particularly within intricate and emotionally complex research such as sexuality studies. This reflective, collaborative autoethnographic study investigates the experiences of a doctoral student and her supervisor. They explored AI generative tools to enhance research processes, quality of supervision and intellectual inquiry. Anchored in Kolb’s Experiential Learning Theory andreconceptualised through an augmented experiential learning framework, the study elucidateshow AI tools like ChatGPT encourage critical thinking. These tools were also used to foster methodological innovation and facilitate ethical reflexivity. Through iterative engagements, AI supported the formulation of sophisticated research questions and bolstered academic writing. It also aided emotional resilience in traversing heteronormative and interdisciplinary landscapes. The study highlights the evolving role of supervisors, not as gatekeepers but as collaboratorsinAI-informed learning. Significant emphasis was placed on prompt engineering, scholarly scrutiny and academic integrity. Ethical guidelines and rigorous documentation practices ensured a responsible AI application without sacrificing originality. Contribution: The findings reveal that AI-augmented supervision promotes deeper theoretical engagement and enhances self-directed learning. It also introduces new pedagogical possibilities for complex research endeavours. Nonetheless, the study also underscores the challenges of bias, overreliance and contextual insensitivity inherent in AI outputs. By suggesting actionable strategies for ethical integration, this paper contributes to emerging global discussions on AI in higher education. It presents a framework for inclusive, transformative and contextually aware supervision practices. Keywords: AI-augmented supervision; doctoral research; experiential learning; ethical AI integration; graduate studies; augmented experiential learning. Introduction The rise of artificial intelligence (AI) tools in higher education has opened new opportunities for the supervision of graduate research. Graduate students globally reported how AI generative tools enhance research competencies, refine academic writing and deepen conceptual grasp as they uphold ethical standards (Khalifa & Albadawy 2024; Nartey 2024; Vargas-Murillo, De la Asuncion & De Jesús Guevara-Soto 2023) . More specifically, in studies related to sexual health, 14 studies illustrated how AI generative tools were used to augmen

FAQs

What is the main focus of the study on AI in graduate supervision?

The study investigates how generative AI tools function as reflexive collaborators in doctoral supervision, improving research processes, supervision quality, and intellectual inquiry.

Which theoretical framework guides the research?

The research is anchored in Kolb’s Experiential Learning Theory and re-conceptualised through an augmented experiential learning framework.

How does the paper describe both benefits and risks of AI outputs in supervision?

It highlights deeper theoretical engagement, enhanced self-directed learning, and new pedagogical possibilities, while also stressing challenges such as bias, overreliance, and contextual insensitivity.

Oct 15, 2026

Uploaded by Margaret