Vol. 2 No. 1 (2027): Volume 2, Issue 1 (2027)
Articles

Transformative Learning in the Age of Artificial Intelligence: A Critical Theory Debate

PDF
  • Ted Fleming
Ted Fleming
Teachers College Columbia University
DOI: https://doi.org/10.46787/ijaipil.v2i1.7291

Published 2026-05-06

Keywords

  • Transformative learning; artificial intelligence; critical theory; AI-mediated education; recognition theory

How to Cite

Fleming, T. (2026). Transformative Learning in the Age of Artificial Intelligence: A Critical Theory Debate. International Journal of AI in Pedagogy, Innovation, and Learning Futures, 2(1). https://doi.org/10.46787/ijaipil.v2i1.7291

Copyright (c) 2026 Ted Fleming

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

This paper examines transformative learning in light of recent developments in artificial intelligence (AI) in education. Drawing on critical theoretical perspectives, particularly the work of Jürgen Habermas and Axel Honneth, it explores how AI might enrich key aspects of transformative learning, including disorienting dilemmas, critical reflection, discourse, and recognition, which remain central to any meaningful integration of AI in education. The paper argues that current approaches to AI in education tend to be instrumental, emphasizing efficiency and performance over meaning-making and emancipatory learning, and raises concerns about distorted discourse, reduced agency, and forms of misrecognition in AI-enriched learning environments. At the same time, it suggests that AI can expand access to information, introduce new perspectives, and support critically reflective inquiry. A model of AI-supported transformative learning is proposed that foregrounds learner agency, critical digital literacy, and ethical dialogue, while also outlining how business and industry, through corporate responsibility plans and charters, can harness AI to foster more democratic and egalitarian workplaces that align technological innovation with workers’ interests in democratic citizenship and emancipatory education.

