Method for Value-added Modeling

Statisticians use a student's past test scores to predict the student's future test scores, on the assumption that students usually score approximately as well each year as they have in past years. The student's actual score is then compared to the predicted score. The difference between the predicted and actual scores, if any, is assumed to be due to the teacher and the school, rather than to the student's natural ability or socioeconomic circumstances.

In this way, value-added modeling isolates the teacher's contributions from factors outside the teacher's control that are known to strongly affect student test performance, including the student's general intelligence, poverty, and parental involvement.

By aggregating all of these individual results, statisticians can determine how much a given teacher typically improves student achievement, compared to how much the typical teacher would have improved student achievement.