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Download full textPatel, Nirmal; Sharma, Aditya; Shah, Tirth; Lomas, Derek – Journal of Educational Data Mining, 2021
Process Analysis is an emerging approach to discover meaningful knowledge from temporal educational data. The study presented in this paper shows how we used Process Analysis methods on the National Assessment of Educational Progress (NAEP) test data for modeling and predicting student test-taking behavior. Our process-oriented data exploration…
Descriptors: Learning Analytics, National Competency Tests, Evaluation Methods, Prediction
Gervet, Theophile; Koedinger, Ken; Schneider, Jeff; Mitchell, Tom – Journal of Educational Data Mining, 2020
Intelligent tutoring systems (ITSs) teach skills using learning-by-doing principles and provide learners with individualized feedback and materials adapted to their level of understanding. Given a learner's history of past interactions with an ITS, a learner performance model estimates the current state of a learner's knowledge and predicts her…
Descriptors: Learning Processes, Intelligent Tutoring Systems, Feedback (Response), Knowledge Level
van de Sande, Brett – Journal of Educational Data Mining, 2013
Bayesian Knowledge Tracing is used very widely to model student learning. It comes in two different forms: The first form is the Bayesian Knowledge Tracing "hidden Markov model" which predicts the probability of correct application of a skill as a function of the number of previous opportunities to apply that skill and the model…
Descriptors: Bayesian Statistics, Markov Processes, Student Evaluation, Probability
