ESEA Waivers And The Perpetuation Of Poor Educational Measurement
Some of the best research out there is a product not of sophisticated statistical methods or complex research designs, but rather of painstaking manual data collection. A good example is a recent paper by Morgan Polikoff, Andrew McEachin, Stephani Wrabel and Matthew Duque, which was published in the latest issue of the journalEducational Researcher.
Polikoff and his colleagues performed a task that makes most of the rest of us cringe: They read and coded every one of the over 40 state applications for ESEA flexibility, or “waivers.” The end product is a simple but highly useful presentation of the measures states are using to identify “priority” (low-performing) and “focus” (schools “contributing to achievement gaps”) schools. The results are disturbing to anyone who believes that strong measurement should guide educational decisions.
There’s plenty of great data and discussion in the paper, but consider just one central finding: How states are identifying priority (i.e., lowest-performing) schools at the elementary level (the measures are of course a bit different for secondary schools).
There are 42 states with accepted waiver applications. Out of these 42, 17 exclusively use some version of proficiency or other cutpoint-based rates to identify priority schools. Another 23 employ a composite index consisting of different measures, but in most of these indexes, proficiency still plays the dominant role. Finally, another two
