From being to becoming a teacher in the age of Artificial Intelligence: A reflection within the university context
DOI:
https://doi.org/10.53485/ret.v5i3.790Keywords:
university teaching, generative artificial intelligence, teacher identity, pedagogical mediation, knowledgeAbstract
This essay reflects on the resignification of university teaching in response to transformations in the production, circulation, and mediation of knowledge associated with generative artificial intelligence. This study is based on the findings of a qualitative phenomenological-hermeneutic study conducted with four university professors, from which an Ontological Semantic Structure of the Teaching Profession was constructed, comprising the human, epistemic, pedagogical, and social dimensions, thereby enabling a second-order hermeneutic-theoretical reinterpretation. These findings are placed in dialogue with recent scientific literature on artificial intelligence, higher education, teacher identity and agency, pedagogical mediation, and ethical responsibility. The reflection shows that artificial intelligence should not be understood solely as an instrumental innovation or as a mechanism for replacing teaching functions, but as a condition that modifies relationships with students, knowledge, teaching, and the university community. This dialogue leads to the interpretive category becoming a teacher, understood as a continuous process of reconstructing knowledge, practices, relationships, and responsibilities in response to transformations in educational contexts and knowledge. The essay concludes that the teacher’s centrality shifts from possessing information toward interpreting, validating, contextualizing, and giving educational meaning to it, while preserving pedagogical relationships, human agency, and social responsibility. The conceptual contribution lies in proposing becoming a teacher as a key for understanding professional transformation in university contexts mediated by artificial intelligence.
References
Alfiras, M. I. I., Emran, A. Q., & Mohamed, A. M. (2026). Ethics and governance of generative AI in education: A systematic review on responsible adoption. *Discover Education, 5*, Article 37. https://doi.org/10.1007/s44217-025-01051-y
Almazán-López, O., Hasbún, H., & Osuna-Acedo, S. (2025). Generative artificial intelligence and (post)digital teacher identity. *IJERI: International Journal of Educational Research and Innovation, 24*, 1–17. https://doi.org/10.46661/ijeri.11160
An, Y., Yu, J. H., & James, S. (2025). Investigating the higher education institutions’ guidelines and policies regarding the use of generative AI in teaching, learning, research, and administration. *International Journal of Educational Technology in Higher Education, 22*, Article 10. https://doi.org/10.1186/s41239-025-00507-3
Autor/a. (2020). *El ser docente universitario, un estudio fenomenológico desde la perspectiva pedagógica* [Tesis doctoral, institución anonimizada].
Baggia, A., Tratnik, A., & Brezavšček, A. (2026). University teachers’ perceptions, attitudes, and practices with generative AI: A systematic literature review with a meta-analytic component. *Quality & Quantity, 60*, 14107–14139. https://doi.org/10.1007/s11135-026-02717-x
Batista, J., Mesquita, A., & Carnaz, G. (2024). Generative AI and higher education: Trends, challenges, and future directions from a systematic literature review. *Information, 15*(11), 676. https://doi.org/10.3390/info15110676
Carranza Alcántar, M. del R., Macías González, G. G., Gómez Rodríguez, H., Jiménez Padilla, A. A., & Jacobo Montes, F. M. (2024). Percepciones docentes sobre la integración de aplicaciones de IA generativa en el proceso de enseñanza universitario. *REDU. Revista de Docencia Universitaria*. https://doi.org/10.4995/redu.2024.22027
Dempere, J., Modugu, K., Hesham, A., & Ramasamy, L. K. (2023). The impact of ChatGPT on higher education. *Frontiers in Education, 8*, 1206936. https://doi.org/10.3389/feduc.2023.1206936
Kahn, P., Carrigan, M., Smith, P., Murtagh, L., Liu, R., & Song, F. (2025). Teacher agency and generative artificial intelligence: Teaching in higher education as a responsive, cultural activity. *Learning, Media and Technology*. https://doi.org/10.1080/17439884.2025.2575993
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., Stadler, M., Weller, J., Kuhn, J., & 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
Li, J., & Zhang, Q. (2026). Teacher identity negotiation in AI-enhanced higher education and its implications for professional development. *Teaching and Teacher Education, 176*, 105499. https://doi.org/10.1016/j.tate.2026.105499
Liang, J., Stephens, J. M., & Brown, G. T. L. (2025). A systematic review of the early impact of artificial intelligence on higher education curriculum, instruction, and assessment. *Frontiers in Education, 10*, 1522841. https://doi.org/10.3389/feduc.2025.1522841
Miao, F., & Cukurova, M. (2024). *AI competency framework for teachers*. UNESCO. https://doi.org/10.54675/ZJTE2084
Pérezchica-Vega, J. E., Sepúlveda-Rodríguez, J. A., & Román-Méndez, A. D. (2024). Inteligencia artificial generativa en la educación superior: usos y opiniones de los profesores. *European Public & Social Innovation Review, 9*. https://doi.org/10.31637/epsir-2024-986
Qian, Y. (2025). Pedagogical applications of generative AI in higher education: A systematic review of the field. *TechTrends, 69*, 1105–1120. https://doi.org/10.1007/s11528-025-01100-1
Rivarola Prados, P., & Fernández Paradas, A. R. (2026). Competencias docentes para la inteligencia artificial generativa en educación superior: perfiles diferenciados y orientaciones para el desarrollo profesional. *MLS Educational Research*. https://doi.org/10.29314/51n99h35
UNESCO. (2023). *Guía para el uso de IA generativa en educación e investigación*. https://unesdoc.unesco.org/ark:/48223/pf0000389227
Universidad Nacional Autónoma de México. (2025). Presencia y uso de la inteligencia artificial generativa en la Universidad Nacional Autónoma de México. *Revista Digital Universitaria, 26*(1). https://doi.org/10.22201/ceide.16076079e.2025.26.1.10
Weng, X., Xia, Q., Gu, M., Rajaram, K., & Chiu, T. K. F. (2024). Assessment and learning outcomes for generative AI in higher education: A scoping review on current research status and trends. *Australasian Journal of Educational Technology, 40*(6), 37–55. https://doi.org/10.14742/ajet.9540
Xia, Q., Weng, X., Ouyang, F., Lin, T. J., & Chiu, T. K. F. (2024). A scoping review on how generative artificial intelligence transforms assessment in higher education. *International Journal of Educational Technology in Higher Education, 21*, Article 40. https://doi.org/10.1186/s41239-024-00468-z
Zhai, X. (2025). Transforming teachers’ roles and agencies in the era of generative AI: Perceptions, acceptance, knowledge, and practices. *Journal of Science Education and Technology, 34*(6), 1323–1333. https://doi.org/10.1007/s10956-024-10174-0
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