Adoption and use of artificial intelligence in university teaching by academics in a regional context
Authors
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Juan Muñoz-Tapia
Universidad de Aconcagua
https://orcid.org/0000-0002-7260-516X
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David Román-Soto
Universidad de Aconcagua
https://orcid.org/0000-0002-0075-4094
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Abstract
Currently, education is marked by the transformations that are taking place as a result of the use of new technologies. In this context, this research identifies how teachers at a Chilean university with campuses in various regions of the country use artificial intelligence (AI) to enhance their work. Based on a pragmatic paradigm, a mixed methodological approach, and a nested sequential design, teachers were surveyed to identify their practices, perceptions, and challenges related to the implementation of AI in higher education contexts. Preliminary results show that the majority of participating teachers use AI as a learning tool, facilitating the process of creating material, but not as a teaching strategy to strengthen the didactic and curricular aspects of their pedagogical work.Keywords:
artificial intelligence, teaching, regional context, higher educationReferences
Alfaro Salas, H., y Díaz Porras, J. A. (2024). Percepciones del personal docente acerca del uso ético de la inteligencia artificial en su labor educativa. Revista Innovaciones Educativas, 26(41), 63–77. https://doi.org/10.22458/ie.v26i41.4952
Cortés, F., De Tezanos-Pinto, P., y Helsper, E. (2022). ¿Se ha reducido la brecha digital en Chile? Diferencias entre acceso, uso y factores asociados al empleo de internet. MIDevidencias, (22), 1–12. https://mideuc.cl/wp-content/uploads/2022/11/MIDevidencias-N22.pdf
Creswell, J. W., y Clark, V. L. P. (2017). Designing and conducting mixed methods research. Sage Publications.
De León, C. H., Ábrego, A., y Gutiérrez, L. (2024). La brecha de conocimiento sobre inteligencia artificial entre catedráticos y estudiantes universitarios en Guatemala: Percepción desde el punto de vista del docente. Revista Espacios, 45(2), 16–28. https://doi.org/10.48082/espacios-a24v45n02p02
Delgado de Frutos, N., Campo-Carrasco, L., Sainz de la Maza, M., y Etxabe-Urbieta, J. M. (2024). Aplicación de la inteligencia artificial (IA) en educación: Los beneficios y limitaciones de la IA percibidos por el profesorado de educación primaria, educación secundaria y educación superior. Revista Electrónica Interuniversitaria de Formación del Profesorado, 27(1), 207–224. https://doi.org/10.6018/reifop.577211
Ertmer, P., y Ottenbreit-Leftwich, A. (2010). Teacher technology change: How knowledge, beliefs, and culture intersect. Journal of Research on Technology in Education, 42(3), 255–284. https://doi.org/10.1080/15391523.2010.10782551
Ferede, B., Elen, J., y Goeman, K. (2022). Instructors’ educational ICT use in higher education in developing countries: Evidence from three Ethiopian universities. Journal of Computing in Higher Education, 34(3), 658–678. https://doi.org/10.1007/s12528-022-09316-3
Johns, B. T., Jamieson, R. K., y Jones, M. N. (2023). Scalable cognitive modelling: Putting Simon’s (1969) ant back on the beach. Canadian Journal of Experimental Psychology / Revue Canadienne de Psychologie Expérimentale. Advance online publication. https://doi.org/10.1037/cep0000306
Kus, Z., y Mert, H. (2024). Digital competence of educators in Turkey according to the European Digital Competence Framework. Journal of Learning and Teaching in Digital Age, 9(1), 102–114. https://doi.org/10.53850/joltida.1301592
Llorent-Vaquero, M., y De Pablos Pons, J. (2022). Estudio comparado de políticas educativas digitales autonómicas en España. Revista Fuentes, 24(1), 28–38. https://doi.org/10.12795/revistafuentes.2022.18564
Maione, E., y García, G. V. (2025). Limits and possibilities for a transfeminist foreign policy. Relaciones Internacionales-Madrid, 58, Article 006. https://doi.org/10.15366/relacionesinternacionales2025.58.006
Mishra, P., y Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017–1054. https://doi.org/10.1111/j.1467-9620.2006.00684.x
Paidicán-Soto, M. Á., y Arredondo-Herrera, P. A. (2024). Conocimiento técnico-pedagógico del contenido (TPACK) en contextos rurales: Una revisión bibliográfica. Revista de Estudios y Experiencias en Educación, 23(51), 128–152. https://doi.org/10.21703/rexe.v23i51.2183
Pérez Pérez, O. J., y González de Pirela, N. J. (2024). Formación docente para el uso de la inteligencia artificial. Ciencia Latina Revista Científica Multidisciplinar, 8(5), 11772–11788. https://doi.org/10.37811/cl_rcm.v8i5.14594
Polimeno, A., Mignone, P., Braghin, C., Anisetti, M., Ceci, M., Malerba, D., y Ardagna, C. A. (2025). Balancing protection and quality in big data analytics pipelines. Big Data, 13(2), 127–143. https://doi.org/10.1089/big.2023.0065
Ramón Fernández, F. (2020). Inteligencia artificial y agricultura: Nuevos retos en el sector agrario. Campo Jurídico, 8(2), 123–139. https://doi.org/10.37497/revcampojur.v8i2.662
Recsko, M., y Aranyossy, M. (2024). User acceptance of social network-backed cryptocurrency: A unified theory of acceptance and use of technology (UTAUT)-based analysis. Financial Innovation, 10(1), Article 57. https://doi.org/10.1186/s40854-023-00511-4
Rivero Panaqué, C., y Beltrán Castañón, C. (2024). La inteligencia artificial en la educación del siglo XXI: Avances, desafíos y oportunidades. Educación, 33(64), 5–7. https://doi.org/10.18800/educacion.202401.p001
Román-Soto, D. (2024). Interclusión: Aproximaciones epistemológicas y didácticas para el devenir educativo contemporáneo. Revista Electrónica Educare, 28(3), 1–19. https://doi.org/10.15359/ree.28-3.18476
Smith, M. C. H., y Bazis, P. S. (2021). Conducting mixed methods research systematic methodological reviews: A review of practice and recommendations. Journal of Mixed Methods Research, 15(4), 546–566. https://doi.org/10.1177/1558689820967626
Tashakkori, A., y Teddlie, C. (2010). Putting the human back in “human research methodology”: The researcher in mixed methods research. Journal of Mixed Methods Research, 4(4), 271–277. https://doi.org/10.1177/1558689810382532
Teo, T. (2011). Factors influencing teachers’ intention to use technology: Model development and test. Computers & Education, 57(4), 2432–2440. https://doi.org/10.1016/j.compedu.2011.06.008
Teräs, M. (2022). Neil Selwyn: Education and technology: Key issues and debates. International Review of Education, 68(5), 757–760. https://doi.org/10.1007/s11159-022-09971-9
Touretzky, D., Gardner-McCune, C., y Seehorn, D. (2023). Machine learning and the five big ideas in AI. International Journal of Artificial Intelligence in Education, 33(2), 233–266. https://doi.org/10.1007/s40593-022-00314-1
UNESCO. (2024). Qué necesita saber acerca del aprendizaje digital y la transformación de la educación. UNESCO. https://www.unesco.org/es/digital-education/need-know
Van Dijk, J. (2020). The digital divide. Polity Press.
Xing, W. L., Nixon, N., Crossley, S., Denny, P., Lan, A., Stamper, J., y Yu, Z. (2025). The use of large language models in education. International Journal of Artificial Intelligence in Education, 35(2), 439–443. https://doi.org/10.1007/s40593-025-00457-x
