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Mapping Network Structure and Diversity of Interdisciplinary Knowledge in Recommended MOOC Offerings
Peer reviewed
Download full textZhang, 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
Khor, Ean Teng; Dave, Darshan – International Review of Research in Open and Distributed Learning, 2022
The COVID-19 pandemic induced a digital transformation of education and inspired both instructors and learners to adopt and leverage technology for learning. This led to online learning becoming an important component of the new normal, with home-based virtual learning an essential aspect for learners on various levels. This, in turn, has caused…
Descriptors: Learning Analytics, Social Networks, Network Analysis, Classification
Czerkawski, Betül C. – International Review of Research in Open and Distributed Learning, 2016
With the emergence of social software and the advance of web-based technologies, online learning networks provide invaluable opportunities for learning, whether formal or informal. Unlike top-down, instructor-centered, and carefully planned formal learning settings, informal learning networks offer more bottom-up, student-centered participatory…
Descriptors: Blended Learning, Informal Education, Conventional Instruction, Electronic Learning
