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Article

Mapping Knowledge Area Analysis in E-Learning Systems Based on Cloud Computing

by
Adriana Dima
1,*,
Alexandru-Mihai Bugheanu
1,
Ruxandra Boghian
1 and
Dag Øivind Madsen
2,*
1
Faculty of Management, The Bucharest University of Economic Studies, 010374 Bucharest, Romania
2
USN School of Business, University of South-Eastern, 3679 Notodden, Norway
*
Authors to whom correspondence should be addressed.
Electronics 2023, 12(1), 62; https://doi.org/10.3390/electronics12010062
Submission received: 6 December 2022 / Revised: 19 December 2022 / Accepted: 20 December 2022 / Published: 23 December 2022

Abstract

Traditional educational systems and learning have been significantly impacted by the quick growth of information and communication technology. Moreover, the learning process is increasingly important for socioeconomic and business success in our modern society. Therefore, at present, cloud computing is crucially important in connection with e-learning systems. The goal of this research is to conduct a thorough assessment of scientific production in the field of e-learning and cloud technology fields using the bibliometric analysis method’s quantitative approach in order to comprehensively review and analyze the subject. The current study reviews the literature by focusing on specific research areas and revealing certain trends. The research examines 637 articles published between 2007 and 2022 in the Web of Science database (WoS) using the VOSviewer software version 1.6.18 (Leiden University, The Netherlands) and bibliometrix R-package. The goal of this research is to conduct a thorough assessment of scientific production in the field of e-learning and cloud technology fields using the bibliometric analysis method’s quantitative approach to comprehensively review and analyze the subject. Currently, there is no unified approach and extensive bibliometric review that tackle both of these topics cohesively; thus, this research aims to fill this gap. The results shed light on the structure, evolution, main trends, and effect of the research field of e-learning systems based on cloud computing by intensively evaluating and analyzing the scientific output, key contributions to the subject, and possible directions for future research. The most productive country in terms of scientific knowledge and number of citations is China. It is noteworthy that the interest of researchers comes from various regions of the world, while the most prolific authors come from Serbia, Japan, and Romania. The average citation number per document is 6.8, while the most citations were obtained by highly influential article about critical factors influencing learner satisfaction for successful e-learning. Regarding the conceptual structure that assists researchers to understand keyword evolution and trend, four clusters were identified, which reside around the topics “Technology”, “Education”, “Delivery Systems” and “Cloud services”. Given these points, the current study’s implications reveal the significance of e-learning technologies based on cloud computing, along with the direct correlation between these two elements.
Keywords: bibliometric analysis; e-learning; smart learning; digital learning; smart education; cloud computing bibliometric analysis; e-learning; smart learning; digital learning; smart education; cloud computing

Share and Cite

MDPI and ACS Style

Dima, A.; Bugheanu, A.-M.; Boghian, R.; Madsen, D.Ø. Mapping Knowledge Area Analysis in E-Learning Systems Based on Cloud Computing. Electronics 2023, 12, 62. https://doi.org/10.3390/electronics12010062

AMA Style

Dima A, Bugheanu A-M, Boghian R, Madsen DØ. Mapping Knowledge Area Analysis in E-Learning Systems Based on Cloud Computing. Electronics. 2023; 12(1):62. https://doi.org/10.3390/electronics12010062

Chicago/Turabian Style

Dima, Adriana, Alexandru-Mihai Bugheanu, Ruxandra Boghian, and Dag Øivind Madsen. 2023. "Mapping Knowledge Area Analysis in E-Learning Systems Based on Cloud Computing" Electronics 12, no. 1: 62. https://doi.org/10.3390/electronics12010062

APA Style

Dima, A., Bugheanu, A.-M., Boghian, R., & Madsen, D. Ø. (2023). Mapping Knowledge Area Analysis in E-Learning Systems Based on Cloud Computing. Electronics, 12(1), 62. https://doi.org/10.3390/electronics12010062

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