This paper summarizes ASAP’s long-term effects and the educational investment in students associated with its services. The program helped students graduate faster, boosted graduation rates by 30 percent, and increased the financial aid students received.
Semistructured interviews involve an interviewer asking some prespecified, open-ended questions, with follow-up questions based on what the interviewee has to say. This Reflections on Methodology post describes a semistructured interview protocol recently used to explore how children who experience poverty perceive their situations, their economic status, and public benefit programs.
Learning from CUNY Start
This paper describes the professional development model used in CUNY Start, a program developed at the City University of New York to support entering students identified as academically underprepared in literacy and mathematics.
Several jurisdictions have instituted procedures meant to affect the use of bail. To determine whether those policies have had effects, a past trend can be used to extrapolate what would have happened had business continued as usual. This post discusses how researchers did such an extrapolation in Mecklenburg, North Carolina.
Assessing an intervention’s effects on multiple outcomes increases the risk of false positives. Procedures that make adjustments to address this risk can reduce power, or the probability of detecting effects that do exist. MDRC’s Reflections on Methodology discusses how to estimate power when making adjustments as well as alternative definitions of power.
To improve outcomes among high-interest borrowers, policymakers need to understand what is driving usage. This second post in MDRC’s Reflections on Methodology series discusses how a data discovery process revealed clusters of borrowers who differed greatly in the kinds of loans and lenders they used and in their loan outcomes.
A Literature Review
Examining the scholarly literature published since a seminal review in 2000, this working paper discusses the principles that underlie project-based learning, how it has been used in K-12 settings, the challenges teachers have confronted in implementing it, and what is known about its effectiveness in improving students’ learning outcomes.
Machine learning algorithms, when combined with the contextual knowledge of researchers and practitioners, offer service providers nuanced estimates of risk and opportunities to refine their efforts. The first post of a new series, Reflections on Methodology, discusses how MDRC helps organizations make the most of predictive modeling tools.
Strategies for Interpreting and Reporting Intervention Effects on Subgroups
This revised paper examines strategies for interpreting and reporting estimates of intervention effects for subgroups of a study sample. Specifically, the paper considers: why and how subgroup findings are important for applied research, the importance of prespecifying subgroups before analyses are conducted, and the importance of using existing theory and prior research to distinguish between subgroups for which study findings are confirmatory, as opposed to exploratory.
Howard Bloom’s Remarks on Accepting the Peter H. Rossi Award
In a speech before the Association for Public Policy Analysis and Management Conference on November 5, 2010, Howard Bloom, MDRC’s Chief Social Scientist, accepted the Peter H. Rossi Award for Contributions to the Theory or Practice of Program Evaluation.