CEPA Undergraduate Research Program

The Center for Education Policy Analysis (CEPA) is seeking undergraduate research assistants (RAs) to work directly with CEPA faculty on active research projects supported by The Office of the Vice Provost for Undergraduate Education (VPUE). Applications will be reviewed as received. Once decisions have been made, applicants will be notified by their faculty mentor.

Eligibility: The CEPA URP program is only open to current Stanford University undergraduates. Students must be enrolled in undergraduate studies in the quarter when they apply for the grant and carry an undergraduate status throughout the period of their project. Selection of RAs will be based on the student’s expressed interest in the project and the fit between faculty needs and student skill sets. Experience working with quantitative data using STATA statistical software is preferred but not required.

Application Process: Students should provide the faculty mentor of the project of interest a resume, an unofficial Stanford transcript, and a one-page cover letter describing the applicant’s interest in education policy, previous research experience including any experience with quantitative analyses, and indicate the particular research project/s the student is interested in working on.

Specific Projects

Project 1: The Educational Opportunity Project (EOP)

Faculty Mentor: sean reardon

Project Description: The Educational Opportunity Project (EOP) at Stanford University uses a range of data on educational conditions, contexts, and outcomes to help scholars, policy makers, educators, and the general public learn about the landscape of educational opportunity and academic achievement in the US. The EOP houses two main initiatives:

  1. The Stanford Education Data Archive (SEDA): SEDA is the first 11-year national database of academic performance based on nearly 450 million 3-8th grade math and reading and language arts test scores from the 2008-2019 school years. We hope that researchers, practitioners, and policy makers will utilize SEDA to generate evidence about what policies and practices are most effective at increasing educational opportunity.
  2. EOP NYSED Equity Indicators Project: We are partnering with the New York State Education Department (NYSED) to construct a series of equity indicators using longitudinal teacher, student, and staff level data. These indicators will help us better understand the landscape of educational equity across NY state and inform system-level changes to improve equitable access to educational opportunity.

The EOP RA will be responsible for assisting on current projects that include the Stanford Education Data Archive (SEDA), the EOP NYSED Equity Indicators Project, and/or work on the Segregation Index project, an initiative jointly run by Professor Reardon and Professor Ann Owens at USC. The RA may also have the opportunity to research and prepare a report on their own topic of interest related to the work of the EOP – past topics include educational opportunity in Puerto Rico, student opt-out, and broadband access. Overall, the RA will gain knowledge about the research process, learn and apply/strengthen quantitative skills, and contribute to the production of data analyses, reports, and other public dissemination products. Interest in education, education policy, and social and educational inequality is desirable. Quantitative skills, such as data cleaning, data analysis, and programming in Stata also desired but not required. Strong ability to work independently, comfort taking initiative, and attention to detail is an asset. Example duties for this position include: Conducting online background research on relevant topics and writing literature reviews; collecting, cleaning, and organizing data for preliminary analyses; producing memos and data reports for various projects; collaborating with EOP research staff, partners, and other RAs; outreach (via email, phone, and conference calls)

Project 2: San Francisco Unified School District (SFUSD) Early Education Programs: Links with Academic and Social-Emotional Outcomes Through Grade 5

Faculty Mentor: Jelena Obradović

Quarters: Winter 2023, Spring 2023, Summer 2023

Project Description: Dr. Jelena Obradović (https://sparklab.stanford.edu) is seeking a research assistant who will work with the current data manager to assist with data cleaning, processing, and analysis of SFUSD administrative data. Her team is creating longitudinal panels of data that include children’s enrollment and attendance in early childhood education programs as well as K–5 classrooms, measures of classroom and teacher quality, and measures of social and emotional learning and academic skills across multiple cohorts of children. The research assistant will gain practical experience in quantitative research and will learn about standardized early childhood social-emotional assessments and early childhood development. They will contribute to study documentation and assist with data cleaning and linking data sources. The ideal candidate will have an interest in early childhood education or developmental psychology, great organization and communication skills, and strong attention to detail. Knowledge of R is required. To apply, visit https://gse.qualtrics.com/jfe/form/SV_9LhEKeYsNxY06hw

Project 3: Preschool and Transitional Kindergarten Classroom Supports for Social-Emotional Development

Faculty Mentor: Jelena Obradović

Quarters: Winter 2023, Spring 2023, Summer 2023

Project Description: Dr. Jelena Obradović (https://sparklab.stanford.edu) is seeking a research assistant who will contribute to data management and processing of quantitative and qualitative data for an ongoing longitudinal study of preschool social-emotional development in San Francisco Unified School District (SFUSD). The research assistant will learn about assessments of early childhood executive functions, emotion knowledge, social skills, theory of mind, and empathy. They will create study documentation and code children’s open-ended responses about self-regulation and empathy to identify common themes, and may code qualitative teacher interviews. There may be opportunities to conduct one-on-one classroom assessments of preschool and transitional kindergarten students’ social and emotional skills in San Francisco. The ideal candidate will have an interest in early childhood education or developmental psychology, great organization and communication skills, and strong attention to detail. Knowledge of R is a plus. To apply, visit https://gse.qualtrics.com/jfe/form/SV_9LhEKeYsNxY06hw

Project 4: Lessons from Abroad: Integrated Math in U.S. High Schools.

