A voluntary program in San Francisco arranged interviews for disadvantaged job-seekers and offered employers temporary wage subsidies to hire them. This study analyzes the one-year, per person program costs and the cost of non-program services, including education and training. The analysis indicates that the program was likely cost-beneficial from society’s perspective.
This study analyzes the per person cost of a subsidized employment program for enrollees in Minnesota’s Temporary Assistance for Needy Families who could not otherwise find employment, and the costs of other services that all sample members may have received. The program’s primary goal was to move participants into unsubsidized employment.
In NYC P-TECH Grades 9-14 schools, students take an integrated sequence of high school and college courses with the goal of completing both high school and college, while simultaneously being exposed to hands-on work experiences. This infographic describes the model and introduces MDRC’s evaluation of it.
The Center for Applied Behavioral Science (CABS) combines MDRC’s decades of experience tackling social policy issues with insights from behavioral science. This graphic explains the CABS’s approach to solving problems.
The SIMPLER framework was developed for the Behavioral Interventions to Advance Self-Sufficiency (BIAS) project ― the first major effort to apply behavioral insights to human services programs in the United States. SIMPLER summarizes several key behavioral concepts that can guide practitioners interested in using behavioral insights to enhance service delivery.
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.
As the first major effort to use a behavioral economics lens to examine human services programs that serve poor and vulnerable families in the United States, the BIAS project demonstrated the value of applying behavioral insights to improve the efficacy of human services programs.
A Primer for Researchers Working with Education Data
Predictive modeling estimates individuals’ probabilities of future outcomes by building and testing a model using data on similar individuals whose outcomes are already known. The method offers benefits for continuous improvement efforts and efficient allocation of resources. This paper explains MDRC’s framework for using predictive modeling in education.
The city’s small, academically nonselective high schools have substantially improved graduation rates for disadvantaged students. This report demonstrates that, because more of their students graduate and do so within four years, the schools have lower costs per graduate than the schools their study counterparts attended.
Using Volunteers to Improve the Academic Outcomes of Underserved Students
School-based mentoring programs have been shown to improve students’ academic performance and self-confidence. This study examines what makes the Big Brothers Big Sisters of America school-based mentoring program effective, offering key insights for practitioners. It also contributes a theoretical structure with which to assess other randomized evaluations of such programs.