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Effective Evaluation of Online Learning Interventions with Surrogate Measures.

, , , and . EDM, International Educational Data Mining Society, (2023)

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Identification, Exploration, and Remediation: Can Teachers Predict Common Wrong Answers?, , , , , , , and . LAK, page 399-410. ACM, (2023)Expert Features for a Student Support Recommendation Contextual Bandit Algorithm., , and . LAK, page 864-870. ACM, (2024)Multiple Choice vs. Fill-In Problems: The Trade-off Between Scalability and Learning., , , , , , and . LAK, page 507-517. ACM, (2024)The Effect of Assistance on Gamers: Assessing The Impact of On-Demand Hints & Feedback Availability on Learning for Students Who Game the System., , , and . LAK, page 462-472. ACM, (2024)WEBsistments: Enabling an Intelligent Tutoring System to Excel at Explaining Rather Than Coaching., , and . ITS, volume 7315 of Lecture Notes in Computer Science, page 268-273. Springer, (2012)Does Immediate Feedback While Doing Homework Improve Learning?, , and . FLAIRS, AAAI Press, (2013)Active Learning for Student Affect Detection., , , , and . EDM, International Educational Data Mining Society (IEDMS), (2019)Semantic Features of Math Problems: Relationships to Student Learning and Engagement., , , , , and . EDM, page 223-230. International Educational Data Mining Society (IEDMS), (2016)Towards better affect detectors: effect of missing skills, class features and common wrong answers., , and . LAK, page 31-35. ACM, (2015)Detection and Analysis of Off-Task Gaming Behavior in Intelligent Tutoring Systems., and . Intelligent Tutoring Systems, volume 4053 of Lecture Notes in Computer Science, page 382-391. Springer, (2006)