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Program and policy effects
Interactive, text message-based advising programs have become an increasingly common strategy to support college access and success for underrepresented student populations. Despite the proliferation of these programs, we know relatively little about how students engage in these text-based advising opportunities and whether that relates to stronger student outcomes – factors that could help explain why we’ve seen relatively mixed evidence about their efficacy to date. In this paper, we use data from a large-scale, two-way text advising experiment focused on improving college completion to explore variation in student engagement using nuanced interaction metrics and automated text analysis techniques (i.e., natural language processing). We then explore whether student engagement patterns are associated with key outcomes including persistence, GPA, credit accumulation, and degree completion. Our results reveal substantial variation in engagement measures across students, indicating the importance of analyzing engagement as a multi-dimensional construct. We moreover find that many of these nuanced engagement measures have strong correlations with student outcomes, even after controlling for student baseline characteristics and academic performance. Especially as virtual advising interventions proliferate across higher education institutions, we show the value of applying a more codified, comprehensive lens for examining student engagement in these programs and chart a path to potentially improving the efficacy of these programs in the future.
A substantial body of experimental evidence demonstrates that in-person tutoring programs can have large impacts on K-12 student achievement. However, such programs typically are costly and constrained by a limited local supply of tutors. In partnership with CovEducation (CovEd), we conduct a pilot program that has potential to ease both of these concerns. We conduct an experiment where volunteer tutors from all over the country meet 1-on-1 with middle school students online during the school day. We find that the program produces consistently positive (0.07σ for math and 0.04σ for reading) but statistically insignificant effects on student achievement. While these estimates are notably smaller than those found in many higher-dosage in-person tutoring programs, they are from a significantly lower-cost program that was delivered within the challenging context of the COVID-19 pandemic. We provide evidence that is consistent with a dosage model of tutoring where additional hours result in larger effects.
Early research on the returns to higher education treated the postsecondary system as a monolith. In reality, postsecondary education in the United States and around the world is highly differentiated, with a variety of options that differ by credential (associates degree, bachelor’s degree, diploma, certificate, graduate degree), the control of the institution (public, private not-for-profit, private for-profit), the quality/resources of the institution, field of study, and exposure to remedial education. In this Chapter, we review the literature on the returns to these different types of higher education investments, which has received increasing attention in recent decades. We first provide an overview of the structure of higher education in the U.S. and around the world, followed by a model that helps clarify and articulate the assumptions employed by different estimators used in the literature. We then discuss the research on the return to institution type, focusing on the return to two-year, four-year, and for-profit institutions as well as the return to college quality within and across these institution types. We also present the research on the return to different educational programs, including vocational credentials, remedial education, field of study, and graduate school. The wide variation in the returns to different postsecondary investments that we document leads to the question of how students from different backgrounds sort into these different institutions and programs. We discuss the emerging research showing that lower-SES students, especially in the U.S., are more likely to sort into colleges and programs with lower returns as well as results from recent U.S.-based interventions and policies designed to support success among students from disadvantaged backgrounds. The Chapter concludes with some broad directions for future research.
New York City’s Pre-K for All (PKA) is the Nation’s largest universal early childhood initiative, currently serving some 70,000 four-year-olds. Stemming from the program’s choice architecture as well as the City’s stark residential segregation, PKA programs are extremely segregated by child race/ethnicity. Our current study explores the complex forces that influence this segregation, including the interplay between family choices, seat availability, site-level enrollment priorities, and the PKA algorithm that weighs these and other considerations. We find that a majority of PKA segregation lies within rather than between local communities, suggesting that reducing segregation would not necessarily require families to choose programs far from home. On a more troubling note, areas with increased options and greater racial/ethnic diversity also exhibit the most extreme segregation.
