¿Se logra predecir el rendimiento académico? Un análisis desde la tecnología educativa

Odiel Estrada Molina; Dieter Fuentes Cancell

doi:10.12795/revistafuentes.2021.14278

Authors

Odiel Estrada Molina Universidad de las Ciencias Informáticas https://orcid.org/0000-0002-0918-418X
Dieter Fuentes Cancell Universidad de las Ciencias Informáticas http://orcid.org/0000-0002-2509-5400

DOI:

https://doi.org/10.12795/revistafuentes.2021.14278

Keywords:

Academic achievement; education; educational technology; educational computing; educational evaluation; higher education; learning; literature reviews.

Abstract

Predicting academic performance is a key element in education, allowing teachers to design preventive didactic actions. Various computational disciplines are involved in this predictive process, with learning analytics, machine learning, educational data mining, artificial neural networks, and fuzzy theories being the most frequently used. A systematic review of the scientific literature (2010-March 2020) indexed in Scopus, IEEE , ACM Digital Library and Springer is presented, with the aim of evaluating how academic performance prediction has behaved in two scenarios: (1) studies online (online) and blended; and (2) technological support for the face-to-face modality. The article concludes with the determination of the trends between the disciplines of educational technologies and the variables of academic performance.

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References

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