On Data, Part Four: Advocating for Data-Informed Decision Making
Slowly but surely lawmakers across the country are voting for teacher evaluation systems that consider how students perform on standardized tests. These new laws indicate an increasing trust in standardized tests and statistical models such as VAM to do the hard work of defining a teacher's quality.
On July 27 Jeff Henig, a professor of education and political science at Columbia University, published a guest post on Rick Hess's blog entitled "Policy by Algorithm." In it, Henig notes the utility of data and algorithms to help systems like public education make decisions, but he cautions,
On July 27 Jeff Henig, a professor of education and political science at Columbia University, published a guest post on Rick Hess's blog entitled "Policy by Algorithm." In it, Henig notes the utility of data and algorithms to help systems like public education make decisions, but he cautions,
"...the high promise of policy by algorithm mutates into cause for concern when data are thin, algorithms theory-bare and untested, and results tied to laws that enshrine automatic rewards and
