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Bibliometric analysis reveals trends in machine learning applications for enhancing student participation in online education.
The efficacy of machine learning (ML) in anticipating and enhancing the learning process of students within various educational contexts has been empirically demonstrated. The research focuses on the use of ML in virtual learning environments, with the objective of improving the effectiveness and personalization of online education. In order to achieve this, it is necessary to examine research trends in this field. Some areas demonstrate the need for a complete bibliography, which is the reason for this objective. The methodology employed a bibliometric analysis, conducted in accordance with the PRISMA 2020 guidelines, utilizing data sourced from Scopus and Web of Science. The results indicate an increase in the production of articles, with a particular focus on topics such as student participation and random forest.
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Valencia-Arías et al. (2025) studied this question.
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