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Mapping Network Structure and Diversity of Interdisciplinary Knowledge in Recommended MOOC Offerings
Zhang, Jingjing; Yang, Yehong; Barbera, Elena; Lu, Yu – International Review of Research in Open and Distributed Learning, 2022
In massive open online courses (MOOCs), recommendation relationships present a collection of associations that imply a new form of integration, such as an interdisciplinary synergy among diverse disciplines. This study took a computer science approach, using the susceptible-infected (SI) model to simulate the process of learners accessing courses…
Descriptors: Network Analysis, Interdisciplinary Approach, MOOCs, Electronic Learning
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
Cheng, Yu-Ping; Cheng, Shu-Chen; Huang, Yueh-Min – International Review of Research in Open and Distributed Learning, 2022
Online learning has been widely discussed in education research, and open educational resources have become an increasingly popular way to help learners acquire knowledge. However, these resources contain massive amounts of information, making it difficult for learners to identify Web articles that refer to computer science knowledge. This study…
Descriptors: Internet, Online Searching, Information Retrieval, Artificial Intelligence

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