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Lorenzen, Stephan; Hjuler, Niklas; Alstrup, Stephen – International Educational Data Mining Society, 2018
Analysis of log data generated by online educational systems is an essential task to better the educational systems and increase our understanding of how students learn. In this study we investigate previously unseen data from Clio Online, the largest provider of digital learning content for primary schools in Denmark. We consider data for 14,810…
Descriptors: Data Collection, Student Behavior, Elementary School Students, Foreign Countries
Development of a Trajectory Model for Visualizing Teacher ICT Usage Based on Event Segmentation Data
Zheng, Longwei; Shi, Rui; Wu, Bingcong; Gu, Xiaoqing; Feng, Yuanyuan – International Educational Data Mining Society, 2017
The adoption of educational technologies such as e-textbook has offered a new opportunity to gain insight into teachers' usage of ICT (Information and Communication Technologies). In the e-textbook platform, customized digital products and the learning activities organized in digital environment require teachers to make greater efforts in planning…
Descriptors: Educational Technology, Technology Uses in Education, Visualization, Data Collection
Olsen, Jennifer K.; Aleven, Vincent; Rummel, Nikol – International Educational Data Mining Society, 2015
Student models for adaptive systems may not model collaborative learning optimally. Past research has either focused on modeling individual learning or for collaboration, has focused on group dynamics or group processes without predicting learning. In the current paper, we adjust the Additive Factors Model (AFM), a standard logistic regression…
Descriptors: Educational Environment, Predictive Measurement, Predictor Variables, Cooperative Learning
Stamper, John C.; Lomas, Derek; Ching, Dixie; Ritter, Steve; Koedinger, Kenneth R.; Steinhart, Jonathan – International Educational Data Mining Society, 2012
Traditional experimental paradigms have focused on executing experiments in a lab setting and eventually moving successful findings to larger experiments in the field. However, data from field experiments can also be used to inform new lab experiments. Now, with the advent of large student populations using internet-based learning software, online…
Descriptors: Internet, Feedback (Response), Computer Software, Data Collection
Lynch, Collin F., Ed.; Merceron, Agathe, Ed.; Desmarais, Michel, Ed.; Nkambou, Roger, Ed. – International Educational Data Mining Society, 2019
The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…
Descriptors: Data Collection, Data Analysis, Information Retrieval, Content 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