GENERATIVE ARTIFICIAL INTELLIGENCE AS SUPPORT FOR ACTIVE LEARNING: FOCUS ON THE FLIPPED CLASSROOM

Abstract

The expansion of generative artificial intelligence has been reshaping social, communicational, and educational practices, producing significant impacts on the ways of teaching, learning, and organizing pedagogical experiences. In education, its presence intensifies debates on personalized learning, student authorship, teacher mediation, and the ethical use of digital technologies. This article analyzes the potential of generative artificial intelligence as support for active learning, with emphasis on the flipped classroom methodology. Methodologically, this is a qualitative, bibliographic, and analytical study based on recent literature on artificial intelligence in education, active methodologies, and digital culture. It is argued that generative tools can strengthen pre-class study stages, broaden access to personalized explanations, diversify teaching materials, and improve classroom time for collaborative practices, problem solving, and closer pedagogical support. The paper also discusses limitations related to cognitive superficiality, technological dependence, algorithmic bias, and redefinitions of school authorship. It concludes that the pedagogical value of artificial intelligence does not lie only in the tool itself, but in didactic intentionality, teacher education, and the development of critical and contextualized uses in Basic Education.