Models of digital teaching competencies and their relationship with artificial intelligence: A systematic review
DOI:
https://doi.org/10.5281/zenodo.20562817Keywords:
digital teaching competence, artificial intelligence, educational modelsAbstract
This research examines the transformation of digital teacher competence (DTC) frameworks in the face of the disruptive impact of artificial intelligence (AI) on contemporary education systems. Through a systematic review, based on the PRISMA methodology, 30 scientific articles indexed in Scopus, ProQuest, and Dialnet were audited. The findings demonstrate that, given the inadequacy of traditional models such as DigCompEdu, there is a growing need for a TPACK-AI approach that integrates design thinking, algorithmic ethics, and advanced AI literacy. The analysis reveals that the effective adoption of these technologies depends not only on infrastructure but also on psychosocial constructs such as perceived self-efficacy and the mitigation of technostress. It concludes that current teachers face a critical gap between instrumental digital skills and the demands of automated teaching, which highlights the risk of a new socioeconomic "access to intelligence gap". Finally, it is emphasized that sustainable innovation requires an urgent update of continuing education policies and institutional maturity that transcends individual efforts, reaffirming the teacher's role as a critical manager of information and an essential pedagogical mediator to guarantee equity and quality in education in the knowledge era.
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