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Download full textPatel, Nirmal; Sharma, Aditya; Shah, Tirth; Lomas, Derek – Journal of Educational Data Mining, 2021
Process Analysis is an emerging approach to discover meaningful knowledge from temporal educational data. The study presented in this paper shows how we used Process Analysis methods on the National Assessment of Educational Progress (NAEP) test data for modeling and predicting student test-taking behavior. Our process-oriented data exploration…
Descriptors: Learning Analytics, National Competency Tests, Evaluation Methods, Prediction
Peer reviewedChoi, Kilchan – Asia Pacific Education Review, 2001
Uses longitudinal study of differences between boys and girls in levels of mathematics and science achievement across grades 7 through 10 to extend hierarchical modeling to allow for regression among latent variables using a fully Bayesian approach. (Contains 30 references.) (PKP)
Descriptors: Bayesian Statistics, Elementary Secondary Education, Longitudinal Studies, Markov Processes
Deping, Li; Oranje, Andreas – ETS Research Report Series, 2006
A hierarchical latent regression model is suggested to estimate nested and nonnested relationships in complex samples such as found in the National Assessment of Educational Progress (NAEP). The proposed model aims at improving both parameters and variance estimates via a two-level hierarchical linear model. This model falls naturally within the…
Descriptors: Hierarchical Linear Modeling, Computation, Measurement, Regression (Statistics)
Johnson, Matthew S.; Jenkins, Frank – ETS Research Report Series, 2005
Large-scale educational assessments such as the National Assessment of Educational Progress (NAEP) sample examinees to whom an exam will be administered. In most situations the sampling design is not a simple random sample and must be accounted for in the estimating model. After reviewing the current operational estimation procedure for NAEP, this…
Descriptors: Bayesian Statistics, Hierarchical Linear Modeling, National Competency Tests, Sampling
