Teacher quality can be measured using value-added student achievement scores. Value-added scores, however, let us do much more. We can measure the value not only of different teachers but of different teaching methods. Thus, value-added scores and more generally big data are tools not just to weed out low-quality teachers but to raise the quality of all teachers.
We matched each teacher to the students they were teaching and assembled data on students’ demographic characteristics, performance on prior state tests, and the averages of such characteristics for the peers in their classroom. We also estimated each teacher’s impact on student performance in the prior school year (2013-14) to use as a control. (We wanted to account for the fact that more effective teachers may choose to use particular textbooks.) After controlling for the measures of student, peer, and teacher influences above, we estimated the variance in student outcomes on the new assessments associated with the textbook used.
The textbook effects were substantial, especially in math. In 4th and 5th grade math classrooms, we estimated that a standard deviation in textbook effectiveness was equivalent to .10 standard deviations in achievement at the student level. That means that if all schools could be persuaded to switch to one of the top quartile textbooks, student achievement would rise overall by roughly .127 student-level standard deviations or an average of 3.6 percentile points. Although it might sound small, such a boost in the average teacher’s effectiveness would be larger than the improvement the typical teacher experiences in their first three years on the job, as they are just learning to teach.
What makes this research especially important is that textbooks have no unions and it’s easy to replace one textbook with a better textbook. Moreover:
An annual report on the effectiveness of textbooks would transform the market, by providing publishers and software developers with a stronger incentive to compete on quality.