¹Nagamurali Eragamreddy, ²Sivareddy Bojja, ³Eman Abdulnoor Omar Cosso

¹General Requirements Unit, Preparatory Studies Center, University of Technology and Applied Sciences, Salalah, Oman

²VR School, India

³English Department, Faculty of Education, University of Fezzan, Libya

DOI : https://doi.org/10.58806/ijsshmr.2026.v5i3n02

Google Scholar Download Pdf
ABSTRACT

The proposed cross-national qualitative research examines how teachers develop and negotiate their professional identity in reaction to the increasing adoption of Generative Artificial Intelligence (GenAI) into the teaching process. It also examines how the adoption or opposition to GenAI is indicative of the changing beliefs, values, and self-perceptions of teachers during the digital age. The participants were thirty Indian, Libyan, Nigerian, Jordanian, South African, Iranian, and Armenian educators who were interviewed in asynchronous and text-based emails to get reflective and narrative answers. The study used the method of cross-contextual patterns to identify the cross-contextual patterns using Braun and Clarke's thematic analysis, using a semi-structured interview guide based on the teacher identity theory and the activity theory. Results showed that GenAI is not only a technological invention but a cultural and ethical mediator that redefines the identity of the teacher, the power and the purpose of pedagogy. Teachers repositioned themselves as contemplative mentors and moral advisors and mediated the conflicts between technological efficacy and ethical accountability. The study has concluded that to remain a teacher in the GenAI era, one must engage in constant reflexivity, ethical literacy, and pedagogical adaptation to the context.

KEYWORDS:

Teacher identity, Generative Artificial Intelligence, technology integration, digital pedagogy, professional transformation

REFERENCES

1) Al-Karasneh, S. M., Kanaan, E. M., Al-Barakat, A. A., AlAli, R. M., Zaher, A. M., & Ibrahim, N. A. (2025). Transforming primary science education: Unlocking the power of generative AI to enhance pupils’ grasp of scientific concepts. International Journal of Learning, Teaching and Educational Research, 24(5), 304-322. https://doi.org/10.26803/ijlter.24.5.16

2) Amri, M., Angelakis, C., & Logan, D. (2021). Utilizing asynchronous email interviews for health research: overview of benefits and drawbacks. BMC Research Notes, 14(1), 148. https://doi.org/10.1186/s13104-021-05547-2

3) Beijaard, D., Meijer, P. C., & Verloop, N. (2004). Reconsidering research on teachers’ professional identity. Teaching and Teacher Education, 20(2), 107–128. https://doi.org/10.1016/j.tate.2003.07.001

4) Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa

5) Campbell, S., Greenwood, M., Prior, S., Shearer, T., Walkem, K., Young, S., Bywaters, D., & Walker, K. (2020). Purposive sampling: complex or simple? Research case examples. Journal of Research in Nursing, 25(8), 652-661. https://doi.org/10.1177/1744987120927206

6) Chan, C. K. Y., & Colloton, T. (2024). Generative AI in higher education: The ChatGPT effect Routledge. https://library.oapen.org/handle/20.500.12657/88443

7) Czerniawski, G. (2025). Teacher educators in the twenty-first century: Identity, knowledge and research. Routledge. https://doi.org/10.4324/9781041057277

8) Dobrin, S. I. (2025). Talking about Generative AI: A Guide for Educators 2.0. Broadview Press.

9) Du, C., Peng, Y., binti Ahmad, N. K., & binti Jamil, A. H. (2025). EFL Teachers’ identity tensions and transformation in AI-driven teaching in China: A dialogical approach. In V.P.H., Pham, A. Lian, A. Lian, & J. White (Eds.), Empowering educators: Integrating AI tools for personalized language instruction (pp. 185-206). Springer. https://doi.org/10.1007/978-3-032-01348-4_7

10) Engeness, I. (2020). Developing teachers’ digital identity: Towards the pedagogic design principles of digital environments to enhance students’ learning in the 21st century. European Journal of Teacher Education, 44(1), 96–114. https://doi.org/10.1080/02619768.2020.1849129

11) Engeström, Y. (2014). Learning by expanding: An activity-theoretical approach to developmental research (2nd ed.). Cambridge University Press. https://doi.org/10.1017/CBO9781139814744

12) Feher, K. (2025). Generative AI, media, and society. Rputledge.

13) Gamlem, S. M., McGrane, J., Brandmo, C., Moltudal, S., Sun, S. Z., & Hopfenbeck, T. N. (2025). Exploring pre-service teachers’ attitudes and experiences with generative AI: A mixed methods study in Norwegian teacher education. Educational Psychology, 1–25. https://doi.org/10.1080/01443410.2025.2528663

14) Gee, J. P. (2000). Chapter 3: Identity as an analytic lens for research in education. Review of Research in Education, 25(1), 99-125. https://doi.org/10.3102/0091732X025001099

15) Gibson, J. J. (1979). The ecological approach to visual perception. Houghton Mifflin.

