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

Reimagining Educator Roles in the Age of Artificial Intelligence: Engagement, Workforce Learning, and the Future of Digital Pedagogy

PDF
  • William Rothwell,
  • Farhan Sadique
DOI: https://doi.org/10.46787/ijaipil.v2i1.7288

Published 2026-05-04

Keywords

  • artificial intelligence; digital pedagogy; educator role transformation; workforce learning

How to Cite

Rothwell, W., & Sadique, F. (2026). Reimagining Educator Roles in the Age of Artificial Intelligence: Engagement, Workforce Learning, and the Future of Digital Pedagogy. International Journal of AI in Pedagogy, Innovation, and Learning Futures, 2(1). https://doi.org/10.46787/ijaipil.v2i1.7288

Copyright (c) 2026 William J. Rothwell and Farhan Sadique

Creative Commons License

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

Abstract

Abstract

This conceptual article examines the transformation of educator roles in the age of artificial intelligence (AI) and its implications for digital pedagogy and workforce learning. As AI, adaptive systems, and hybrid learning environments become increasingly embedded in education, traditional instructor-centered models are less aligned with learner expectations, engagement needs, and labor market demands. Drawing on engagement theory, digital learning research, and workforce education literature, the article argues that educators must move beyond content delivery toward the design of interactive, personalized, collaborative, and application-centered learning experiences. It proposes an AI-driven digital pedagogy framework organized around three commitments: engagement-centered design, AI-supported but human-led learning, and workforce alignment. The article further identifies four evolving educator roles designer, facilitator, navigator, and coach; that reflect the pedagogical, ethical, and developmental responsibilities of teaching in AI-mediated environments. It concludes that AI should be understood as a catalyst rather than a solution, and that the future of education depends on educators’ ability to integrate technology with human-centered, ethically grounded, and workforce-relevant learning practices.

