Uneven Recovery Between Urban and Rural Districts

Saayili Budhiraja, Thomas Pearson, Emmanuel Prunty, and Niu Gao
6 min read
school bus on a country road

National test scores show the deleterious effects of the pandemic on student learning. In this blog, we explore the urban-rural divide in learning loss and recovery. Urban districts lost more ground in math, while rural districts lost more in reading. As districts recover, Latino students and economically disadvantaged students in rural areas are further left behind. Those findings point to a divergent path to recovery for students in rural communities and call for renewed focus to support an equitable recovery.

Rural districts are smaller, less racially diverse, but as economically diverse as urban districts.

Half of California’s K-12 students are enrolled in urban or rural districts. Urban districts are bigger, more racially diverse, and enroll higher shares of English learners. For example, while urban districts only make up 15% of the school districts, they are home to 45% of the K-12 students. Rural districts, on the other hand, are much smaller: although they account for 37% of districts, they only enroll 5% of the K-12 population. Roughly half of students in urban and rural districts are economically disadvantaged. Because of the smaller size, rural districts tend to lack the organizational capacity and staffing to implement recovery programs; on the other hand, however, the smaller size, ample outdoor space, and lower population density made it easier for rural schools to stay open during the pandemic.

Rural districts lost more ground in reading.

In 2022, only 33 percent of students in California were proficient in math, down from 40 percent in 2019. The 7 percentage point (pp) drop translates to 210,000 fewer students who are proficient in math. Urban districts experienced a bigger drop in math proficiency while rural districts lost more ground in reading. This echoes a national trend which showed that rural districts fared better in math but not in reading. For example, average reading proficiency decreased by nearly 5 pp in rural areas, compared to 4 pp among urban districts. Economically disadvantaged students in both urban and rural areas had a somewhat smaller decrease in math and reading proficiency, but Latino students in those areas experienced a bigger decrease in math proficiency. The urban-rural divide points to the disparate effects of the pandemic on students in different geographic locations. It further compounds the challenges that both urban and rural areas face such as staffing shortages, which make it difficult to implement learning recovery strategies.

Rural districts are catching up faster than urban.

California districts received over $40 billion in state stimulus funding to combat learning loss. Most of the stimulus funding, such as the Expanded Learning Opportunities Grant, is designed to be flexible and districts are encouraged to blend and braid multiple funding sources. In 2023, statewide math proficiency increased by 1.2 percentage point (i.e. 36,000 more students gained proficiency) but English proficiency remained unchanged. The slow improvement echoes national data which point to a stagnant educational recovery.

The pace of recovery is slower among urban and rural districts. In 2023, 38.4% of students in urban areas were proficient in math, up from 37.7% in 2022. The growth is slightly bigger among rural districts – from 30.3% to 31.2% in 2023. However, average English proficiency continued to decline among urban and rural districts, though the rural drop is somewhat less pronounced.

Figure 1. Rural districts lost more ground, but are catching up

Latino and economically disadvantaged students in rural areas are falling further behind.

District average proficiency rates mask important variation by student characteristics. Economically disadvantaged students and Latino students in rural districts are worse off compared to their counterparts in urban districts. Those students in rural areas experienced smaller gains in math proficiency rates and continue to lose ground in reading. English proficiency continued to drop from 34.3% to 34.1% among economically disadvantaged students in rural schools, and the decline is substantially bigger among Latino students in rural settings (from 36.2% to 35.8%). The uneven recovery renews the calls for targeted supports for economically disadvantaged students and Latino students in rural schools. Our ongoing work examines the differences in learning recovery strategies between urban and rural areas, and we invite you to explore the learning loss and recovery for urban and rural districts in the interactive map below.

Figure 2. Learning Loss and Recovery in Urban and Rural Districts

Four years since the onset of the pandemic, there has been little or slow progress in closing the learning gaps. Congress has allocated nearly $190 billion to help schools recover, however, recent studies point to the challenges in implementing research based recovery strategies, particularly at scale. Our analysis shows a different path to recovery in urban and rural communities. What could explain the urban - rural divide, particularly for students from historically marginalized communities? Which recovery strategies may move the needle to close the learning gaps? Our future work will examine the variation in learning recovery strategies by district geographic location, and seek to identify effectiveness strategies that support an equitable recovery.


The research reported here is supported by the Institute of Education Sciences, U.S. Department of Education, through grant R305X220028 to the Public Policy Institute of California. The opinions expressed are those of the authors and do not represent views of the Institute or the U.S. Department of Education, or the California Department of Education.

About the authors

Saayili Budhiraja is a project assistant at the Public Policy Institute of California, where she is examining the impact of the COVID-19 pandemic on K–12 education. Saayili is an undergraduate student at Vanderbilt University, where she studies economics and applied mathematics.

Thomas Pearson is an information technology specialist at the California Department of Education (CDE), where he provides research data support with an emphasis on geographic information systems for CDE projects and partnerships.  His areas of interest include math and science education, social emotional learning, and student achievement.  He holds a BA in economics, and an MS in geography from the University of Wisconsin-Madison.

Emmanuel Prunty is a research associate at the Public Policy Institute of California, where he has worked on topics such as distance learning, transitional kindergarten, and declining enrollment during the pandemic. Previously, he interned at the Hutchins Center at the Brookings Institution and served as a graduate student instructor at the University of California, Berkeley, where he majored in economics and ethnic studies, and minored in demography.

Niu Gao is a senior fellow at the Public Policy Institute of California, specializing in K–12 education. Her areas of interest include math and science education, digital learning in K–12 schools, and student transition from high school to college. Prior to joining PPIC, she worked as a quantitative policy analyst at Stanford. She holds a PhD in educational policy and an MS in economics from Florida State University.


Carbonari, M.V., Davison, M., DeArmond M. et al (2023). The Challenges of Implementing Academic COVID Recovery Interventions: Evidence From the Road to Recovery Project. https://cepr.harvard.edu/sites/hwpi.harvard.edu/files/cepr/files/the_challenges_of_implementing_academic_covid_recovery.pdf?m=1677190353

Education Recovery Scorecard. (2023). https://educationrecoveryscorecard.org/

Elharake, J.A., Akbar, F., Malik, A.A. et al (2023). Mental Health Impact of COVID-19 among Children and College Students: A Systematic Review. Child Psychiatry Hum Dev 54, 913–925 (2023). https://doi.org/10.1007/s10578-021-01297-1

Lewis, K., and Kuhfeld, M. (2023). Education’s Long COVID: 2022-23 Achievement Data Reveal Stalled Progress Toward Pandemic Recovery. NWEA. https://www.nwea.org/research/publication/educations-long-covid-2022-23-achievement-data-reveal-stalled-progress-toward-pandemic-recovery/

National Center for Education Statistics (2022). NAEP Report Card: 2022 NAEP Mathematics Assessment. https://www.nationsreportcard.gov/highlights/mathematics/2022/