Faculty Mentor: Tom Dee

Project description: Most high school students in the United States complete a sequence of math courses that cover discrete topics – Algebra I, Geometry, and Algebra II. However, this curricular approach stands apart from both international and K-8 programs of study and has long been critiqued by math education experts. Researchers argue that students build stronger understanding when algebraic, geometric, and statistical topics are integrated into single courses and concepts are annually reinforced. Yet, take-up of an integrated approach (i.e., Mathematics I, Mathematics II, Mathematics III) was rare in the U.S. until the implementation of the Common Core math standards. These guidelines presented recommended pathways for both traditional and integrated sequences, lending formal legitimacy to the integrated model for the first time. A moderate wave of sequence reform across states and district followed, including dozens of California school districts. However, administrators, teachers, and parents have continued to express skepticism about the implementation hurdles (e.g., teacher retraining, parent backlash) and academic consequences (e.g., on college preparation) of adopting a new sequence. This project will provide the first descriptive analysis on the prevalence and characteristics of reform districts and present leading evidence on the impacts of adopting integrated pathways. It will use the University of California’s course articulation resource as well as course enrollment data from the California Department of Education (CDE) to classify districts by sequence type (i.e., traditional, integrated, hybrid) over time. The project will also draw on other publicly available CDE files including data on high school test scores, measures of college readiness, student enrollment and composition, and teacher hiring, to estimate student- and system-level reform effects with a difference-in-differences framework. This project is looking to hire an RA to assist with classifying California school districts by curricular model using the UC articulation resource, district webpages and news resources. If comfortable using Stata, the RA may also process administrative data, conduct descriptive analyses, and verify policy codes using CDE data. If interested, there is also an opportunity to contribute to a literature review on math curriculum design and secondary math education in international contexts. This work can be done remotely.

Project 5: Race and Child Health in the United States

Faculty Mentor: Francis Alvin Pearman

Project Description: Racial disparities in child health have been well-documented in the United States for as long as researchers have had reliable data to assess them. Although prominent explanations for these disparities point to the longstanding association that race has with a variety of predictors of health and well-being, including poverty, segregation, and health care access, a growing number of researchers and medical professionals have become interested in the role played by structural racism—in particular, how racial inequality in health may be linked to prevailing attitudes and behaviors, codified in law, culture, policy, and institutional practice, that disadvantage Black people through unwitting or blatant prejudice, ignorance, or racist stereotyping. Indeed, the persistence of racial disparities in child health reflects broader patterns of social stratification and oppression in the United States. And yet, the extant literature has frequently focused on individual racial prejudices, leaving the role of community and cultural racial biases borne of systemic inequities under-examined. The broad aim of this project is to integrate several national datasets to begin to build a knowledge base about the role that structural racism plays in production of child health disparities by race in the United States. This study is looking for a research assistant who can assist in the cleaning and merging of datasets—essentially data management. Familiarity with or openness to learning statistical software packages, including Stata or R, is a requirement for this position. The RA will have the capacity to work remotely and will participate in monthly meetings with the research team.

Project 6: Race and teacher well-being: Improving teacher retention and student outcomes

Faculty Mentor: Francis Alvin Pearman

Project Description: Racial disparities in student academic achievement and disciplinary outcomes in the United States are persistent and pervasive, and they continue to be a pressing civil rights issue in the San Francisco Unified School District (SFUSD). Toward addressing these disparities, this project focuses on one of most important school-based factors in students’ academic and behavioral outcomes: teachers. What interferes with teachers’ effectiveness? One likely factor is well-being. And yet, our current understanding of teacher well-being is incomplete. First, studies of teacher well-being are based largely on research samples of White teachers. Relatedly, these studies rarely consider the roles of teacher race, student race, or school context in teacher well-being. Finally, exactly how teacher well-being is associated with student academic, socioemotional, and disciplinary outcomes is underexplored. In this project, we aim to examine the relationships between teacher well-being, teacher race, school context, and student academic, socioemotional, and disciplinary outcomes. To do this, we will use teacher surveys from the San Francisco Unified School District (SFUSD) from 2017-2019, as well as SFUSD SEL surveys and achievement and disciplinary data from the corresponding school years. A long-term goal of this project is to help the district to better support and retain their teachers and, by extension, better serve the students of SFUSD. In service of this long-term goal, we will conduct a comprehensive literature review of past interventions and programs to improve teacher well-being, with a particular focus on the extent to which teacher race is considered in the intervention. This literature review will be the primary task for undergraduate research assistants hired for this project. In addition to compiling relevant research articles and reports, research assistants will produce an interpretable summary report of this literature to be shared with the district. This work can be done entirely remotely, if necessary. In combination with our analyses of past teacher well-being in SFUSD, this literature review report will equip us—in collaboration with the district—to design and implement a tailored well-being intervention for SFUSD teachers.