Integration of Generative Artificial Intelligence in Teacher Education: Cognitive Implications for Students at Universidad Pedagógica Veracruzana

Authors

Keywords:

generative artificial intelligence, higher education, teacher education, pedagogical mediation, digital skills

Abstract

The use of Generative Artificial Intelligence (GAI) in higher education has transformed the ways in which students produce content, organize information, and carry out academic activities. This study analyzed the perceptions and uses of GAI among students enrolled in the Bachelor’s Degree in Basic Education at the Universidad Pedagógica Veracruzana, based on a learning experience implemented in the Basic Computing course during the August 2025–January 2026 academic term. The research adopted a descriptive-interpretative mixed-methods approach and compared two groups with different levels of pedagogical mediation in the use of artificial intelligence tools. A total of 47 students, distributed across two academic groups, participated in the study. Data were collected through a Likert-scale questionnaire and semi-structured interviews. The results indicate that the group receiving greater pedagogical mediation demonstrated broader integration of GAI in activities related to text production, presentation design, image generation, and the development of audiovisual materials. This group also reported more favorable perceptions regarding the pedagogical usefulness of these tools. However, both groups expressed concerns about the accuracy and reliability of AI-generated information, as well as issues related to technological dependence and the potential impact on critical thinking. The study concludes that the educational integration of GAI depends not only on access to digital tools but also on the forms of pedagogical mediation that guide their use and foster more reflective learning processes.

Downloads

Download data is not yet available.

References

Biggs, J. (2005). Quality learning at university (2nd ed.). Open University Press.

Bray, M., Adamson, B., & Mason, M. (Eds.). (2014). Comparative education research: Approaches and methods (2nd ed.). Comparative Education Research Centre, The University of Hong Kong; Springer. https://doi.org/10.1007/978-3-319-05594-7

Braun, V., & Clarke, V. (2021). Thematic analysis: A practical guide. SAGE.

Creswell, J. W., & Plano Clark, V. L. (2018). Designing and conducting mixed methods research (3rd ed.). SAGE.

Chao-Rebolledo, C., & Rivera-Navarro, M. Á. (2024). Usos y percepciones de herramientas de inteligencia artificial en la educación superior en México. Revista Iberoamericana de Educación, 95(1), 57–72. https://doi.org/10.35362/rie9516259

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008

Denzin, N. K., & Lincoln, Y. S. (Eds.). (2018). The SAGE handbook of qualitative research (5th ed.). SAGE.

Fernández-Prados, J. S., Lozano-Díaz, A., Bellido-Cáceres, J. M., & Martínez-Salvador, I. (2025). Percepciones de la inteligencia artificial en estudiantes universitarios: El rol de la ansiedad tecnológica y las competencias digitales. Formación Universitaria, 18(5), 115–124. https://doi.org/10.4067/S0718-50062025000500115

Flick, U. (2018). An introduction to qualitative research (6th ed.). SAGE.

Hernández-Sampieri, R., & Mendoza Torres, C. P. (2018). Metodología de la investigación: Las rutas cuantitativa, cualitativa y mixta. McGraw-Hill.

Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign. https://curriculumredesign.org/wp-content/uploads/AIED-Book-Excerpt-CCR.pdf

Ifenthaler, D., & Schumacher, C. (2023). Reciprocal issues of artificial and human intelligence in education. Journal of Research on Technology in Education, 55(1), 1–6. https://doi.org/10.1080/15391523.2022.2154511

Kerlinger, F. N., & Lee, H. B. (2002). Investigación del comportamiento: Métodos de investigación en ciencias sociales (4.ª ed.). McGraw-Hill.

Kvale, S., & Brinkmann, S. (2009). InterViews: Learning the craft of qualitative research interviewing (2nd ed.). SAGE.

Likert, R. (1932). A technique for the measurement of attitudes. Archives of Psychology, 140, 1–55.

Martínez Bonilla, I., Guarneros Reyes, E., & Silva Rodríguez, A. (2025). Usos y percepciones de la inteligencia artificial generativa en la educación superior en México: Una revisión sistemática. Transdigital, 6(12), e492. https://doi.org/10.56162/transdigital492

Mollick, E. R., & Mollick, L. (2023). Assigning AI: Seven approaches for students, with prompts [Working paper]. SSRN. https://doi.org/10.2139/ssrn.4475995

Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill.

Núñez-Valdés, K. P., Sepúlveda-Irribarra, C. A., Villegas-Dianta, C. A., & Castillo-Paredes, A. J. (2025). Inteligencia artificial y formación docente: Análisis de las percepciones estudiantiles. Formación Universitaria, 18(4), 1–12. https://doi.org/10.4067/S0718-50062025000400001

Rentería García, C. D. (2024). El impacto de la inteligencia artificial en la educación superior: Representaciones sociales y transformación institucional. TIES. Revista de Tecnología e Innovación en Educación Superior, 11, 53–71. https://doi.org/10.22201/dgtic.26832968e.2024.11.47

Sallam, M. (2023). ChatGPT utility in healthcare education, research, and practice: Systematic review on the promising perspectives and valid concerns. Healthcare, 11(6), 887. https://doi.org/10.3390/healthcare11060887

Selwyn, N. (2016). Education and technology: Key issues and debates (2nd ed.). Bloomsbury Academic.

Selwyn, N. (2019). Should robots replace teachers? AI and the Future of Education. (1st ed.) Polity Press.

Secretaría de Educación Pública. (2025). Dossier de resultados de la Encuesta Nacional sobre Inteligencia Artificial Generativa (ENIAG 2025). Gobierno de México. https://www.gob.mx/cms/uploads/attachment/file/1071411/Dossier_Resultados_ENIAG2025_SEP_.pdf

Soto, J. y Reyes, I. (2024). Apreciaciones de estudiantes universitarios sobre el uso del ChatGPT. Revista Paraguaya de Educación a Distancia (REPED), 5(2), 56–65. https://doi.org/10.56152/reped2024-dossierIA1-art5

Sweller, J. (2019). Cognitive load theory and educational technology. Educational Technology Research and Development, 67, 1–16. https://doi.org/10.1007/s11423-019-09701-3

UNESCO. (2021). AI and education: Guidance for policy-makers. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000376709

UNESCO. (2023). Guidance for generative AI in education and research. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000386693

Watkins, D. A. (2001). La comparación de maneras de aprender. En M. Bray, B. Adamson, & M. Mason (Eds.), Educación comparada: Enfoques y métodos (pp. 361–382). Granica.

Zikmund, W. G., Babin, B. J., Carr, J. C., & Griffin, M. (2013). Business research methods (9th ed.). Cengage Learning.

Downloads

Published

2026-07-30

How to Cite

Integration of Generative Artificial Intelligence in Teacher Education: Cognitive Implications for Students at Universidad Pedagógica Veracruzana (J. L. Soto Ortiz , Trans.). (2026). Latin American Journal of Humanities and Educational Divergences, 5(1), 302-321. https://revistas.jjsanmarcos.org/index.php/lajhed/article/view/224