Carnegie Knowledge Network Concluding Recommendations. What We Know Series

It is common knowledge that teacher quality is a key in-school factor affecting student achievement. While the quality of teaching clearly matters for how much students learn, this quality is challenging to measure. Evaluating teacher quality based on the level of their students' end-of-year test scores has been one method of assessing teacher quality, but this approach favors those teachers of students who begin the year already at a high academic level. Value-added methodology is an alternative use of annual test score data to assess teacher quality. As opposed to using the level of student achievement on a test at the end of the year to assess a teacher's effectiveness, value-added methodology seeks to isolate a teacher's contribution to student growth from other factors that contribute to student achievement, such as prior achievement or socio-economic status. Methodologists generally agree that value added estimates can serve as a gauge of some dimensions of teacher effectiveness. Yet the experts also agree that value-added measures have significant limitations. Most clearly, they do not capture a teacher's entire contribution to student learning because they are based solely on test performance, itself an imprecise signal of teacher effectiveness. There is disagreement among experts on the extent to which value added is biased. Thus there remains considerable debate about how value-added measures should be used to inform personnel policies, if they are to be used at all. As the real impacts of reforms using value added emerge and as researchers assess these effects, educators will learn more about the consequences of different uses of value added. Until then, the Carnegie Knowledge Network (CKN) briefs have provided a rich picture of current research on the use of value-added measures for teacher evaluation. Reviewing the briefs and their implications for practitioners, CKN arrived at the following recommendations: (1) When using value added, allow educational leaders to make judgments in interpreting the value-added results in light of other available measures of teacher quality and the principals' own assessments; (2) Use value added with other measures that are valid and have variation; (3) Choose a test that measures knowledge that is valued; (4) Consider differences in teaching contexts when using value added to compare teachers; and (5) Take specific steps to ensure the overall credibility of the teacher evaluation system. Data from millions of students and thousands of teachers as well as careful thought and analysis have taught us much about the statistical properties of value added. Yet these measures are only just beginning to be put into widespread use for teacher evaluation. As these new systems roll out, states and districts should be learning and experimenting, determining what works and what doesn't. They should use this time to collect data and monitor their evaluation systems, using what they learn to make revisions.