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Henderson, Nathan; Min, Wookhee; Emerson, Andrew; Rowe, Jonathan; Lee, Seung; Minogue, James; Lester, James – International Educational Data Mining Society, 2021
Recent years have seen significant interest in multimodal frameworks for modeling learner engagement in educational settings. Multimodal frameworks hold particular promise for predicting visitor engagement in interactive science museum exhibits. Multimodal models often utilize video data to capture learner behavior, but video cameras are not…
Descriptors: Museums, Audiences, Participation, Exhibits
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Li, Hang; Ding, Wenbiao; Liu, Zitao – International Educational Data Mining Society, 2020
With the rapid emergence of K-12 online learning platforms, a new era of education has been opened up. It is crucial to have a dropout warning framework to preemptively identify K-12 students who are at risk of dropping out of the online courses. Prior researchers have focused on predicting dropout in Massive Open Online Courses (MOOCs), which…
Descriptors: At Risk Students, Online Courses, Elementary Secondary Education, Learning Modalities
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Boyer, Kristy Elizabeth, Ed.; Yudelson, Michael, Ed. – International Educational Data Mining Society, 2018
The 11th International Conference on Educational Data Mining (EDM 2018) is held under the auspices of the International Educational Data Mining Society at the Templeton Landing in Buffalo, New York. This year's EDM conference was highly competitive, with 145 long and short paper submissions. Of these, 23 were accepted as full papers and 37…
Descriptors: Data Collection, Data Analysis, Computer Science Education, Program Proposals