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- Implementation and process evaluation
- Education program and policy analysis
- Systematic reviews
- Evidence-based technical assistance
- Human Services
- Criminal Justice
- Family Support
- Teacher and Principal Preparation and Support
- Effective Data Use
- Early Childhood
- Systematic Evidence Reviews
Marykate Zukiewicz is a researcher with diverse experience in several key areas, including education, criminal justice and family support. She has played a lead role in both local and national evaluations, implementation and process evaluations, evidence-based technical assistance projects, and systematic evidence reviews.
Zukiewicz has led a number of state and local projects, several of which were conducted in her home state of Colorado. Together with the Colorado Evaluation and Action Lab and the Colorado Department of Corrections, she leads a collaborative partnership focused on identifying successful reentry practices for individuals in prison and on parole. Zukiewicz has also led several evidence-based technical assistance projects with local human service agencies in Colorado, including technical assistance on the use of rapid-cycle evaluations to test and refine program improvement efforts.
In addition, Zukiewicz has played a lead role in several large-scale, national projects. She has served as task lead on several education studies, including her role as recruitment task lead for the Data-Driven Instruction Study and her role as lead author on the implementation analysis conducted for the Teach For America Investing in Innovation study. Within the area of early childhood, Zukiewicz has led the Home Visiting Evidence of Effectiveness impact study review team, applying rigorous evidence standards in the identification of evidence-based maternal and infant home visiting programs eligible for federal funding.
Prior to joining Mathematica, Zukiewicz served as a corps member in Teach For America’s New York City program and also worked as a legislative director at New York City Council. She presents her work at conferences sponsored by the Association for Public Policy Analysis and Management, the Association for Education Finance and Policy, and other organizations. She holds an M.P.A. from New York University and an M.Ed. in bilingual education from the City University of New York Lehman College.
Modeling Successful Reentry Practices in Colorado
Mathematica in partnership with the Colorado Department of Corrections (CDOC) Division of Adult Parole and the Colorado Evaluation and Action Lab (Colorado Lab) will leverage an existing data set to examine ways to target reentry services so that they can best help reduce incarceration across the state.
Colorado Department of Corrections Reentry Systems Mapping
The Colorado Evaluation and Action Lab (“Colorado Lab”) partners with the Office of Colorado’s Governor and works with state agencies to improve the lives of Colorado’s residents.
Project IMPROVE: Improving Program Outcomes Via Evidence-Based Technical Assistance
Improving service delivery for clients, increasing efficiency, and minimizing costs are key goals for TANF programs. In recent years, evidence, evaluation, and program analytics have helped harness the power of evidence and data to improve program outcomes.
How Effective Is Home Visiting?
The Home Visiting Evidence of Effectiveness study is a thorough and transparent review of the home visiting research literature and an assessment of the evidence of effectiveness for home visiting programs that serve families with pregnant women and children from birth to age 5.
Evaluation of Support for Using Student Data to Inform Teachers' Instruction
Mathematica is conducting an experimental impact evaluation of the effects of data-driven instruction (DDI) on student achievement. This involves the implementation of high quality DDI professional development and estimating its effects on student achievement.
Support for Data-Driven Instruction Comes Up Short in New Study
Although most school districts help teachers use data to improve student learning, a new Mathematica study shows that providing schools with data coaches and professional development to support their efforts did not result in increased data use by teachers.