PDF

References

  1. Alagic, M., & Byun, J. (2026). Transformative learning in the age of generative AI: Educators’ perspectives on a paradigm shift. In D. Guralnick, M. E. Auer, & A. Poce (Eds.), Creativity and new technologies in learning for the workplace and higher education (TLIC 2025) (pp. 29–41). Springer. https://doi.org/10.1007/978-3-032-09905-1_3
  2. Antal, A. B., & Sobczak, A. (2004). Beyond CSR: Organisational learning for global responsibility. Journal of General Management, 30(2), 77–98. https://doi.org/10.1177/0306307004030002
  3. Baker, R. S., & Siemens, G. (2022). Learning analytics and educational data mining. In R. K. Sawyer (Ed.), The Cambridge handbook of the learning sciences (2nd ed., pp. 259–279). Cambridge University Press.
  4. Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021). On the dangers of stochastic parrots: Can language models be too big? In Proceedings of the 2021 ACM conference on fairness, accountability, and transparency (pp. 610–623). ACM. https://doi.org/10.1145/3442188.3445922
  5. Birhane, A. (2021). Algorithmic injustice: A relational ethics approach. Patterns, 2(2), 100205. https://doi.org/10.1016/j.patter.2021.100205
  6. Brookfield, S. D. (2005). The power of critical theory: Liberating adult learning and teaching. Jossey-Bass.
  7. Brookfield, S. D. (2018). Becoming a critically reflective teacher (2nd ed.). Jossey-Bass.
  8. Carnevale, A. P., Smith, N., & Strohl, J. (2020). Recovery: Job growth and education requirements through 2030. Georgetown University Center on Education and the Workforce. https://cew.georgetown.edu/cew-reports/recovery2020/
  9. Celik, I. (2023). Towards intelligent-TPACK: An empirical study on teachers’ professional knowledge to ethically integrate artificial intelligence (AI)-based tools into education. Computers in Human Behavior, 138, 107468. https://doi.org/10.1016/j.chb.2022.107468
  10. Cranton, P., & Taylor, E. W. (2013). A theory in progress? Issues in transformative learning theory. European Journal for Research on the Education and Learning of Adults, 4(1), 33–47. https://doi.org/10.3384/rela.2000-7426.rela5000
  11. Dirkx, J. M. (1997). Nurturing soul in adult learning. New Directions for Adult and Continuing Education, 1997(74), 79–88. https://doi.org/10.1002/ace.7409
  12. Feenberg, A. (2017). Technosystem: The social life of reason. Harvard University Press. http://www.jstor.org/stable/j.ctv24w64m4
  13. Feldstein, A. (2026). The AI paradox: How efficiency is dismantling the relational infrastructure of transformative learning. In L. Declercq, J. Loeckx, M. De Laat, N. B. Dohn, & T. Ryberg (Eds.), Proceedings of the international conference on networked learning (Vol. 15). https://doi.org/10.54337/nlc.v15.11092
  14. Floridi, L., & Chiriatti, M. (2020). GPT-3: Its nature, scope, limits, and consequences. Minds and Machines, 30(4), 681–694. https://doi.org/10.1007/s11023-020-09548-1
  15. Habermas, J. (1984). The theory of communicative action: Vol. 1. Reason and the rationalization of society. Beacon Press.
  16. Habermas, J. (1987). The theory of communicative action: Vol. 2. Lifeworld and system. Beacon Press.
  17. Habermas, J. (1989). The structural transformation of the public sphere: An inquiry into a category of bourgeois society. Polity.
  18. Habermas, J. (2023). A new structural transformation of the public sphere and deliberative politics. Polity.
  19. Hoggan, C. D. (2016). Transformative learning as a metatheory: Definition, criteria, and typology. Adult Education Quarterly, 66(1), 57–75. https://doi.org/10.1177/0741713615611216
  20. Holmes, W., & Tuomi, I. (2022). State of the art and practice in AI in education. European Journal of Education, 57(4), 542–570. https://doi.org/10.1111/ejed.12533
  21. Holmes, W., Bialik, M., & Fadel, C. (2022). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign. https://curriculumredesign.org/wp-content/uploads/AIED-Book-Excerpt-CCR.pdf
  22. Honneth, A. (1995). The struggle for recognition: The moral grammar of social conflicts. MIT Press.
  23. Honneth, A. (2023). The poverty of our freedom: Essays 2012–2019. Polity.
  24. Honneth, A. (2024). The working sovereign: Labor and democratic citizenship. Polity.
  25. Jandrić, P., Knox, J., Besley, T., Ryberg, T., Suoranta, J., & Hayes, S. (2018). Postdigital science and education. Educational Philosophy and Theory, 50(10), 893–899. https://doi.org/10.1080/00131857.2018.1454000
  26. Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., & 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
  27. Kharbach, M. (2026). Critical AI literacy vs AI literacy: A short guide for teachers, definitions, frameworks, and questions for your class. Educators Technology. https://www.educatorstechnology.com/2026/04/critical-ai-literacy-vs-ai-literacy.html
  28. Long, D., & Magerko, B. (2020). What is AI literacy? Competencies and design considerations. In Proceedings of the 2020 CHI conference on human factors in computing systems (pp. 1–16). ACM. https://doi.org/10.1145/3313831.3376727
  29. Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. Pearson.
  30. Mayer, S. J. (2026). Why measuring everything ruins everything. John Dewey Society Democracy Initiative. https://jdsdemocracyinitiative.substack.com/p/why-measuring-everything-ruins-everything
  31. Mezirow, J. (1991). Transformative dimensions of adult learning. Jossey-Bass.
  32. Mezirow, J. (2000). Learning as transformation: Critical perspectives on a theory in progress. Jossey-Bass.
  33. Mezirow, J. (2009). Transformative learning theory. In J. Mezirow & E. Taylor (Eds.), Transformative learning in practice (pp. 18–32). Jossey-Bass.
  34. Miao, F., & Holmes, W. (2023). Guidance for generative AI in education and research. UNESCO Publishing. https://doi.org/10.54675/EWZM9535
  35. Mollick, E. (2024). Co-intelligence: Living and working with AI. Penguin.
  36. Ng, W., Leung, D., Chu, S. K. W., & Qiao, M. S. (2021). Conceptualizing AI literacy: An exploratory review. Computers and Education: Artificial Intelligence, 2, 100041. https://doi.org/10.1016/j.caeai.2021.100041
  37. Noddings, N. (2013). Caring: A relational approach to ethics and moral education (2nd ed.). University of California Press.
  38. OECD. (2023). AI and the future of skills: Methods for evaluating AI capabilities (Vol. 2). OECD Publishing. https://doi.org/10.1787/a9fe53cb-en
  39. Selwyn, N. (2019). Should robots replace teachers? AI and the future of education. Polity.
  40. Selwyn, N. (2021). Education and technology: Key issues and debates (3rd ed.). Bloomsbury.
  41. Taylor, E. W. (2017). Transformative learning theory. In A. Laros, T. Fuhr, & E. W. Taylor (Eds.), Transformative learning meets Bildung: An international exchange (pp. 17–29). Sense Publishers.
  42. Wheelahan, L. (2015). Not just skills: What a focus on knowledge means for vocational education. Journal of Curriculum Studies, 47(6), 750–762. https://doi.org/10.1080/00220272.2015.1089942
  43. Williamson, B., & Eynon, R. (2020). Historical threads, missing links, and future directions in AI in education. Learning, Media and Technology, 45(3), 223–235. https://doi.org/10.1080/17439884.2020.1798997
  44. World Economic Forum. (2023). The future of jobs report 2023. https://www3.weforum.org/docs/WEF_Future_of_Jobs_2023.pdf
  45. Xia, Q., Weng, X., Ouyang, F., et al. (2024). A scoping review on how generative artificial intelligence transforms assessment in higher education. International Journal of Educational Technology in Higher Education, 21, 40. https://doi.org/10.1186/s41239-024-00468-z
  46. Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education—Where are the educators? International Journal of Educational Technology in Higher Education, 16(1), 39. https://doi.org/10.1186/s41239-019-0171-0