Estimating Test-Score Growth with a Gap Year in the Data
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 district- and school-level growth measures that are estimated with and without a gap year. We find that growth estimates based on the full data and gap-year data are generally similar, and our results highlight an advantage of using comprehensive growth models with rich controls for student and schooling circumstances. With the caveat that there is looming uncertainty about which students will be tested in public schools when testing resumes, and how they will be tested, our findings establish the potential for estimating useful growth measures with a gap year in testing.
Citation: Ishtiaque Fazlul, Cory Koedel, Eric Parsons, Cheng Qian (2021). Estimating Test-Score Growth with a Gap Year in the Data. CALDER Working Paper No. 248-0121
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