Integrating AI in higher education: transforming teachers' roles in boosting student agency
DOI:
https://doi.org/10.55056/etq.943Keywords:
artificial intelligence, student agency, higher education, teachers' roles, role theoryAbstract
Artificial intelligence (AI) has emerged as an integral part of education. It is revolutionising teaching and learning by offering personalised and engaging atmospheres to learners. Specifically, AI competes with agency-building among learners and teachers. Broadly, AI has strengthened learner agency despite teachers' ongoing uncertainty about whether it supports or complicates their work. This study aimed to assess how AI integration in higher education affects teachers' roles in promoting student agency and to explore how AI has transformed teachers' roles in fostering student agency. A sequential mixed method was used as the design of the study. A survey using a five-point Likert scale was conducted to analyse the roles of teachers in the context of integrating AI to enhance agency in higher education. A total of 121 teachers from seven different universities in Nepal duly completed the Google Form, which was distributed via email and social media platforms. Similarly, in-depth interviews were conducted with three teachers teaching at the same level to gather qualitative information and derive qualitative findings. The findings suggest that integrating AI in teachers' roles significantly enhances student agency. The findings also elaborate that AI integration in higher education largely affects teachers' roles in promoting student agency. Similarly, this study contributes to enhancing student agency within the context of changing teachers' roles due to the use of AI in the teaching-learning process. To tackle the issue effectively, the researchers emphasise the need to shift the traditional role of teachers to that of mentors or facilitators, ensuring seamless enhancement of student agency through the integration of AI.
Downloads
References
Adams-Webber, J. and Mirc, E., 1976. Assessing the development of student teachers’ role conceptions. British Journal of Educational Psychology, 46(3), pp.338–340. Available from: https://doi.org/10.1111/j.2044-8279.1976.tb02332.x. DOI: https://doi.org/10.1111/j.2044-8279.1976.tb02332.x
Adhikari, D.P., 2024. Constructing student agency: The nexus between classroom activities and engagement. International Journal of Education and Practice, 12(3), p.819–830. Available from: https://doi.org/10.18488/61.v12i3.3759. DOI: https://doi.org/10.18488/61.v12i3.3759
Adiguzel, T., Kaya, M.H. and Cansu, F.K., 2023. Revolutionizing education with AI: Exploring the transformative potential of ChatGPT. Contemporary Educational Technology, 15(3), p.ep429. Available from: https://doi.org/10.30935/cedtech/13152. DOI: https://doi.org/10.30935/cedtech/13152
Aghaei, P., Bavali, M. and Behjat, F., 2020. An In-depth Qualitative Study of Teachers’ Role Identities: A Case of Iranian EFL Teachers. International Journal of Instruction, 13(2), pp.601–620. Available from: https://doi.org/10.29333/iji.2020.13241a. DOI: https://doi.org/10.29333/iji.2020.13241a
Ahmed, A.A.A., Agarwal, S., Kurniawan, I.G.A., Anantadjaya, S.P.D. and Krishnan, C., 2022. Business boosting through sentiment analysis using Artificial Intelligence approach. International Journal of System Assurance Engineering and Management, 13(1), pp.699–709. Available from: https://doi.org/10.1007/s13198-021-01594-x. DOI: https://doi.org/10.1007/s13198-021-01594-x
Akour, I.A., Al-Maroof, R.S., Alfaisal, R. and Salloum, S.A., 2022. A conceptual framework for determining metaverse adoption in higher institutions of gulf area: An empirical study using hybrid SEM-ANN approach. Computers and Education: Artificial Intelligence, 3, p.100052. Available from: https://doi.org/10.1016/j.caeai.2022.100052. DOI: https://doi.org/10.1016/j.caeai.2022.100052
Bandura, A., 1986. From Thought to Action: Mechanisms of Personal Agency. New Zealand Journal of Psychology, 15(1), pp.1–17. Available from: https://www.psychology.org.nz/journal-archive/NZJP-Vol151-1986-1-Bandura.pdf.