PDF

References

  1. Baker, R. S., & Siemens, G. (2014). Educational data mining and learning analytics. In R. K. Sawyer (Ed.), The Cambridge handbook of the learning sciences (2nd ed., pp. 253–274). Cambridge University Press.
  2. Bailenson, J. N. (2021). Nonverbal overload: A theoretical argument for the causes of Zoom fatigue. Technology, Mind, and Behavior, 2(1). https://doi.org/10.1037/tmb0000030
  3. Billett, S. (2011). Vocational education: Purposes, traditions and prospects. Springer.
  4. Bloom, B. S., Engelhart, M. D., Furst, E. J., Hill, W. H., & Krathwohl, D. R. (1956). Taxonomy of educational objectives: The classification of educational goals. Handbook I: Cognitive domain. David McKay.
  5. Borup, J., Graham, C. R., West, R. E., Archambault, L., & Spring, K. J. (2020). Academic communities of engagement: An expansive lens for examining support structures in blended and online learning. Educational Technology Research and Development, 68(2), 807–832. https://doi.org/10.1007/s11423-020-09744-x
  6. Boyer, E. L. (1990). Scholarship reconsidered: Priorities of the professoriate. Carnegie Foundation for the Advancement of Teaching.
  7. Carnevale, A. P., Smith, N., & Strohl, J. (2013). Recovery: Job growth and education requirements through 2030. Georgetown University Center on Education and the Workforce. https://eric.ed.gov/?id=ED584413
  8. Chen, X., Xie, H., Zou, D., & Hwang, G.-J. (2020). Application and theory gaps during the rise of artificial intelligence in education. Computers and Education: Artificial Intelligence, 1, 100002. https://doi.org/10.1016/j.caeai.2020.100002
  9. Cox, M. D. (2013). The impact of communities of practice in support of early-career academics. International Journal for Academic Development, 18(1), 18–30. https://doi.org/10.1080/1360144X.2011.599600
  10. Csikszentmihalyi, M. (1990). Flow: The psychology of optimal experience. Harper & Row.
  11. Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and self-determination in human behavior. Springer.
  12. Eby, L. T., Allen, T. D., Evans, S. C., Ng, T., & DuBois, D. L. (2008). Does mentoring matter? A multidisciplinary meta-analysis comparing mentored and non-mentored individuals. Journal of Vocational Behavior, 72(2), 254–267. https://doi.org/10.1016/j.jvb.2007.04.005
  13. Freeman, S., Eddy, S. L., McDonough, M., Smith, M. K., Okoroafor, N., Jordt, H., & Wenderoth, M. P. (2014). Active learning increases student performance in science, engineering, and mathematics. Proceedings of the National Academy of Sciences, 111(23), 8410–8415. https://doi.org/10.1073/pnas.1319030111
  14. Garrison, D. R., Anderson, T., & Archer, W. (2000). Critical inquiry in a text-based environment: Computer conferencing in higher education. The Internet and Higher Education, 2(2–3), 87–105. https://doi.org/10.1016/S1096-7516(00)00016-6
  15. Goodyear, P. (2015). Teaching as design. HERDSA Review of Higher Education, 2, 27–50.
  16. Grant, A. M. (2014). The efficacy of executive coaching in times of organisational change. Journal of Change Management, 14(2), 258–280. https://doi.org/10.1080/14697017.2013.805159
  17. Hodges, C., Moore, S., Lockee, B., Trust, T., & Bond, A. (2020). The difference between emergency remote teaching and online learning. EDUCAUSE Review. https://er.educause.edu/articles/2020/3/the-difference-between-emergency-remote-teaching-and-online-learning
  18. Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign.
  19. Jordan, K. (2015). Massive open online course completion rates revisited. International Review of Research in Open and Distributed Learning, 16(3), 341–358. https://doi.org/10.19173/irrodl.v16i3.2112
  20. Kahu, E. R., & Nelson, K. (2018). Student engagement in the educational interface. Higher Education Research & Development, 37(1), 58–71. https://doi.org/10.1080/07294360.2017.1344197
  21. Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., & Kasneci, G. (2023). ChatGPT for good? Learning and Individual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274
  22. Kezar, A. (2014). How colleges change: Understanding, leading, and enacting change. Routledge.
  23. Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and development. Prentice Hall.
  24. Laurillard, D. (2012). Teaching as a design science: Building pedagogical patterns for learning and technology. Routledge.
  25. Long, D., & Magerko, B. (2020). What is AI literacy? In Proceedings of the 2020 CHI conference (pp. 1–16). ACM. https://doi.org/10.1145/3313831.3376727
  26. Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. Pearson.
  27. Maier, U., & Klotz, C. (2022). Personalized feedback in digital learning environments. Computers and Education: Artificial Intelligence, 3, 100080. https://doi.org/10.1016/j.caeai.2022.100080
  28. Martin, F., Sun, T., & Westine, C. D. (2020). A systematic review of research on online teaching and learning. Computers & Education, 159, 104009. https://doi.org/10.1016/j.compedu.2020.104009
  29. Noe, R. A., Clarke, A. D. M., & Klein, H. J. (2014). Learning in the twenty-first-century workplace. Annual Review of Organizational Psychology and Organizational Behavior, 1, 245–275.
  30. OECD. (2023). AI and the future of skills: Volume 2: AI and education. OECD Publishing.
  31. Prince, M. J. (2013). Does active learning work? Journal of Engineering Education, 93(3), 223–231.
  32. Qian, Y. (2025). Pedagogical applications of generative AI in higher education. TechTrends, 69, 1105–1120. https://doi.org/10.1007/s11528-025-01100-1
  33. Reich, J., & Ruipérez-Valiente, J. A. (2019). The MOOC pivot. Science, 363(6423), 130–131. https://doi.org/10.1126/science.aav7958
  34. Rosen, L. D., Lim, A. F., Carrier, L. M., & Cheever, N. A. (2011). Educational impact of task switching. Psicología Educativa, 17(2), 163–177. https://doi.org/10.5093/ed2011v17n2a4
  35. Rothwell, W. J., Zaballero, A., & Sadique, F. (2024). Measuring ROI in technology-based learning. In R. A. Reiser et al. (Eds.), Trends and issues in instructional design and technology (5th ed., pp. 237–251). Routledge. https://doi.org/10.4324/9781003502302-20
  36. Rothwell, W. J., Zaballero, A. G., Sadique, F., & Bakhshandeh, B. (2024). Revolutionizing the online learning journey. Taylor & Francis. https://doi.org/10.4324/9781003431046
  37. Sadique, F. (2026). Strategic workforce development. In S. Dhiman (Ed.), The Palgrave encyclopedia of leadership and organizational change. Palgrave Macmillan. https://doi.org/10.1007/978-3-031-51650-4_238-1
  38. Saha, S., Rahbari, F., Sadique, F., Velamakanni, S. K. C., Farooque, M., & Rothwell, W. J. (2025). Next-gen education: Enhancing AI for microlearning. ASEE Annual Conference Proceedings. https://doi.org/10.18260/1-2--56998
  39. Selwyn, N. (2016). Education and technology: Key issues and debates (2nd ed.). Bloomsbury.
  40. Selwyn, N. (2019). Should robots replace teachers? Polity Press.
  41. Selwyn, N. (2021). Education and technology: Key issues and debates (3rd ed.). Bloomsbury.
  42. Seo, K., Tang, J., Roll, I., Fels, S., & Yoon, D. (2021). AI and learner–instructor interaction. International Journal of Educational Technology in Higher Education, 18, 54. https://doi.org/10.1186/s41239-021-00292-9
  43. Siemens, G. (2005). Connectivism: A learning theory. International Journal of Instructional Technology and Distance Learning, 2(1), 3–10.
  44. Trust, T., Carpenter, J. P., & Krutka, D. G. (2017). Professional learning networks in higher education. The Internet and Higher Education, 35, 1–11. https://doi.org/10.1016/j.iheduc.2017.06.001
  45. UNESCO. (2023). Guidance for generative AI in education and research. UNESCO Publishing.
  46. Vroom, V. H. (1964). Work and motivation. Wiley.
  47. Wang, S., Wang, F., Zhu, Z., Wang, J., Tran, T., & Du, Z. (2024). Artificial intelligence in education. Expert Systems with Applications, 252, 124167. https://doi.org/10.1016/j.eswa.2024.124167
  48. Williamson, B. (2023). Education, data and the rise of AI. Routledge.
  49. Williamson, B., & Eynon, R. (2020). Historical threads in AI in education. Learning, Media and Technology, 45(3), 223–235.
  50. World Economic Forum. (2023). The future of jobs report 2023. World Economic Forum.
  51. Xu, D., & Jaggars, S. S. (2014). Performance gaps in online vs. face-to-face courses. The Journal of Higher Education, 85(5), 633–659. https://doi.org/10.1080/00221546.2014.11777343
  52. Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). AI applications in higher education. International Journal of Educational Technology in Higher Education, 16, 39. https://doi.org/10.1186/s41239-019-0171-0