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Baker, 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
Warnakulasooriya, Rasil; Palazzo, David J.; Pritchard, David E. – Journal of the Experimental Analysis of Behavior, 2007
We studied students performing a complex learning task, that of solving multipart physics problems with interactive tutoring on the web. We extracted the rate of completion and fraction completed as a function of time on task by retrospectively analyzing the log of student-tutor interactions. There was a spontaneous division of students into three…
Descriptors: Physics, Tutoring, Internet, Feedback (Response)