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Program and policy effects
Enrollment in higher education has risen dramatically in Latin America, especially in Chile. Yet graduation and persistence rates remain low. One way to improve graduation and persistence is to use data and analytics to identify students at risk of dropout, target interventions, and evaluate interventions’ effectiveness at improving student success. We illustrate the potential of this approach using data from eight Chilean universities. Results show that data available at matriculation are only weakly predictive of persistence, while prediction improves dramatically once data on university grades become available. Some predictors of persistence are under policy control. Financial aid predicts higher persistence, and being denied a first-choice major predicts lower persistence. Student success programs are ineffective at some universities; they are more effective at others, but when effective they often fail to target the highest risk students. Universities should use data regularly and systematically to identify high-risk students, target them with interventions, and evaluate those interventions’ effectiveness.
India took a decisive step toward universal basic education by proclaiming a constitutionally-guaranteed Right to Education (RTE) Act in 2009 that called for full access of children aged 6-14 to free schooling. This paper considers the offsetting effects to RTE from induced expansion of private tutoring in the educationally competitive districts of India. We develop a unique database of registrations of new private educational institutions offering tutorial services by local district between 2001-2015. We estimate the causal impact of RTE on private supplemental education by comparing the growth of these private tutorial institutions in districts identified a priori as having very competitive educational markets to those that had less competitive educational markets. We find a strong impact of RTE on the private tutoring market and show that this holds across alternative definitions of highly competitive districts and a variety of robustness checks, sensitivity analyses, and controls. Finally, we provide descriptive evidence that these private tutoring schools do increase the achievement (and competitiveness) of students able to afford them.
This study used college dormitory room and social group assignment data to investigate the peer effect on the probability of college students switching their major fields of study. The results revealed strong evidence of peer effects on students’ decisions to switch majors. In particular, the number of a student’s peers who have the same major significantly reduces the student’s likelihood of switching majors; however, when a same-major peer switches majors, it significantly increases a student’s probability of switching majors. This study also found that peers’ majors affected students’ choice of destination majors. Students in the same peer group are more likely to choose the same destination majors, compared to non-peers. Finally, we found that in general peer effects at the dormitory room level, both in choice and persistence of major, were stronger than were peer effects at the social group level.
Valid and reliable measurements of teaching quality facilitate school-level decision-making and policies pertaining to teachers, but conventional classroom observations are costly, prone to rater bias, and hard to implement at scale. Using nearly 1,000 word-to-word transcriptions of 4th- and 5th-grade English language arts classes, we apply novel text-as-data methods to develop automated, objective measures of teaching to complement classroom observations. This approach is free of rater bias and enables the detection of three instructional factors that are well aligned with commonly used observation protocols: classroom management, interactive instruction, and teacher-centered instruction. The teacher-centered instruction factor is a consistent negative predictor of value-added scores, even after controlling for teachers’ average classroom observation scores. The interactive instruction factor predicts positive value-added scores.
States and districts are increasingly incorporating measures of achievement growth into their school accountability systems, but there is little research on how these changes affect the public’s perceptions of school quality. We conduct a nationally representative online survey experiment to identify the effects of providing participants with information about their local school districts’ average achievement status and/or average achievement growth. In the control group, participants who live in higher status districts tend to grade their local schools more favorably. The provision of status information does not fundamentally alter this relationship. The provision of growth information, however, reshapes Americans’ views about educational performance. Once informed, participants’ evaluations of their local public schools better reflect the variation in district growth.
We provide the first estimated economic impacts of students’ access to an entire sector of public higher education in the U.S. Approximately half of Georgia high school graduates who enroll in college do so in the state’s public four-year sector, which requires minimum SAT scores for admission. Regression discontinuity estimates show enrollment in public four-year institutions boosts students’ household income around age 30 by 20 percent, and has even larger impacts for those from low income high schools. Access to this sector has little clear impact on student loan balances or other measures of financial health. For the marginal student, enrollment in such institutions has large private returns even in the short run and positive returns to state budgets in the long run.
English Learners (ELs) lag behind their peers in postsecondary attainment. As the EL population in the U.S. continues to grow, so does concern over their underrepresentation in higher education. Research shows that Early College High Schools have a significant impact on high school and college outcomes for students from low income and racial/ethnic minority backgrounds, but how similar opportunities might extend to ELs remains unknown. We report findings from the first three years of an intervention that offers Early College opportunities in high schools serving large EL populations. Leveraging an exogenous policy change and rich administrative records, we examine the outcomes of pre- and post-program cohorts of ELs (N=15,090) in treated and untreated high schools. We find a large, significant impact on the number of college credits earned in 12th grade but no effect on immediate college attendance after high school. The probability of attending a four-year college significantly decreased.
While teacher evaluation policies have been central to efforts to enhance teaching quality over the past decade, little is known about how teachers change their instructional practices in response to such policies. To address this question, this paper drew on classroom observation and survey data to examine how early career teachers’ (ECTs’) perceptions of pressure associated with teacher evaluation policies seemed to affect their enactment of ambitious mathematics instruction. As part of our analysis, we also considered the role that mathematical knowledge for teaching (MKT) and school norms regarding teaching mathematics shape the potential influence of teacher evaluation policies on ECTs’ instructional practices. Understanding how the confluence of these factors is associated with teachers’ instruction provides important insights into how to improve teaching quality, which is one of the most important inputs for student learning.
Family and social networks are widely believed to influence important life decisions but identifying their causal effects is notoriously difficult. Using admissions thresholds that directly affect older but not younger siblings’ college options, we present evidence from the United States, Chile, Sweden and Croatia that older siblings’ college and major choices can significantly influence their younger siblings’ college and major choices. On the extensive margin, an older sibling’s enrollment in a better college increases a younger sibling’s probability of enrolling in college at all, especially for families with low predicted probabilities of enrollment. On the intensive margin, an older sibling’s choice of college or major increases the probability that a younger sibling applies to and enrolls in that same college or major. Spillovers in major choice are stronger when older siblings enroll and succeed in more selective and higher-earning majors. The observed spillovers are not well-explained by price, income, proximity or legacy effects, but are most consistent with older siblings transmitting otherwise unavailable information about the college experience and its potential returns. The importance of such personally salient information may partly explain persistent differences in college-going rates by geography, income, and other determinants of social networks.
Researchers commonly interpret effect sizes by applying benchmarks proposed by Cohen over a half century ago. However, effects that are small by Cohen’s standards are large relative to the impacts of most field-based interventions. These benchmarks also fail to consider important differences in study features, program costs, and scalability. In this paper, I present five broad guidelines for interpreting effect sizes that are applicable across the social sciences. I then propose a more structured schema with new empirical benchmarks for interpreting a specific class of studies: causal research on education interventions with standardized achievement outcomes. Together, these tools provide a practical approach for incorporating study features, cost, and scalability into the process of interpreting the policy importance of effect sizes.