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Chopra, Harshita; Lin, Yiwen; Samadi, Mohammad Amin; Cavazos, Jacqueline G.; Yu, Renzhe; Jaquay, Spencer; Nixon, Nia – International Educational Data Mining Society, 2023
Exploring students' discourse in academic settings over time can provide valuable insight into the evolution of learner engagement and participation in online learning. In this study, we propose an analytical framework to capture topics and the temporal progression of learner discourse. We employed a Contextualized Topic Modeling technique on…
Descriptors: Semantics, Computer Mediated Communication, Pandemics, COVID-19
Kumar, Muthu; Kan, Min-Yen; Tan, Bernard C. Y.; Ragupathi, Kiruthika – International Educational Data Mining Society, 2015
With large student enrollment, MOOC instructors face the unique challenge in deciding when to intervene in forum discussions with their limited bandwidth. We study this problem of "instructor intervention." Using a large sample of forum data culled from 61 courses, we design a binary classifier to predict whether an instructor should…
Descriptors: Intervention, Open Education, Large Group Instruction, Group Discussion
Crossley, Scott; McNamara, Danielle S.; Baker, Ryan; Wang, Yuan; Paquette, Luc; Barnes, Tiffany; Bergner, Yoav – International Educational Data Mining Society, 2015
Completion rates for massive open online classes (MOOCs) are notoriously low, but learner intent is an important factor. By studying students who drop out despite their intent to complete the MOOC, it may be possible to develop interventions to improve retention and learning outcomes. Previous research into predicting MOOC completion has focused…
Descriptors: Online Courses, Large Group Instruction, Information Retrieval, Data Analysis