A growing body of research highlights the classroom teacher as one of the most important predictors of student success. While research and policy conversations increasingly focus on the vital relationship between teacher and student, most of our current data systems are unable to inform these discussions. Only 18 states report the ability to connect their teacher data with student data in any grade, and even fewer actually use the resulting information to inform policy and practice.
One of the most important elements of a longitudinal-data system is the ability to collect and use quality information on educators over time and, most importantly, to relate the performance of teacher and students; the identification of the most effective teachers makes possible the study of any differences in their training, professional development, and teaching practices as compared with those of other teachers. Only when we have longitudinal-data systems that connect teacher and student data will we be able to guide our investments—of time, training, and even compensation—based on evidence that those investments reap the ultimate benefit: increased student achievement.
