|Title:||Assessing Teacher Effectiveness: How Can We Predict Who Will be a High Quality Teacher?|
|Principal Investigator:||Harris, Douglas||Awardee:||Florida State University|
|Program:||Effective Teachers and Effective Teaching [Program Details]|
|Award Period:||4 years||Award Amount:||$978,698|
Research shows that teacher quality is associated with student outcomes. Most states certify teachers based on a combination of college coursework, degree attainment, and performance on pedagogical and/or content-based examinations. Despite their importance, however, relatively little is currently known about the ability of these assessment schemes to identify the most effective teachers-those who will contribute the most to student learning. This project is designed to address the question of what assessments and strategies can be used to select teachers who are effective in raising student achievement.
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 to be included 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 in 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.
The primary goal of this research is 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. The unique database also allows for methodological advancements in the calculation of value added, which is becoming an increasingly important tool for research on teachers.
Project Website: http://www.teacherqualityresearch.org.
Publications from this project:
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.
Harris, D., and Rutledge, S. (2010). Models and Predictors of Teacher Effectiveness: A Review of the Evidence with Lessons from (and for) Other Occupations. Teachers College Record, 112 (3): 914–960.
Harris, D., and Sass, T. (2007). Teacher Training, Teacher Quality, and Student Achievement. National Center for the Analysis of Longitudinal Data in Education Research (CALDER). Working Paper #3. Washington, DC: Urban Institute.
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.
** This project was submitted to and funded under Teacher Quality: Reading and Writing in FY 2004.