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Ramesh, Arti; Goldwasser, Dan; Huang, Bert; Daume, Hal; Getoor, Lise – IEEE Transactions on Learning Technologies, 2020
Maintaining and cultivating student engagement is critical for learning. Understanding factors affecting student engagement can help in designing better courses and improving student retention. The large number of participants in massive open online courses (MOOCs) and data collected from their interactions on the MOOC open up avenues for studying…
Descriptors: Online Courses, Learner Engagement, Student Behavior, Success
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Hansen, Christian; Hansen, Casper; Hjuler, Niklas; Alstrup, Stephen; Lioma, Christina – International Educational Data Mining Society, 2017
The analysis of log data generated by online educational systems is an important task for improving the systems, and furthering our knowledge of how students learn. This paper uses previously unseen log data from Edulab, the largest provider of digital learning for mathematics in Denmark, to analyse the sessions of its users, where 1.08 million…
Descriptors: Foreign Countries, Markov Processes, Mathematical Models, Student Behavior
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Geigle, Chase; Zhai, ChengXiang – Journal of Educational Data Mining, 2017
Massive open online courses (MOOCs) provide educators with an abundance of data describing how students interact with the platform, but this data is highly underutilized today. This is in part due to the lack of sophisticated tools to provide interpretable and actionable summaries of huge amounts of MOOC activity present in log data. To address…
Descriptors: Large Group Instruction, Online Courses, Educational Technology, Technology Uses in Education
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Fox, Jean-Paul – Journal of Educational and Behavioral Statistics, 2005
The randomized response (RR) technique is often used to obtain answers on sensitive questions. A new method is developed to measure latent variables using the RR technique because direct questioning leads to biased results. Within the RR technique is the probability of the true response modeled by an item response theory (IRT) model. The RR…
Descriptors: Item Response Theory, Models, Probability, Markov Processes