Over the last two decades, twenty-two states have moved away from traditional defined benefit (DB) pension systems and toward pension plan structures like the defined contribution (DC) plans now prevalent in the private sector. Others are considering such a reform as it is seen as a means of limiting future pension funding risk. It is important to understand the implications of such reforms for end-of-career exit patterns and workforce composition. Empirical evidence on the relationship between pension plan structure and retirement timing is currently limited, primarily because, most state pension reforms are so new that few employees enrolled in those alternative plans have reached retirement age. An exception, and the subject of our analysis, is the teacher retirement system in Washington State, which introduced a hybrid DB-DC plan in 1996 and allowed employees in its traditional DB plan to transfer into the new plan. Our analysis focuses on a years-of-service threshold, the crossing of which grants employees early retirement eligibility and, in many cases, a large upward shift in retirement wealth. The financial implications of crossing this threshold are far greater under the state’s traditional DB plan than under the hybrid plan. We find that employees are responsive to crossing the years-of-service threshold, but we fail to find significant evidence that the propensity to exit the workforce varies according to plan enrollment.
This study assesses the effects of two text messaging programs for parents that aim to support the development of math skills in prekindergarten students. One program focuses purely on math, while the other takes an identical approach but focuses on a combination of math, literacy, and social-emotional skills. We find no evidence that the math-only program benefits children’s math development. However, the combination program shows greater promise, particularly for girls. Quantile regressions indicate that the effects are concentrated in the lower half of the outcome distribution. We discuss and provide evidence for various hypotheses that could explain these differences.
Highlights:
- We test the effects of two text messaging curricula that leverage behavioral economics principles to help parents support the math development of prekindergarteners in the home.
- We find that a program that cycles through literacy, mathematics, and social-emotional skills increases math achievement for girls, while a program focusing solely on mathematics has no effects.
- Benefits for girls are concentrated on those with weaker performance on mathematics assessments.
- We posit potential mechanisms based on the literature.
Many preschool agencies nationwide continue to experience closures and/or conversions to virtual or hybrid instruction due to the ongoing COVID-19 pandemic. Despite the importance of understanding young children’s learning and development during the COVID emergency, limited knowledge exists on adaptable practices of assessing young children during the pandemic. We detail practices used to assess learning in 336 Head Start children across four states during three different time periods in the 2020-21 school year, using adaptation of traditionally in-person assessments of early numeracy, early literacy, and executive functioning. In doing so, we distill early lessons for the field from the application of a novel, virtual assessment method with the early childhood population. The paper describes adaptations of assessment administration for virtual implementation and incorporation of feedback into continued virtual delivery of assessments. Applications and limitations in broader contexts are discussed.
Black and Latinx students are under-represented in Advanced Placement (AP) and Dual Enrollment (DE), and implicit bias of educators has been discussed as one potential contributing factor. In this study, I test whether implicit and explicit racial bias are related to AP and DE participation and racial/ethnic gaps in participation, controlling for various observable contextual factors. I find a small relationship between implicit racial bias and disparate AP participation for Black students relative to White students, and suggestive evidence of a relationship between explicit racial bias and disparate DE participation for Black students relative to White students. Further, more explicitly-biased communities tend to have lower AP participation rates overall. Implications for school leaders regarding implicit bias training and other ways to address systemic inequities in access are discussed.
We show that natural disasters affect a region’s aggregate human capital through at least four channels. In addition to causing out-migration, natural disasters reduce student achievement, lower high school graduation rates, and decrease post-secondary attendance. We estimate that disasters that cause at least $500 in per capita property damage reduce the net present value (NPV) of an affected county’s human capital by an average of $505 per person. These negative effects on human capital are not restricted to large disasters: less severe events – disasters with property damages of $100-$500 per capita – also cause significant and persistent reductions in student achievement and post-secondary attendance.
This article reviews the development of my thesis that the California Supreme Court's Serrano decisions, which began in 1971 and sought to disconnect district school spending with local property taxes, led to the fiscal conditions that caused California voters to embrace Proposition 13 in 1978, which radically undermined the local property tax system. I submit that my thesis is most likely true because of Proposition 13’s durability and the absence of alternative explanations that account for its longstanding power over California politics. The article then circles back to John Serrano himself. I want to respectfully suggest that John’s views about the role of public education and my own have more in common than might be suspected. At the very least I want to correct the impression that John supported Proposition 13, which was suggested by the title of my last full article about this topic.