The Purpose of Assessment Data

Dr. William Sanders scored a hit with educators and policy makers when he analyzed student test scores. By breaking out combined student test results and matching them against teacher ability, Dr. Sanders was able to show that student test scores can validate the fact that better teachers make a positive difference in student learning.

The significance of Dr. Sanders’ work is magnified by the widespread availability of student test data. In addition, Dr. Sanders was also able to avoid the socio-economic issues that can dilute the significance of quantitative data. The point Dr. Sanders brought home so adroitly is that data can help us understand events and, as a result, should be used to support better decisions.

The CEA offers educators the opportunity to make an even stronger statement about their positive contribution. Even though people associate test scores with education, other important influences should be considered. The CEA advocates going beyond test scores and using faculty, resource, productivity, and additional candidate data to describe educator impact.

The purpose of using faculty data is to gain a better understanding of the relationship between teacher quality and the faculty that prepares teachers. Resource data assists in understanding the relationship between teacher preparation and the funding available to prepare teachers. Productivity data compares the unit to the institution in order to better understand performance in light of available resources. Additional candidate data shows how non-test performance measures can give us a better understanding of education programs.

TEAS© demonstrates how these important, independent variables relate to education program performance.