Technological trends in the prevention of school dropout at different educational levels: a documentary review
DOI:
https://doi.org/10.66707/ms.v2i1.252Keywords:
school dropout, learning analytics, artificial intelligence, student retention, educational technologiesAbstract
Technological trends aimed at preventing school dropout at different educational levels are a key aspect of transformation permeated by the current digital environment. Therefore, the objective of this study was to explore technological trends in school dropout prevention at different educational levels. The methodology employed, with an interpretive scope structured under the PRISMA protocol, allowed for the compilation of a corpus of 31 documents from Scopus, Redalyc, and Google Scholar. The results reveal five predominant trends: learning analytics and predictive models, artificial intelligence and automation, institutional digital platforms, mobile technologies and digital inclusion, and structural factors in dialogue with technology. The transition toward data-driven early warning systems to identify dropout risk is highlighted. It is concluded that technological effectiveness depends on its integration with pedagogical, institutional, and contextual conditions, given the multidimensional nature of school dropout.
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