Bandura, A., 1999. Social Cognitive Theory: An Agentic Perspective. Asian Journal of Social Psychology, 2(1), pp.21–41. Available from: https://doi.org/10.1111/1467-839X.00024. DOI: https://doi.org/10.1111/1467-839X.00024
Bandura, A., 2001. Social Cognitive Theory: An Agentic Perspective. Annual Review of Psychology, 52, pp.1–26. https://ssrlsig.org/wp-content/uploads/2018/01/bandura-2001-social-cognitive-theory-an-agentic-perspective.pdf, Available from: https://doi.org/10.1146/annurev.psych.52.1.1. DOI: https://doi.org/10.1146/annurev.psych.52.1.1
Bénabou, R. and Tirole, J., 2003. Intrinsic and Extrinsic Motivation. The Review of Economic Studies, 70(3), pp.489–520. Available from: https://doi.org/10.1111/1467-937X.00253. DOI: https://doi.org/10.1111/1467-937X.00253
Bidwell, C.E., 1957. Some Effects of Administrative Behavior: A Study in Role Theory. Administrative Science Quarterly, 2(2), pp.163–181. Available from: https://doi.org/10.2307/2390688. DOI: https://doi.org/10.2307/2390688
Bredemeier, M.E., 1979. Role Theory and Educational Practice: Contingencies of Statuses for Persons. Journal of Teacher Education, 30(6), pp.13–16. Available from: https://doi.org/10.1177/002248717903000606. DOI: https://doi.org/10.1177/002248717903000606
Chen, L., Chen, P. and Lin, Z., 2020. Artificial Intelligence in Education: A Review. IEEE Access, 8, pp.75264–75278. Available from: https://doi.org/10.1109/ACCESS.2020.2988510. DOI: https://doi.org/10.1109/ACCESS.2020.2988510
Chiu, T.K.F., Moorhouse, B.L., Chai, C.S. and Ismailov, M., 2024. Teacher support and student motivation to learn with Artificial Intelligence (AI) based chatbot. Interactive Learning Environments, 32(7), pp.3240–3256. Available from: https://doi.org/10.1080/10494820.2023.2172044. DOI: https://doi.org/10.1080/10494820.2023.2172044
Chiu, T.K.F., Xia, Q., Zhou, X., Chai, C.S. and Cheng, M., 2023. Systematic literature review on opportunities, challenges, and future research recommendations of artificial intelligence in education. Computers and Education: Artificial Intelligence, 4, p.100118. Available from: https://doi.org/10.1016/j.caeai.2022.100118. DOI: https://doi.org/10.1016/j.caeai.2022.100118
Cohen, A., Soffer, T. and Henderson, M., 2022. Students’ use of technology and their perceptions of its usefulness in higher education: International comparison. Journal of Computer Assisted Learning, 38(5), pp.1321–1331. Available from: https://doi.org/10.1111/jcal.12678. DOI: https://doi.org/10.1111/jcal.12678
Conner, J., Mitra, D.L., Holquist, S.E., Rosado, E., Wilson, C. and Wright, N.L., 2024. The pedagogical foundations of student voice practices: The role of relationships, differentiation, and choice in supporting student voice practices in high school classrooms. Teaching and Teacher Education, 142, p.104540. Available from: https://doi.org/10.1016/j.tate.2024.104540. DOI: https://doi.org/10.1016/j.tate.2024.104540
Cook-Sather, A., 2020. Student voice across contexts: Fostering student agency in today’s schools. Theory Into Practice, 59(2), pp.182–191. Available from: https://doi.org/10.1080/00405841.2019.1705091. DOI: https://doi.org/10.1080/00405841.2019.1705091
Cook-Sather, A. and Matthews, K.E., 2023. Practising Student Voice in University Teaching and Learning: Three Anchoring Principles. Journal of University Teaching and Learning Practice, 20(6), pp.1–11. Available from: https://doi.org/10.53761/1.20.6.2. DOI: https://doi.org/10.53761/1.20.6.2
Creswell, J.W., Klassen, A.C., Plano Clark, V.L. and Smith, K.C., 2011. Best Practices for Mixed Methods Research in the Health Sciences. Office of Behavioral and Social Sciences Research. Available from: https://obssr.od.nih.gov/sites/obssr/files/Best_Practices_for_Mixed_Methods_Research.pdf. DOI: https://doi.org/10.1037/e566732013-001
Daubney, K., 2024. Lessons in Readiness: Self-determination and Student Agency in Careers, Employability, and Success. Journal of the Australian and New Zealand Student Services Association, 32(1), pp.10–18. Available from: https://doi.org/10.30688/janzssa.2024-1-04. DOI: https://doi.org/10.30688/janzssa.2024-1-04
Erss, M., Loogma, K. and Jõgi, A.L., 2024. The effect of teacher agency support, students’ personal perseverance and work experience on student agency in secondary schools with Estonian and Russian instructional language. Cogent Education, 11(1), p.2314515. Available from: https://doi.org/10.1080/2331186X.2024.2314515. DOI: https://doi.org/10.1080/2331186X.2024.2314515
Furman, J. and Seamans, R., 2019. AI and the Economy. Innovation Policy and the Economy, 19, pp.161–191. Available from: https://doi.org/10.1086/699936. DOI: https://doi.org/10.1086/699936
George, B. and Wooden, O., 2023. Managing the Strategic Transformation of Higher Education through Artificial Intelligence. Administrative Sciences, 13(9), p.196. Available from: https://doi.org/10.3390/admsci13090196. DOI: https://doi.org/10.3390/admsci13090196
Ghiasvand, F., Jahanbakhsh, A.A. and Sharifpour, P., 2023. Designing and validating an assessment agency questionnaire for EFL teachers: an ecological perspective. Language Testing in Asia, 13(1), p.41. Available from: https://doi.org/10.1186/s40468-023-00255-z. DOI: https://doi.org/10.1186/s40468-023-00255-z
Goldspink, C., Winter, P. and Foster, M., 2008. Student Engagement and Quality Pedagogy. European Conference on Educational Research. Gothenborg. Available from: https://web.archive.org/web/20221117011235/https://www.education.sa.gov.au/sites/default/files/student_engagement_and_quality_pedagogy.pdf.
