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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
Van Norman, Ethan R.; Ysseldyke, James E. – School Psychology Review, 2020
Within multitiered systems of support, assessment practices that limit the amount of time students miss instruction should be prioritized. At the same time, decisions about student response to intervention need to be based upon technically adequate data. We evaluated the impact of data collection frequency and trend estimation method on the…
Descriptors: Data Collection, Adaptive Testing, Computer Assisted Testing, Computation
Nelson, Peter M.; Van Norman, Ethan R.; Klingbeil, Dave A.; Parker, David C. – Psychology in the Schools, 2017
Although extensive research exists on the use of curriculum-based measures for progress monitoring, little is known about using computer adaptive tests (CATs) for progress-monitoring purposes. The purpose of this study was to evaluate the impact of the frequency of data collection on individual and group growth estimates using a CAT. Data were…
Descriptors: Progress Monitoring, Computer Assisted Testing, Data Collection, Scheduling
Ruffini, Stephen J.; Miskell, Ryan; Lindsay, Jim; McInerney, Maurice; Waite, Winsome – Regional Educational Laboratory Midwest, 2016
Many schools identified by states as needing improvement through their Elementary and Secondary Education Act waivers have selected Response to Intervention (RTI), a three-tiered instruction program sometimes referred to as tiered levels of instruction, as one of their main strategies for improving school performance and closing achievement gaps.…
Descriptors: Program Implementation, Fidelity, Response to Intervention, Public Schools
Ruffini, Steffen J.; Lindsay, Jim; Miskell, Ryan; Proger, Amy – Regional Educational Laboratory Midwest, 2016
Regional Educational Laboratory Midwest assisted Milwaukee Public Schools in developing a fidelity monitoring system for measuring schools' progress in implementing Response to Intervention (RTI). The study examined the ratings produced by that system to determine the system's reliability, schools' progress in implementing RTI, and whether ratings…
Descriptors: Program Implementation, Fidelity, Response to Intervention, Public Schools
Olsen, Jennifer K.; Aleven, Vincent; Rummel, Nikol – Grantee Submission, 2015
Student models for adaptive systems may not model collaborative learning optimally. Past research has either focused on modeling individual learning or for collaboration, has focused on group dynamics or group processes without predicting learning. In the current paper, we adjust the Additive Factors Model (AFM), a standard logistic regression…
Descriptors: Educational Environment, Predictive Measurement, Predictor Variables, Cooperative Learning
Olsen, Jennifer K.; Aleven, Vincent; Rummel, Nikol – International Educational Data Mining Society, 2015
Student models for adaptive systems may not model collaborative learning optimally. Past research has either focused on modeling individual learning or for collaboration, has focused on group dynamics or group processes without predicting learning. In the current paper, we adjust the Additive Factors Model (AFM), a standard logistic regression…
Descriptors: Educational Environment, Predictive Measurement, Predictor Variables, Cooperative Learning