About

Kelli A. Bird is a research associate professor of public policy at the University of Virginia Frank Batten School of Leadership and Public Policy. Her research focuses on policies and strategies aimed to improve postsecondary education and workforce outcomes, particularly for students from disadvantaged backgrounds. She applies a wide set of rigorous quantitative methods, including randomized controlled trials, quasi-experimental methods using econometric models of causal inference, predictive analytics with machine learning models, and detailed descriptive analyses. Her current research portfolio is centered on evaluating intensive college advising initiatives and workforce training programs. Bird’s work has been published in several highly regarded economics, public policy, and education journals. Her research is funded by various public and private organizations, such as Arnold Ventures, Ascendium Education Group, Bloomberg Philanthropies, and the Institute for Education Sciences. Her research has been cited in prominent outlets like the New York Times and was included in the 2023 Economic Report of the President.

Research topics

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

Selected publications

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

  AEA Papers and Proceedings · 2026-05-01

  article1st authorCorresponding

  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

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

  Brown Digital Repository · 2026-05-21

  articleOpen access1st authorCorresponding
  PublisherDOI

• 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

  article1st authorCorresponding
  PublisherDOI

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

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

  article1st author
  PublisherDOI

• Anti-inflammatory reliever therapy for asthma using inhaled budesonide/formoterol as-needed with or without maintenance in South African children (AIR-SA 001): a description of a randomised clinical trial protocol

  BMJ Open Respiratory Research · 2025-11-01

  articleOpen access

  Background Asthma is the most common non-communicable disease among children, with increasing prevalence. The current standard of care in high-income countries in adults and adolescents includes the use of combination inhaled corticosteroids (ICSs) with rapid-onset long-acting ß 2 agonists (LABA) for all severities of asthma. The primary objective of this trial is to assess the efficacy of a budesonide/formoterol inhaler used ‘both as required, and regularly’ to reduce asthma exacerbations compared with the standard of care for asthma in children and adolescents. Methods Children and adolescents aged 6–18 years with a diagnosis of asthma with at least one asthma exacerbation in the previous 12 months will be randomised to receive either budesonide/formoterol inhaler or the standard of care, which includes ICS and short-acting ß 2 agonist (SABA). The primary outcome will be the number of severe asthma exacerbations over 1-year follow-up period. Secondary objectives will include evaluating the quality of life, lung function and health economic outcomes. Discussion The current standard of care in South Africa recommends use of separate ICSs and SABA inhalers for asthma management in children with no recommendation for ICS/LABA in children under the age of 12 years for non-severe asthma. Budesonide/formoterol has transformed asthma treatment in high-income countries for use ‘as needed’ as anti-inflammatory reliever and for maintenance and reliever in adolescence, 12−18 years and adults. This strategy has been shown to reduce asthma exacerbations and hospitalisations. This trial will bridge the gap for the efficacy of budesonide/formoterol in children <12 years of age and address the economic arguments and safety of this approach for implementation in the lower to middle income countries. If this trial demonstrates positive results in the study population, it could provide strong scientific evidence and policy relevance to be adopted by policymakers for clinical implementation. Trial registration number This study has been registered and approved by the South African Health Regulatory Authority 20231016, on 14 December 2023, KwaZulu Natal Health Research Committee KZ_202304_008 on 11 January 2024, University of KwaZulu Natal Biomedical Research Ethics Committee BREC/0000/5663/2023 on 6 February 2024, South African Clinical Trials Register DOH-27-032024-4778 on 14 March 2024, ClinicalTrial.gov NCT06429475 on 20 May 2024 and Pan African Clinical Trial Registry on 27 February 2025; the unique identification number for the registry is PACTR202502547023775.

  PublisherOA PDFDOI

• College Forward RCT Follow-Up: Labor Market Impacts

  AEA Randomized Controlled Trials · 2025-08-27

  dataset
  PublisherDOI

• College Forward RCT Follow-Up: Labor Market Impacts

  AEA Randomized Controlled Trials · 2025-08-27

  dataset
  PublisherDOI

• 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

• 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 access1st authorCorresponding

  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

• Input incentives, student engagement, and post-secondary success: Experimental evidence from a national college advising program

  AEA Randomized Controlled Trials · 2023-05-12

  datasetSenior author
  PublisherDOI

Frequent coauthors

• Benjamin Castleman

  University of Virginia

  14 shared

• Ben Castleman

  7 shared

• William Skimmyhorn

  Williams (United States)

  6 shared

• Andrew Barr

  Mitchell Institute

  5 shared

• William Skimmyhorn

  3 shared

• Jeffrey T. Denning

  3 shared

• Andrew C. Barr

  Texas A&M University

  2 shared

• Gabrielle Lohner

  University of California, Berkeley

  2 shared

Education

• Education Policy Studies, Doctoral Student

  University of Virginia

• Economics, M.A.

  University of Virginia

  2011

• Economics, B.S.

  University of Kansas

  2008