About

Benjamin Castleman is a professor of public policy and education at the University of Virginia. His research focuses on policies and strategies to improve postsecondary educational and workforce outcomes for individuals from lower-income communities. Castleman conducts this research through collaborative research-policy partnerships with public agencies and organizations at the local, state, and federal levels. His current work emphasizes innovations to increase economic mobility among lower-wage adults and examines the economic and life outcomes generated by intensive college advising programs. His research has been published in top journals such as The American Economic Review, The Journal of Labor Economics, The Journal of Public Economics, and the Proceedings of the National Academy of Sciences. Castleman has received the Presidential Early Career Award for Scientists and Engineers, and his work has been supported by numerous philanthropic foundations and covered extensively in media outlets including The New York Times, National Public Radio, and The Washington Post. Prior to his academic career, he was a public school teacher and administrator in Providence, Rhode Island.

Research topics

• Political Science
• Medicine
• Psychology
• Business
• Medical education
• Geography
• Computer Science
• Public relations
• Economics
• Accounting
• Sociology
• Economic growth
• Social psychology
• Multimedia
• Actuarial science
• Pedagogy
• Data science
• Engineering
• Environmental health
• Demography
• Mathematics education
• Finance

Selected publications

• Do Financial Incentives Increase the Take-Up and Impact of Large-Scale Programs? Experimental Evidence from a National College Advising Initiative

  Journal of Political Economy Microeconomics · 2026-01-07

  articleSenior author
  PublisherDOI

• Meeting People Where They Are: Experimental Evidence on Embedded Supports, Service Use, and Educational Outcomes

  Brown Digital Repository · 2026-05-21

  articleOpen accessSenior author
  PublisherDOI

• Do Embedded Supports Promote Engaged Learning? Experimental Evidence on Resource Use among Community College Students

  AEA Papers and Proceedings · 2026-05-01

  articleSenior author

  We report results from an experimental evaluation of an intervention in which tutoring and advising services were embedded directly into “gateway” community college courses and targeted to students identified by faculty and staff as at risk of not completing the course. Students in treated sections significantly increased their meetings with instructors, tutors, and advisors while decreasing their use of online learning management system resources. The positive impact on staff resource utilization was particularly strong among first-generation college students. The findings suggest that providing readily available in-person support substantially increases its uptake, potentially as a preferred alternative to asynchronous online materials.

  PublisherDOI

• Increasing Degree Attainment among Low-Income Students: The Role of Intensive Advising and College Quality

  American Economic Review · 2025-10-30 · 1 citations

  articleSenior author

  A college degree offers a pathway to economic mobility for low-income students. Using a multisite randomized controlled trial combined with administrative and survey data, we demonstrate that intensive advising during high school and college significantly increases bachelor’s degree attainment among lower-income students. We leverage unique data on preadvising college preferences and causal forest methods to show that these gains are primarily driven by improvements in initial enrollment quality. Our results suggest that strategies targeting college choice may be a more effective and efficient means of increasing degree attainment than those focused solely on affordability. (JEL G51, I21, I22, I23)

  PublisherDOI

• Behavioral nudges prevent loan delinquencies at scale: A 13-million-person field experiment

  Proceedings of the National Academy of Sciences · 2025-01-23 · 9 citations

  articleOpen access

  Americans collectively hold over $1.6 trillion in student loan debt, and over the last decade millions of borrowers have defaulted on loans, with serious consequences for their financial health. In a 13-million-person field experiment with the U.S. Department of Education, we tested the effectiveness of different email interventions to inform borrowers about alternative repayment options after a missed loan payment. Our interventions tested whether sending monthly behaviorally-informed emails, providing follow-up reminders, framing benefits in percentage (vs. dollar) terms, and providing just one recommended action step at a time (vs. two) affected borrower outcomes. We find that i) behaviorally-informed emails reduce estimated 60-d delinquencies by 0.42 pp, ii) reminders boost the efficacy of such emails by 0.57 pp, iii) describing potential savings in percentage terms is more effective than describing these benefits in dollar terms, reducing estimated delinquencies by 0.14 pp, and iv) encouraging two actions (i.e., enrollment in income-driven repayment plans and auto debit programs) repeatedly across two emails is marginally more effective than encouraging one action at-a-time across two emails, reducing estimated delinquencies by 0.05 pp. Overall, if scaled to all 13-million borrowers in our experiment, we estimate that our best-performing intervention would have averted approximately 79,800 60-d delinquencies. Our findings i) highlight the benefits of describing potential savings in percentage terms, which may magnify perceived savings for recipients, ii) underscore the risks of oversimplification, and iii) demonstrate that nudges can be an effective, low-cost complement to other policies for reducing delinquencies and supporting borrowers with student loan debt.