16) Keränen-Pantsu, R., & Heikkinen, H. (2019). Pedagogical purposes of narratives in worldview education: Teachers' conceptions. International Journal of Learning, Teaching and Educational Research, 18(5), 58-72. https://doi.org/10.26803/ijlter.18.5.5

17) Knox, J. (2022). (Re)politicising data-driven education: from ethical principles to radical participation. Learning, Media and Technology, 48(2), 200-212. https://doi.org/10.1080/17439884.2022.2158466

18) Lan, Y. (2024). Through tensions to identity-based motivations: Exploring teacher professional identity and AI integration. Teaching and Teacher Education, 151, 104736. https://doi.org/10.1016/j.tate.2024.104736

19) Lave, J., & Wenger, E. (1991). Situated learning: Legitimate peripheral participation. Cambridge University Press. https://doi.org/10.1017/CBO9780511815355

20) Leont'ev, A. N. (1978). Activity, consciousness, and personality. Prentice-Hall.

21) Lei, Y. (2024). The interplay of job embeddedness, collective efficacy, and work meaningfulness on teacher well-being: A mixed-methods study with digital ethnography in China. Frontiers in Psychology, 15, 1448446. https://doi.org/10.3389/fpsyg.2024.1448446

22) Matos, T., Santos, W., Zdravevski, E., Coelho, P. J., Pires, I. M., & Madeira, F. (2025). A systematic review of artificial intelligence applications in education: Emerging trends and challenges. Decision Analytics Journal, 15, 100571. https://doi.org/10.1016/j.dajour.2025.100571

23) Meho, L. I. (2006). E-mail interviewing in qualitative research: A methodological discussion. Journal of the American Society for Information Science and Technology, 57(10), 1284–1295. https://doi.org/10.1002/asi.20416

24) Norman, D. A. (2013). The design of everyday things. Basic Books.

25) Nyaaba, M. (2024). Transforming teacher education in developing countries: The role of generative AI in bridging theory and practice. arXiv:2411.10718. https://arxiv.org/abs/2411.10718

26) Patton, M. Q. (2015). Qualitative research & evaluation methods: Integrating theory and practice (4th ed.). SAGE Publications.

27) Ratislavová, K., & Ratislav, J. (2014 ). Asynchronous email interview as a qualitative research method in the humanities. Human Affairs, 24(4), 452–460. https://doi.org/10.2478/s13374-014-0240-y

28) Samala, A. D., Rawas, S., Wang, T., Reed, J. M., Kim, J., Howard, N. J., & Ertz, M. (2025). Unveiling the landscape of generative artificial intelligence in education: A comprehensive taxonomy of applications, challenges, and future prospects. Education and Information Technologies, 30(3), 3239-3278. https://doi.org/10.1007/s10639-024-12936-0

29) Satvati, N., Kamali, J., Safian Boldaji, F., Khodadadi, M., & Akhondi, S. (2025). AI integration into language education and teacher identity: An ecological perspective. Language Teaching Research Quarterly, 47, 1-19. https://doi.org/10.32038/ltrq.2025.47.01

30) Selwyn, N. (2019). Should robots replace teachers? AI and the future of education. Polity Press.

31) Shobeiry, M. (2024). A longitudinal qualitative study on Iranian university lecturers' identity reconstruction during the COVID-19 pandemic through text-mining: A dynamic approach. Asian-Pacific Journal of Second and Foreign Language Education, 9(13), 1-28. https://doi.org/10.1186/s40862-023-00234-0

32) Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Harvard University Press.

33) Zapata, G. C. (Ed.). (2025). Generative AI technologies, multiliteracies, and language education. Routledge. https://doi.org/10.4324/9781003531685

34) Zhai, X. (2024). Transforming teachers’ roles and agencies in the era of generative AI: Perceptions, acceptance, knowledge, and practices. Journal of Science Education and Technology, 1-11. https://doi.org/10.1007/s10956-024-10174-0

Cite this Article:Eragamreddy, N., Bojja, S., & Cosso, E. A. O. (2026). Teacher Identity and Technology use in the Gen Ai Era. INTERNATIONAL JOURNAL OF SOCIAL SCIENCE HUMANITY & MANAGEMENT RESEARCHS, 5(3), 444-453. https://doi.org/10.58806/ijsshmr.2026.v5i3n02

VOlUME 05 ISSUE 03 March 2026