CRESP 2016-2021 Strategic Plan


CRESP is committed to addressing education and social policy challenges with rigorous, relevant research.

Founded in 2013, CRESP recognizes that poverty, educational achievement, and chronic disease prevention are intertwined in a complex social web that challenges communities and policymakers alike.  CRESP’s mission, values, and scientific priorities seek to inform program and policy development across local, state, and federal levels.  We work alongside program professionals, academic leaders, and students to foster engagement in high-quality, practice-driven research and evaluation. CRESP researchers are trained in evaluation methodology, randomized field experiments, natural experiments, qualitative methods, statistical analysis, mixed-method evaluation and survey research.

 

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Download CRESP’s 2016-2021 Strategic Plan here.

PRIORITIES

CRESP will emphasize its work in these four priority areas over the next five years. 
Our work will:
1. Improve student achievement and reduce gaps in K-16 educational settings;
2. Improve understanding of how to increase consumption of healthy foods;
3. Identify and address health disparities, especially among children;
4. Advance understanding of the connections between education, social policy, and health

RESEARCH EXPERTISE
Rigorous, high-quality research is at the core of our mission, and our experienced staff engages in a variety of methods to understand how, why, and if programs or policies are effective. We conduct both qualitative and quantitative research and maintain staff expertise in:

  • Applied policy research investigating public health and educational innovations and interventions;
  • Program evaluation;
  • Quantitative analyses of large administrative, state, regional, and national databases;
  • Qualitative methods to promote knowledge of important, but difficult-to-measure characteristics of programs and collaborative partnerships;
  • Randomized controlled field trials;
  • Longitudinal studies of changes over time that combine data from disparate sources;
  • Application of statistical methods from economics, engineering, and other disciplines to social programs and policies.