Thinking with ChatGPT: An Autoethnographic Inquiry into Epistemic Transformation in Higher Education
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Abstract
This study examines how sustained engagement with generative artificial intelligence, specifically ChatGPT, reshaped my ways of thinking, writing, and learning as a doctoral student in higher education. Adopting autoethnography as methodology, I situate personal experiences within wider educational and technological landscapes to explore the epistemic implications of human–AI interaction. Through narrative vignettes and thematic analysis, I trace how generative AI became embedded in academic practice and identity formation. Drawing on Cognitive Flexibility Theory, I document a reorientation from linear knowledge production to more iterative, dialogic, and adaptive thinking. I introduce the notion of AI as a thought partner—a collaborative presence that enables recursive prompting, reframing, and co-construction of meaning. By foregrounding the relational and cognitive dimensions of working with AI, this study contributes to educational research in two ways: methodologically, by demonstrating the value of autoethnography in investigating emergent human–AI practices; and conceptually, by expanding current understandings of learning with AI beyond dominant narratives of efficiency or misconduct. These insights invite interdisciplinary dialogue on how generative AI can foster epistemic growth, metacognitive awareness, and reflective learning across higher education contexts.
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References
Abbas, M., Jam, F. A., & Khan, T. I. (2024). Is it harmful or helpful? Examining the causes and consequences of generative AI usage among university students. International Journal of Educational Technology in Higher Education, 21(1), 10. https://doi.org/10.1186/s41239-024-00444-7
An, Y., Yu, J. H., & James, S. (2025). Investigating the higher education institutions’ guidelines and policies regarding the use of generative AI in teaching, learning, research, and administration. International Journal of Educational Technology in Higher Education, 22(1), 10. https://doi.org/10.1186/s41239-025-00507-3
Anderson, L. (2006). Analytic autoethnography. Journal of Contemporary Ethnography, 35(4), 373–395. https://doi.org/10.1177/0891241605280449
Boufoy-Bastick, B. (2004). Auto-interviewing, auto-ethnography and critical incident methodology for eliciting a self-conceptualised worldview. Forum Qualitative Sozialforschung/forum: Qualitative Social Research, 5(1), 651. https://doi.org/10.17169/fqs-5.1.651
Chan, C. K. Y. (2023). A comprehensive AI policy education framework for university teaching and learning. International Journal of Educational Technology in Higher Education, 20(1), 38. https://doi.org/10.1186/s41239-023-00408-3
Chan, C. K. Y., & Hu, W. (2023). Students’ voices on generative AI: Perceptions, benefits, and challenges in higher education. International Journal of Educational Technology in Higher Education, 20(1), 43. https://doi.org/10.1186/s41239-023-00411-8
Chaudhry, I. S., Sarwary ,Sayed Ahmad M., El Refae ,Ghaleb A., & and Chabchoub, H. (2023). Time to revisit existing student’s performance evaluation approach in higher education sector in a new era of ChatGPT — A Case Study. Cogent Education, 10(1), 2210461. https://doi.org/10.1080/2331186X.2023.2210461
Ellis, C., Adams, T. E., & Bochner, A. P. (2011). Autoethnography: An overview. Forum Qualitative Sozialforschung/forum: Qualitative Social Research, 12(1), 1589. https://doi.org/10.17169/fqs-12.1.1589
Ellis, C., & Bochner, A. P. (2006). Analyzing analytic autoethnography: An autopsy. Journal of Contemporary Ethnography, 35(4), 429–449. https://doi.org/10.1177/0891241606286979
Lincoln, Y. S., & Guba, E. G. (1986). But is it rigorous? Trustworthiness and authenticity in naturalistic evaluation. New Directions for Program Evaluation, 1986(30), 73–84. https://doi.org/10.1002/ev.1427
Luo (Jess), J. (2024). A critical review of GenAI policies in higher education assessment: A call to reconsider the “originality” of students’ work. Assessment & Evaluation in Higher Education, 49(5), 651–664. https://doi.org/10.1080/02602938.2024.2309963
Mao, J., Romero-Hall, E., & Reeves, T. C. (2024). Autoethnography as a research method for educational technology: A reflective discourse. Educational Technology Research and Development, 72(5), 2725–2741. https://doi.org/10.1007/s11423-023-10281-6
Reuters. (2023, January 27). Top French university bans use of ChatGPT to prevent plagiarism. https://www.reuters.com/technology/top-french-university-bans-use-chatgpt-prevent-plagiarism-2023-01-27/
Savin-Baden, M., & Major, C. H. (2013). Qualitative research: The essential guide to theory and practice. Routledge.
Song, Y., Huang, L., Zheng, L., Fan, M., & Liu, Z. (2025). Interactions with generative AI chatbots: Unveiling dialogic dynamics, students’ perceptions, and practical competencies in creative problem-solving. International Journal of Educational Technology in Higher Education, 22(1), 12. https://doi.org/10.1186/s41239-025-00508-2
Spiro, R. J., & Jehng, J. C. (2012). Cognitive flexibility and hypertext: Theory and technology for the nonlinear and multidimensional traversal of complex subject matter. In Cognition, education, and multimedia (pp. 163-205). Routledge.
Stahlke Wall, S. (2016). Toward a moderate autoethnography. International Journal of Qualitative Methods, 15(1). https://doi.org/10.1177/1609406916674966
Stojanov, A. (2023). Learning with ChatGPT 3.5 as a more knowledgeable other: An autoethnographic study. International Journal of Educational Technology in Higher Education, 20(1), 35. https://doi.org/10.1186/s41239-023-00404-7
Walter, Y. (2024). Embracing the future of Artificial Intelligence in the classroom: The relevance of AI literacy, prompt engineering, and critical thinking in modern education. International Journal of Educational Technology in Higher Education, 21(1), 15. https://doi.org/10.1186/s41239-024-00448-3
Yusuf, A., Pervin, N., & Román-González, M. (2024). Generative AI and the future of higher education: A threat to academic integrity or reformation? Evidence from multicultural perspectives. International Journal of Educational Technology in Higher Education, 21(1), 21. https://doi.org/10.1186/s41239-024-00453-6
Zawacki-Richter, O., Bai, J. Y. H., Lee, K., Slagter van Tryon, P. J., & Prinsloo, P. (2024). New advances in artificial intelligence applications in higher education? International Journal of Educational Technology in Higher Education, 21(1), 32. https://doi.org/10.1186/s41239-024-00464-3