Methods
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.
Leveraging Item Parameter Drift to Assess Transfer Effects in Vocabulary Learning
Longitudinal models of individual growth typically emphasize between-person predictors of change but ignore how growth may vary within persons because each person contributes only one point at each time to the model. In contrast, modeling growth with multi-item assessments allows evaluation of… more →
Estimating Learning When Test Scores Are Missing: The Problem and Two Solutions
Longitudinal studies can produce biased estimates of learning if children miss tests. In an application to summer learning, we illustrate how missing test scores can create an illusion of large summer learning gaps when true gaps are close to zero. We demonstrate two methods that reduce bias by… more →
When Pell Today Doesn’t Mean Pell Tomorrow: Evaluating Aid Programs With Dynamic Eligibility
Generally, need-based financial aid improves students’ academic outcomes. However, the largest source of need-based grant aid in the United States, the Federal Pell Grant Program (Pell), has a mixed evaluation record. We assess the minimum Pell Grant in a regression discontinuity framework,… more →
Disparate Teacher Effects, Comparative Advantage, and Match Quality
Does student-teacher match quality exist? Prior work has documented large disparities in teachers' impacts across student types but has not distinguished between sorting and causal effects as the drivers of these disparities. I propose a disparate value-added model and derive a novel measure of… more →
Multiply by 37 (or Divide by 0.023): A Surprisingly Accurate Rule of Thumb for Converting Effect Sizes from Standard Deviations to Percentile Points
Educational researchers often report effect sizes in standard deviation units (SD), but SD effects are hard to interpret. Effects are easier to interpret in percentile points, but converting SDs to percentile points involves a calculation that is not transparent to educational stakeholders. We… more →