Every time you give students an assessment, you expect to see a series of output measures that will help inform critical academic decisions. Maybe you’re focused on growth.
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This October, we’re excited to announce a few new handy features that will provide meaningful data at your fingertips, offer additional assessment flexibility, support customizable data conversations, and deliver more learning path transparency.
Whenever we use instruments to measure things, whether it’s a yardstick to measure height, a clock to measure drive time, or a test to measure student ability, there is some amount of noise that can result in slightly different measurements each time. That noise is called measurement error. In educational testing, this measurement error is more often referred to as the standard error of measurement—abbreviated “SEM.”
In this video, we’re exploring standard deviation—the statistics term you may (or may not) remember but will find handy when it comes to analyzing your assessment data! Let’s take a closer look at what standard deviation is, and then how you can use it to make sense of your data, starting with a simple definition.
Making sense of assessment data can be complicated—we’re here to break it down so that reading your reports doesn’t require a translator. Let’s look at scale scores—the underlying way assessment performance is often reported.
While it’s certainly important to understand the academic skills of these incoming kinder students, it’s just as critical to measure physical well-being and social and emotional development. Let’s take a closer look at how several states are rising to the challenge.