Getting Smart with Data: Using Existing Data to Develop Early Warning Systems

July 14, 2016

Can the data captured by IEP Systems help districts develop Early Warning Systems to target at-risk students?

Over the past decade, education, like virtually every other professional field, has both benefitted from and struggled to grapple with the massive influx of data made available through advances in technology and a proliferation of tools and resources for collecting this data.  As educators, data can give us more information about our students, about the effectiveness of our own practices, and can, when used well, help us make better decisions to support students.  As more data become available along with more sophisticated technology for collecting and using data, there has been a push in the education world for districts, schools, and educators to not only defend their own decisions using data, but to use data to make better decisions.

In 2014, when the Department of Education announced Results Driven Accountability (RDA), a new accountability framework for special education which shifts the emphasis from compliance to results, the need for more data, particularly in regards to student progress, became pressing. Schools and EdTech companies have since been scrambling to get systems and tools into the hands of educators that can supply this kind of data.

And while this shift from holding schools accountable for results over compliance is more student centered and ultimately positive, it follows a similar trend in education of focusing perhaps too heavily on test scores, which can encourage schools to zero in on results while ignoring the underlying forces behind these results. Or, more simply put, it might be a case of putting the cart before the horse.

Using Data to Identify Struggling Students  

It is patently clear that data on student progress is crucial to measuring instructional effectiveness and knowing whether students are learning and schools should continue to develop systems and technology for collecting this kind of data. But it is also true that thanks to a multitude of SIS systems, school districts are already sitting upon massive amounts of data that can help them target struggling students and take meaningful action early on. Such efforts are already gaining steam nation-wide. Using data on student attendance and grades, districts in Tennessee, Pennsylvania, Illinois and elsewhere are adopting Early Warning Systems, which allow them to target struggling students and develop intervention plans.

According to Elaine Allensworth of the University of Chicago Consortium of School Research, “This shift from focusing on test scores to focusing on attendance and grades–it’s been a complete transformation in terms of how schools are working with students and it’s much more effective.”

While the jury is out on how effective such systems will be, there is evidence in places like Chicago Public Schools–where graduation rates have increased 22 percentage points in the last decade and a half–that focusing on struggling students in 9th grade and developing interventions to keep them in school and pass classes has contributed to the significant increase in graduation rates.

Such success begs the question, when it comes to special education, what data do we have, and how can we put this data to better use?

IEP Systems and Early Warning Systems

Early Warning Systems focus on using information found in SIS systems about students, like attendance and grades, to alert schools that students may be at risk. It is up to the school to take meaningful action on this data. Like SIS systems, IEP systems also contain valuable information about students. This data is already being used by districts to avoid due process suits and alert them when they are out of compliance, but such data can also give schools valuable information that can help them pro-actively target students at risk. For example, using  Accelify’s IEP and Service Tracking systems, districts are able to zero in on students who are consistently missing the services prescribed in their IEPs, like speech or occupational therapy.  They can also track whether timelines are being met for things like special education evaluation, and can gain insight into why these timelines are not being met–whether it has to do with difficulty connecting with parents or a failure on the part of providers, etc.  Again, such information can be invaluable in predicting a student’s success or failure and can help districts learn how to better allocate resources and time to where they will be the most effective.

Earlier this week, the findings of an annual review of state special education programs was released, indicating that fewer than half of states are meeting their obligations to students under IDEA. Given this information, it is imperative that schools do more to improve outcomes for students with disabilities. As schools continue to determine methods for collecting student data and reporting on results, it is important that we keep in mind that data does not only help us defend decisions we are already making, but helps us make better decisions. And while data on results is critical to knowing whether we are effective, schools can and should do more to tap into the abundance of data already at their fingertips and use what we know about the predictors of student success and failure to proactively intervene, before it is too late. The results will speak for themselves.