Global trends of educational data mining in online learning
Educational data mining (EDM) in online learning involves data mining techniques to analyze data from online environments to gain insights into student behavior, performance, and engagement. This study explored EDM in online learning publication trends and focuses. It involved a bibliometric analysi...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English English |
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International Journal of Technology in Education
2023
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| Online Access: | https://eprints.ums.edu.my/id/eprint/38391/1/ABSTRACT.pdf https://eprints.ums.edu.my/id/eprint/38391/2/FULL%20TEXT.pdf |
| _version_ | 1796912080400416768 |
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| author | Nie Hui Ling Chwen Jen Chen Chee Siong Teh Dexter Sigan John Looi Chin Ch’ng Yoon Fah Lay |
| author_facet | Nie Hui Ling Chwen Jen Chen Chee Siong Teh Dexter Sigan John Looi Chin Ch’ng Yoon Fah Lay |
| author_sort | Nie Hui Ling |
| collection | UMS |
| description | Educational data mining (EDM) in online learning involves data mining techniques to analyze data from online environments to gain insights into student behavior, performance, and engagement. This study explored EDM in online learning publication trends and focuses. It involved a bibliometric analysis of 615 scholarly works related to EDM in online learning as recorded in Scopus, the largest peer-reviewed citation database, on February 1, 2023. The study examined EDM in online learning publications regarding its evolution and distribution, key focus areas, impact and performance, and prominent authors and collaborations in the last decade, in which the timespan is the period from 2012 to 2022. This bibliometric analysis shows that EDM in online learning is a dynamic area of scientific research as related publications grow steadily throughout the years and involve worldwide collaborations. The study reveals current research trends, offering valuable insights for future researchers to guide their investigations in this field.research, potential research directions, and the current state of knowledge on the topic, allowing a better understanding of the research landscape. |
| first_indexed | 2024-03-06T03:28:09Z |
| format | Article |
| id | ums.eprints-38391 |
| institution | Universiti Malaysia Sabah |
| language | English English |
| last_indexed | 2024-03-06T03:28:09Z |
| publishDate | 2023 |
| publisher | International Journal of Technology in Education |
| record_format | dspace |
| spelling | ums.eprints-383912024-02-29T00:49:48Z https://eprints.ums.edu.my/id/eprint/38391/ Global trends of educational data mining in online learning Nie Hui Ling Chwen Jen Chen Chee Siong Teh Dexter Sigan John Looi Chin Ch’ng Yoon Fah Lay LC3991-4000 Gifted children and youth LC8-6691 Special aspects of education QA1-43 General Educational data mining (EDM) in online learning involves data mining techniques to analyze data from online environments to gain insights into student behavior, performance, and engagement. This study explored EDM in online learning publication trends and focuses. It involved a bibliometric analysis of 615 scholarly works related to EDM in online learning as recorded in Scopus, the largest peer-reviewed citation database, on February 1, 2023. The study examined EDM in online learning publications regarding its evolution and distribution, key focus areas, impact and performance, and prominent authors and collaborations in the last decade, in which the timespan is the period from 2012 to 2022. This bibliometric analysis shows that EDM in online learning is a dynamic area of scientific research as related publications grow steadily throughout the years and involve worldwide collaborations. The study reveals current research trends, offering valuable insights for future researchers to guide their investigations in this field.research, potential research directions, and the current state of knowledge on the topic, allowing a better understanding of the research landscape. International Journal of Technology in Education 2023 Article NonPeerReviewed text en https://eprints.ums.edu.my/id/eprint/38391/1/ABSTRACT.pdf text en https://eprints.ums.edu.my/id/eprint/38391/2/FULL%20TEXT.pdf Nie Hui Ling and Chwen Jen Chen and Chee Siong Teh and Dexter Sigan John and Looi Chin Ch’ng and Yoon Fah Lay (2023) Global trends of educational data mining in online learning. International Journal of Technology in Education, 6 (4). pp. 1-26. https://doi.org/10.46328/ijte.558 |
| spellingShingle | LC3991-4000 Gifted children and youth LC8-6691 Special aspects of education QA1-43 General Nie Hui Ling Chwen Jen Chen Chee Siong Teh Dexter Sigan John Looi Chin Ch’ng Yoon Fah Lay Global trends of educational data mining in online learning |
| title | Global trends of educational data mining in online learning |
| title_full | Global trends of educational data mining in online learning |
| title_fullStr | Global trends of educational data mining in online learning |
| title_full_unstemmed | Global trends of educational data mining in online learning |
| title_short | Global trends of educational data mining in online learning |
| title_sort | global trends of educational data mining in online learning |
| topic | LC3991-4000 Gifted children and youth LC8-6691 Special aspects of education QA1-43 General |
| url | https://eprints.ums.edu.my/id/eprint/38391/1/ABSTRACT.pdf https://eprints.ums.edu.my/id/eprint/38391/2/FULL%20TEXT.pdf |
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