Harnisch, S., 2010. Role theory: Operationalization of key concepts. Available from: https://www.uni-heidelberg.de/md/politik/harnisch/person/publikationen/harnisch_2010_role_theory_conceptualization_of_key_concepts.pdf.
Hider, U. and Arsalan, H., 2024. Transformative Teaching: Navigating Challenges in Generative AI Integration. Available from: https://doi.org/10.13140/RG.2.2.12977.80480.
Huang, J., Saleh, S. and Liu, Y., 2021. A Review on Artificial Intelligence in Education. Academic Journal of Interdisciplinary Studies, 10(3), pp.206–217. Available from: https://doi.org/10.36941/ajis-2021-0077. DOI: https://doi.org/10.36941/ajis-2021-0077
Johnson, R.L. and Morgan, G.B., 2016. Survey Scales: A Guide to Development, Analysis, and Reporting. Guilford Press. Available from: https://tinyurl.com/8b5zrww7.
Kankam-Kwarteng, C., Osei, F. and Donkor, G.N.A., 2022. Innovation, Environmental Antecedents and Performance Outcomes of Metropolitan, Municipal and District Assemblies in Ghana. EMAJ: Emerging Markets Journal, 12(2), pp.26–35. Available from: https://doi.org/10.5195/emaj.2022.265. DOI: https://doi.org/10.5195/emaj.2022.265
Kenwright, B., 2023. Exploring the Power of Creative AI Tools and Game-Based Methodologies for Interactive Web-Based Programming. Available from: https://doi.org/10.48550/arXiv.2308.11649.
Klemenčič, M., 2015. What is student agency? An ontological exploration in the context of research on student engagement in student engagement in Europe. In: S. Klemenčič, R. Bergan and R. Primožič, eds. Student engagement in Europe: Society, higher education and student governance. Strasbourg: Council of Europe Publishing, Higher Education Series 20, pp.11–29. Available from: https://scholar.harvard.edu/files/manja_klemencic/files/2015_klemencic_what_is_student_agency_submission_version.pdf.
Klemenčič, M., 2023. A theory of student agency in higher education. In: C. Baik and E.R. Kahu, eds. Research Handbook on the Student Experience in Higher Education. Edward Elgar Publishing, Elgar Handbooks in Education, chap. 3, pp.25–40. Available from: https://doi.org/10.4337/9781802204193.00010. DOI: https://doi.org/10.4337/9781802204193.00010
Kusters, M., van der Rijst, R., de Vetten, A. and Admiraal, W., 2023. University lecturers as change agents: How do they perceive their professional agency? Teaching and Teacher Education, 127, p.104097. Available from: https://doi.org/10.1016/j.tate.2023.104097. DOI: https://doi.org/10.1016/j.tate.2023.104097
Kuzhabekova, A. and Amankulova, Z., 2024. International Student Agency in Emergency: Insights from Government-funded Students from Kazakhstan. Journal of International Students, 14(3), pp.131–148. Available from: https://doi.org/10.32674/jis.v14i3.6107. DOI: https://doi.org/10.32674/jis.v14i3.6107
Leavy, P., 2023. Research Design: Quantitative, Qualitative, Mixed Methods, Arts-Based, and Community-Based Participatory Research Approaches. 2nd ed. Guilford Publications. Available from: https://tinyurl.com/mvfk6hhm.
Li, J., Huang, X. and Huang, H., 2024. Fostering Student Agency in learning Mathematics: Perspectives from Expert Teachers in Shanghai. Proceedings of the 14th International Congress on Mathematical Education. World Scientific Connect, chap. 21, pp.311–325. Available from: https://doi.org/10.1142/9789811287183_0021. DOI: https://doi.org/10.1142/9789811287183_0021
Lodico, M.G., Spaulding, D.T. and Voegtle, K.H., 2006. Methods in Educational Research: From Theory to Practice. Jossey-Bass. Available from: https://stikespanritahusada.ac.id/wp-content/uploads/2017/04/Marguerite_G._Lodico_Dean_T._Spaulding_KatherinBookFi.pdf.
