We just published on Medium an important article that traces the recent history of education research to show how an unfortunate legacy of NCLB has weakened research methods, as applied to school use of edtech, and made invisible resulting achievement gaps. This article was originally a set of four blog posts by CEO Denis Newman and Chief Scientist Andrew Jaciw. The article shows how the legacy belief that differential subgroup effects (e.g., based on poverty, prior achievement, minority status, English proficiency) found in experiments are, at best, a secondary exploration that has left serious achievement gaps unexamined. And the false belief that only studies based on data collected before program implementation are free of misleading biases has given research the warranted reputation as very slow and costly. Instead, we present a rationale for low-cost and fast-turnaround studies using cloud-based edtech usage data combined with already collected school district administrative data. Working in districts that have already implemented the program lowers the cost to the point that a dozen small studies each examining subgroup effects, which Jaciw has shown to be relatively unbiased, can be combined to produce generalizable results. These results are what school decision-makers need in order to purchase edtech that works for all their students.
Or read the 4-part blog series we posted this past summer.