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K-12 Education
Panel or grouped data are often used to allow for unobserved individual heterogeneity in econometric models via fixed effects. In this paper, we discuss identification of a panel data model in which the unobserved heterogeneity both enters additively and interacts with treatment variables. We present identification and estimation methods for parameters of interest in this model under both strict and weak exogeneity assumptions. The key identification insight is that other periods' treatment variables are instruments for the unobserved fixed effects. We apply our proposed estimator to matched student-teacher data used to estimate value-added models of teacher quality. We show that the common assumption that the return to unobserved teacher quality is the same for all students is rejected by the data. We also present evidence that No Child Left Behind-era school accountability increased the effectiveness of teacher quality for lower performing students.
Hardware requirements are a barrier to widespread adoption of digital learning software among low-income populations. We investigate the demand among smallholder-farming households for a simple, adaptive math learning tool that can be accessed by widely available ``brick'' phones, and its effect on educational outcomes. Over a quarter of invited households used the tool, with greater demand among households lacking electricity, radios, or televisions. Usage was highest when schools were out of session. Engagement lapsed without regular reminders to use the service. Using random variation in access to the service, we find evidence that the platform increased test scores, school attendance, and grade attainment. Interpretation of these estimates is complicated by potentially endogenous outcome observation.
School closures induced by the COVID-19 pandemic led to concerns about student learning. This paper evaluates the effect of school closures on student learning in Uzbekistan, using a unique dataset that allows assessing change in learning over time. The findings show that test scores in math for grade 5 students improved over time by 0.29 standard deviation despite school closures. The outcomes among students who were assessed in 2019 improved by an average of 0.72 standard deviation over the next two years, slightly lower than the expected growth of 0.80 standard deviation. The paper explores the reasons for no learning loss.
Given the importance of early literacy to long-term student success, by 2021, 41 states and the District of Columbia adopted early literacy policies to improve student literacy by the end of third grade. We use an event-study approach to examine the impact of these policies on high- and low-stakes test scores. Our results suggest that adopting an early literacy policy improves elementary students’ reading achievement on high-stakes assessments, particularly in third grade and in states with comprehensive early literacy policies and third-grade retention requirements. We also find suggestive evidence that early literacy policies reduce socioeconomic and racial high-stakes achievement gaps in reading and have positive spillover effects on math achievement. However, we find little evidence of significant gains in low-stakes test scores except in states with comprehensive policies. Our findings highlight the importance of content and incentives for early literacy policies.
Heightened concerns about the health of the teaching profession highlight the importance of studying the early teacher pipeline. This exploratory, descriptive paper examines preservice teachers' (PST) expressed motivation for pursuing a teaching career and its relationship with PST characteristics and outcomes. Using data from one of the largest teacher education programs in Texas, we use a natural language processing algorithm to categorize into topical groups roughly 2,800 essay responses to the prompt, "Explain why you decided to become a teacher.'' We identify 11 topics that largely reflect altruistic and intrinsic (though not extrinsic) reasons for teaching. The frequency of motivation topics varied substantially by PST gender, race/ethnicity, and certification area. While topics collectively explained little of the variance in PST outcomes, we found preliminary evidence that intrinsic enjoyment of teaching and prior experiences with adversity predicted higher performance during clinical teaching and lower attrition as a full-time K–12 teacher.
Fadeout is a pervasive phenomenon: post-test impacts on cognitive skills commonly decrease in the years following an educational intervention. Less is known, although much is theorized, about social-emotional skill persistence. The current meta-analysis investigated whether educational RCT impacts on social-emotional skills demonstrated greater persistence than impacts on cognitive skills among 87 interventions involving 59,237 participants and 443 outcomes measured at post-test and at least one follow-up. For post-test impacts of the same magnitude, persistence rates were similar (43% of post-test magnitude) across skill types for follow-ups occurring 6 to 12 months after post-test. At 1- to 2-year follow-ups, persistence rates were larger for cognitive skills (37%) than for social-emotional skills. Interestingly, smaller posttest impacts persisted at proportionately higher rates than larger impacts, which may benefit interventions measuring social-emotional outcomes given their smaller post-test impacts. Considered in whole, social-emotional and cognitive skills demonstrated similar patterns of fadeout.
There is growing concern that some nonprofit public service providers may be nonprofit in name but not in fact. We consider this concern in the context of nonprofit charter schools, which sometimes subcontract their daily operations to for-profit management organizations. We use unique data from Ohio to study how nonprofit charter schools’ reliance on for-profit operators affects student achievement and attendance. The results indicate that nonprofit charters that subcontract with for-profit operators tend to be more effective and equitable in promoting student achievement (but not attendance, a less salient outcome) than nearby traditional public schools serving similar students. However, nonprofit charters that subcontract with for-profit operators tend to be less effective (with regard to both achievement and attendance) and less equitable (with regard to attendance) than other nonprofit charters nearby. Further analysis comparing the administration and outcomes of for-profit and nonprofit operators suggests that the profit motive may help explain the inferior performance of nonprofit charters with for-profit operators. Our study offers theoretical insights for literatures on charter schools, contracting, performance monitoring, and sector boundaries, and it has immediate implications for education policy and management.
The COVID-19 pandemic resulted in substantial unfinished learning for U.S. students, but to differing degrees for various subgroups. For example, students of color, from low-income families, or who attended high-poverty schools experienced greater unfinished learning. In this study we examined the degree of unfinished learning for students who went into the pandemic scoring in the top or bottom 10% in the math or reading achievement distributions. Our results show that students who scored at or below the 10th percentile grew less during the pandemic than their similarly-scoring, pre-COVID peers and, as of the end of the 2021 – 2021 school year, had yet to rebound toward pre-COVID levels of growth or achievement. Conversely, students who scored at or above the 90th percentile largely grew at rates closer to their pre-COVID peers. These students were harmed less academically and have recovered more quickly than their peers scoring at or below the 10th percentile.
School mobility, compounding socioeconomic inequities, can undermine academic achievement and behavior, particularly during middle school years. This study investigates the effect of a school-based integrated student support intervention – City Connects – on the achievement and behavior of middle school students who experience school mobility. Using administrative data from a large, urban, public school district in the U.S., we apply student fixed effects and event studies methods to analyze the academic and behavioral performance of students changing schools. The results indicate that students who moved to schools implementing the City Connects intervention performed better academically and behaviorally than other students.
Providing consistent, individualized feedback to teachers is essential for improving instruction but can be prohibitively resource-intensive in most educational contexts. We develop M-Powering Teachers, an automated tool based on natural language processing to give teachers feedback on their uptake of student contributions, a high-leverage dialogic teaching practice that makes students feel heard. We conduct a randomized controlled trial in an online computer science course (n=1,136 instructors), to evaluate the effectiveness of our tool. We find that M-Powering Teachers improves instructors’ uptake of student contributions by 13% and present suggestive evidence that it also improves students’ satisfaction with the course and assignment completion. These results demonstrate the promise of M-Powering Teachers to complement existing efforts in teachers’ professional development.