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Mapping the Research on Educational Technology: An Overview through Text Mining

Year 2023, Volume: 31 Issue: 2, 202 - 217, 31.03.2023
https://doi.org/10.24106/kefdergi.1271474

Abstract

Purpose: In this study, it is aimed to determine the trends of studies in the field of educational technologies with the text mining method.
Design/Methodology/Approach: In study, 10,218 studies published since 2000 by the top ten journals in the "Educational Technology" sub-category in Google Scholar Metrics were analyzed by text mining.
Findings: Although it showed that the number of articles in the clusters increased daily, the rate of increase was higher in some clusters than in others. It has been seen that the most studied theories in the field of educational technologies are Cognitive Load Theory and Technology Acceptance Model. When examined in terms of variables, it is seen that the variables of Motivation, Success, Commitment and Social Presence find their place in educational technology studies.
Highlights: It has been determined that the studies in the field of Educational Technologies include articles in 20 thematic clusters in seven main categories. It is possible to collect clusters under seven headings: Assessment, Language Learning, Instructional Design, Technology in Learning Environments, Theoretical Foundations, Computational Thinking and Online Learning. While it is foreseen that some of these issues will be discussed again, especially after the pandemic, some studies are thought to be needed more. In addition, the field of educational technology is seen as an interdisciplinary field, as stated before. For this reason, it is known that more subject areas are related to the clusters created here. Different perspectives can be revealed by using different methods in similar data sets.

Mapping the Research on Educational Technology: An Overview through Text Mining

Year 2023, Volume: 31 Issue: 2, 202 - 217, 31.03.2023
https://doi.org/10.24106/kefdergi.1271474

Abstract

Purpose: In this study, it is aimed to determine the trends of studies in the field of educational technologies with the text mining method.
Design/Methodology/Approach: In study, 10,218 studies published since 2000 by the top ten journals in the "Educational Technology" sub-category in Google Scholar Metrics were analyzed by text mining.
Findings: Although it showed that the number of articles in the clusters increased daily, the rate of increase was higher in some clusters than in others. It has been seen that the most studied theories in the field of educational technologies are Cognitive Load Theory and Technology Acceptance Model. When examined in terms of variables, it is seen that the variables of Motivation, Success, Commitment and Social Presence find their place in educational technology studies.
Highlights: It has been determined that the studies in the field of Educational Technologies include articles in 20 thematic clusters in seven main categories. It is possible to collect clusters under seven headings: Assessment, Language Learning, Instructional Design, Technology in Learning Environments, Theoretical Foundations, Computational Thinking and Online Learning. While it is foreseen that some of these issues will be discussed again, especially after the pandemic, some studies are thought to be needed more. In addition, the field of educational technology is seen as an interdisciplinary field, as stated before. For this reason, it is known that more subject areas are related to the clusters created here. Different perspectives can be revealed by using different methods in similar data sets.

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Details

Primary Language English
Subjects Studies on Education
Journal Section Research Article
Authors

Muhammed Murat Gümüş 0000-0002-3677-8928

Volkan Kukul This is me 0000-0002-9546-3790

Ömer Düzenli This is me 0000-0001-5726-2907

Publication Date March 31, 2023
Acceptance Date March 9, 2023
Published in Issue Year 2023 Volume: 31 Issue: 2

Cite

APA Gümüş, M. M., Kukul, V., & Düzenli, Ö. (2023). Mapping the Research on Educational Technology: An Overview through Text Mining. Kastamonu Education Journal, 31(2), 202-217. https://doi.org/10.24106/kefdergi.1271474

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