  PublisherOA PDFDOI

• Increasing Degree Attainment Among Low-Income Students: The Role of Intensive Advising and College Quality

  National Bureau of Economic Research · 2025-06-01 · 1 citations

  reportOpen accessSenior author

  A college degree offers a pathway to economic mobility for low-income students.Using a multisite randomized controlled trial combined with administrative and survey data, we demonstrate that intensive advising during high school and college significantly increases bachelor's degree attainment among lower-income students.We leverage unique data on pre-advising college preferences and causal forest methods to show that these gains are primarily driven by improvements in initial enrollment quality.Our results suggest that strategies targeting college choice may be a more effective and efficient means of increasing degree attainment than those focused solely on affordability.

  PublisherDOI

• Is Big Data Better? LMS Data and Prediction Accuracy in Postsecondary Education

  Journal of Research on Educational Effectiveness · 2025-04-15 · 2 citations

  articleCorresponding
  PublisherDOI

• Are algorithms biased in education? Exploring racial bias in predicting community college student success

  Journal of Policy Analysis and Management · 2024-01-31 · 22 citations

  articleOpen access

  Abstract Predictive analytics are increasingly pervasive in higher education. However, algorithmic bias has the potential to reinforce racial inequities in postsecondary success. We provide a comprehensive and translational investigation of algorithmic bias in two separate prediction models—one predicting course completion, the second predicting degree completion. We show that if either model were used to target additional supports for “at‐risk” students, then the algorithmic bias would lead to fewer marginal Black students receiving these resources. We also find the magnitude of algorithmic bias varies within the distribution of predicted success. With the degree completion model, the amount of bias is over 5 times higher when we define at‐risk using the bottom decile than when we focus on students in the bottom half of predicted scores; in the course completion model, the reverse is true. These divergent patterns emphasize the contextual nature of algorithmic bias and attempts to mitigate it. Our results moreover suggest that algorithmic bias is due in part to currently‐available administrative data being relatively less useful at predicting Black student success, particularly for new students; this suggests that additional data collection efforts have the potential to mitigate bias.

  PublisherOA PDFDOI

• Can information and advising affect postsecondary participation and attainment for military personnel? Evidence from a large‐scale experiment with the U.S. Army

  Journal of Policy Analysis and Management · 2024-02-15 · 1 citations

  articleOpen access

  Abstract Despite generous financial aid, military veterans have high rates of undermatch and generally poor postsecondary outcomes. We conducted a large‐scale, multi‐arm field experiment with the U.S. Army to investigate whether personalized information about postsecondary options and access to advising affects service members’ postsecondary choices and outcomes. We find no impact of the intervention on whether or where veterans enroll in college or on their college persistence. These results suggest that light touch strategies that have been effective at addressing similar challenges among traditional students, and which we modified for the military context, are not sufficient to improve veterans’ postsecondary outcomes.

  PublisherOA PDFDOI

• A "Sludge Audit" for Health System Colorectal Cancer Screening Services

  The American Journal of Managed Care · 2023 · 9 citations

  • Medicine
  • Environmental health
  • Business

  OBJECTIVES: "Sludge," or the frictions or administrative burdens that make it difficult for people to attain what they want or need, is an unexplored health care delivery factor that may contribute to deficiencies in colorectal cancer (CRC) screening. We piloted a method to identify and quantify sludge in a southeastern US health system's delivery of CRC screening services. STUDY DESIGN: Mixed methods sludge audit. METHODS: We collected and analyzed quantitative (insurance claims, electronic health record, and administrative files) and qualitative (stakeholder interviews and process observations) data associated with CRC screening for instances of sludge. Because they contribute to sludge and reduce system capacity for high-value screening, we also evaluated low-value CRC screening processes. RESULTS: Although specific results were likely amplified by effects of the COVID-19 pandemic, the sludge audit revealed important areas for improvement. A 60.4% screening rate was observed. Approximately half of screening orders were not completed. The following categories of sludge were identified: communication, time, technology, administrative tasks, paperwork, and low-value care. For example, wait times for screening colonoscopy were substantial, duplicate orders were common, and some results were not accessible in the electronic health record. Of completed screenings, 32% were low-value and 38% were associated with low-value preoperative testing. There was evidence of a differential negative impact of sludge to vulnerable patients. CONCLUSIONS: Our sludge audit method identified and quantified multiple instances of sludge in a health system's CRC screening processes. Sludge audits can help organizations to systematically evaluate and reduce sludge for more effective and equitable CRC screening.

  DOI

Frequent coauthors

• Richard C. Cabot

  1996 shared

• Tracy B. Mallory

  The University of Texas MD Anderson Cancer Center

  847 shared

• Virginia W. Towne

  Harvard University

  741 shared

• Edith E. Parris

  658 shared

• Betty U. McNeely

  301 shared

• Betty U. Kibbee

  285 shared

• Robert E. Scully

  University of St Andrews

  172 shared

• Lindsay C. Page

  29 shared

Awards & honors

• Presidential Early Career Award for Scientists and Engineers