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Dual-enrollment courses are theorized to promote students' preparedness for college in part by bolstering their beneficial beliefs, such as academic self-efficacy, educational expectations, and sense of college belonging. These beliefs may also shape students' experiences and outcomes in dual-enrollment courses, yet few if any studies have examined this possibility. We study a large dual-enrollment program created by a university in the Southwest to examine these patterns. We find that mathematics self-efficacy and educational expectations predict performance in dual-enrollment courses, even when controlling for students' academic preparedness, while factors such as high school belonging, college belonging, and self-efficacy in other academic domains are unrelated to academic performance. However, we also find that students of color and first-generation students tend to have lower self-efficacy and educational expectations before enrolling in dual-enrollment courses, in addition to having lower levels of academic preparation. These findings suggest that students from historically marginalized populations may benefit from social-psychological as well as academic supports in order to receive maximum benefits from early postsecondary opportunities such as dual-enrollment. Our findings have implications for how states and dual-enrollment programs determine eligibility for dual-enrollment as well as how dual-enrollment programs should be designed and delivered in order to promote equity in college preparedness.
This paper reports the results of a large, school-level randomized controlled trial evaluating a set of three informational interventions for young people choosing high schools in 473 middle schools, serving over 115,000 8th graders. The interventions differed in their level of customization to the student and their mode of delivery (paper or online); all treated schools received identical materials to scaffold the decision-making process. Every intervention reduced likelihood of application to and enrollment in schools with graduation rates below the city median (75 percent). An important channel is their effect on reducing nonoptimal first choice application strategies. Providing a simplified, middle-school specific list of relatively high graduation rate schools had the largest impacts, causing students to enroll in high schools with 1.5-percentage point higher graduation rates. Providing the same information online, however, did not alter students’ choices or enrollment. This appears to be due to low utilization. Online interventions with individual customization, including a recommendation tool and search engine, induced students to enroll in high schools with 1-percentage point higher graduation rates, but with more variance in impact. Together, these results show that successful informational interventions must generate engagement with the material, and this is possible through multiple channels.
Despite the prevalence of school tracking, evidence on whether it improves student success is mixed. This paper studies how tracking within high school impacts high-achieving students’ short- and longer-term academic outcomes. Our setting is a large and selective Chinese high school, where first-year students are separated into high-achieving and regular classrooms based on their performance on a standardized exam. Classrooms differ in terms of peer ability, teacher quality, class size, as well as level and pace of instruction. Using newly collected administrative data and a regression discontinuity design, we show that high-achieving classrooms improve math test scores by 23 percent of a standard deviation, with effects persisting throughout the three years of high school. Effects on performance in Chinese and English language subjects are more muted. Importantly, we find that high-achieving classrooms substantially raise enrollment in elite universities, as they increase scores on the national college entrance exam—the sole determinant of university admission in China.
We explore the dynamics of competitive search in the K-12 public education sector. Using data from Boston Public Schools, we document how teacher labor supply varies substantially by position types, schools, and the timing of job postings. We find that early-posted positions are more likely to be filled and end up securing new hires that are better-qualified, more-effective, and more likely to remain at a school. In contrast, the number of applicants to a position is largely unassociated with hire quality, suggesting that schools may struggle to identify and select the best candidates even when there is a large pool of qualified applicants. Our findings point to substantial unrealized potential for improving teacher hiring.
In the competitive U.S. higher education market, institutions differentiate themselves to attract both students and tuition dollars. One understudied example of this differentiation is the increasing trend of "colleges" becoming "universities" by changing their names. Leveraging variation in the timing of such conversions in an event study framework, I show that becoming a university increases enrollments at both the undergraduate and graduate levels, which leads to an increase in degree production and total revenues. I further find that these effects are largest when institutions are the first in their market to convert to a university and can lead to negative spillover effects on non-converting colleges.
