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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.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/artificial-intelligence-as-a-reflexive-collaborator-in-graduate-studies-supervision/582300/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/artificial-intelligence-as-a-reflexive-collaborator-in-graduate-studies-supervision/582300.png","ImageObject",300,407,{"name":92,"@type":93},"Margaret","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-11-15","2026-10-15",true,{"@type":102,"interactionType":103,"userInteractionCount":52},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What is the main focus of the study on AI in graduate supervision?","Question",{"text":112,"@type":113},"The study investigates how generative AI tools function as reflexive collaborators in doctoral supervision, improving research processes, supervision quality, and intellectual inquiry.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"Which theoretical framework guides the research?",{"text":117,"@type":113},"The research is anchored in Kolb’s Experiential Learning Theory and re-conceptualised through an augmented experiential learning framework.",{"name":119,"@type":110,"acceptedAnswer":120},"How does the paper describe both benefits and risks of AI outputs in supervision?",{"text":121,"@type":113},"It highlights deeper theoretical engagement, enhanced self-directed learning, and new pedagogical possibilities, while also stressing challenges such as bias, overreliance, and contextual insensitivity.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},582300,1792061714,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":52,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":39,"language":139,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":67,"update_tm":143,"read_time":46,"preview_page_count":4},137451207643,"https://ap-avatar.wpscdn.com/davatar_3d24733baf745e90a7e4bdd5f77d97b2","Transformation in Higher Education  \nISSN: (Online) 2519-5638,(Print) 2415-0991  \n~~ ~~ Page 1 of 8  \nOrigina~~l Research ~~  \nArtificial intelligence as a reflexive collaborator in graduate studies supervision  \nAuthors:  \nAnthony Brown1  Jane Rossouw2   \nAffiliations:  \n1School of Interdisciplinary Research and Graduate Studies, College of Graduate Studies, University of South Africa, Pretoria, South Africa  \n2Department of Psychology of Education, College of  \nEducation, University of South Africa, Pretoria,  \nSouth Africa  \nCorresponding author:  \nAnthony Brown, [browna@unisa.ac.za](browna@unisa.ac.za)  \nDates:  \nReceived: 27 July 2025  \nAccepted: 19 Nov. 2025  \nPublished: 07 Feb. 2026  \nHow to cite this article:  \nBrown, 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)  \nCopyright:  \n© 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/) .  \nRead online:  \nScan this QR code with your smart phone or mobile device to read online.  \nThe 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.  \nContribution: 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.  \nKeywords: AI-augmented supervision; doctoral research; experiential learning; ethical AI integration; graduate studies; augmented experiential learning.  \nIntroduction  \nThe 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","cbCaipdsMpNCK6yo","https://ap.wps.com/l/cbCaipdsMpNCK6yo","pdf",381939,"English","# Introduction\n## Background and opportunities for AI in supervision\n## Research focus and approach","[{\"question\":\"What is the main focus of the study on AI in graduate supervision?\",\"answer\":\"The study investigates how generative AI tools function as reflexive collaborators in doctoral supervision, improving research processes, supervision quality, and intellectual inquiry.\"},{\"question\":\"Which theoretical framework guides the research?\",\"answer\":\"The research is anchored in Kolb’s Experiential Learning Theory and re-conceptualised through an augmented experiential learning framework.\"},{\"question\":\"How does the paper describe both benefits and risks of AI outputs in supervision?\",\"answer\":\"It highlights deeper theoretical engagement, enhanced self-directed learning, and new pedagogical possibilities, while also stressing challenges such as bias, overreliance, and contextual insensitivity.\"}]","Artificial intelligence as a reflexive collaborator in graduate studies supervision | PDF",1792042993]