At a gala for the American Association of People with Disabilities in March, Education Secretary Arne Duncan affirmed the current administration’s commitment to maintaining high expectations for special education populations, noting that “students with disabilities should be judged with the same accountability system as everyone else.” While most educators would readily support this goal, they would also probably tell you that achieving it is a lot easier said than done—especially when it comes to using student achievement data as a factor in evaluating special education teachers.

In an education reform landscape that seems saturated with increasingly complex questions about accountability systems (particularly around the use of value-added models in educator evaluation), determining where special education students and teachers fit into those systems poses some of the most complex questions of all. So what progress have we made to determine how value-added data should be used to measure achievement in special education students? The answer seems to be…not that that much.

There are plenty of pretty obvious reasons why value-added models pose fundamental problems in the special education world. One potentially insurmountable obstacle is the lack of standardized test scores. Most value-added models require at least two years’ worth of test data for each student. This makes it nearly impossible to collect value-added data for students with severe cognitive disabilities that qualify for their state’s alternate assessment. Alternative assessments, which were mandated as part of the reauthorization of IDEA in 1997, are scored on completely different scales than the state standardized tests. While some states have attempted to scale the scores and create comparable data for completing value-added analysis, most have chosen to exclude this group of students completely.

Assessment experts have also pointed out that the results that alternative assessments yield lack the “fine tuning” that is needed to complete value-added calculations with confidence. Although there is a strong push by the US Department of Education to substantially reduce the number of students with disabilities taking the alternate assessment (which is expected to be backed by the reauthorization of the Elementary and Secondary Education Act coming next fall), it will be years before states even have the option of including students from this group as part of their value-added calculations.

The challenges aren’t limited to using value-added data to measure progress for special education students who are taking the alternate assessment. A report by the National Comprehensive Center for Teacher Quality issued last July identified a number of obstacles that impact a wider group of students, including the fact that researchers have yet to identify an appropriate way to account for the impact of testing accommodations on test scores of special education students who take the regular state test.

Without a way to control for the impact of testing accommodations on student performance, the testing data from this group of students is difficult (if not impossible) to use to draw precise conclusions about the “value” added by special education teachers. Although states continue to work tirelessly to develop educator evaluation systems that incorporate value-added data, efforts to find new ways to incorporate precise measures that capture student achievement in the context of special educators’ evaluations seem to be lagging behind. While the challenges listed above (among a host of others) may represent valid reasons why standard value-added models may not work with special education data, there is important work to be done in developing other means for determining precise measures of progress for special education students.

This is not to say that special education teachers are excluded from the emerging high stakes evaluation models—they certainly aren’t. States have developed a variety of alternatives to using value-added data for evaluating special education teachers, but the accuracy and precision of the information they provide has far less backing by research than the models applied to general education populations. If the measures used to determine the effectiveness of special education teachers aren’t as precise as those used for general education teachers, states and districts will be limited in their ability use that data to drive meaningful professional development and support.

In a field that is historically lacking in quality professional development, it seems that states are missing a valuable opportunity to use their evaluation systems to make vast improvements in the quality of support special educators are afforded. If we aren’t doing enough to determine how to measure progress accurately for special education students, it means that we aren’t doing enough to support special education teachers in becoming more effective.