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Agarwal, Deepak; Baker, Ryan S.; Muraleedharan, Anupama – International Educational Data Mining Society, 2020
There has been considerable interest in techniques for modelling student learning across practice problems to drive real-time adaptive learning, with particular focus on variants of the classic Bayesian Knowledge Tracing (BKT) model proposed by Corbett & Anderson, 1995. Over time researches have proposed many variants of BKT with…
Descriptors: Intelligent Tutoring Systems, Models, Skill Development, Mastery Learning
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Kai, Shimin; Almeda, Ma. Victoria; Baker, Ryan S.; Heffernan, Cristina; Heffernan, Neil – Journal of Educational Data Mining, 2018
Research on non-cognitive factors has shown that persistence in the face of challenges plays an important role in learning. However, recent work on wheel-spinning, a type of unproductive persistence where students spend too much time struggling without achieving mastery of skills, show that not all persistence is uniformly beneficial for learning.…
Descriptors: Decision Making, Models, Intervention, Computer Assisted Instruction
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Baker, Ryan S.; Hershkovitz, Arnon; Rossi, Lisa M.; Goldstein, Adam B.; Gowda, Sujith M. – Journal of the Learning Sciences, 2013
We present a new method for analyzing a student's learning over time for a specific skill: analysis of the graph of the student's moment-by-moment learning over time. Moment-by-moment learning is calculated using a data-mined model that assesses the probability that a student learned a skill or concept at a specific time during learning (Baker,…
Descriptors: Learning Processes, Intelligent Tutoring Systems, Probability, Skill Development