Every summer, the Biocomplexity Institute’s Social and Decision Analytics Division’s Data Science for the Public Good (DSPG) Young Scholars program draws university students from around the country to work together on projects that use computational expertise to address critical social issues faced by local, regional, state or federal governments. The students conduct research at the intersection of statistics, computation, and the social sciences to determine how information generated within every community can be leveraged to improve quality of life and inform public policy. The program, held at the University of Virginia’s Arlington offices, runs for 10 weeks for undergraduate interns and 11 weeks for graduate fellows who work in teams collaborating with postdoctoral associates and research faculty from the division, and project stakeholders.
The 2019 cohort conducted nine research projects, and their methodologies and discoveries will be presented at MethodSpace over the next three weeks as part of our examinations of Methods In Action. The descriptions of the projects were penned by the students themselves, and their names, mentors and sponsors appear under the DSPG logo in the text.
Recidivism is one of the most commonly-cited statistics when referencing the failures of the criminal justice system in the United States. Not only does the U.S. incarcerate the highest number of people per capita compared to every other country in the world, but a large majority of those individuals (68 percent) are rearrested within three years. One form of programming geared toward reducing recidivism is postsecondary prison education programs, which have been shown to lower odds of recidivating by 48 percent.
While there is significant research on the outcomes of a few prison education programs, the field is diverse in terms of the topics that are covered, types of instruction, and length of programming. During the Data Science for the Public Good (DSPG) summer program hosted by the Biocomplexity Institute and Initiative at the University of Virginia, our team took a deep dive into the prison education programs around the United States in an effort to synthesize information regarding prisoner education and reentry into society. All DSPG summer projects focus on using data science to promote the public good. Prison education is an area where data can help support policy-makers to determine how best to allocate limited funds and structure these programs to best optimize outcomes of participants.
After examining some of the largest prison education programs in the U.S., we compiled a set of best practices for any programs looking to evaluate their work or interested in expanding prison education. We know that prison education works, but in order for it to have the desired impacts, programming should be created with specific outcomes in mind and target the specific needs of the criminogenic population. Our research seeks to understand if current programs are investing in the right areas and provide suggestions for those who are just starting out.
Most policy focuses solely on reducing recidivism as an ideal outcome, but recidivism itself is an imperfect measure. Recidivism refers to three different components: rearrest, reconviction, and reincarceration. In addition, it only accounts for reported crime, is measured inconsistently, can be misleading when presented as a single data point, and considers returning offenders equally (regardless of offense). In researching effective prison education programs, we searched for those that not only led to reduced recidivism, but also focused on other positive outcomes including better employment opportunities, higher salaries, health care, savings and financial management, housing stability, resource networks, and general well-being. We found that prison education programs at all levels resulted not only in lowered recidivism (across all types), but also positive effects on post-release earnings and employment and lowered the odds of inmates engaging in misconduct. In addition to clarifying measures of recidivism, assessments of prison education effectiveness should be expanded to include additional measures that take these other positive impacts into account.
The most effective prison education programs share a number of characteristics we believe are essential for any successful program. We determined success in our analysis by reviewing the program effectiveness reports provided by prison education programs and conducting interviews with different program administrators to get a sense of what works and how programs approach prison education differently. From the outset, any program should have rigorously designed course syllabi that are geared directly toward the criminogenic population. This includes adding activities that might not directly relate to the course material but are important for classroom management, like addressing antisocial behaviors, stress, and past traumas. It also means matching the right instructor to the course. For example, prisoners who have previously completed a course could serve as a valuable asset to an instructor by assisting as a teaching aid or mentoring current students in the classroom. Each prison education course should also be eligible for college credit, so that students can demonstrate their knowledge and value outside of prison with an official document to show potential employers. Instructors should be held to a predetermined standard: they should either be certified by the state (as teachers are) or go through a rigorous training process to ensure they are effectively presenting course content.
Programs should target those who would stand to benefit the most, not those who are already excelling. This helps to limit both selection bias and improve impact. There should be no restrictions by type of offense, highest degree obtained, or limits based on behavior (with perhaps a few exceptions if that behavior is disruptive to a classroom setting). Programs should also create a matched control sample of individuals who match the characteristics of those admitted to the program but are, due to capacity reasons, unable to attend. This allows for an easier comparison as to the effects of the program years down the line, as both populations can be tracked over time. In some states, prisons can recruit students across the entire state network, while in others, education is limited to specific prisons and their populations. This can have a dramatic impact on the pool of potential applicants, and programs should work with their respective state department of corrections to reach as a broad a population as possible.
Program evaluations should be tied directly to course syllabi to ensure that objectives are being met. For example, if a course is geared toward increasing financial literacy and preparing for the job market, the program should administer a pre- and post- evaluation of students’ financial skills. A Situational Judgement Test could be used to estimate students’ knowledge of appropriate business behaviors in different scenarios (e.g., preparing for an interview, writing a resume).
Lastly, to maximize the benefits of prison education, programs should be tied to a post-release component that assists students in building and maintaining positive relationships on the inside and outside. While this would add to the cost of running an educational program, it would significantly reduce the costs of adding people back into that population. If all prison education programs adopt these best practices, then programs will be more effective in reducing recidivism, which in turn will reduce the significant social and financial costs of reincarceration to individuals and society at large.