Uses of AI and LA in secondary education to promote meaningful learning: a systematic mapping review
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Keywords:
Generative artificial intelligence, learning analytics, meaningful learning, personalized learning, secondary education
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Abstract
Generative AI (GenAI) and Learning Analytics (LA) are rapidly transforming education by enabling personalization, adaptive systems, and predictive interventions, yet their integration also raises challenges related to data privacy, infrastructure, and teacher readiness. This study aims to analyse the combined potential of GenAI and LA in enhancing learning while identifying barriers to implementation in formal education. A systematic literature review was conducted using the PRISMA framework to ensure transparent selection and analysis of relevant studies. Results indicate that LA facilitates data-driven decision-making through mining, visualization, and predictive models, while GenAI supports adaptive feedback and content generation; together, they enable personalized learning pathways that improve outcomes. However, ethical concerns, technological requirements, and professional training remain significant obstacles. Overall, GenAI and LA offer strong opportunities to enhance education, but their sustainable adoption requires careful attention to ethical, technical, and pedagogical dimensions.
Supporting agencias
- This project has been funded by the Department of Education of the Generalitat of Catalonia through the Educational Research Grant.
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Copyright (c) 2026 Daniel Amo-Filva, Marta López Costa, Belén Donate-Beby, Maria Alsina-Claret, Sogia Aguayo-Mauri, Alba Llauró, Nati Cabrera Lanzo, Marcelo Fabián Maina, Lourdes Guàrdia, Guillermo Bautista
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