Mathematica designed and conducted three large-scale studies on the relationship between teacher preparation and effectiveness, using the most rigorous approach possible—random assignment of students to teachers from different kinds of programs—and compared student test scores to gauge teacher effectiveness.
- Rapid-cycle evaluation
- Evidence-based decision making
- Technical assistance
- Evaluation methodology
- Teacher evaluation
- Value-added methodology
- Analytical technical assistance and development
- Effective Data Use
- Teacher and Principal Effectiveness
- Strengthening and Disseminating Research
Alexandra Resch is an expert in program evaluation methodology, teacher evaluation, and value-added methods. Resch’s current work is focused on making research more accessible to end users and helping states and localities use complex methods to improve programs and policies.
Resch leads several projects using rapid-cycle evaluation to help school districts make better decisions. She leads a team that is developing a toolkit that will allow school districts and other users conduct rigorous, quick-turnaround evaluations of education technologies they use in schools. She is also leading teams working with Race to the Top-District grantees to conduct rapid-cycle evaluations of personalized learning strategies implemented through their grants. In related work focused on reducing barriers to using rigorous evaluation methods, she recently co-authored two guides on opportunistic experiments, a way of embedding rigorous research in planned pilots or policy changes, for the U.S. Department of Education and is currently providing technical assistance to state Temporary Assistance for Needy Families agencies on conducting efficient, rigorous evaluations using existing administrative and program data.
Resch played key roles on several teacher evaluation projects. She serves as project director for the development of a new teacher and principal evaluation system to support Charleston (SC) County School District’s Teacher Incentive Fund (TIF) grant, an effort that includes developing value-added measures of teacher and principal effectiveness. Resch directed Mathematica’s value-added work for the Washington, DC, public schools for use with high-stakes teacher assessment systems. On the evaluation of the federal TIF, she provided technical assistance to grantees on the design and implementation of performance-based teacher and principal compensation systems.
Resch writes for a wide range of audiences, publishing documents ranging from peer-reviewed journal articles to user-friendly briefs directed at school leaders. She has been published in the BE Press Journal of Economic Analysis and Policy, Review of Economics and Statistics, and National Tax Journal. Resch holds a Ph.D. in public policy and economics from the University of Michigan.