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E-Learning Research Trends in Higher Education in Light of COVID-19: A Bibliometric Analysis.
Brika, Said Khalfa Mokhtar; Chergui, Khalil; Algamdi, Abdelmageed; Musa, Adam Ahmed; Zouaghi, Rabia.
  • Brika SKM; University of Bisha, Bisha, Saudi Arabia.
  • Chergui K; University of Oum El Bouaghi, Oum El Bouaghi, Algeria.
  • Algamdi A; University of Bisha, Bisha, Saudi Arabia.
  • Musa AA; University of Bisha, Bisha, Saudi Arabia.
  • Zouaghi R; Binghamton University, Binghamton, NY, United States.
Front Psychol ; 12: 762819, 2021.
Article in English | MEDLINE | ID: covidwho-1753404
ABSTRACT
This paper provides a broad bibliometric overview of the important conceptual advances that have been published during COVID-19 within "e-learning in higher education." E-learning as a concept has been widely used in the academic and professional communities and has been approved as an educational approach during COVID-19. This article starts with a literature review of e-learning. Diverse subjects have appeared on the topic of e-learning, which is indicative of the dynamic and multidisciplinary nature of the field. These include analyses of the most influential authors, of models and networks for bibliometric analysis, and progress towards the current research within the most critical areas. A bibliometric review analyzes data of 602 studies published (2020-2021) in the Web of Science (WoS) database to fully understand this field. The data were examined using VOSviewer, CiteSpace, and KnowledgeMatrix Plus to extract networks and bibliometric indicators about keywords, authors, organizations, and countries. The study concluded with several results within higher education. Many converging words or sub-fields of e-learning in higher education included distance learning, distance learning, interactive learning, online learning, virtual learning, computer-based learning, digital learning, and blended learning (hybrid learning). This research is mainly focused on pedagogical techniques, particularly e-learning and collaborative learning, but these are not the only trends developing in this area. The sub-fields of artificial intelligence, machine learning, and deep learning constitute new research directions for e-learning in light of COVID-19 and are suggestive of new approaches for further analysis.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Reviews Language: English Journal: Front Psychol Year: 2021 Document Type: Article Affiliation country: Fpsyg.2021.762819

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Reviews Language: English Journal: Front Psychol Year: 2021 Document Type: Article Affiliation country: Fpsyg.2021.762819