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Kazuhiro Yamaguchi – Journal of Educational and Behavioral Statistics, 2025
This study proposes a Bayesian method for diagnostic classification models (DCMs) for a partially known Q-matrix setting between exploratory and confirmatory DCMs. This Q-matrix setting is practical and useful because test experts have pre-knowledge of the Q-matrix but cannot readily specify it completely. The proposed method employs priors for…
Descriptors: Models, Classification, Bayesian Statistics, Evaluation Methods
Yang Du; Susu Zhang – Journal of Educational and Behavioral Statistics, 2025
Item compromise has long posed challenges in educational measurement, jeopardizing both test validity and test security of continuous tests. Detecting compromised items is therefore crucial to address this concern. The present literature on compromised item detection reveals two notable gaps: First, the majority of existing methods are based upon…
Descriptors: Item Response Theory, Item Analysis, Bayesian Statistics, Educational Assessment
Sainan Xu; Jing Lu; Jiwei Zhang; Chun Wang; Gongjun Xu – Grantee Submission, 2024
With the growing attention on large-scale educational testing and assessment, the ability to process substantial volumes of response data becomes crucial. Current estimation methods within item response theory (IRT), despite their high precision, often pose considerable computational burdens with large-scale data, leading to reduced computational…
Descriptors: Educational Assessment, Bayesian Statistics, Statistical Inference, Item Response Theory
Uglanova, Irina – Practical Assessment, Research & Evaluation, 2021
There is increased use of Bayesian networks (BN) in educational assessment. In psychometrics, BN serves as a measurement model with high flexibility, suitable to model educational assessment data with a complex structure. BN is a novel psychometric approach and not all aspects of its application are well-known. The article aims to provide the…
Descriptors: Bayesian Statistics, Educational Assessment, Psychometrics, Criticism
Klein Entink, Rinke H.; Kuhn, Jorg-Tobias; Hornke, Lutz F.; Fox, Jean-Paul – Psychological Methods, 2009
In current psychological research, the analysis of data from computer-based assessments or experiments is often confined to accuracy scores. Response times, although being an important source of additional information, are either neglected or analyzed separately. In this article, a new model is developed that allows the simultaneous analysis of…
Descriptors: Psychological Studies, Monte Carlo Methods, Markov Processes, Educational Assessment
Phillips, Gary W.; Adcock, Eugene P. – 1997
Because public schools do not randomly assign students and teachers across schools (a methodological utopia), multilevel evaluation methods which account for student and school contextual and practice variables in their natural settings provide the most rigorous means for showing empirically what is actually happening in school classrooms.…
Descriptors: Academic Achievement, Bayesian Statistics, Educational Assessment, Elementary Secondary Education
Novick, Melvin R.; And Others – 1980
The Computer-Assisted Data Analysis (CADA) Monitor is a set of conversational-language interactive computer programs that permit relatively inexperienced persons to perform relatively complex statistical data analysis. The Monitor leads the user through an analysis on a step-by-step basis providing the necessary direction, information, and…
Descriptors: Bayesian Statistics, Computer Assisted Instruction, Computer Programs, Data Analysis
Sinharay, Sandip – Journal of Educational and Behavioral Statistics, 2006
Bayesian networks are frequently used in educational assessments primarily for learning about students' knowledge and skills. There is a lack of works on assessing fit of Bayesian networks. This article employs the posterior predictive model checking method, a popular Bayesian model checking tool, to assess fit of simple Bayesian networks. A…
Descriptors: Models, Educational Assessment, Diagnostic Tests, Evaluation Methods

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