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Jihong Zhang; Jonathan Templin; Xinya Liang – Journal of Educational Measurement, 2024
Recently, Bayesian diagnostic classification modeling has been becoming popular in health psychology, education, and sociology. Typically information criteria are used for model selection when researchers want to choose the best model among alternative models. In Bayesian estimation, posterior predictive checking is a flexible Bayesian model…
Descriptors: Bayesian Statistics, Cognitive Measurement, Models, Classification
Jihong Zhang – ProQuest LLC, 2022
Recently, Bayesian diagnostic classification modeling has been becoming popular in health psychology, education, and sociology. Typically information criteria are used for model selection when researchers want to choose the best model among alternative models. In Bayesian estimation, posterior predictive checking is a flexible Bayesian model…
Descriptors: Bayesian Statistics, Cognitive Measurement, Models, Classification
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Wang, Ling Ling; Jian, Sun Xiao; Liu, Yan Lou; Xin, Tao – Applied Measurement in Education, 2023
Cognitive diagnostic assessment based on Bayesian networks (BN) is developed in this paper to evaluate student understanding of the physical concept of buoyancy. we propose a three-order granular-hierarchy BN model which accounts for both fine-grained attributes and high-level proficiencies. Conditional independence in the BN structure is tested…
Descriptors: Bayesian Statistics, Networks, Cognitive Measurement, Diagnostic Tests
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Valdés Aguirre, Benjamín; Ramírez Uresti, Jorge A.; du Boulay, Benedict – International Journal of Artificial Intelligence in Education, 2016
Sharing user information between systems is an area of interest for every field involving personalization. Recommender Systems are more advanced in this aspect than Intelligent Tutoring Systems (ITSs) and Intelligent Learning Environments (ILEs). A reason for this is that the user models of Intelligent Tutoring Systems and Intelligent Learning…
Descriptors: Intelligent Tutoring Systems, Models, Open Source Technology, Computers
Aims, Doug – 1971
A Markov model for predicting performance on criterion-referenced tests is presented,. The model is expressed mathematically as a function of transition matrix, a current state vector, and a future state vector. The matrix is defined in terms of conditional probabilities, i.e., the probability of making a transition to a specific future…
Descriptors: Bayesian Statistics, Criterion Referenced Tests, Decision Making, Mastery Tests
Shields, W. S. – 1974
A procedure for predicting categorical outcomes using categorical predictor variables was described by Moonan. This paper describes a related technique which uses prior probabilities, updated by joint likelihoods, as classification criteria. The procedure differs from Moonan's in that the outcome having the greatest posterior probability is…
Descriptors: Bayesian Statistics, Behavioral Science Research, Classification, Higher Education
Barnes, Tiffany, Ed.; Desmarais, Michel, Ed.; Romero, Cristobal, Ed.; Ventura, Sebastian, Ed. – International Working Group on Educational Data Mining, 2009
The Second International Conference on Educational Data Mining (EDM2009) was held at the University of Cordoba, Spain, on July 1-3, 2009. EDM brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large data sets to answer educational research questions. The increase in instrumented…
Descriptors: Data Analysis, Educational Research, Conferences (Gatherings), Foreign Countries