IES Grant
Title: | Assessing Teacher Effectiveness: How Can We Predict Who Will be a High Quality Teacher? | ||
Center: | NCER | Year: | 2004 |
Principal Investigator: | Harris, Douglas N. | Awardee: | Florida State University |
Program: | Teaching, Teachers, and the Education Workforce [Program Details] | ||
Award Period: | 4 years | Award Amount: | $978,698 |
Type: | Measurement | Award Number: | R305M040121 |
Description: | Purpose: In this study, the researchers proposed to determine which assessments and strategies can be used to select teachers who are effective in raising student achievement. The researchers' primary goal was to shed light on both the merits of general strategies used to select high-quality teachers (professional judgments versus standardized measures) and on the specific assessment criteria that are most highly associated with student outcomes. To conduct this work, the researchers would leverage a unique database also that allowed for methodological advancements in the calculation of value added, which was becoming an increasingly important tool for research on teachers in the early 2000s. Structured Abstract THE FOLLOWING CONTENT DESCRIBES THE PROJECT AT THE TIME OF FUNDING The first part of the study examines associations between teacher characteristics and student outcomes using data on students in grades 3 through 10 and their teachers. These data are drawn from a Florida statewide database that includes longitudinal information on nearly the entire population of teachers and students in the state. Statistical modeling procedures will be applied to the data in order to derive "value-added" scores for more than 5,000 teachers; these scores represent estimates of the contributions that individual teachers make to student achievement. To address questions regarding what teacher characteristics best predict effectiveness, associations between these effectiveness scores and a set of teacher characteristics will then be examined. Teacher characteristics in these analyses include measures of general verbal and quantitative skills, college course-taking, and certification test scores. The size of the database will allow for detailed breakdowns for sub-groups of students, teachers, and school. The second part of the project involves the use of a mixed methods approach to compare principals' opinions of the factors that predict teacher effectiveness with the measures found to be the best predictors of value added from the first set of analyses. In addition, the degree to which principals can predict and identify which of the teachers in their own schools produce the largest value added to student outcomes is being examined. For this part of the project, value-added scores are calculated for each teacher, as in the first part of the project, and are compared with coded data from principal interviews. Products and Publications ERIC Citations: Find available citations in ERIC for this award here. Select Publications: Book chapters Harris, D. (2008). The Policy Uses and Policy Validity of Value-Added and Other Teacher Quality Measures. In D.H. Gitomer (Ed.),Measurement Issues and the Assessment of Teacher Quality (pp. 99–130). Thousand Oaks, CA: SAGE Publications. Journal articles Harris, D.N., Ingle, W.K., and Rutledge, S.A. (2014). How Teacher Evaluation Methods Matter for Accountability: A Comparative Analysis of Teacher Effectiveness Ratings by Principals and Teacher Value-Added Measures. American Educational Research Journal, 51(1), 73–112. Harris, D., and Rutledge, S. (2010). Models and Predictors of Teacher Effectiveness: A Comparison of Research About Teaching and Other Occupations. Teachers College Record, 112(3): 914–960. Harris, D.N., and Sass, T.R. (2011). Teacher Training, Teacher Quality And Student Achievement. Journal of Public Economics, 95(7–8), 798–812. Harris, D.N., and Sass, T.R. (2014). Skills, Productivity and the Evaluation of Teacher Performance. Economics of Education Review, 40, 183–204. Rutledge, S., and Harris, D. (2008). Certify, Blink, Hire: An Examination of the Process and Tools of Teacher Selection. Leadership and Policy in Schools, 7(3): 237–263. Sass, T.R., Semykina, A., and Harris, D.N. (2014). Value-Added Models and the Measurement of Teacher Productivity. Economics of Education Review, 38, 9–23. ** This project was submitted to and funded under Teacher Quality: Reading and Writing in FY 2004. |
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