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Time to Scale: Generalizable Affect Detection for Tens of Thousands of Students across an Entire School Year
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Hutt, Stephen; Grafsgaard, Joseph F.; D'Mello, Sidney K. – Grantee Submission, 2019
We developed generalizable affect detectors using 133,966 instances of 18 affective states collected from 69,174 students who interacted with an online math learning platform called Algebra Nation over the entire school year. To enable scalability and generalizability, we used generic interaction features (e.g., viewing a video, taking a quiz),…
Descriptors: Affective Behavior, Online Courses, Educational Technology, Technology Uses in Education