Comparative analysis of artificial intelligence competency frameworks in education

Authors

DOI:

https://doi.org/10.21556/edutec.2025.93.3699

Keywords:

education, artificial inteligence, digital skills, comparative education

Abstract

The integration of digital competencies associated with artificial intelligence (AI) has emerged as a fundamental component in teacher professionalization. This study seeks to examine national and international reference frameworks for AI competencies within the educational sector. A non-experimental, cross-sectional, descriptive, and comparative design is employed, analyzing the structure and content of fourteen frameworks developed by various institutions and authors. Findings reveal that most frameworks lack specification regarding educational levels and predominantly emphasize competency development for educators. Content analysis highlights four primary areas: AI knowledge and ethics, pedagogy, technology, and professional commitment. While certain frameworks prioritize technological dimensions, others place greater emphasis on pedagogical approaches. The increasing role of AI in education necessitates that educators acquire the skills required to manage, implement, and teach with AI-based tools. These findings underscore the critical need for teacher training in AI competencies to foster a professionalization process that aligns with current educational demands.

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Author Biographies

Alba Galán-Íñigo, European University of Madrid (Spain)

PhD candidate at the European University of Madrid. Her doctoral thesis focuses on the integration of artificial intelligence in higher education. She teaches on the Master's Degree in Educational Innovation at the European University of Madrid and is a member of the Innedu-UEM research group. Her academic background includes an Official Master's Degree in University Education (2021, UEM), a Bachelor's Degree in Primary Education (2015, UCM) and a Bachelor's Degree in Audiovisual Communication (2012, UCM), during which she spent a semester at Kingston University of London (2011). She is a teacher specialising in emerging methodologies and neuroeducation. Her professional experience includes serving as academic coordinator of Secondary Education and Baccalaureate at the Desconect@ Psychological Institute (Madrid) and as a teacher-tutor at the International Leadership of Texas school (USA). Her latest studies and conference presentations focus on the integration of AI and the analysis of innovative spaces in higher education.

Judit Ruiz-Lázaro, National University of Distance Education (Spain)

Doctor of Education from the Complutense University of Madrid (2021) with an "International Doctorate" distinction, "Summa Cum Laude" grade and "Extraordinary Doctorate Award". Accredited as a University Lecturer by ANECA (2024). She has six years of active research experience. Currently, Assistant Professor at the National Distance Education University (UNED, Department of Didactics, School Organisation and Special Didactics). Her latest studies and publications focus on university entrance assessment in the Spanish context, the analysis of teacher training in Spain and the use of artificial intelligence in education. She is a member of the consolidated research group Measurement of Assessment and Educational Systems (MESE) at the UCM and ForInterMed at the UNED.

Eva Jiménez-García, European University of Madrid (Spain)

Accredited Doctor in Education with an Extraordinary Doctorate Award (2016) and a degree in Pedagogy from the Complutense University of Madrid. She currently works as Director of Research and Director of the Educational Research Centre (CIE-UE) at the Faculty of Education of the European University of Madrid. Professor of Research Methods and Diagnosis in Education (ANECA). Her research activity focuses on the measurement and evaluation of educational systems. She is part of the Research Group on Measurement and Evaluation of Educational Systems at the Complutense University of Madrid. Member of the Advisory Board of the journal Tendencias Pedagógicas and member of the Evaluation Board of two high-impact journals.

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Published

30-09-2025

How to Cite

Galán-Íñigo, A., Ruiz-Lázaro, J., & Jiménez-García, E. (2025). Comparative analysis of artificial intelligence competency frameworks in education. Edutec, Revista Electrónica De Tecnología Educativa, (93), 185–208. https://doi.org/10.21556/edutec.2025.93.3699

Issue

No. 93 (2025): Edutec Issue 93 - September 2025

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Journal articles

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