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NWEA MAP Growth assessment and longitudinal achievement database

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Evidence · 11 claims (11 for) · 4 studies (4 associational), q2–q3 · 0 of 4 report an effect size · 11 claims rest on one study

Description

A longitudinal database of student achievement and growth scores collected through NWEA's MAP Growth assessments and used for large-scale educational analysis.

Components

  • MAP Growth test-score dataset covering 4.9 million U.S. students in Grades 3-8: The study's evidence base is a large-scale dataset of test scores from U.S. students, described in the abstract as follows: "The data included test scores from 4.9 million U.S. students in Grades 3 through 8." The authors used these scores to model student achievement trends prior to and during the pandemic, with particular focus on growth in 2020-2021. The dataset spans math and reading outcomes across elementary and middle school grades. (Megan Kuhfeld et al. (2022))
  • National K–8 fall and spring achievement dataset covering 840,000 students in 8,800 public schools: The study leverages achievement data measured at two points in each school year — "in the fall and spring of kindergarten through eighth grade" — for a national sample of "840,000 students attending 8,800 public schools." This seasonal structure allows the authors to separate school-year growth from summer loss and to compare rural and nonrural schools. It is the empirical basis for all findings in the article. (Angela Johnson et al. (2021))
  • NWEA dataset of 162,000 eighth-grade students across 22 states: The empirical basis of the brief is a large NWEA dataset covering "162,000 eighth-grade students across 22 states." The dataset supports analysis of both school-level Algebra offerings and individual student placement into the course, enabling equity comparisons by poverty, geography, and race/ethnicity. (Daniel Long et al. (2025))
  • NWEA dataset of 186,139 ever-ELs and never-EL peers in 1,520 schools: The study leverages what the author calls "unique data that include 186,139 ever-ELs and their never-EL peers in 1,520 schools." This large-scale dataset supports within-year (fall-to-spring) achievement and gain comparisons across grades K-8 for three EL status groups against the all-student average. Its scale permits grade-level pattern analysis of growth for relatively small subgroups such as dually-identified students. (Angela Johnson (2020))
  • Multi-occasion K-8 math and reading achievement dataset (2016-17, over seven million students): The study's evidence base is a dataset of "math and reading test scores for over seven million students in kindergarten through 8th grade" collected "across the fall, winter, and spring of the 2016-17 school year." Its three within-year test occasions are what permit testing whether growth trajectories are linear rather than assuming so. The article uses it to evaluate the linearity assumption underlying school-year policy analysis and summer-loss research. (Megan Kuhfeld (2020))
  • NWEA test-score dataset of over 2.5 million kindergarten through eighth-grade students across three cohorts (2015-2018): A large-scale longitudinal test-score dataset used to examine seasonal patterns of racial/ethnic achievement gaps. The article states it draws on "test scores from over 2.5 million kindergarten to eighth-grade students" and follows "three different cohorts of students from 2015 to 2018," enabling comparison of gap growth when school is in versus out of session across grades K-8. (Megan Kuhfeld et al. (2020))
  • NWEA MAP Growth assessment dataset (3.4 million students) as the evidence base for seasonal learning analysis: The article's evidence base is score data from "the 3.4 million students who took the NWEA MAP Growth assessments," used to estimate school-year gains and summer loss across a very large student population. The scale of the dataset is what allows the article to identify that the students with the greatest summer loss were those who made the greatest prior school-year gains. The dataset is described only in the abstract of the available text. (Megan Kuhfeld (2019))

Claims

Key Sources

  • Megan Kuhfeld, James Soland, Karyn Lewis, Erik Ruzek, Angela Johnson. (2022). The COVID-19 school year: Learning and recovery across 2020-2021. AERA Open, 8. https://doi.org/10.1177/23328584221099306
  • Angela Johnson, Megan Kuhfeld, James Soland. (2021). The forgotten 20 percent: Achievement and growth in rural schools across the nation. AERA Open. https://www.nwea.org/research/publication/the-forgotten-20-percent-achievement-and-growth-in-rural-schools-across-the-nation/
  • Daniel Long, Megan Kuhfeld, Scott J. Peters. (2025). Unequal Access to 8th-Grade Algebra: How School Offerings and Placement Practices Limit Opportunity. NWEA Research brief. https://www.nwea.org/research/publication/unequal-access-to-8th-grade-algebra-how-school-offerings-and-placement-practices-limit-opportunity/
  • Angela Johnson. (2020). Within-year achievement gains for English Learners. NWEA Research working paper. https://www.nwea.org/research/publication/within-year-achievement-gains-for-english-learners/
  • Megan Kuhfeld, James Soland. (2020). The learning curve: Revisiting the assumption of linear growth across the school year. NWEA Research working paper. https://www.tandfonline.com/doi/full/10.1080/19345747.2020.1839990
  • Megan Kuhfeld, Dennis Condron, Doug Downey. (2020). When does inequality grow? A seasonal analysis of racial/ethnic disparities in learning from kindergarten through eighth grade. Educational Researcher. https://doi.org/10.3102/0013189X20977854
  • Megan Kuhfeld. (2019). Rethinking summer slide: The more you gain, the more you lose. KappanOnline. https://www.nwea.org/research/publication/rethinking-summer-slide-the-more-you-gain-the-more-you-lose/
Page metadata
Field Value
type product
id nwea-map-growth-assessment-and-longitudinal-achievement-database
title NWEA MAP Growth assessment and longitudinal achievement database
description A longitudinal database of student achievement and growth scores collected through NWEA's MAP Growth assessments and used for large-scale educational analysis.
status review
moved_from element/map-growth-4-9-million-students-dataset, element/national-k8-fall-spring-achievement-dataset-840000-students, element/nwea-162000-eighth-graders-22-states-dataset, element/nwea-186k-ever-el-dataset, element/nwea-2016-17-k8-three-occasion-dataset, element/nwea-k8-three-cohort-seasonal-dataset, element/nwea-map-growth-3-4-million-seasonal-dataset
product_kind dataset
generated by process:sweep-kinds on 2026-10-10
trust unverified — no one has confirmed this page's content
sources 6 — megan-kuhfeld-2022, angela-johnson-2021, daniel-long-2025, angela-johnson-2020, megan-kuhfeld-2020, megan-kuhfeld-2019

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