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Detecting latent topics and trends in blended learning using LDA topic modeling.
1School of Economics and Commerce, University of Electronic Science and Technology of China, Zhongshan Institute, Zhongshan, China.
Education and Information Technologies
|June 13, 2022
Summary
This study analyzed 3772 blended learning papers, revealing a shift in research focus. Key elements like learning outcomes and teacher factors are now emphasized, with
Area of Science:
- Educational Technology
- Learning Sciences
- Higher Education Research
Background:
- Blended learning has seen rapid global adoption, generating extensive research.
- Analyzing research topics and trends is crucial for understanding the field's evolution.
- A significant body of literature necessitates systematic review and analysis.
Purpose of the Study:
- To identify and analyze the main research topics in blended learning.
- To examine the development trends of these topics from 2003 to 2021.
- To provide insights for future blended learning research.
Main Methods:
- Collected 3772 eligible paper abstracts from the Web of Science core collection (2003-2021).
- Applied Latent Dirichlet Allocation (LDA) topic modeling for abstract text analysis.
- Utilized word cloud analysis to visualize keyword characteristics and research focus shifts.
Main Results:
- Identified 7 well-defined research topics in blended learning.
- Observed a research shift from specific subjects (health, math) to learning elements (outcomes, teacher factors, presence).
- Found a significant increase in the popularity of 'presence' and a low frequency of 'formative assessment'.
Conclusions:
- Blended learning research has evolved, focusing more on pedagogical and student-centered elements.
- 'Presence' is an emerging key area, while 'formative assessment' requires further investigation.
- The findings offer valuable implications for researchers and educators in the blended learning landscape.
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