Pedagogical innovation models based on artificial intelligence and learning analytics as a strategy for strengthening educational quality

Abstract

The incorporation of intelligent technologies into the educational field has created new opportunities to transform the way teaching and learning processes are developed. Artificial intelligence and learning analytics have become significant tools for understanding students’ needs, strengthening teaching practice and promoting more personalised, flexible and adaptive learning experiences. The research aimed to examine the scientific evidence related to pedagogical innovation models based on artificial intelligence and learning analytics, considering their main conceptual approaches, contributions, benefits, challenges and development trends associated with the enhancement of educational quality. A qualitative approach was adopted through a systematic literature review based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, enabling the interpretation of the main contributions identified in the specialised literature. The findings show that these technologies support student-centred education by enabling personalised learning, continuous monitoring of academic performance, timely feedback and the identification of educational needs. Furthermore, it is recognised that their impact depends on a balanced integration of technological innovation, teaching competencies and ethical principles aimed at ensuring the responsible use of educational data. In this regard, artificial intelligence and learning analytics represent strategic resources for promoting more inclusive, efficient educational models focused on the continuous improvement of educational quality.