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MSAEM Estimation for Confirmatory Multidimensional Four-Parameter Normal Ogive Models
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Jia Liu; Xiangbin Meng; Gongjun Xu; Wei Gao; Ningzhong Shi – Grantee Submission, 2024
In this paper, we develop a mixed stochastic approximation expectation-maximization (MSAEM) algorithm coupled with a Gibbs sampler to compute the marginalized maximum a posteriori estimate (MMAPE) of a confirmatory multidimensional four-parameter normal ogive (M4PNO) model. The proposed MSAEM algorithm not only has the computational advantages of…
Descriptors: Algorithms, Achievement Tests, International Assessment, Foreign Countries
MSAEM Estimation for Confirmatory Multidimensional Four-Parameter Normal Ogive Models
Peer reviewed Peer reviewed
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Jia Liu; Xiangbin Meng; Gongjun Xu; Wei Gao; Ningzhong Shi – Journal of Educational Measurement, 2024
In this paper, we develop a mixed stochastic approximation expectation-maximization (MSAEM) algorithm coupled with a Gibbs sampler to compute the marginalized maximum a posteriori estimate (MMAPE) of a confirmatory multidimensional four-parameter normal ogive (M4PNO) model. The proposed MSAEM algorithm not only has the computational advantages of…
Descriptors: Algorithms, Achievement Tests, Foreign Countries, International Assessment
Using Machine Learning to Predict UK and Japanese Secondary Students' Life Satisfaction in PISA 2018
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Zexuan Pan; Maria Cutumisu – British Journal of Educational Psychology, 2024
Background: Life satisfaction is a key component of students' subjective well-being due to its impact on academic achievement and lifelong health. Although previous studies have investigated life satisfaction through different lenses, few of them employed machine learning (ML) approaches. Objective: Using ML algorithms, the current study predicts…
Descriptors: Artificial Intelligence, Secondary School Students, Life Satisfaction, Foreign Countries
Stacking: An Ensemble Learning Approach to Predict Student Performance in PISA 2022
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Ersoy Öz; Okan Bulut; Zuhal Fatma Cellat; Hülya Yürekli – Education and Information Technologies, 2025
Predicting student performance in international large-scale assessments (ILSAs) is crucial for understanding educational outcomes on a global scale. ILSAs, such as the Program for International Student Assessment and the Trends in International Mathematics and Science Study, serve as vital tools for policymakers, educators, and researchers to…
Descriptors: Foreign Countries, Achievement Tests, Secondary School Students, International Assessment
Optimizing Large-Scale Educational Assessment with a "Divide-and-Conquer" Strategy: Fast and Efficient Distributed Bayesian Inference in IRT Models
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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