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Analysis of Course Structures and Learners’ Engagement in MOOCs: The Case of Thai MOOCs

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dc.contributor.advisor Anutariya, Chutiporn
dc.contributor.author Thongsuntia, Wanlipa
dc.contributor.other Dailey, Matthew
dc.contributor.other Pongnumkul, Suporn
dc.date.accessioned 2019-05-07T04:31:37Z
dc.date.available 2019-05-07T04:31:37Z
dc.date.issued 2019-05
dc.identifier.other AIT
dc.identifier.uri http://www.cs.ait.ac.th/xmlui/handle/123456789/937
dc.description 116 p. en_US
dc.description.abstract Recently, Massive Open Online Courses (MOOCs) have achieved more than 100 million registered learners around the world. Based on several active research, the influential ac- complishment of MOOCs is a number of learners’ engagement. MOOCs, nevertheless, has major issues including not only low instructional quality, but also high dropout rate. As from the above fact, the research question of this thesis is to find out how the difference in course structure design may affect learners engagement. With regard to the scope of this thesis, it focuses on Thai MOOC courses in STEM subject area. The dataset contains 28 STEM courses. The learners’ engagement dataset selects the top 20 of the most popular courses according to registered learners. This paper applies the learning analytics to analyze the patterns and clustering of two significant dimensions: i) course design & structure and ii) learners’ performance & engagement. Furthermore, this thesis explores the relationships of both dimensions by using data mining, machine learning, and visualization techniques. Regarding the course design & structure, there are four dimen- sions including course length & effort, Bloom’s taxonomy, number of learning components, and sequence components. Regarding learning analytics outcomes, the results show that courses with medium lengths and efforts have the highest percentage of passing learners and comprehensive learners in the dimension of course length & effort. Furthermore, Applying-focus is the best group which has the highest percent not only passing learners, also comprehensive learners in Bloom’s Taxonomy dimension. With clustering of components, the best group of Number of com- ponents is video-HTML focus. For sequence components clustering, the highest percentage of passing learners and comprehensive learners is in the group of discussion-HTML and video-HTML focus. The visualization of learning analytics are illustrated in MOOCA (Massive Open Online Course Analytics) 1 . MOOCA is a web application implemented using Node.js, D3 and Plotly for visualization. In addition, MOOCA has an essential function as ‘Recommen- dation’ which advises users when they design the courses. The outcome of this function presents the cluster of the course. Consequently, the result shows that the course is in the group of high passing learners or not. en_US
dc.description.sponsorship Royal Thai Government Fellowship en_US
dc.publisher AIT en_US
dc.subject Bloom’s Taxonomy en_US
dc.subject Learning Analytics en_US
dc.subject Learners’ Engagement en_US
dc.subject Massive Open Online Courses (MOOCs) en_US
dc.title Analysis of Course Structures and Learners’ Engagement in MOOCs: The Case of Thai MOOCs en_US
dc.type Thesis en_US


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