
Susanna Loeb
· ProfessorVerifiedStanford University · Education Policy and Social Context
Active 1995–2026
About
Susanna Loeb is a Professor at the Stanford Graduate School of Education and holds the title of Professor, Graduate School of Education. She was previously the Director of the Annenberg Institute at Brown University, where she was also a Professor of Education and of International and Public Affairs. Loeb is the founder and executive director of the National Student Support Accelerator, which aims to expand access to relationship-based, high-impact tutoring in response to the Covid-19 pandemic. Her research broadly focuses on education policy and its role in improving educational opportunities for students, addressing issues such as educator career choices and professional development, school finance and governance, and early childhood systems. She was the founding director of the Center for Education Policy at Stanford and co-director of Policy Analysis for California Education, leading research for projects like Getting Down to Facts for California schools. Loeb has been recognized for her contributions by election to the American Academy of Arts and Sciences, and she is an affiliate at NBER and JPAL, as well as a member of the National Academy of Education.
Research topics
- Political Science
- Psychology
- Demography
- Marketing
- Public relations
- Business
- Pedagogy
- Sociology
- Developmental psychology
- Social psychology
- Economic growth
- Economics
- Medicine
Selected publications
OSF Preprints (OSF Preprints) · 2026-01-02
preprintOpen access1st authorCorrespondingA stimulating and supportive home learning environment helps children to be cognitively and emotionally ready to learn by age 5. Despite the increased availability of parenting information, the attainment gap between rich and poor continues to widen in many developed nations. Tips by Text is a 12-month text-message programme developed in the US, and designed to integrate developmental activities into everyday tasks that parents and children do together. The messages aim to enhance language, literacy, numeracy, and socioemotional skills in 4-year-olds. The programme was adapted and tested in a large-scale randomised controlled trial involving 109 schools in England from 2019 to 2021 (n=3,600). Post-intervention data collection was impacted by the Covid-19 pandemic, resulting in approximately 70% random attrition on the primary outcome measure and a final analytical sample of n=753. This sample is comparable to the US-based sample in which the efficacy of Tips by Text was originally assessed, and so we proceed with analysis. In this study, we conduct secondary data analysis to examine the effectiveness of the programme on the sample that could be obtained. We explore whether students facing various challenges, including economic and neighbourhood disadvantage, English as an additional language, special educational needs, and multiple simultaneous challenges, were differentially impacted by the programme.
The Role of Human Support in Student Engagement with AI Tutoring Platforms
Brown Digital Repository · 2026-04-10
articleOpen accessSenior author2026-01-02
articleOpen accessA stimulating and supportive home learning environment helps children to be cognitively and emotionally ready to learn by age 5. Despite the increased availability of parenting information, the attainment gap between rich and poor continues to widen in many developed nations. Tips by Text is a 12-month text-message programme developed in the US, and designed to integrate developmental activities into everyday tasks that parents and children do together. The messages aim to enhance language, literacy, numeracy, and socioemotional skills in 4-year-olds. The programme was adapted and tested in a large-scale randomised controlled trial involving 109 schools in England from 2019 to 2021 (n=3,600). Post-intervention data collection was impacted by the Covid-19 pandemic, resulting in approximately 70% random attrition on the primary outcome measure and a final analytical sample of n=753. This sample is comparable to the US-based sample in which the efficacy of Tips by Text was originally assessed, and so we proceed with analysis. In this study, we conduct secondary data analysis to examine the effectiveness of the programme on the sample that could be obtained. We explore whether students facing various challenges, including economic and neighbourhood disadvantage, English as an additional language, special educational needs, and multiple simultaneous challenges, were differentially impacted by the programme.
Open MIND · 2026-02-19
articleOpen accessSenior authorEducation Sciences · 2026-01-16
articleOpen accessSenior authorTutoring has played a significant role in pandemic-related learning recovery, supporting student learning and engagement. This paper follows up on a recent randomized controlled trial (RCT) estimating that one-on-one virtual early literacy tutoring was nearly twice as effective as two-on-one tutoring for improving student learning. To better understand this gap, we analyze transcripts from 16,629 tutoring sessions from this RCT—which included over 3.7 million tutor utterances—using natural language processing and machine learning techniques. We explore how tutors allocate attention across content instruction, relationship building, and classroom management between one-on-one and two-on-one formats. While tutors dedicate similar time to content instruction and relationship building across both formats, students receiving one-on-one tutoring receive more attention and personalized support. To improve the effectiveness of two-on-one tutoring, it may be beneficial to equip tutors with strategies that engage multiple students simultaneously, thereby reducing downtime and minimizing the potential for disengagement.
The Impact of Tutor Gender Match on Girls’ STEM Interest, Engagement, and Performance
American Educational Research Journal · 2026-03-04
articleOpen accessSenior authorGender disparities in STEM persist despite girls performing as well as boys academically, suggesting girls may benefit from role models who shape their perceptions of STEM. We examine whether female math tutors influence girls’ STEM interest, attendance, and performance. We randomly assigned 422 ninth-grade students taking Algebra 1 to a same-gender or opposite-gender tutor. Girls assigned to female tutors reported higher STEM interest (.73 SD) and were more likely to pass the course with a C– or better (3.9 percentage points) than those with male tutors. We found no impact on attendance. Effects were stronger for students working with tutors in-person rather than virtually. We provide the first experimental evidence that female tutors can boost girls’ STEM self-concept and academic outcomes.
Business Not as Usual: Understanding Factors for Organizational Change after a Crisis
Teachers College Record The Voice of Scholarship in Education · 2025-07-01 · 1 citations
articleDrawing on the crisis management cycle (CMC) framework, this study examines the organizational adjustments made by school systems in response to the COVID-19 pandemic, with a focus on the implementation of high-impact tutoring (HIT) to address the pandemic’s academic impacts. Analyzing 112 interviews across 10 local education agencies, we identify three postcrisis organizational change pathways: stagnation without learning, change through learning, and stagnation after initial learning. Critical to navigating these pathways are stakeholder alignment, external partnerships, access to expertise, effective resource allocation, and organizational readiness for adaptation. Our research highlights how these factors collectively determine an educational institution’s resilience and capacity for long-term structural adjustment following a crisis. By elucidating the mechanisms that enable or impede organizational learning and change, this paper contributes insights into overcoming entrenched practices, thereby enhancing schools’ preparedness and response capabilities for future crises and current policy challenges.
AEA Randomized Controlled Trials · 2025-05-22
datasetSenior authorResearch Square · 2025-02-06
preprintOpen accessAEA Randomized Controlled Trials · 2025-05-22
datasetSenior author
Frequent coauthors
- 125 shared
Kalena E. Cortes
- 116 shared
James Wyckoff
University of Virginia
- 94 shared
Hamilton Lankford
- 88 shared
Donald Boyd
- 54 shared
Hans Fricke
Amazon (Germany)
- 50 shared
Hans Fricke
University of Michigan–Ann Arbor
- 39 shared
Demetra Kalogrides
Stanford University
- 36 shared
Pamela Grossman
Labs
Susanna Loeb LabPI
Education
Ph.D., Education Policy
Stanford University
M.A., Education and International and Public Affairs
Brown University
B.A.
Harvard University
Awards & honors
- Elected to the American Academy of Arts and Sciences (2020)
- Member of the National Academy of Education
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