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Download full textBloom, Howard S.; Weiss, Michael J. – MDRC, 2018
The benefits of understanding variation apply on multiple levels. Local policymakers and practitioners need to know both the average impact of an intervention and its variation across settings to properly assess its likely benefits and risks for their jurisdictions. For social scientists, cross-site impact variation offers opportunities to learn…
Descriptors: Program Effectiveness, Research Methodology, Geographic Location, Intervention
Preel-Dumas, Camille; Hendra, Richard; Denison, Dakota – MDRC, 2023
This brief explores data science methods that workforce programs can use to predict participant success. With access to vast amounts of data on their programs, workforce training providers can leverage their management information systems (MIS) to understand and improve their programs' outcomes. By predicting which participants are at greater risk…
Descriptors: Labor Force Development, Programs, Prediction, Success
Raudenbush, Stephen W.; Bloom, Howard S. – MDRC, 2015
The present paper, which is intended for a diverse audience of evaluation researchers, applied social scientists, and research funders, provides a broad overview of the conceptual and statistical issues involved in using multisite randomized trials to learn "about" and "from" variation in program effects across…
Descriptors: Program Effectiveness, Research Methodology, Statistical Analysis, Differences
Zhu, Pei; Jacob, Robin; Bloom, Howard; Xu, Zeyu – MDRC, 2011
This paper provides practical guidance for researchers who are designing and analyzing studies that randomize schools--which comprise three levels of clustering (students in classrooms in schools)--to measure intervention effects on student academic outcomes when information on the middle level (classrooms) is missing. This situation arises…
Descriptors: Intervention, Academic Achievement, Research Methodology, Research Design
Rutschow, Elizabeth Zachry; Schneider, Emily – MDRC, 2011
One of the greatest challenges that community colleges face in their efforts to increase graduation rates is improving the success of students in their developmental, or remedial, education programs--the courses that students without adequate academic preparation must take before they can enroll in courses for college credit. Emphasizing results…
Descriptors: Graduation Rate, Research Methodology, Academic Achievement, Developmental Studies Programs
Rutschow, Elizabeth Zachry; Schneider, Emily – MDRC, 2011
One of the greatest challenges that community colleges face in their efforts to increase graduation rates is improving the success of students in their developmental, or remedial, education programs--the courses that students without adequate academic preparation must take before they can enroll in courses for college credit. Emphasizing results…
Descriptors: Journal Articles, Models, College Readiness, Evidence
Direct linkBloom, Howard S.; Richburg-Hayes, Lashawn; Black, Alison Rebeck – MDRC, 2005
This paper examines how controlling statistically for baseline covariates (especially pretests) improves the precision of studies that randomize schools to measure the impacts of educational interventions on student achievement. Part I of the paper introduces the concepts, issues, and options involved. Parts II and III present empirical findings…
Descriptors: Program Effectiveness, Reading Achievement, Mathematics Achievement, Research Methodology
