There are a number of pressing world calamities in play right now. The aftermath of a major tsunami and earthquake, a clear and present nuclear meltdown threat, and military actions in the Middle East are sufficient for a reprisal of our favorite caped crusader. So, for planning purposes, let us assume that Superman is tied up and will not be able to help us with the current challenges we are facing in education, particularly the education of low-income, urban and rural public school students. Given his busy schedule, we figured we had better get things started in the area that is our wheelhouse – education data. 

Over the past five years, we have regularly encountered a series of challenges related to education data. While we have been able to tackle these issues on a client-by-client basis, our natural curiosity and passion for educational improvement is moving us toward national research on overcoming these challenges systematically. We are therefore pursuing research, complemented by our client experience,  to address and uncover good practice related to the following challenges

1. Metrics Dilution: Today we tend to measure education activities versus educational outcomes. We describe school models by virtue of how long the school day is, how long the school year is, and how many hours of math or English instruction students are receiving. When we collect what we believe are outcomes data, we do so on a lagging basis furthering weakening their value.  Furthermore, we settle for bad proxies of what we really want to know about students, teachers, and schools. For example, instead of uncovering and decoding key aspects of student engagement, we measure attendance, truancy, and discipline. We have encountered several places where we see the metrics getting closer to indicate the outcome, and we seek even more strong examples in the field through this research. 
2. Data System Limitations Force Us Toward Lower Value Outcomes: Technical limitations and the desperate desire for common metrics have driven us toward measuring lower value outcomes. Data system providers have developed comprehensive methods to capture data that computers can house, rather than the data we might actually want. In the focus on efficiency, we have quite possibly ignored data that are likely more compelling and informative, but also more challenging to systematically capture. In particular, today’s data systems tend to warehouse lagging indicators rather than serving as a school intelligence system of leading indicators. Many of the data initiatives in place now focus on simply collecting more of the data we collect now over longer periods of time and at the student level. Our hope with many of these system investments is that we can also create ways to collect data that are more meaningful over time and shed a bright light on the student experience. 
3. Chasm between those who need the data and those who own the data: Perhaps the most significant issue we encounter in our education measurement work is the disconnect between those who need measurement data in order to improve, redirect, and celebrate, such as students, teachers, and parents, and those who own the data. With districts and states serving as primary data owners, we see a gulf in both time and space between those who have and control the data and those who need it to do their work. Getting data to those who are in a position to respond and deliver improved results is the final challenge and high priority of this work.  

If you have thoughts on the challenges above or would like to participate in a research interview on these topics, feel free to contact me at Pranav@missionmeasurement.com or @pgktweet.