From UNESCO to UNAM: Adaptation of a framework of teaching competencies in artificial intelligence for education

Main Article Content

Erik Carbajal-Degante

Abstract

This work analyzes the attributes proposed by UNESCO regarding competencies in artificial intelligence, establishing their relationship with the responsibilities of the stakeholders involved in the educational sector. Furthermore, these guidelines are linked to the programmatic lines of UNAM’s Institutional Development Program, which outlines strategies and objectives for the 2023-2027 period. In this way, the study aims to align digital competencies with institutional goals, promoting the ethical, responsible and effective integration of these technologies in both secondary and higher education, including traditional, open and distance education.

Article Details

How to Cite
Carbajal-Degante, . E. (2025). From UNESCO to UNAM: Adaptation of a framework of teaching competencies in artificial intelligence for education. Revista Mexicana De Bachillerato a Distancia, 17(33). https://doi.org/10.22201/cuaieed.20074751e.2025.33.90977

Citas en Dimensions Service

References

Foro Económico Mundial / World Economic Forum. (2024, enero 17). From climate to coding, AI’s impact is ramping up. These 7 principles ensure it remains human-centric. https://www.weforum.org/stories/2024/01/7-principles-integrate-artificial-intelligence-impact/

Hutson, J., Jeevanjee, T., Graaf, V. V., Lively, J., Weber, J., Weir, G., Arnone, K., Carnes, G., Vosevich, K., Plate, D., Leary, M., y Edele, S. (2022). Artificial Intelligence and the Disruption of Higher Education: Strategies for Integrations across Disciplines. Creative Education, 13(12), 3953–3980. https://doi.org/10.4236/ce.2022.1312253

Miao, F., & Cukurova, M. (2024). AI competency framework for teachers. UNESCO. https://doi.org/10.54675/ZJTE2084

Miao, F., & Holmes, W. (2023). Guidance for generative AI in education and research. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000386693

Mosqueda Chávez, E. (2024). La inteligencia artificial como aliada del aprendizaje y el pensamiento crítico. Revista Mexicana de Bachillerato a Distancia, 16(32). https://doi.org/10.22201/cuaieed.20074751e.2024.32.89555

Rodríguez-Triana, M. J., Prieto, L. P., Martínez-Monés, A., Asensio-Pérez, J. I., y Dimitriadis, Y. (2018). The teacher in the loop: Customizing multimodal learning analytics for blended learning. Proceedings of the 8th International Conference on Learning Analytics and Knowledge, 417–426. https://doi.org/10.1145/3170358.3170364

Sánchez Mendiola, M., y Carbajal Degante, E. (2023). La inteligencia artificial generativa y la educación universitaria. Perfiles Educativos, 45(Especial), 70–86. https://doi.org/10.22201/iisue.24486167e.2023.Especial.61692

Universidad Nacional Autónoma de México [UNAM]. (2024). Gaceta UNAM. (2024, mayo 23). Listo, el Plan de Desarrollo Institucional 2023-2027. Gaceta UNAM. https://www.gaceta.unam.mx/listo-el-plan-de-desarrollo-institucional-2023-2027/

Universidad Nacional Autónoma de México [UNAM]. (2024, mayo 14). Plan de desarrollo institucional de la Universidad Nacional Autónoma de México. https://www.rector.unam.mx/docs/PDI-2023-2027.pdf

Wu, X., Xiao, L., Sun, Y., Zhang, J., Ma, T., y He, L. (2022). A survey of human-in-the-loop for machine learning. Future Generation Computer Systems, 135, 364–381. https://doi.org/10.1016/j.future.2022.05.014