The purpose of education is to help people learn. Learning is a natural physiological process of the human brain and the nature of those processes define the rules within which educators (and education policy makers) must play. While it might be convenient for policy makers to define test scores as a measure of learning, those tests may not align with the nature of learning and knowledge in the real world. If tests give educators an unnatural lens to understand learning, then the policy must be adjusted.
Recent generations of educators have focused intensely on standards in education, while also arguing “one size fits all” education is not the goal. Different pathways to the same standard outcome is an oxymoron. If the ends are standardized learners, then the means are irrelevant.
While claiming to be “data-driven,” educators are incredibly sloppy with their collection, analysis, management, and reporting of data. Their sloppiness derives from blind acceptance that tests measure what they proportion (and other unchallengeable assumptions), their reliance on single measures, and their lack of sophistication in analysis. Statisticians have created tools to help us understand large data sets. Let’s insist they start using those tools.