Merton, R.K., 1957. The Role-Set: Problems in Sociological Theory. British Journal of Sociology, 8(2), pp.106–120. https://sites.temple.edu/stsnetwork/files/2022/01/The-Role-Set_Problems-in-Sociological-Theory.pdf, Available from: https://doi.org/10.2307/587363. DOI: https://doi.org/10.2307/587363
Moore, I., 2022. The effect of student voice on the perception of student agency. International Journal of Educational Research, 112, p.101923. Available from: https://doi.org/10.1016/j.ijer.2022.101923. DOI: https://doi.org/10.1016/j.ijer.2022.101923
Moore, R.L., Jiang, S. and Abramowitz, B., 2023. What would the matrix do?: a systematic review of K-12 AI learning contexts and learner-interface interactions. Journal of Research on Technology in Education, 55(1), pp.7–20. Available from: https://doi.org/10.1080/15391523.2022.2148785. DOI: https://doi.org/10.1080/15391523.2022.2148785
Nguyen, M.H. and Ngo, X.M., 2023. An activity theory perspective on Vietnamese preservice English teachers’ identity construction in relation to tensions, emotion and agency. Language Teaching Research, p.13621688221151046. Available from: https://doi.org/10.1177/13621688221151046. DOI: https://doi.org/10.1177/13621688221151046
Noteboom, J., 2024. Everyday datafication and higher education: Student agency, trust and resignation. In: M. Cutajar, C. Borg, M. De Laat, N.B. Dohn and T. Ryberg, eds. Proceedings of the Fourteenth International Conference on Networked Learning Conference. vol. 14. Available from: https://doi.org/10.54337/nlc.v14i1.8083. DOI: https://doi.org/10.54337/nlc.v14i1.8083
Othman, N. and Kadir, M.A., 2004. The problems with problem-based learning in the language classroom. 5th Asia-Pacific Conference on Problem-based Learning: Pursuit of Excellence in Education. Petaling Jaya, Malaysia.
Pedler, M., Hudson, S. and Yeigh, T., 2020. The Teachers’ Role in Student Engagement: A Review. Australian Journal of Teacher Education, 45(3), pp.48–62. Available from: https://doi.org/10.14221/ajte.2020v45n3.4. DOI: https://doi.org/10.14221/ajte.2020v45n3.4
Richards, K.A.R., 2015. Role socialization theory: The sociopolitical realities of teaching physical education. European Physical Education Review, 21(3), pp.379–393. Available from: https://doi.org/10.1177/1356336X15574367. DOI: https://doi.org/10.1177/1356336X15574367
Van Maanen, J. and Schein, E.H., 1978. Toward a theory of organizational socialization. In: B. Staw, ed. Annual review of research in organizational behavior. New York: JIP Press, vol. 1, pp.209–261. Available from: https://dspace.mit.edu/handle/1721.1/1934.
Vighnarajah, Luan, W.S. and Bakar, K.A., 2008. The Shift in the Role of Teachers in the Learning Process. European Journal of Social Sciences, 7(2), pp.33–41. Available from: https://cmapspublic2.ihmc.us/rid=1N5PWK5N9-23N1RFF-37Y8/Vighnarajah%20The%20shift%20in%20the%20role%20of%20teachers.pdf.
Xia, Q., Chiu, T.K.F., Lee, M., Sanusi, I.T., Dai, Y. and Chai, C.S., 2022. A self-determination theory (SDT) design approach for inclusive and diverse artificial intelligence (AI) education. Computers & Education, 189, p.104582. Available from: https://doi.org/10.1016/j.compedu.2022.104582. DOI: https://doi.org/10.1016/j.compedu.2022.104582
Yan, L., Martinez-Maldonado, R. and Gasevic, D., 2024. Generative Artificial Intelligence in Learning Analytics: Contextualising Opportunities and Challenges through the Learning Analytics Cycle. Proceedings of the 14th Learning Analytics and Knowledge Conference. New York, NY, USA: Association for Computing Machinery, LAK ’24, p.101–111. Available from: https://doi.org/10.1145/3636555.3636856. DOI: https://doi.org/10.1145/3636555.3636856
Downloads
Submitted
Published
Data Availability Statement
Data are available upon resonable request.
Issue
Section
License
Copyright (c) 2025 Devi Prasad Adhikari, Gopal Prasad Pandey

This work is licensed under a Creative Commons Attribution 4.0 International License.
How to Cite
Accepted 2025-05-10
Published 2025-06-20
