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Fazlul, Ishtiaque; Koedel, Cory; Parsons, Eric; Qian, Cheng – AERA Open, 2021
We evaluate the feasibility of estimating test-score growth for schools and districts with a gap year in test data. Our research design uses a simulated gap year in testing when a true test gap did not occur, which facilitates comparisons of district- and school-level growth estimates with and without a gap year. We find that growth estimates…
Descriptors: Scores, Achievement Gains, Computation, School Districts
Fazlul, Ishtiaque; Koedel, Cory; Parsons, Eric; Qian, Cheng – National Center for Analysis of Longitudinal Data in Education Research (CALDER), 2021
We evaluate the feasibility of estimating test-score growth with a gap year in testing data, informing the scenario when state testing resumes after the 2020 COVID-19-induced test stoppage. Our research design is to simulate a gap year in testing using pre-COVID-19 data--when a true test gap did not occur--which facilitates comparisons of…
Descriptors: Scores, Achievement Gains, Computation, Growth Models
Data Quality Campaign, 2020
States can and should continue to measure student growth in 2021. Growth data will be crucial to understanding how school closures due to COVID-19 have affected student progress and what supports they will need to get back on track. Education leaders will also need growth data to ensure that any recovery efforts are equitable as well as effective…
Descriptors: Student Evaluation, Growth Models, State Policy, State Standards