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Eagle, Michael; Corbett, Albert; Stamper, John; Mclaren, Bruce – International Educational Data Mining Society, 2018
In this work we use prior to tutor-session data to generate an individualized student knowledge model. Intelligent learning environments use student models to individualize curriculum sequencing and help messages. Researchers decompose the learning tasks into sets of Knowledge Components (KCs) that represent individual units of knowledge; the…
Descriptors: Individualized Instruction, Models, Data Analysis, Knowledge Level
Liu, Ran; Koedinger, Kenneth R. K – International Educational Data Mining Society, 2017
Research in Educational Data Mining could benefit from greater efforts to ensure that models yield reliable, valid, and interpretable parameter estimates. These efforts have especially been lacking for individualized student-parameter models. We collected two datasets from a sizable student population with excellent "depth" -- that is,…
Descriptors: Data Analysis, Intelligent Tutoring Systems, Bayesian Statistics, Pretests Posttests
Khajah, Mohammad; Lindsey, Robert V.; Mozer, Michael C. – International Educational Data Mining Society, 2016
In theoretical cognitive science, there is a tension between highly structured models whose parameters have a direct psychological interpretation and highly complex, general-purpose models whose parameters and representations are difficult to interpret. The former typically provide more insight into cognition but the latter often perform better.…
Descriptors: Bayesian Statistics, Data Analysis, Prediction, Intelligent Tutoring Systems
Wang, Lijuan; Hamaker, Ellen; Bergeman, C. S. – Psychological Methods, 2012
Intra-individual variability over a short period of time may contain important information about how individuals differ from each other. In this article we begin by discussing diverse indicators for quantifying intra-individual variability and indicate their advantages and disadvantages. Then we propose an alternative method that models…
Descriptors: Evaluation Methods, Data Analysis, Individual Differences, Models

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