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Yu, Albert; Douglas, Jeffrey A. – Journal of Educational and Behavioral Statistics, 2023
We propose a new item response theory growth model with item-specific learning parameters, or ISLP, and two variations of this model. In the ISLP model, either items or blocks of items have their own learning parameters. This model may be used to improve the efficiency of learning in a formative assessment. We show ways that the ISLP model's…
Descriptors: Item Response Theory, Learning, Markov Processes, Monte Carlo Methods
Boorse, Jaclin; Van Norman, Ethan R. – Psychology in the Schools, 2021
Prior research on the Measures of Academic Progress (MAP), a computer-adaptive test distributed by the Northwest Evaluation Association, has primarily focused on the Reading MAP for screening/benchmarking in elementary grades. The purpose of this study was to explore the functional form of growth and the extent to which student variability in…
Descriptors: Achievement Tests, Mathematics Tests, Adaptive Testing, Computer Assisted Testing
Ethan R. Van Norman; Emily R. Forcht – Journal of Education for Students Placed at Risk, 2024
This study evaluated the forecasting accuracy of trend estimation methods applied to time-series data from computer adaptive tests (CATs). Data were collected roughly once a month over the course of a school year. We evaluated the forecasting accuracy of two regression-based growth estimation methods (ordinary least squares and Theil-Sen). The…
Descriptors: Data Collection, Predictive Measurement, Predictive Validity, Predictor Variables
Qian, Jiahe – ETS Research Report Series, 2018
The 2-parameter logistic multidimensional item response theory (MIRT) model was employed to model growth for the National Education Longitudinal Study of 1988 (NELS:88). The 3 measurement waves of NELS:88 (base year, first follow-up, and second follow-up) represented 3 dimensions.The inquiry aimed to improve modeling performance growth based on…
Descriptors: Growth Models, Longitudinal Studies, Item Response Theory, National Surveys

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