Adaptive learning model with artificial intelligence to improve academic performance among Ecuadorian university students [Modelo de aprendizaje adaptativo con inteligencia artificial para mejorar rendimiento académico en universitarios ecuatorianos]
DOI:
https://doi.org/10.62574/rmpi.v5iEducativa.451Keywords:
artificial intelligence, higher education, educational technologyAbstract
Digital transformation in Latin American higher education faces challenges related to educational massification, student diversification, and budgetary constraints, demanding technological alternatives that enhance educational processes without compromising institutional equity. The research aims to design an adaptive learning model with artificial intelligence to improve academic performance among Ecuadorian university students. A descriptive documentary design was used through systematic analysis of sixteen bibliographic references published between 2022 and 2025, selected for their thematic relevance and methodological rigour, applying categorical analysis in four sequential phases. The results showed conceptual consensus on adaptive systems and benefits in student retention. A contextualised model was designed that integrates five interrelated components: a comprehensive multi-domain diagnostic system, an algorithmic engine for pedagogical personalisation, a modular repository of adaptive content, an immediate feedback system, and a continuous assessment module with predictive analytics. The proposal offers a techno-pedagogical framework adaptable to Ecuadorian particularities, requiring empirical validation through implementation studies.
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