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Direct linkBaker, Ryan S. J. D.; Goldstein, Adam B.; Heffernan, Neil T. – International Journal of Artificial Intelligence in Education, 2011
Intelligent tutors have become increasingly accurate at detecting whether a student knows a skill, or knowledge component (KC), at a given time. However, current student models do not tell us exactly at which point a KC is learned. In this paper, we present a machine-learned model that assesses the probability that a student learned a KC at a…
Descriptors: Intelligent Tutoring Systems, Mastery Learning, Probability, Knowledge Level
Molina, Brooke S. G.; Flory, Kate; Bukstein, Oscar G.; Greiner, Andrew R.; Baker, Jennifer L.; Krug, Vicky; Evans, Steven W. – Journal of Attention Disorders, 2008
Objective: This pilot study tests the feasibility and preliminary efficacy of an after-school treatment program for middle schoolers with ADHD using a randomized clinical trial design. Method: A total of 23 students with ADHD (25% female, 48% African American) from a large public middle school were randomly assigned to a 10-week program or to…
Descriptors: Middle School Students, Homework, School Activities, Academic Achievement
Download full textLynch, Collin F., Ed.; Merceron, Agathe, Ed.; Desmarais, Michel, Ed.; Nkambou, Roger, Ed. – International Educational Data Mining Society, 2019
The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…
Descriptors: Data Collection, Data Analysis, Information Retrieval, Content Analysis
