Algorithmic pedagogical rationality in higher health education: a scoping review

Abstract

This study aimed to analyze how the incorporation of artificial intelligence (AI) is articulated with formative processes in higher health education and to discuss its pedagogical, ethical, and institutional implications. This is a scoping review conducted according to the Joanna Briggs Institute recommendations and reported in accordance with the PRISMA-ScR. Searches were performed in the PubMed/ MEDLINE, SciELO, and Virtual Health Library (BVS) databases, considering publications from 2020 to 2025. After applying eligibility criteria and reviewing the corpus, 17 studies were included. The thematic synthesis, utilizing a hybrid approach, organized the findings into five interrelated axes: reconfiguration of teaching mediation; transformations in evaluative processes; competency development; ethical implications and academic integrity; and academic governance and institutional regulation. The studies describe applications of AI in supporting learning, feedback, simulation, and assessment, accompanied by challenges related to teaching supervision, autonomy, academic integrity, and responsible use. The predominance of recent, exploratory, and short-term studies limits conclusions regarding the effectiveness and sustained formative effects of these applications. Based on the articulation of the findings, algorithmic pedagogical rationality is proposed as an analytical category to understand how different uses of AI can participate in the organization of formative processes. It is concluded that the field remains in consolidation, demanding more robust and longitudinal studies on its pedagogical, ethical, and institutional implications.