The Education Doctorate in the Context of Generative Artificial Intelligence
Epistemic Shifts and Challenges to Practical Wisdom
DOI:
https://doi.org/10.5195/ie.2025.485Keywords:
AI Integration, AI, generative AI, genAI, education doctorate, EdD, curricula, learning, teaching, knowledge epistemologies, technology, practical wisdomAbstract
The emergence of generative artificial intelligence (GenAI) fundamentally shifts how educational knowledge is created, shared, and validated. Through the lens of epistemic technologies—tools that transform knowledge creation and dissemination—we analyze how GenAI challenges traditional notions of practical wisdom in education doctorate (EdD) programs. Drawing on parallels with previous epistemic shifts like written language, print, and digital media, we explore how GenAI, as a generative, dialogic, multimodal, and sometimes unpredictable technology, transforms practitioner knowledge and decision-making. We discuss implications for EdD programs, emphasizing the need to balance AI integration with the preservation of human judgment and ethical decision-making to maintain practical wisdom for scholarly practice.
References
Alkaissi, H., & McFarlane, S. I. (2023). Artificial hallucinations in ChatGPT: Implications in scientific writing. Cureus, 15(2). https://doi.org/10.7759%2Fcureus.35179
Alvarado, R. (2023). AI as an epistemic technology. Science and Engineering Ethics, 29(5), 32. https://doi.org/10.1007/s11948-023-00451-3
Anthony, C. (2018). To question or accept? How status differences influence responses to new epistemic technologies in knowledge work. Academy of Management Review, 43(4), 661–679. https://doi.org/10.5465/amr.2016.0334
Barberá, P. (2020). Social media, echo chambers, and political polarization. In N. Persily & J. A. Tucker (Eds.), Social media and democracy: The state of the field, prospects for reform. Cambridge University Press.
Bearman, M., & Ajjawi, R. (2023). Learning to work with the black box: Pedagogy for a world with artificial intelligence. British Journal of Educational Technology, 54(5), 1160–1173. https://doi.org/10.1111/bjet.13337
Beghetto, R. A. (2023). A new horizon for possibility thinking: A conceptual case study of Human × AI collaboration. Possibility Studies & Society, 1(3), 324–341. https://doi.org/10.1177/27538699231160136
Christensen, C. (2012, March 30). Disruptive innovation explained [Video]. YouTube. https://www.youtube.com/watch?v=qDrMAzCHFUU
Chu, S. K. W., Reynolds, R. B., Tavares, N. J., Notari, M., & Lee, C. W. Y. (2017). 21st century skills development through inquiry-based learning from theory to practice. Springer Singapore.
https://doi.org/10.1007/978-981-10-2481-8
Cohen, D. W. (1989). The undefining of oral tradition. Ethnohistory, 36(1), 9–18. https://doi.org/10.2307/482738
Dredge, Stuart (2016, February 3). Why are YouTube stars so popular? The Guardian. https://www.theguardian.com/technology/2016/feb/03/why-youtube-stars-popular-zoella
Dunnigan, J., Henriksen, D., Mishra, P., & Lake, R. (2023). “Can we just please slow it all down?” School leaders take on ChatGPT. TechTrends, 67(6), 878–884. https://doi.org/10.1007/s11528-023-00914-1
Eisenstein, E. L. (1979). The printing press as an agent of change (Vol. 1–2). Cambridge University Press.
Eubanks, V. (2018). Automating inequality: How high-tech tools profile, police, and punish the poor. St. Martin’s Press.
Fawns, T. (2022). An entangled pedagogy: Looking beyond the pedagogy–technology dichotomy. Postdigital Science and Education, 4, 711–728. https://doi.org/10.1007/s42438-022-00302-7
Firth, J., Torous, J., Stubbs, B., Firth, J. A., Steiner, G. Z., Smith, L., Alvarez-Jimenez, M., Gleeson, J., Vancampfort, D., Armitage, C. J., & Sarris, J. (2019). The “online brain”: How the Internet may be changing our cognition. World Psychiatry, 18(2), 119–129. https://doi.org/10.1002/wps.20617
Goodfellow, J. (2003). Practical wisdom in professional practice: The person in the process. Contemporary Issues in Early Childhood, 4(1), 48–63. https://doi.org/10.2304/ciec.2003.4.1.6
Hatch, J. A. (2023). Doing qualitative research in education settings (2nd ed.). State University of New York Press.
Henriksen, D., Henderson, M., Creely, E., Carvalho, A. A., Cernochova, M., Dash, D., Davis, T., & Mishra, P. (2021). Creativity and risk-taking in teaching and learning settings: Insights from six international narratives. International Journal of Educational Research Open, 2, 100024. https://doi.org/10.1016/j.ijedro.2020.100024
Henriksen, D., Mishra, P., & Torrejon-Capurro, C. (2022). A socio-cultural perspective on creativity and technology: New synergies for education. In J. Plucker (Ed.), Creativity and innovation: Theory, research & practice (pp. 327–346). Routledge.
Hu, J. (2018, September 12). Social networks make the world’s largest nations seem small. Quartz. https://qz.com/1386649/social-networks-make-the-worlds-largest-nations-seem-small/
Hunt, N., & Melrose, S. (2005). Techne, technology, technician: The creative practices of the mastercraftsperson. Performance Research, 10(4), 70–82. https://doi.org/10.1080/13528165.2005.10871452
Ji, Z., Lee, N., Frieske, R., Yu, T., Su, D., Xu, Y., Ishii, E., Bang, Y. J., Madotto, A., & Fung, P. (2023). Survey of hallucination in natural language generation. ACM Computing Surveys, 55(12), 1–38. https://doi.org/10.1145/3571730
Kaplan, D. M. (Ed.). (2017). Philosophy, technology, and the environment. MIT Press.