We study the long-term effects of a psychological intervention on longitudinal academic outcomes and degree completion of college students. All freshmen at a large public university were randomized to an online growth mindset, belonging, or control group. We tracked students’ academic outcomes including GPA, number of credits attempted and earned, major choices, and degree completion. We found no evidence of longitudinal academic treatment effects in the full sample. However, the mindset treatment improved term GPAs for Latinx students and the probability for Pell-eligible and Latinx students to major in selective majors. We also found no evidence of increased rates of on-time graduation, however, the treatment raised the probability to graduate with selective majors in four years, especially for Latinx students.
School closures induced by COVID-19 placed heightened emphasis on alternative ways to measure student learning besides in-person exams. We leverage the administration of phone-based assessments (PBAs) measuring numeracy and literacy for primary school children in Kenya, along with in-person standardized tests administered to the same students prior to school shutdowns, to assess the validity of PBAs. Compared to repeated in-person assessments, PBAs did not severely misclassify students’ relative performance, but PBA scores did tend to be further from baseline in-person scores than repeated in-person assessments from each other. As such, PBAs performed well at measuring aggregate but not individual learning levels. Administrators can therefore use these tools for aggregate measurement, such as in the context of impact evaluation, but be wary of PBAs for individual-level tracking or high-stakes decisions. Results also reveal the importance of making deliberate efforts to reach a representative sample and selecting items that provide discriminating power.
Despite growing evidence that classroom interventions in science, technology, engineering, and mathematics (STEM) can increase student achievement, there is little evidence regarding how these interventions affect teachers themselves and whether these changes predict student learning. We present results from a meta-analysis of 37 experimental studies of preK-12 STEM professional learning and curricular interventions, seeking to understand how STEM classroom interventions affect teacher knowledge and classroom instruction, and how these impacts relate to intervention impacts on student achievement. Compared with control group teachers, teachers who participated in STEM classroom interventions experienced improvements in content and pedagogical content knowledge and classroom instruction, with a pooled average impact estimate of +0.56 standard deviations. Programs with larger impacts on teacher practice yielded larger effects on student achievement, on average. Findings highlight the positive effects of STEM instructional interventions on teachers, and shed light on potential teacher-level mechanisms via which these programs influence student learning.
Families and governments are the primary sources of investment in children, proving access to basic resources and other developmental opportunities. Recent research identifies significant class gaps in parental investments that contribute to high levels of inequality by family income and education and, potentially, to inequality in children’s development. State-level public investments in children and families have the potential to reduce class inequality in children’s developmental environments by affecting parents’ behavior. Using newly assembled administrative data from 1998-2014, linked to household-level data from the Consumer Expenditure Survey, we examine how public sector investment in income support, health and education is associated with the private expenditures of low and high-SES parents on developmental items for children. Are class gaps in parental investments in children narrower in contexts of higher public investment for children and families? We find that more generous public spending for children and families is associated with significantly narrower class gaps in private parental investments. Moreover, we find that equalization is driven by bottom up increases in low-SES household spending for the progressive investments of income support and health, and by top down decreases in high-SES household spending for the universal investment of public education.
Recent expansions of child tax, food assistance and health insurance programs have made American families’ need for a robust social safety net highly evident, while researchers and policymakers continue to debate the best way to support families via the welfare state. How much do children – and which children – benefit from social spending? Using the State-by-State Spending on Kids Dataset, linked to National Vital Statistics System birth data from 1998-2017, we examine how state-level child spending affects infant health across maternal education groups. We find that social spending has benefits for both low birth weight and preterm birth rates, especially among babies born to mothers with less than a high school education. The stronger benefits of social spending among lower-educated families lead to meaningful declines in educational gaps in infant health as social spending increases. Finally, mediation analyses suggest that social spending benefits infant health through mothers’ increased access to prenatal services, as well as improvements in health behaviors. Our findings are consistent with the idea that a strong local welfare state benefits child health and increases equality of opportunity, and that spending on non-health programs is equally beneficial for child health as investments in health programs.