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Program and policy effects
While multiple studies have examined the impact of school turnaround, less is known about reforms under the Every Student Succeeds Act (ESSA). To advance this literature, we examine North Carolina’s Restart (NCR) model. NCR aligns with ESSA by giving school leaders increased flexibility. Also, NCR differs from previous turnaround models by repackaging a traditionally sanction-based approach to instead motivate school leaders with increased autonomy. Using comparative interrupted time series models, we find positive NCR effects in math, but not in English Language Arts or on non-test-based student outcomes. Also, nearly a quarter of the positive NCR effect can be explained by decreased teacher and principal turnover. These results provide evidence to support current shifts toward reform models featuring local autonomy.
While recent studies have demonstrated the potential of automated feedback to enhance teacher instruction in virtual settings, its efficacy in traditional classrooms remains unexplored. In collaboration with TeachFX, we conducted a pre-registered randomized controlled trial involving 523 Utah mathematics and science teachers to assess the impact of automated feedback in K-12 classrooms. This feedback targeted “focusing questions” – questions that probe students’ thinking by pressing for explanations and reflection. Our findings indicate that automated feedback increased teachers’ use of focusing questions by 20%. However, there was no discernible effect on other teaching practices. Qualitative interviews revealed mixed engagement with the automated feedback: some teachers noticed and appreciated the reflective insights from the feedback, while others had no knowledge of it. Teachers also expressed skepticism about the accuracy of feedback, concerns about data security, and/or noted that time constraints prevented their engagement with the feedback. Our findings highlight avenues for future work, including integrating this feedback into existing professional development activities to maximize its effect.
Practice-based teacher education has increasingly been adopted as an alternative to more traditional, conceptually-focused pedagogies, yet the field lacks causal evidence regarding the relative efficacy of these approaches. To address this issue, we randomly assigned 185 college students to one of three experimental conditions reflective of common conceptually-focused and practice-based teacher preparation pedagogies. We find significant and large positive effects of practice-based pedagogies on participants’ skills in eliciting and responding to student thinking as demonstrated through a written assessment and a short teaching episode. Our findings contribute to a developing evidence base that can assist policymakers and teacher educators in designing effective teacher preparation at scale.
This paper studies how school spending impacts student achievement by exploiting the US interstate branching deregulation as state tax revenue shocks. Leveraging school finance data from universal school districts, our difference-in-differences estimation reveals that deregulation leads to an increase in per-pupil total revenue and expenditure. The rise in revenue is primarily attributed to higher state revenues, while the expenditure increase is more prominent in low-income school districts. Using restricted-use student assessments from the Nation’s Report Card, we find that deregulation results in improved student achievement, with no distributional effects evident across students’ ability, race, or free lunch status. We introduce an instrumental variables approach that accounts for dynamic treatment effects and estimate that a one-thousand-dollar increase in per-pupil spending leads to a 0.035 standard deviation improvement in student achievement.
Noncognitive constructs such as self-e cacy, social awareness, and academic engagement are widely acknowledged as critical components of human capital, but systematic data collection on such skills in school systems is complicated by conceptual ambiguities, measurement challenges and resource constraints. This study addresses this issue by comparing the predictive validity of two most widely used metrics on noncogntive outcomes|observable academic behaviors (e.g., absenteeism, suspensions) and student self-reported social and emotional learning (SEL) skills|for the likelihood of high school graduation and postsecondary attainment. Our ndings suggest that conditional on student demographics and achievement, academic behaviors are several-fold more predictive than SEL skills for all long-run outcomes, and adding SEL skills to a model with academic behaviors improves the model's predictive power minimally. In addition, academic behaviors are particularly strong predictors for low-achieving students' long-run outcomes. Part-day absenteeism (as a result of class skipping) is the largest driver behind the strong predictive power of academic behaviors. Developing more nuanced behavioral measures in existing administrative data systems might be a fruitful strategy for schools whose intended goal centers on predicting students' educational attainment.
Career and Technical Education (CTE) has long played a substantial, though controversial, role within America’s public schools. While supporters argue that CTE may increase student engagement and prepare students for success in the workforce, detractors caution that CTE may inhibit students’ access to the rigorous academic coursework needed for college and high-status careers. As students’ time in high school is a relatively fixed resource, this paper seeks to better understand the extent to which CTE is associated with trade-offs within students’ high school curricula. Using a robust statewide longitudinal data system, this study explores the extent to which CTE may limit course taking in a wide range of subjects (including core academic subjects, electives, and Advanced Placement courses). Special attention is paid to how curricular trade-offs may occur differently among different student populations, keeping in mind the legacy of tracking as a long-employed mechanism for reducing opportunity. On average, results indicate that CTE courses do crowd out students’ enrollment in non-CTE elective areas, but that CTE does not lead to large declines in college preparatory coursetaking, though there are nuances for certain student populations. Overall, these findings counter longstanding narratives that CTE participation limits student access to college preparatory coursework.
Decentralized matching markets experience high rates of instability due to information frictions. This paper explores the role of these frictions in one of the most unstable markets in the United States, the labor market for first-year school teachers. We develop and estimate a dynamic model of labor mobility that considers non-pecuniary information frictions directly. We find that teachers overestimate the value of hidden amenities and their own preferences for teaching. Improving access to information improves stability by 12% and reduces between-school switching by 18%, but reduces teacher labor supply by over 5%. Compared to each tested alternative, including targeted wage premiums at hard-to-staff schools, bonuses that incentivize retention, and lowered tenure requirements, information revelation improves match quality most.
School districts historically approached conflict-resolution from a zero-sum perspective: suspend students seen as disruptive and potentially harm them, or avoid suspensions and harm their classmates. Restorative practices (RP) -- focused on reparation and shared ownership of disciplinary justice -- are designed to avoid this trade-off by addressing undesirable behavior without imparting harm. This study examines Chicago Public Schools' adoption of RP. We identify decreased suspensions, improved school climate, and find no evidence of increased classroom disruption. We estimate a 19% decrease in arrests, including for violent offenses, with reduced arrests outside of school, providing evidence that RP substantively changed behavior.
News media plays a crucial role in the student loan policy ecosystem by influencing how policymakers and the public understand the “problem” of student loans. Prior research emphasizes the causal impact of the media on the social construction of policy issues and the lack of knowledge about the authors of news articles. Theory also suggests that it is more difficult for new information to reach people in the core of a social network given their insular relationships. Therefore, we used social network analysis to investigate the college backgrounds for authors of student loan articles published in eight prominent newspapers between 2006 and 2021. We found evidence of a stark status hierarchy among the colleges attended (e.g., over half of the authors attended an Ivy Plus or Public Flagship institution). Our findings also identified a negative relationship between that hierarchy and an innovative practice, the use of racialized language in student loan news articles. We discuss how this status hierarchy might explain current patterns of racialized language in student loan policy and the implications of this relationship for the intersection of status and novel practices.
Despite documented benefits to college completion, more than a third of students who initially enroll in college do not ultimately earn a credential. Completing college requires students to navigate both institutional administrative tasks (e.g., registering for classes) and academic tasks within courses (e.g., completing homework). In postsecondary education, several promising interventions have shown that text-based outreach and communication can be a low-cost, easy to implement, and effective strategy for supporting administrative task navigation. In this paper, we report on two randomized controlled trials testing the effect of a text-based chatbot with artificial intelligence (AI) capability on students' academic task navigation in introductory courses (political science and economics). We find the academic chatbot significantly shifted students’ final grades, increasing the likelihood students received a course grade of B or higher by 5-6 percentage points and reduced the likelihood students dropped the course.