Archive for the ‘Data Use’ Category

Pinchok Nick
Nick Pinchok
Senior Program Associate
Learning Point Associates

Tennessee’s recent win in the first round of Race to the Top (RTTT) competition arguably could be attributed to past work in developing value-added growth modeling and plans to tie student academic growth data to educator evaluations and effectiveness. As other state education agencies look to appear more serious about changing their current systems for the second round of RTTT, growth modeling is one area that states may emphasize more and attempt to impose more serious accountability reforms.

Growth models in today’s accountability-driven system could be described as calculations attempting to measure whether students, on average, are increasing their scores at a pace to be “on track” to earn a desired proficiency level on a particular test. More specifically, they “use 2 or more years of assessment results as an indicator of school performance and attach decision rules to changes in performance” (Goldschmidt & Choi, 2007).

With the need to honor the complexity of individual student learning and the fact that students start at different levels of learning across the United States, growth models have helped draw attention to the importance of measuring the accumulation of student achievement below the proficiency threshold. What gets measured, how we measure, and what else we analyze beyond academic measurements are all as important as the growth model itself, however. Expectations for growth models to measure student achievement and to determine teacher, principal, and school effectiveness will be extremely high after Tennessee’s win. In spite of some criticism of, and imperfections with, growth models, aren’t these models what we want and need?

As an administrator, I would want to know as specifically as possible how much progress our students are making from expensive investments in curricula, professional development, and assessment systems—what’s working and what’s not. Growth models can help identify teacher strengths and areas of need and adjust appropriately to make improvements along the way. As a teacher, I would want to know what’s working with my kids. If I’m reflective and data driven, I would want the investment of my time to pay off with my students.

Knowing that there is still anxiety about tying teacher performance to assessment data, what recommendations do you have that could make growth modeling more effective and powerful for teachers, students, and administrators? What assessment, program, and demographic data will help make growth models fair for students and teachers, as well as for accountability systems? What else can our experts be doing to build better growth models, or what have you seen that you recommend?

Goldschmidt, P., & Choi, K. (2007). The practical benefits of growth models for accountability and the limitations under NCLB. Washington, DC: Council of Chief State School Officers. Retrieved April 20, 2010, from