Artificial intelligence is advancing in education at a pace that does not always find teachers equally prepared to incorporate it with sound pedagogical judgment. Knowing how to use an AI tool is only part of the challenge: teachers also need to understand its possibilities and limitations, integrate it into instructional design, and address issues related to bias, privacy, equity, and automated decision-making.
Against this backdrop, Aurelio Villa Sánchez, Evelyn Pizarro Fuentes, and Simone Fernandes Queiroz developed an instrument designed to diagnose the competencies teachers need for the pedagogically sound, critical, and responsible integration of artificial intelligence.
The study began with an initial 72-item questionnaire, developed after reviewing different digital competence and artificial intelligence frameworks and submitted to the judgment of 28 experts. It was subsequently administered to a sample of 360 higher education professionals from Chile and Brazil and, through successive stages of item refinement and factor analysis, a final 43-item version was obtained.
The instrument is organized into five broad dimensions: knowledge and beliefs about AI, teachers’ digital competencies, initial and continuing professional development, pedagogical and didactic uses of AI, and ethical, critical, and reflective attitudes. The instrument as a whole shows very high internal consistency, with a Cronbach’s alpha of .950 and a McDonald’s omega of .952.
One of the study’s most interesting contributions is precisely its understanding of teachers’ competence in relation to AI as something far broader than technical proficiency. Training to work with artificial intelligence also means knowing when to use it, for what purpose, with what educational goals, and according to which ethical criteria. The questionnaire therefore provides a tool that can help identify training needs and guide professional development programs.
The results themselves, however, suggest that the instrument should still be regarded as open to further refinement: although its theoretical structure is coherent and its reliability is high, the confirmatory analysis shows limited fit indices, meaning that the model will need to be further tested and refined with new samples and in different contexts. The underlying question raised by the study is particularly timely: given the rapid expansion of AI, perhaps what matters most is not simply that teachers learn how to use it, but that they develop the competencies needed to decide how, when, and why to do so.
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How to Cite: Villa Sánchez, A., Pizarro Fuentes, E., & Fernandes Queiroz, S. (2026). Validation of a questionnaire to diagnose teaching competencies in the pedagogical integration of artificial intelligence. RIED-Revista Iberoamericana de Educación a Distancia, 29(2), 153–178. https://doi.org/10.5944/ried.46988
