Learning Analytics and Student Engagement in Distance Higher Education: A Cluster-Based Systematic Review (2020–2025)

Autores/as

  • Heleny Soley Terán Plasencia Universidad Privada del Norte - (PE), Perú
  • Alberto Daniel Rojas Balletta Universidad Privada del Norte - (PE), Perú
  • Hegel Daza Chicana Universidad Privada del Norte - (PE), Perú

DOI:

https://doi.org/10.18687/LACCEI2026.1.1.1043

Palabras clave:

distance education, data analysis, student engagement.

Resumen

The objective of this study was to analyze the patterns identified in the scientific literature on the use of learning analytics and student engagement in distance higher education (2020–2025). A systematic review was conducted following the PRISMA 2020 model, using Scopus as the sole source. The search yielded 74 records; after filtering and refinement, 58 documents were analyzed, and after screening and full-text evaluation, 29 studies were included in the final synthesis. Bibliometric analysis was applied exploratorily with VOSviewer (keyword co-occurrence) to organize the evidence into four thematic clusters. The findings show an evolution from descriptive approaches to predictive and prescriptive models, with increasing use of AI, dashboards, and learning management systems to monitor, explain, and promote student engagement.

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Publicado

2026-07-27

Número

Sección

Articles

Licencia

Licencia Creative Commons

Esta obra está bajo una Licencia Creative Commons Atribución-NoComercial-CompartirIgual 4.0 Internacional.

LACCEI conserva el copyright de todos los artículos publicados bajo los términos de su acuerdo de transferencia de copyright. Como titular del copyright, LACCEI distribuye los artículos al público bajo la Licencia Internacional Creative Commons Atribución-NoComercial-CompartirIgual 4.0 (CC BY-NC-SA 4.0).

Cómo citar

Terán Plasencia, H. S., Rojas Balletta, A. D., & Daza Chicana, H. (2026). Learning Analytics and Student Engagement in Distance Higher Education: A Cluster-Based Systematic Review (2020–2025). LACCEI, 1(14). https://doi.org/10.18687/LACCEI2026.1.1.1043