The Annenberg Institute for School Reform at Brown University, in partnership with the SCALE Initiative at Stanford University, offers this national working paper series to provide open access to high-quality papers from multiple disciplines and from multiple universities and research organizations on a wide variety of topics related to education. EdWorkingPapers focuses particularly on research with strong implications for education policy. EdWorkingPapers circulates papers prior to publication for comment and discussion; these papers have not gone through a peer review processes.
NEW EdWorkingPapers
Addressing Threats to Validity in Supervised Machine Learning: A Framework and Best Practices for Education Researchers
Given the rapid adoption of machine learning methods by education researchers, and growing acknowledgement of their inherent risks, there is an urgent need for tailored methodological guidance on how to improve and evaluate the validity of inferences drawn from these methods. Drawing upon an integrative literature review and extending a well-known framework for theorizing validity in the… more →
Who’s Matched Up? Access to Same-Race Instructors in Higher Education
Despite consistent evidence on the benefits of same-race instructor matching in K-12 settings and developing work in higher education, research has yet to conceptualize and document the incidence of same-race matching. That is, even if same-race matching produces positive effects, how likely are racially minoritized students to ever experience an instructor of the same race?
The (Conference) Room Where it Happens: Explaining Disproportional Representation in Gifted and Talented Education
The current study leveraged comprehensive data from a large school district to better understand the degree to which disproportional representation in gifted education can be explained by mean assessment score differences across racial and socioeconomic groups.
A Global Regression Discontinuity Design: Theory and Application to Grade Retention Policies
We use a marginal treatment effect (MTE) representation of a fuzzy regression discontinuity setting to propose a novel estimation approach. The estimator can be thought of as extrapolating a traditional fuzzy regression discontinuity estimate or as an observational study that adjusts for endogenous selection into treatment using information at the discontinuity.
Effects of High-Impact Tutoring on Student Attendance: Evidence from the OSSE HIT Initiative in the District of Columbia
Student absenteeism, which skyrocketed during and after the COVID-19 pandemic, has negative consequences for student engagement and achievement. This study examines the impact of the High-Impact Tutoring (HIT) Initiative, implemented by the Office of the State Superintendent of Education in Washington DC, on reducing absenteeism. The HIT initiative was designed to mitigate learning loss by… more →
How are Institutions Positioned on the Brink of the Enrollment Cliff?: Evidence from Ohio
Since 2018, institutions of higher education have been aware of the "enrollment cliff" which refers to expected declines in future enrollment. This paper attempts to describe how prepared institutions in Ohio are for this future by looking at trends leading up to the anticipated decline. Using IPEDS data from 2012-2022, we analyze trends in enrollment, revenues, debt and staffing across Ohio's… more →