The 2025 norms update addresses several critical factors: evolving U.S. student demographics, documented shifts in academic performance following the COVID-19 pandemic, and the item-selection algorithm in the newly enhanced MAP® Growth™.

This document presents the test design and specifications for Spanish MAP Reading Fluency.

This technical report documents the processes and procedures employed by NWEA to build and support the English MAP Reading Fluency assessment.

This document presents results from a linking study conducted by NWEA in May 2024 to statistically connect the grades 1–5 English Amira Reading Mastery (ARM) scores with the Scaled-Words-Correct-Per-Minute (SWCPM) scores from the MAP Reading Fluency benchmark assessment taken during Fall and Winter 2023–2024.

This executive summary outlines results from the Content Proximity spring 2022 pilot study, including information on the validity, reliability, and test score comparability of MAP Growth assessments that leverage this new item-selection algorithm.

The purpose of this research report is to provide detailed information about updates to the MAP Growth item-selection algorithm. This brief includes results from the Content Proximity pilot study, including information on the validity, reliability, and test score comparability of MAP Growth assessments that leverage this new item-selection algorithm.

This report documents the procedure used to produce the achievement and growth user norms for a series of the course-specific MAP® Growth™ subject tests, including Algebra 1, Geometry, Algebra 2, Integrated Math I, Integrated Math II, Integrated Math III, and Biology/Life Science. Among these tests, Integrated Math I, Integrated Math II, Integrated Math III, and Biology/Life Science were the first time to have their norms available. The remaining tests, i.e., Algebra 1, Geometry, and Algebra 2, had their norms updated including receiving more between-term growth norms by using more recent test events. Procedure for norm sample selection and a model-based approach using the multivariate true score model (Thum & He, 2019) that factors out known imprecision of scores to generate the norms are also provided in detail, along with the snapshots of the achievement and growth norms for each test.