We have a winner! Or rather, 9 winners. Today the Departments of Education and Health and Human Services announced the 9 successful states in the Race to the Top – Early Learning Challenge grant competition. North Carolina, Massachusetts, Washington, Delaware, Ohio, Maryland, Minnesota, Rhode Island, and California will share a portion of the $500 million pot. For some background on the competition, I’ve covered RTT-ELC on this blog, and others have provided even more extensive coverage over the last few months.
At Ed Week’s Politics K-12 blog, Michele McNeil walks through three of the biggest losers from today’s announcement (including California, which received half the amount of money it requested by token of being the lowest-scoring among the 9 winners). Here’s her take on New Mexico’s misfortune:
“The state narrowly missed winning, at 7.6 points behind 9th-place finisher and winner California. The merits of New Mexico’s proposal aside, this state had a wild swing in scores among the five judges. On a 280-point scale, the difference between the highest-scoring judge and the lowest-scoring judge was a whopping 90 points! That was clearly enough to kick the state out of the winners’ circle. The effect of scoring outliers was also an issue in last year’s $4 billion Race to the Top. (To see score breakdowns by judge, click on the spreadsheet called “State Data Workbook” on this Education Department web page.)”
What Michele doesn’t mention is that in RTT-ELC applications, states could prioritize their activities. RTT-ELC specified two “core areas” and three “focused investment areas.” In the focus areas, states could pick and choose how many criteria to address. Focus areas were 1) Promoting Early Learning and Development Outcomes for Children, 2) A Great Early Childhood Education Workforce, and 3) Measuring Outcomes and Progress. Within the first (worth 60 points), states had to address at least 2 of 4 criteria. In the latter two (worth 40 points each), states needed to address at least 1 of 2 criteria.
The key here is “at least.” Each component within the focus areas was weighted equally, so there was no advantage for states that chose to address everything. In fact, states could be penalized if they scored dramatically lower on any of the additional criteria they chose. As Sara Mead noted, this feature of RTT-ELC “means states will have to be strategic in choosing exactly how many and which of the activities to address in their response to focus criteria.”
This is exactly what happened with New Mexico and California. California provided a focused application – only addressing the minimum number of activities in each focus area. For example, the state’s application did not mention how they planned to build or enhance an early learning data system to improve instruction, practices, services, and policies. Given the state’s recent history with data systems, this was a very strategic move. No doubt, the state would have scored poorly in that activity, resulting in a lower score overall (California scored 243.6 points).
New Mexico, on the other hand, chose to address both of the criteria in the workforce focus area and the measuring outcomes and progress focus area. But, the state would have been better off with a less ambitious application. Had the state only addressed “developing a workforce knowledge and competency framework and a progression of credentials” and building their early learning data system, their application would have scored 7.2 points higher – increasing their overall score to 243.2, less than half a point behind California.
While this would not have pulled the state into 9th place, such a narrow finish might have led the Departments to reconsider awarding California their $50 million prize. They were certainly one of the biggest surprises in the RTT-ELC winner’s circle. No matter what your opinion is of either state’s merits in the competition (is a focused application better than a more ambitious one?), this kind of result should lead to serious questioning about how federal competitive grant competitions are scored. With millions of dollars (not to mention, learning opportunities for children) at stake, should the outcome really hinge on which state had the best application strategy?