Abstract
The feedback mechanism known as course reviews within massive open online courses (MOOCs) has spurred the creation of extensive textual feedback. This information, encompassing not just learners' perspectives, thoughts, and emotions regarding their MOOC learning encounters, tends to be subjective and holds immense value for online education. This study conducted a systematic review of theories, themes, and methods related to online course review analysis. The analysis suggests that there are 12 key themes that constitute a coding framework. for online course review analysis should be encapsulated in its categories. These themes are lecture materials, faculty team, course structure, course content, interaction, assignment and assessment, learner support, technology, instructional approaches, course value, certificate and credits, and course difficulty. With this understanding, scholars would enhance their proficiency in crafting or choosing frameworks. We also evaluate theories and methods related to online course review analysis to comprehend the guiding theoretical perspectives in conducting research and how different methods or technologies can inform decisions for MOOC instructional enhancement.
Original language | English |
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Title of host publication | 2024 International Symposium on Educational Technology, ISET 2024 : Proceedings |
Editors | Kwok Tai CHUI, Yan Keung HUI, Dingqi YANG, Lap-Kei LEE, Leung-Pun WONG, Barry Lee REYNOLDS |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 430-434 |
Number of pages | 5 |
ISBN (Electronic) | 9798350361414 |
ISBN (Print) | 9798350361421 |
DOIs | |
Publication status | Published - 2024 |
Event | 10th International Symposium on Educational Technology, ISET 2024 - Macao, China Duration: 29 Jul 2024 → 1 Aug 2024 |
Conference
Conference | 10th International Symposium on Educational Technology, ISET 2024 |
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Country/Territory | China |
City | Macao |
Period | 29/07/24 → 1/08/24 |
Bibliographical note
Publisher Copyright:© 2024 IEEE.
Funding
This work was supported by the National Natural Science Foundation of China (No. 62307010).
Keywords
- analysis methods
- online learning
- review comments
- systematic review
- themes
- theories