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Download full textChopra, 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
Švábenský, Valdemar; Baker, Ryan S.; Zambrano, Andrés; Zou, Yishan; Slater, Stefan – International Educational Data Mining Society, 2023
Students who take an online course, such as a MOOC, use the course's discussion forum to ask questions or reach out to instructors when encountering an issue. However, reading and responding to students' questions is difficult to scale because of the time needed to consider each message. As a result, critical issues may be left unresolved, and…
Descriptors: Generalization, Computer Mediated Communication, MOOCs, State Universities
Liu, Chengyuan; Cui, Jialin; Shang, Ruixuan; Xiao, Yunkai; Jia, Qinjin; Gehringer, Edward – International Educational Data Mining Society, 2022
An online peer-assessment system typically allows students to give textual feedback to their peers, with the goal of helping the peers improve their work. The amount of help that students receive is highly dependent on the quality of the reviews. Previous studies have investigated using machine learning to detect characteristics of reviews (e.g.,…
Descriptors: Peer Evaluation, Feedback (Response), Computer Mediated Communication, Teaching Methods
Chen, Zhaorui; Demmans, Carrie – International Educational Data Mining Society, 2020
Discussion forums are used to support socio-collaborative learning processes among students in online courses. However, complex forum structures and lengthy discourse require that students spend their limited time searching and filtering through posts to find those that are relevant to them rather than spending that time engaged in other…
Descriptors: Cooperative Learning, Computer Mediated Communication, Recordkeeping, Online Courses
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
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection
