Causal Inference and COVID: Contrasting Methods for Evaluating Pandemic Impacts Using State Assessments

Autor/in	Shear, Benjamin R.
Titel	Causal Inference and COVID: Contrasting Methods for Evaluating Pandemic Impacts Using State Assessments
Quelle	In: Educational Measurement: Issues and Practice, 42 (2023) 1, S.99-109 (11 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Shear, Benjamin R.)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0731-1745
DOI	10.1111/emip.12540
Schlagwörter	COVID-19; Pandemics; School Closing; Measurement; State Standards; Academic Achievement; Colorado + Suchen Sie Ihr Suchwort? School closings; Schule; Schließung; Schließung (von Schulen); Messverfahren; Schulleistung
Abstract	In the spring of 2021, just 1 year after schools were forced to close for COVID-19, state assessments were administered at great expense to provide data about impacts of the pandemic on student learning and to help target resources where they were most needed. Using state assessment data from Colorado, this article describes the biggest threats to making valid inferences about student learning to study pandemic impacts using state assessment data: measurement artifacts affecting the comparability of scores, secular trends, and changes in the tested population. The article compares three statistical approaches (the Fair Trend, baseline student growth percentiles, and multiple regression with demographic covariates) that can support more valid inferences about student learning during the pandemic and in other scenarios in which the tested population changes over time. All three approaches lead to similar inferences about statewide student performance but can lead to very different inferences about student subgroups. Results show that controlling statistically for prepandemic demographic differences can reverse the conclusions about groups most affected by the pandemic and decisions about prioritizing resources. (As Provided).
Anmerkungen	Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01