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Martínez-Carrascal, Juan Antonio; Hlosta, Martin; Sancho-Vinuesa, Teresa – International Review of Research in Open and Distributed Learning, 2023
High dropout rates constitute a major concern for higher education institutions, due to their economic and academic impact. The problem is particularly relevant for institutions offering online courses, where withdrawal ratios are reported to be higher. Both the impact and these high rates motivate the implementation of interventions oriented to…
Descriptors: College Students, Online Courses, Withdrawal (Education), At Risk Persons
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Hu, Yung-Hsiang – International Review of Research in Open and Distributed Learning, 2022
Early warning systems (EWSs) have been successfully used in online classes, especially in massive open online courses, where it is nearly impossible for students to interact face-to-face with their teachers. Although teachers in higher education institutions typically have smaller class sizes, they also face the challenge of being unable to have…
Descriptors: Dropout Prevention, At Risk Students, Online Courses, Private Colleges
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Rodríguez, M. Elena; Guerrero-Roldán, Ana Elena; Baneres, David; Karadeniz, Abdulkadir – International Review of Research in Open and Distributed Learning, 2022
This work discusses a nudging intervention mechanism combined with an artificial intelligence (AI) system for early detection of learners' risk of failing or dropping out. Different types of personalized nudges were designed according to educational principles and the learners' risk classification. The impact on learners' performance, dropout…
Descriptors: Artificial Intelligence, Electronic Learning, College Students, Intervention