Artificial Intelligence as a Reflexive Collaborator in Graduate Studies Supervision
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| Title: | Artificial Intelligence as a Reflexive Collaborator in Graduate Studies Supervision |
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| Language: | English |
| Authors: | Anthony Brown (ORCID |
| Source: | Transformation in Higher Education. 2026 11. |
| Availability: | AOSIS. 15 Oxford Street, Durbanville, Cape Town, 7550 South Africa. Tel: +27-21-975-2602; Fax: +27-21-975-4635; e-mail: publishing@aosis.co.za; Web site: https://thejournal.org.za/index.php/thejournal |
| Peer Reviewed: | Y |
| Page Count: | 8 |
| Publication Date: | 2026 |
| Document Type: | Journal Articles Reports - Research |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Artificial Intelligence, Supervision, Doctoral Students, Technology Uses in Education, Sexuality, Research, Supervisor Supervisee Relationship, Doctoral Dissertations, Technology Integration, College Faculty, Foreign Countries, Developing Nations, Student Experience, Student Attitudes, Teacher Attitudes, Reflection |
| Geographic Terms: | South Africa |
| ISSN: | 2415-0991 2519-5638 |
| Abstract: | 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 and reconceptualised through an augmented experiential learning framework, the study elucidates how 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 collaborators in AI-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. |
| Abstractor: | As Provided |
| Entry Date: | 2026 |
| Accession Number: | EJ1501311 |
| Database: | ERIC |
| Abstract: | 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 and reconceptualised through an augmented experiential learning framework, the study elucidates how 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 collaborators in AI-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. |
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| ISSN: | 2415-0991 2519-5638 |
