Methods
Integrating Open Science Principles into Quasi-Experimental Social Science Research
Quasi-experimental methods are a cornerstone of applied social science, providing critical answers to causal questions that inform policy and practice. Although open science principles have influenced experimental research norms across the social sciences, these practices are rarely implemented… more →
Examining the Relationship Between Randomization Strategies and Control Group Crossover in Higher Education Interventions
This article examines the risk of crossover contamination in individual-level randomization, a common concern in experimental research, in the context of a large-enrollment college course. While individual-level randomization is more efficient for assessing program effectiveness, it also… more →
Mechanisms of Effect Size Differences Between Researcher Developed and Independently Developed Outcomes: A Meta-Analysis of Item-Level Data
Differences in effect sizes between researcher developed (RD) and independently developed (ID) outcome measures are widely documented but poorly understood in education research. We conduct a meta-analysis using item-level outcome data to test potential mechanisms that explain differences in… more →
Teacher-colleague race congruence and mobility: Do colleague demographics impact teacher retention?
Teacher turnover is especially pronounced among teachers of color who play critically important roles in the success of students of color. A growing literature points to racial isolation as one factor that is associated with Black teacher job satisfaction in particular, which in turn could play… more →
Leveraging Modern Machine Learning to Improve Early Warning Systems and Reduce Chronic Absenteeism in Early Childhood
Chronic absenteeism is a critical issue that has been linked to many adverse student outcomes. The current study focuses on improving a key system already in place in many school districts—early warning systems (EWSs)—in order to decrease chronic absenteeism in students’ earliest schooling years… more →
Using Meta-Analytic Data to Examine Fadeout and Persistence of Intervention Impacts on Constrained and Unconstrained Skills
Recent reviews of the educational intervention literature have noted patterns of intervention impact fadeout on cognitive skills, whereby skill trajectories between children in the intervention and control group converge in the years following the end of the intervention. Some early childhood… more →
The Role of Comprehensive Student Support Interventions during School Turnaround
The persistence of underperformance in schools within large urban districts remains a significant challenge in the U.S. K-12 education system. Education policymakers have enacted legislation aiming at improving these schools through ``turnaround'' initiatives. However, students attending… more →
Same Idea, Shifting Standards: An Experimental Study of Racial-Ethnic Biases in Ambitious Math Teaching
Teacher expectations and judgments about student capabilities are predictive of student achievement, yet such judgments may be influenced by salient dimensions of student identity and invite biases. Moreover, ambitious math teaching may also invite teacher biases due to the emphasis on student-… more →
Does Charter School Autonomy Improve Matching of Teacher Attributes with Student Needs?
We examine the efficiency of traditional school districts versus charter schools in providing students with teachers who meet their demographic and education needs. Using panel data from the state of Michigan, we estimate the relationship between enrollment of Black, Hispanic, special education… more →
Using Gaussian Process Regression in Two-Dimensional Regression Discontinuity Designs
Sometimes a treatment, such as receiving a high school diploma, is assigned to students if their scores on two inputs (e.g., math and English test scores) are above established cutoffs. This forms a multidimensional regression discontinuity design (RDD) to analyze the effect of the educational… more →
Classifying Courses at Scale: a Text as Data Approach to Characterizing Student Course-Taking Trends with Administrative Transcripts
Students’ postsecondary course-taking is of interest to researchers, yet has been difficult to study at large scale because administrative transcript data are rarely standardized across institutions or state systems. This paper uses machine learning and natural language processing to standardize… more →
Applying to Lead: A Mixed-Methods Investigation of Prospective Principals’ Job Application Strategies in Two Urban Districts
Purpose: Urban school districts often face challenges in filling principal vacancies with effective leaders, especially in high-needs schools. Prospective principals’ engagement with the job application process may contribute to these challenges. The goal of this study is to… more →
What Impacts Should We Expect from Tutoring at Scale? Exploring Meta-Analytic Generalizability
U.S. public schools are engaged in an unprecedented effort to expand tutoring in the wake of the pandemic. Broad-based support for scaling tutoring emerged, in part, because of the large effects on student achievement found in prior meta-analyses. We conduct an expanded meta-analysis of 282… more →
A Quantitative Study of Mathematical Language in Upper Elementary Classrooms
This study provides the first large-scale quantitative exploration of mathematical language use in upper elementary U.S. classrooms. Our approach employs natural language processing techniques to describe variation in teachers’ and students’ use of mathematical language in 1,657 fourth and fifth… more →
Scaffolding Middle-School Mathematics Curricula With Large Language Models
Despite well-designed curriculum materials, teachers often face challenges in their implementation due to diverse classroom needs. This paper investigates whether Large Language Models (LLMs) can support middle-school math teachers by helping create high-quality curriculum scaffolds, which we… more →
STEM teacher workforce in high-need schools resilient despite shrinking supply and increasing demand
The teacher workforce in science, technology, engineering, and math (STEM) has been a perpetual weak spot in public schools’ teaching rosters. Prior reports show the pipeline of new STEM teachers into the profession is weak while demand for instruction in STEM fields continues to grow. This… more →
The Promises and Pitfalls of Using Language Models to Measure Instruction Quality in Education
Assessing instruction quality is a fundamental component of any improvement efforts in the education system. However, traditional manual assessments are expensive, subjective, and heavily dependent on observers’ expertise and idiosyncratic factors, preventing teachers from getting timely and… more →
The Effects of In-School Virtual Tutoring on Student Reading Development: Evidence from a Short-Cycle Randomized Controlled Trial
This paper describes a 12-week cluster randomized controlled trial that examined the efficacy of BookNook, a virtual tutoring platform focused on reading. Cohorts of first- through fourth-grade students attending six Rocketship public charter schools in Northern California were randomly assigned… more →
Does One Plus One Always Equal Two? Examining Complementarities in Educational Interventions
Public policies targeting individuals based on need often impose disproportionate burden on communities that lack the resources to implement these policies effectively. In an elementary school setting, I examine whether community-level interventions focusing on similar needs and providing… more →
Disentangling Person-Dependent and Item-Dependent Causal Effects: Applications of Item Response Theory to the Estimation of Treatment Effect Heterogeneity
Analyzing heterogeneous treatment effects (HTE) plays a crucial role in understanding the impacts of educational interventions.