Project Activities
The researchers will apply a variety of statistical techniques to analyze data from the Florida Education Data Warehouse and to sort out the relationships among different variables. Student outcomes to be studied will include performance on the state standards-referenced assessment as well as another norm-referenced assessment, high school graduation rate and the type of diploma received, time of drop out for students who do not complete high school, and post-school employment, military and educational experiences.
Structured Abstract
Setting
The Florida Education Data Warehouse (Data Warehouse) contains individual-level longitudinal data for the universe of public school students and teachers in the state. The Data Warehouse also includes the entire college transcript (including specific courses taken and grades received) for all teachers who attended a Florida public university and the subject matter and length of every professional development course taken by Florida teachers once they begin their careers.
Sample
The population to be studied includes the students with disabilities whose data are available in the Florida Education Data Warehouse. The Data Warehouse has data for about 400,000 special education students each year since 1995.
Pre-service and in-service teacher training experiences and other relevant variables as recorded in the Data Warehouse will be analyzed for possible associations with student outcomes. Data on the teachers' certification status, pre-service coursework and degrees attained, and content and duration of professional development activities will be included.
Research design and methods
See "Key Measures" and "Data Analytic Strategy" below.
Control condition
n/a
Key measures
The project will employ several different measures, including the "Sunshine State Standards" Florida Comprehensive Achievement Test, the Florida Comprehensive Achievement Test - Norm-Referenced Test, high school enrollment and completion, type of the diploma received, post-secondary outcomes, classroom peer characteristics, and teacher characteristics.
Data analytic strategy
Analysis of the data will involve estimation of the impact of teacher training on student achievement, the probability of graduating from high school, and the post-secondary education and employment outcomes of students with disabilities. A variety of value-added models of student achievement and educational attainment will be estimated along with survival analysis, probit models, and multinomial logit models.
People and institutions involved
IES program contact(s)
Project contributors
Products and publications
Products: The expected outcomes from this study include reports and presentations of findings on teacher training factors that are associated with improved student outcomes for students with disabilities. These findings may suggest interventions for improving teacher quality and student outcomes in the future.
Journal article, monograph, or newsletter
Sass. T., and Feng, L. (2013). What Makes Special Education Teachers Special? Teacher Training and Achievement of Students With Disabilities. Economics of Education Review, 36: 122-134. doi:10.1016/j.econedurev.2013.06.006
Questions about this project?
To answer additional questions about this project or provide feedback, please contact the program officer.