{"id":5055,"date":"2025-07-18T05:00:00","date_gmt":"2025-07-18T12:00:00","guid":{"rendered":"\/blog\/?p=5055"},"modified":"2025-09-05T21:18:34","modified_gmt":"2025-09-06T04:18:34","slug":"making-sense-of-standard-error-of-measurement","status":"publish","type":"post","link":"https:\/\/www.nwea.org\/blog\/2025\/making-sense-of-standard-error-of-measurement\/","title":{"rendered":"Making sense of standard error of measurement"},"content":{"rendered":"
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If you want to track student progress over time, it\u2019s critical to use an assessment that offers accurate and precise estimates of student achievement. That precision can be described through a concept called standard error of measurement (SEM). Understanding SEM can help educators and school leaders interpret test scores more effectively and make more confident, data-informed decisions.<\/p>\n

What is standard error of measurement?<\/h2>\n

First, it\u2019s important to remember that all assessment scores are estimates. No matter how well-designed the assessment is, there is always some level of measurement error, meaning we can never know a student\u2019s true score with complete certainty. But we can estimate the range in which that true score likely falls. A smaller range means we have a more precise estimate of the student\u2019s true score.<\/p>\n

The size of this range is determined by the standard error of measurement. Smaller SEM means higher precision. When SEM is small, we can detect smaller changes in a student\u2019s learning over time with greater confidence. Larger SEM reduces our ability to distinguish between meaningful progress from random variation.<\/p>\n

Standard error of measurement and MAP Growth<\/h2>\n

When a student takes MAP\u00ae Growth\u2122<\/a>, their RIT score<\/a> comes with an associated SEM. In many reports, it appears as a score range, like this: Student score range: 185\u2013188\u2013191. This tells us that:<\/p>\n