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Anirudhan Badrinath; Zachary Pardos – Journal of Educational Data Mining, 2025
Bayesian Knowledge Tracing (BKT) is a well-established model for formative assessment, with optimization typically using expectation maximization, conjugate gradient descent, or brute force search. However, one of the flaws of existing optimization techniques for BKT models is convergence to undesirable local minima that negatively impact…
Descriptors: Bayesian Statistics, Intelligent Tutoring Systems, Problem Solving, Audience Response Systems
Qiao, Xin; Jiao, Hong; He, Qiwei – Journal of Educational Measurement, 2023
Multiple group modeling is one of the methods to address the measurement noninvariance issue. Traditional studies on multiple group modeling have mainly focused on item responses. In computer-based assessments, joint modeling of response times and action counts with item responses helps estimate the latent speed and action levels in addition to…
Descriptors: Multivariate Analysis, Models, Item Response Theory, Statistical Distributions
Pavel Chernyavskiy; Traci S. Kutaka; Carson Keeter; Julie Sarama; Douglas Clements – Grantee Submission, 2024
When researchers code behavior that is undetectable or falls outside of the validated ordinal scale, the resultant outcomes often suffer from informative missingness. Incorrect analysis of such data can lead to biased arguments around efficacy and effectiveness in the context of experimental and intervention research. Here, we detail a new…
Descriptors: Bayesian Statistics, Mathematics Instruction, Learning Trajectories, Item Response Theory
Goldin, Ilya M.; Koedinger, Kenneth R.; Aleven, Vincent – International Educational Data Mining Society, 2012
Although ITSs are supposed to adapt to differences among learners, so far, little attention has been paid to how they might adapt to differences in how students learn from help. When students study with an Intelligent Tutoring System, they may receive multiple types of help, but may not comprehend and make use of this help in the same way. To…
Descriptors: Performance Factors, Intelligent Tutoring Systems, Individual Differences, Prediction
Rafferty, Anna N., Ed.; Whitehill, Jacob, Ed.; Romero, Cristobal, Ed.; Cavalli-Sforza, Violetta, Ed. – International Educational Data Mining Society, 2020
The 13th iteration of the International Conference on Educational Data Mining (EDM 2020) was originally arranged to take place in Ifrane, Morocco. Due to the SARS-CoV-2 (coronavirus) epidemic, EDM 2020, as well as most other academic conferences in 2020, had to be changed to a purely online format. To facilitate efficient transmission of…
Descriptors: Educational Improvement, Teaching Methods, Information Retrieval, Data Processing
Mislevy, Robert J.; Huang, Chun-Wei – National Center for Research on Evaluation, Standards, and Student Testing (CRESST), 2006
Advances in cognitive research increase the need for assessment that can address the processes and the strategies by which persons solve problems. Several psychometric models have been introduced to handle claims cast in information-processing terms, explicitly modeling performance in terms of theory-based predictions of performance. Cognitively…
Descriptors: Cognitive Science, Cognitive Processes, Problem Solving, Psychometrics
Yan, Duanli; Almond, Russell; Mislevy, Robert – ETS Research Report Series, 2004
Diagnostic score reports linking assessment outcomes to instructional interventions are one of the most requested features of assessment products. There is a body of interesting work done in the last 20 years including Tatsuoka's rule space method (Tatsuoka, 1983), Haertal and Wiley's binary skills model (Haertal, 1984; Haertal & Wiley, 1993),…
Descriptors: Comparative Analysis, Models, Bayesian Statistics, Statistical Inference

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