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., … Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274
Koschmann, T. (2012). Paradigm shifts and instructional technology: An introduction. In T. Koschmann (Ed.), Cscl: Theory and practice of an emerging paradigm (pp. 1–23). Routledge.
Lai, J. W., & Bower, M. (2020). Evaluation of technology use in education: Findings from a critical analysis of systematic literature reviews. Journal of Computer Assisted Learning, 36(3), 241–259. https://doi.org/10.1111/jcal.12412
Lunenberg, M., & Korthagen, F. (2009). Experience, theory, and practical wisdom in teaching and teacher education. Teachers and Teaching: Theory and Practice, 15(2), 225–240. https://doi.org/10.1080/13540600902875316
McLuhan, M. (1964). Understanding media: The extensions of man. McGraw-Hill.
McNeil, I. (Ed.). (2002). An encyclopedia of the history of technology. Routledge.
Michel-Villarreal, R., Vilalta-Perdomo, E., Salinas-Navarro, D. E., Thierry-Aguilera, R., & Gerardou, F. S. (2023). Challenges and opportunities of generative AI for higher education as explained by ChatGPT. Education Sciences, 13(9), 856. https://doi.org/10.3390/educsci13090856
Mishra, P., Oster, N., & Henriksen, D. (2024). Generative AI, teacher knowledge and educational research: Bridging short- and long-term perspectives. TechTrends, 68, 205–210.
https://doi.org/10.1007/s11528-024-00938-1
Mishra, P., Spiro, R. J. & Feltovich, P. (1996). Technology, representation & cognition. In von Oostendorp, H. (Ed.), Cognitive aspects of electronic text processing (pp. 287–306). Ablex Publishing Corporation.
Mishra, P., Warr, M., & Islam, R. (2023). TPACK in the age of ChatGPT and Generative AI. Journal of Digital Learning in Teacher Education, 39(4), 235–251. https://doi.org/10.1080/21532974.2023.2247480
Ong, W. J. (1982). Orality and literacy: The technologizing of the word. Methuen.
Pea, R. D. (1987). Cognitive technologies for mathematics education. In A. H. Schoenfeld (Ed.), Cognitive science and mathematics education (pp. 89–122). Lawrence Erlbaum Associates.
Plato. (n.d.). Phaedrus. Perseus Catalogue, Tufts University. https://www.perseus.tufts.edu/hopper/text?doc=Perseus%3Atext%3A1999.01.0174%3Atext%3DPhaedrus%3Apage%3D275
Postman, N. (1992). Technopoly: The surrender of culture to technology. Random House.
Postman, N. (1998). Five things we need to know about technological change. https://web.cs.ucdavis.edu/~rogaway/classes/188/materials/postman.pdf
Rafner, J., Dellermann, D., Hjorth, A., Veraszto, D., Kampf, C., MacKay, W., & Sherson, J. (2022). Deskilling, upskilling, and reskilling: A case for hybrid intelligence. Morals & Machines, 1(2), 24–39. https://doi.org/10.5771/2747-5174-2021-2
Sawyer, R. K., & Henriksen, D. (2024). Explaining creativity: The science of human innovation. Oxford University Press.
Schon, D. A., & DeSanctis, V. (1986). The reflective practitioner: How professionals think in action. The Journal of Continuing Higher Education, 34(3), 29–30.
https://doi.org/10.1080/07377366.1986.10401080
Shulman, L. S. (2007). Response to comments: Practical wisdom in the service of professional practice. Educational Researcher, 36(9), 560–563. https://doi.org/10.3102/0013189X07313150
Shulman, L. S., Golde, C. M., Bueschel, A. C., & Garabedian, K. J. (2006). Reclaiming education’s doctorates: A critique and a proposal. Educational Researcher, 35(3), 25–32. https://doi.org/10.3102/0013189X035003025
Shulman, L. S., & Wilson, S. M. (2004). The wisdom of practice: Essays on teaching, learning, and learning to teach. Jossey-Bass.
Smith, K. (2020, January 2). 60 incredible and interesting Twitter stats and statistics. Brandwatch.
https://www.brandwatch.com/blog/twitter-stats-and-statistics/
Stenberg, K., & Maaranen, K. (2022). Promoting practical wisdom in teacher education: A qualitative descriptive study. European Journal of Teacher Education, 45(5), 617–633. https://doi.org/10.1080/02619768.2020.1860012
Storey, V. A. (2023). AI technology and academic writing: Knowing and mastering the “craft skills.” International Journal of Adult Education and Technology (IJAET), 14(1), 1–15. http://doi.org/10.4018/IJAET.325795
Wang, N., Wang, X., & Su, Y. S. (2024). Critical analysis of the technological affordances, challenges and future directions of Generative AI in education: A systematic review. Asia Pacific Journal of Education, 44(1), 139–155. https://doi.org/10.1080/02188791.2024.2305156
Warr, M., Oster, N., & Isaac, R. (2023). Implicit bias in large language models: Experimental proof and implications for education. SSRN. https://ssrn.com/abstract=4625078
Wergin, J. (2011). Rebooting the EdD. Harvard Educational Review, 81(1), 119–140. https://doi.org/10.17763/haer.81.1.fp775268x77n0122
Zhao, W. X., Zhou, K., Li, J., Tang, T., Wang, X., Hou, Y., Min, Y., Zhang, B., Zhang, J., Dong, Z., Du, Y., Yang, C., Chen, Y., Chen, Z., Jiang, J., Ren, R., Li, Y., Tang, X., Liu, Z., … Wen, J.-R. (2023). A survey of large language models. arXiv. https://arxiv.org/abs/2303.18223
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