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Content Learning Analysis Using the Moment-by-Moment Learning Detector.

, , and . ITS, volume 7315 of Lecture Notes in Computer Science, page 434-443. Springer, (2012)

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Content Learning Analysis Using the Moment-by-Moment Learning Detector., , and . ITS, volume 7315 of Lecture Notes in Computer Science, page 434-443. Springer, (2012)Towards Predicting Future Transfer of Learning., , and . AIED, volume 6738 of Lecture Notes in Computer Science, page 23-30. Springer, (2011)Affective states and state tests: investigating how affect throughout the school year predicts end of year learning outcomes., , , , and . LAK, page 117-124. ACM, (2013)Predicting Future Learning Better Using Quantitative Analysis of Moment-by-Moment Learning., , , and . EDM, page 74-81. International Educational Data Mining Society, (2013)An Analysis of the Differences in the Frequency of Students' Disengagement in Urban, Rural, and Suburban High Schools., and . EDM, page 11-20. www.educationaldatamining.org, (2010)Ensembling Predictions of Student Knowledge within Intelligent Tutoring Systems., , , , and . UMAP, volume 6787 of Lecture Notes in Computer Science, page 13-24. Springer, (2011)The sum is greater than the parts: ensembling models of student knowledge in educational software., , , and . SIGKDD Explor., 13 (2): 37-44 (2011)Extending Log-Based Affect Detection to a Multi-User Virtual Environment for Science., , , , and . UMAP, volume 8538 of Lecture Notes in Computer Science, page 290-300. Springer, (2014)Towards an Understanding of Affect and Knowledge from Student Interaction with an Intelligent Tutoring System., , , and . AIED, volume 7926 of Lecture Notes in Computer Science, page 41-50. Springer, (2013)Sensor-free automated detection of affect in a Cognitive Tutor for Algebra., , , , , , , , , and . EDM, page 126-133. www.educationaldatamining.org, (2012)