We are no longer accepting applications
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 and the interview process will begin immediately. Once decisions have been made, applicants will be notified and work will begin immediately.
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.
Financial Support: RAs can get up to $1500 for an academic quarter and/or $7000 for an immersive summer project depending on the guidelines set by your particular faculty and the number of hours you work. You will be paid via stipend processed by Financial Aid. For research done during the academic year (fall, winter spring), your stipend will be processed at the end of your research quarter, much the same way that grades are processed at the end of the quarter for students who are doing research for credit. For summer research, stipends are processed in May. The administrative process takes about 2-3 weeks.
Application Process: Students should provide 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.
Project 1: Field and Lab Data Collection Using Novel Tablet Computer Assessments of Social and Emotional Learning
Faculty Mentor: Jelena Obradović
Project Description: Social and emotional learning refers to non-academic skills that are crucial for children’s success in school. Dr. Jelena Obradović (https://web.stanford.edu/group/sparklab/) is using a novel tablet computer app to measure social and emotional learning in elementary school students (grades K-5). These games test students ability to delay gratification, think flexibly, remember information, control behavior, tolerate frustration, persevere, and challenge themselves. Measuring these skills is crucial because they are associated with physical and mental health, educational attainment, and career success. But existing table-top assessment tools are time consuming, require extensive training, and are difficult to administer consistently. The innovative tablet-based assessment provides an accessible, standardized, and low cost alternative for educators and researchers, and can be used in a group setting to assess many children simultaneously.
Dr. Obradović is seeking a research assistant to assist with data collection using this app in both field and lab settings. We are currently collecting data in partnership with the Boys and Girls Clubs of the Peninsula and our research team is using this app to collect data at after school programs, museums, libraries, and other field sites. This data collection will be supplemented with electrocardiogram (EKG) data to understand how children’s autonomic nervous system activity supports their social and emotional learning skills.
The research assistant will gain practical experience in field and lab based research, and will learn about psychophysiology and social and emotional learning skills. The ideal candidate will be friendly, outgoing, and enjoy working with parents and children. Work hours will include weekends. Having a valid driver’s license and access to a car is desirable, but not required.
Project 2: Patterns, Trends, and Causes of Academic Achievement Gaps
Faculty Mentor: sean reardon
Project Description: This project uses roughly 300 million test score records (from every student in grades 3-8 in the US from 2009-2015) to examine patterns of academic achievement and achievement gaps across the US. We will be adding more years of data to the project, analyzing trends, patterns, and causes of achievement gaps, and making maps and other web-based interactive data visualizations. I am seeking RAs with interests in educational and social inequality and skills (and interest in developing skills) in data scraping, data management (stata/excel), descriptive statistical analysis, data visualization, and/or GIS mapping software. Depending on their interests and skills, RAs may be involved in the study of educational inequality through helping with data assembly, data analysis, and/or data visualization.
Project 3: Early Warning Systems in Action in San Francisco Unified School District (SFUSD)
Faculty Mentor: Thomas Dee
Project Description: SFUSD has two systems for early identification of educationally vulnerable students: the Transition Program (TP) which identifies students based on input from school social workers (i.e., “soft” criteria) and the Early Warning Indicator (EWI) which identifies students based on school measures including attendance and GPA (i.e., “hard” criteria).
The John Gardner Center at the Graduate School of Education, under the guidance of Prof. Tom Dee, has been working in collaboration with SFUSD, to better understand the characteristics of students who are identified by each of the systems, the services the students receive, and their subsequent academic, engagement, and behavioral outcomes. The research employs both qualitative and quantitative methods. Preliminary findings will be presented at the Stanford-SFUSD Annual Meeting on April 19.
The research project is looking for a Research Assistant (RA) during the Winter quarter. The RA would help with review and summary of the literature, and the collection, organization, and preliminary analysis of interview data. In addition, the RA would participate in bi-monthly internal project meetings. The ideal candidate is able to type quickly, familiar with best practices related to conducting and documenting interviews, able to identify and clearly summarize relevant literature, is familiar with SFUSD, and has a valid driver’s license and access to a car (or lives in SF).
Project 4: Academic Freedom: The Choices of Student Athletes in Americas Most Profitable Conferences
Faculty Mentor: Michelle Reininger (with Solomon Hughes)
Project Description: It is often the case that students who compete as amateurs on varsity athletic teams at post-secondary institutions, are tasked with balancing the remarkably engrossing experience of being full-time students while competing as highly competitive athletes on teams and within conferences whose financial revenues rival many of the professional sports organizations in America. While data that shows how student athletes fare in comparison to their peers (who are not participating in varsity sports) in retention and graduation rates, scarce research has examined the more intricate academic decisions that student athletes make about their academic pursuits. This project will examine the academic major choices of student athletes competing in the most profitable and visible college athletic conferences. We are seeking RAs with interests in college athletics policy and educational and inequality and skills in data scraping, data management (stata/excel), descriptive statistical analysis, data visualization, and/or GIS mapping software.
