Diana McCallum’s research spans the education and family support topics. She specializes in evaluation technical assistance and conducting systematic reviews to inform policy.
She currently provides evaluation technical assistance to Performance Partnership Pilot (P3) grantees who are conducting experimental, quasi-experimental, and implementation evaluations of programs to served disconnected youth. She has also provided technical assistance to Office of Adolescent Health grantees who are conducting evaluations to determine impacts of teen pregnancy prevention programs. McCallum has also contributed her expertise to several systematic review efforts, focusing on both identifying high-quality studies and synthesizing findings for various audiences. She worked on a review of programs for pregnant and parenting adolescents to identify impacts on educational attainment, repeat pregnancy, and contraceptive use. In addition, she oversees protocol development and reviews for a systematic review of school choice policies and the effects on students that are accepted into schools of choice, and those that do not participate. McCallum is also a certified reviewer for the What Works Clearinghouse.
Before joining Mathematica, McCallum worked for the U.S. Department of Health and Human Services and the U.S. Department of Education as a research analyst, overseeing federal systematic reviews and national evaluations. In 2010, she was the recipient of the Society for Research on Adolescence’s Best Journal Article award for Parent Involvement in Middle School: A Meta-Analytic Assessment of the Strategies that Promote Success. She holds a Ph.D. in developmental psychology and a certificate in education policy from Duke University.
When the Office of Planning, Research, and Evaluation (OPRE) within the Administration for Children and Families was tasked by Congress with standing up a central repository of information about what works to help job seekers facing persistent economic hardship secure gainful employment, there were important technical questions to address about how to best find that information and assess it.
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