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The Track, Hotspot and Frontier of International MOOC Research 2008–2018 — A Scientometric Analysis Based on SCI and SSCI.

Authors :
Zhang, Wei
Zhao, Liang
Source :
International Journal of Pattern Recognition & Artificial Intelligence; Mar2021, Vol. 35 Issue 03, pN.PAG-N.PAG, 25p
Publication Year :
2021

Abstract

The aim of this paper is to objectively present the development and trend of international MOOC research. Metadata taken from 660 literature records is used to visualize the state of MOOC research. The records were published between 2008 and 2018, and Citespace software is employed to visualize key data about the research contained on the SCI and SSCI platform. It has the following findings. First, since 2012, the number of international MOOC research papers and cited frequency has shown an upward trend. The research force was mainly concentrated in North America, Europe and Asia, and the publishing institutions were mainly concentrated in Universities of various countries, and formed a more obvious international cooperation network. Second, journals such as ≪ INT REV RES OPEN DIS ≫ and ≪ COMPUTERS & EDUCATION ≫ are the foundational literatures of MOOC research. George Siemens, Stephen Downes, John Daniel and others have made important contributions to the foundation research of MOOC. Third, Breslow, Liyanagunawardena et al. were cited more frequently and formed eight research clusters such as teaching interaction, relativism/behaviorism theory, individualized learning and diversified education. Fourth, distance education, online learning, learning situation analysis, curriculum construction and platform construction are the hot topics of international MOOC research in the recent decade. Fifth, the development of international MOOC has spread to various disciplines and promoted the interdisciplinary research of environment, biology, medicine, philosophy, psychology and other disciplines. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02180014
Volume :
35
Issue :
03
Database :
Complementary Index
Journal :
International Journal of Pattern Recognition & Artificial Intelligence
Publication Type :
Academic Journal
Accession number :
149378317
Full Text :
https://doi.org/10.1142/S0218001421590096