ID: 33768
The integration of generative artificial intelligence into education has rapidly reshaped the conditions under which teaching and learning take place, bringing renewed urgency to the question of the competencies teachers need to engage with it in pedagogically meaningful, critical, and responsible ways. At the same time, many of the existing conceptual and implementation frameworks associated with educational technology approach this issue from a predominantly technical or instrumental perspective, with limited connection to normative or pedagogical approaches, including those related to open education. In this context, the challenge is no longer simply to learn how to use AI tools, but to define the knowledge, skills, and attitudes teachers require in order to integrate them within complex, situated, and ethically grounded educational settings. In response, this paper presents DocIAComp, a teacher competency framework for the pedagogical use of artificial intelligence in education, grounded in the principles of open education. The framework is based on the premise that teacher competence in AI cannot be reduced to technical mastery or effective tool use alone, but must be understood in relation to a broader set of principles and practices associated with open education, including openness, reuse, adaptation, accessibility, collaboration, co-creation, and ethical responsibility. From this perspective, open education is not limited to access to resources, but encompasses forms of knowledge production, review, and circulation that are being profoundly transformed by the presence of AI. Accordingly, the framework situates the pedagogical use of AI in direct relation to open educational resources, open educational practices, inclusion, cognitive justice, and the preservation of human agency in education. The study adopted a sequential qualitative design with empirical validation in three stages: first, a systematic review of international and regional frameworks and guidelines on teacher competencies, artificial intelligence, and open education; second, the development of a preliminary competency chart based on that review; third, its validation through surveys administered to students and graduates of the postgraduate program in Educational Technology at the Technological University of Uruguay (UTEC), followed by a theoretical-empirical triangulation of the resulting data to consolidate the final DocIAComp framework. The resulting framework is organized into eight competency areas: Professional Engagement with AI; Curation, Creation, and Adaptation of Educational Resources with AI; Pedagogical Design with AI; Mediation and Support of Learning with AI; Open, Authentic, and Transparent Assessment with AI; Ethics, Rights, Data, and Licensing in AI Ecosystems; Inclusion, Accessibility, and Cognitive Justice with AI; and Research, Openness, and Continuous Improvement with AI. These areas provide institutions with a concrete instrument for diagnosis, teacher education, curriculum design, and the development of institutional policies, with criteria that are transferable across diverse regional and institutional contexts. The paper concludes that DocIAComp constitutes an original contribution that centers attention on open educational practices as a way of harnessing the potential of AI without relinquishing equity, human agency, and the public value of knowledge, thereby offering a grounded and replicable roadmap for education on a global scale.
