Review various publications related to Data Quality and Data Systems.
StudentTeacher Linkage Verification: Model Process and Recommendations
Educator compensation reforms supported by TIF and other recent federal initiatives involve holding teachers accountable for their students' performance. In order to do this, data systems must be able to accurately link students and teachers. This paper describes a model process for verifying student-teacher links and offers recommendations at each step.
Emerging Solutions To ImproveStudentTeacher Linkage
This paper summarizes several emerging solutions for improving the accuracy and quality of studentteacher linkage. The emerging solutions fall into two main categories: (1) leveraging different data sources and (2) improving data systems. Districts and states with interest in improving studentteacher linkage quality should consider the options presented in this paper.
Why Are Student-Teacher Linkages Important? An Introduction to Data Quality Concerns and Solutions in the Context of Classroom-Level Performance Measures
This paper discusses the complexities that states, districts, and schools face in developing accurate student-teacher linkages. It also emphasizes the importance for states, districts, and schools to invest time and resources to improve data quality in this area.
Annotated Bibliography of Data and Technology
The following annotated bibliography provides TIF grantees and other interested stakeholders a list of publications related to data and technology. For additional sources and more recent articles, use the CECR Online Library.
Evaluating Student-Teacher Linkage Data in Teacher Incentive Fund (TIF) Sites: Acquisition, Verification, and System Development
Data Quality Harvesting Paper: Findings from an exploratory study of eight TIF grantees about how they acquired, verified, and managed their student-teacher linkage data through system development.