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Selective college admissions are fundamentally a question of tradeoffs: Given capacity, admitting one student means rejecting another. Research to date has generally estimated average effects of college selectivity, and has been unable to distinguish between the effects on students gaining access and on those losing access under alternative admissions policies. We use the introduction of the Top Ten Percent rule and administrative data from the State of Texas to estimate the effect of access to a selective college on student graduation and earnings outcomes. We estimate separate effects on two groups of students. The first--highly ranked students at schools which previously sent few students to the flagship university--gain access due to the policy; the second--students outside the top tier at traditional "feeder" high schools--tend to lose access. We find that students in the first group see increases in college enrollment and graduation with some evidence of positive earnings gains 7-9 years after college. In contrast, students in the second group attend less selective colleges but do not see declines in overall college enrollment, graduation, or earnings. The Top Ten Percent rule, introduced for equity reasons, thus also seems to have improved efficiency.
We examine through a field experiment whether outreach and support provided through an AI-enabled chatbot can reduce summer melt and improve first-year college enrollment at a four-year university and at a community college. At the four-year college, the chatbot increased overall success with navigating financial aid processes, such that student take up of educational loans increased by four percentage points. This financial aid effect was concentrated among would-be first-generation college goers, for whom loan acceptances increased by eight percentage points. In addition, the outreach increased first-generation students’ success with course registration and fall semester enrollment each by three percentage points. For the community college, where the randomized experiment could not be robustly implemented due to limited cell phone number information, we present a qualitative analysis of organizational readiness for chatbot implementation. Together, our findings suggest that proactive outreach to students is likely to be most successful when targeted to those who may be struggling (for example, in keeping up with required administrative tasks). Yet, such targeting requires university systems to have ready access to and ability to make use of their administrative data.
Revealed preferences for equal college access may be due to beliefs that equal access increases societal income or income equality. To isolate preferences for those goods, we implement an online discrete choice experiment using social statistics generated from true variation among commuting zones. We find that, ceteris paribus, the average income that individuals are willing to sacrifice is (i) $4,984 dollars to increase higher education (HE) enrollment by 1 standard deviation (14%); (ii) $1,168 dollars to decrease rich/poor gaps in HE enrollment by 1 standard deviation (8%); (iii) $2,900 to decrease the 90/10 income inequality ratio by 1 standard deviation (1.66). In addition, we find that political affiliation is an important moderator of preferences for equality. While both Democrats and Republicans are willing to trade over $4,000 dollars to increase HE enrollment by 1 standard deviation, Democrats are willing to sacrifice nearly three times more income to decrease either rich/poor gaps in HE enrollment or the 90/10 income inequality ratio by 1 standard deviation.
We study within-family spillovers in college enrollment to show college-going behavior is transmissible between peers. Because siblings’ test scores are weakly correlated, we exploit college-speciﬁc admissions thresholds that directly affect older but not younger siblings’ college options. Older siblings’ admissibility substantially increases their own four-year college enrollment rate and quality of college attended. Their improved college choices in turn raise younger siblings’ college enrollment rate and quality of college chosen, particularly for families with low predicted probabilities of college enrollment. Some younger siblings follow their older sibling to the same campus but many upgrade by choosing other colleges. 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 income, geography and other characteristics that deﬁne a community.
We examine the effects of a comprehensive college transition program (CCTP) on four psychosocial outcomes associated with postsecondary success: sense of belonging, mattering, and academic and social self-efficacy. The CCTP operates on three four-year campuses and includes a range of supports, including shared academic courses, peer mentoring, and residential or common community spaces. We leverage the randomization of Angrist et al. (2014), but restrict our comparison to scholarship recipients with and without CCTP exposure. To account for differential attrition from the experimental sample, we rely on a “selection on observables” assumption for our primary analysis. Results suggest that the program significantly and substantially increased students’ sense of belonging and mattering, but had no effect on academic or social self-efficacy.
This paper provides the first causal evidence on the impact of college advisor quality on student outcomes. To do so, we exploit a unique setting where students are randomly assigned to faculty advisors during their first year of college. We find that higher advisor value-added (VA) substantially improves freshman year GPA, time to complete freshman year and four-year graduation rates. Additionally, higher advisor VA increases high-ability students’ likelihood of enrolling and graduating with a STEM degree. Our results indicate that allocating resources towards improving the quality of academic advising may play a key role in promoting college success.
Up to three-fourths of college students can be classified as “non-traditional”, yet whether typical policy interventions improves their education and labor market outcomes is understudied. I use a regression discontinuity design to estimate the impacts of a state financial aid program aimed towards non-traditional students. Eligibility has no impacts on degree completion for students intending to enroll in community colleges or four-year colleges but increases bachelor’s degrees for students interested in large, for-profit colleges by four percentage points. I find no impacts on employment or earnings for all applicants. This research highlights challenges in promoting human capital investment for adults.
We explore the intergenerational occupational transmission between parents and their children as it pertains to entry into the STEM field. Using the Education Longitudinal Study of 2002, we study student’s aspirations to work in a STEM field and eventual STEM education and employment. We show how these patterns change depending on whether the student’s parents work in a STEM field. We find strong effects of parental occupation type on student’s STEM outcomes that are heterogeneous by student gender. High school boys are more likely to aspire to work in STEM if one of their parents do so. By adulthood, both boys and girls have a higher probability of majoring and working in a STEM field if their parents also do, and in this case, estimated effects are stronger for girls despite a lack of effects on high school girls’ aspirations. For girls but not for boys, having a parent working in STEM increases the probability of entering the STEM field in adulthood above and beyond aspirations to enter the STEM field during adolescence.
More than half of U.S. children fail to meet proficiency standards in mathematics and science in fourth grade. Teacher professional development and curriculum improvement are two of the primary levers that school leaders and policymakers use to improve children’s science, technology, engineering and mathematics (STEM) learning, yet until recently, the evidence base for understanding their effectiveness was relatively thin. In recent years, a wealth of rigorous new studies using experimental designs have investigated whether and how STEM instructional improvement programs work. This article highlights contemporary research on how to improve classroom instruction and subsequent student learning in STEM. Instructional improvement programs that feature curriculum integration, teacher collaboration, content knowledge, pedagogical content knowledge, and how students learn all link to stronger student achievement outcomes. We discuss implications for policy and practice.