Project 5: Data Cleaning and Analysis for Quantitative Research in Early Childhood Education
Faculty Mentor: Jelena Obradović
Project Description: In this project, we will examine how different aspects of preschool (Pre-K) classroom experience (e.g., emotional, instructional, organizational) uniquely relate to the growth of children’s academic, social, and emotional learning skills. We will investigate whether these associations vary by children’s ethnic background, language proficiency, or initial skill levels. We are answering research questions such as, which students are likely to benefit from a Pre-K program the most?
Dr. Jelena Obradović (https://web.stanford.edu/group/sparklab/) is seeking a research assistant who will work with the current data manager to assist with data cleaning, linking, and analysis. Her team is creating longitudinal panels of data that include children’s enrollment and attendance in early childhood education programs, measures of classroom and teacher quality, and measures of social and emotional learning skills across several cohorts of children. The measures need to be linked between teachers, classrooms, and students over time in order to answer the research questions.
The research assistant will gain practical experience in quantitative research and will learn about standardized early-childhood SEL assessments and early childhood development. The ideal candidate will be detail-oriented and be available up to 8 hours per week. Knowledge of R is preferred but not required. Work hours will be flexible and will be negotiated with other analysts who are working off of the same secure data server.
Project 6: Biological Bases of Self-Regulated Learning
Faculty Mentor: Jelena Obradović
Project Description: Dr. Jelena Obradović (https://web.stanford.edu/group/sparklab/) is examining (1) how young children’s stress physiology is affected by the everyday challenges that occur in educational settings; and (2) whether children’s acute physiological responses are malleable in ways that can promote successful learning outcomes. The goal is to identify ways to help young children achieve and maintain well-regulated physiology and behavior despite acute learning-related challenges. She is seeking a research assistant interested in the interplay of biology, behavior, and environment to assist with basic research that will lay the groundwork for experimental intervention studies that will improve children's emotional and physiological self-regulation skills. The research assistant will have the opportunity to work on multiple studies focused on the biological bases of self-regulated learning.
The research assistant will learn about the significance autonomic nervous system functioning. S/he will assist in collecting behavioral and electrocardiogram (EKG) data in field and laboratory settings and will learn how to process and clean EKG data. The research assistant will also test different devices for collecting EKG data.
The ideal candidate will have great organization skills and attention to detail, and will be friendly, outgoing, and enjoy working with parents and children. Work hours will include
Project 7: Improving College Access for Low-Income and First Generation High School Students
Faculty Mentor: Eric Bettinger
Project Description: This ongoing project started in 2012 and will continue through 2019. This project includes two college access experimental studies in Texas with the goal of improving college enrollment among low-income and first-generation high school students. One experiment randomly assigned students to receive extra college counseling from a recent college graduate working full time in the high school. In the other experiment, we randomly assigned high schools to receive a full time recent college graduate to work as a college counselor across the school. Both experiments are ongoing, but we are currently gathering survey and administrative outcome data.
The RAs will be integrated into both of the ongoing research projects. The work will revolve around quantitative data collection and analysis. Data analysis will incorporate regression and propensity score matching techniques. Assistance with survey design will also be useful. We also are considering several additional experimental studies, and we expect the RA to contribute to future research design. The RA would participate in weekly meetings and phone calls with the intervention team. The student will meet with Professor Bettinger on a weekly basis both on these phone calls and in person. The undergraduate student and professor would jointly work on developing their work tasks for the week. Graduate students and Professor Bettinger would work with the undergraduate to make sure that they have the skills necessary to succeed on the task. The RA should be able to attend weekly meetings with one of the professors or graduate students leading the project, and should be willing to travel once to Texas for data collection.
Project 8: Documenting Educational Appropriations Made Through the US Department of the Interior
Faculty Mentor: Thomas S. Dee
Project Description: Federal education funding is primarily distributed through appropriations to the US Department of Education. However, some federal education funding is appropriated through the US Department of the Interior (DOI). In particular, the US DOI’s annual budget includes funding for the Bureau of Indian Affairs, which provides educational support to Bureau of Indian Education (BIE) schools and public schools serving large numbers of American Indian/Alaska Native students. This project documents funding levels over time for federal educational appropriations distributed through the US DOI. It will also identify the timing when BIE schools transitioned in and out of grant/contract status. Such documentation will enable improved analysis of historical funding disparities for both K-12 and higher education.
The research project is looking for a Research Assistant (RA) during the Spring and Summer of 2019. The RA will record when BIE schools transitioned in and out of grant/contract status and use historical documents to collect, organize and clean federal funding data. In addition, the RA will participate in weekly internal project meetings. The ideal candidate is someone comfortable with Microsoft Excel, interested in issues of educational equity, and familiar with BIE schools and/or Johnson O’Malley funding.
The project focuses on helping students attend college, and undergraduates are particularly suited to give advice on the process of admissions and attendance. As such, the undergraduate will be a full participant during our team meetings.