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      Projecting the Potential Impact of COVID-19 School Closures on Academic Achievement

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          Abstract

          As the COVID-19 pandemic upended the 2019–2020 school year, education systems scrambled to meet the needs of students and families with little available data on how school closures may impact learning. In this study, we produced a series of projections of COVID-19-related learning loss based on (a) estimates from absenteeism literature and (b) analyses of summer learning patterns of 5 million students. Under our projections, returning students are expected to start fall 2020 with approximately 63 to 68% of the learning gains in reading and 37 to 50% of the learning gains in mathematics relative to a typical school year. However, we project that losing ground during the school closures was not universal, with the top third of students potentially making gains in reading.

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          Flaking Out: Student Absences and Snow Days as Disruptions of Instructional Time

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            The Effects of Summer Reading on Low-Income Children’s Literacy Achievement From Kindergarten to Grade 8

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              Job Loss in the Great Recession and its Aftermath: U.S. Evidence from the Displaced Workers Survey

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                Author and article information

                Contributors
                Journal
                Educational Researcher
                Educational Researcher
                American Educational Research Association (AERA)
                0013-189X
                1935-102X
                November 2020
                October 28 2020
                November 2020
                : 49
                : 8
                : 549-565
                Affiliations
                [1 ]NWEA, Portland, OR
                [2 ]University of Virginia, Charlottesville, VA
                [3 ]University of Maryland, College Park, MD
                Article
                10.3102/0013189X20965918
                1a6c9b16-5564-4d2e-ab5e-a02e227622f7
                © 2020

                http://journals.sagepub.com/page/policies/text-and-data-mining-license

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