Training Strategy for the Ethical and Normative Use of Artificial Intelligence in University Teaching

Abstract

Objective: To design training strategies that strengthen the ethical and regulatory use of artificial intelligence among university faculty, reducing resistance to technological and cultural changes and promoting its responsible and relevant pedagogical integration. Methods: A Design-Based Research (DBR) approach was used, restricted to the phases of contextual analysis and conceptual design. The process included reviewing the background and gaps reported in the literature, as well as the iterative construction of a pedagogical intervention proposal grounded in current theoretical frameworks. Results: The training strategy was structured into three core components: ethics of generative AI, normative literacy with emphasis on responsible APA 7 citation, and critical pedagogical integration of AI tools in higher education contexts. Theoretical validation highlighted its internal coherence, formative relevance and alignment with current frameworks for responsible AI use. Conclusions: The design provides a solid and contextually grounded formative model that addresses identified gaps and informs future phases of implementation and impact evaluation.