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Post-secondary education

Carycruz Bueno, Lindsay C. Page, Jonathan Smith.

We investigate whether and how Achieve Atlanta’s college scholarship and associated services impact college enrollment, persistence, and graduation among Atlanta Public School graduates experiencing low household income.  Qualifying for the scholarship of up to $5,000/year does not meaningfully change college enrollment among those near the high school GPA eligibility thresholds. However, scholarship receipt does have large and statistically significant effects on early college persistence (i.e., 14%) that continue through BA degree completion within four years (22%).  We discuss how the criteria of place-based programs that support economically disadvantaged students may influence results for different types of students.

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Daniel Oliver.

The role of racial diversity at college campuses has been debated for over a half a century with limited quasi-experimental evidence from classrooms. To fill this void, I estimate the extent that classmate racial compositions affect Hispanic and African-American students at a large and over-subscribed California community college where they are minorities. I find that when minority students are exposed to a greater share of same race classmates, they are more likely to complete the class with a pass and are more likely to enroll in a same subject course the subsequent term. The findings are robust to first-time students with the lowest registration priority vs. all students and different combinations of fixed effects (e.g., student, class, and instructor race).

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Benjamin T. Skinner, Taylor Burtch, Hazel Levy.

Increasing numbers of students require internet access to pursue their undergraduate degrees, yet broadband access remains inequitable across student populations. Furthermore, surveys that currently show differences in access by student demographics or location typically do so at high levels of aggregation, thereby obscuring important variation between subpopulations within larger groups. Through the dual lenses of quantitative intersectionality and critical race spatial analysis, we use Bayesian multilevel regression and census microdata to model variation in broadband access among undergraduate populations at deeper interactions of identity. We find substantive heterogeneity in student broadband access by gender, race, and place, including between typically aggregated subpopulations. Our findings speak to inequities in students’ geographies of opportunity and suggest a range of policy prescriptions at both the institutional and federal level.

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Fulya Y Ersoy, Jamin D. Speer.

We study the importance of job-related and non-job-related factors in students’ college major choices. Using a staggered intervention that allows us to provide students information about many different aspects of majors and to compare the magnitudes of the effects of each piece of information, we show that major choices depend on a wide set of factors. While students do not change their choices when given information about earnings, they do update their choices when told about other aspects of majors. The non-job-related factors, such as a major’s course difficulty and gender composition, are important to students but not well-known to them. We also find that male and female students value different major characteristics in different ways. Lower-ability females flee from majors that they learn are more difficult than they had believed, while other students do not. On the other hand, male students are averse to being taught by female faculty, while female students are not. Overall, our results show that a variety of factors are important for students’ major choices and that different factors matter for male and female students.

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Federick Ngo, Tatiana Melguizo.

AB705 is a landmark higher education policy that has changed approaches to developmental/remedial education in the California Community College system. We study one district that implemented reforms by placing most students in transfer-level math/English courses and encouraging enrollment in support courses based on multiple measures of academic preparation (e.g., GPA). We use regression discontinuity designs to examine the impact of these new placement procedures, finding benefits to English support course recommendations for low GPA students, but no evidence of benefits or penalties for math. We use inverse probability weighted regression adjustment to explore the relationship between support course enrollment and subsequent outcomes. While enrollment in concurrent support courses appeared beneficial, enrollment in developmental courses was associated with poorer outcomes.

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Aaron Phipps, Alexander Amaya.

Given the simultaneous rise in time-to-graduation and college GPA, it may be that students reduce their course load to improve their performance. Yet, evidence to date only shows increased course loads increase GPA. We provide a mathematical model showing many unobservable factors -- beyond student ability -- can generate a positive relationship between course load and GPA unless researchers control student schedules. West Point regularly implements the ideal experiment by randomly modifying student schedules with additional training courses. Using 19 years of administrative data, we provide the first causal evidence that taking more courses reduces GPA and increases course failure rates, sometimes substantially.

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Kelli A. Bird, Benjamin L. Castleman, Yifeng Song, Renzhe Yu.

Data science applications are increasingly entwined in students’ educational experiences. One prominent application of data science in education is to predict students’ risk of failing a course in or dropping out from college. There is growing interest among higher education researchers and administrators in whether learning management system (LMS) data, which capture very detailed information on students’ engagement in and performance on course activities, can improve model performance. We systematically evaluate whether incorporating LMS data into course performance prediction models improves model performance. We conduct this analysis within an entire state community college system. Among students with prior academic history in college, administrative data-only models substantially outperform LMS data-only models and are quite accurate at predicting whether students will struggle in a course. Among first-time students, LMS data-only models outperform administrative data-only models. We achieve the highest performance for first-time students with models that include data from both sources. We also show that models achieve similar performance with a small and judiciously selected set of predictors; models trained on system-wide data achieve similar performance as models trained on individual courses.

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Alex Eble, Feng Hu.

Colleges can send signals about their quality by adopting new, more alluring names. We study how this affects college choice and labor market performance of college graduates. Administrative data show name-changing colleges enroll higher-aptitude students, with larger effects for alluring-but-misleading name changes and among students with less information. A large resume audit study suggests a small premium for new college names in most jobs, and a significant penalty in lower-status jobs. We characterize student and employer beliefs using web-scraped text, surveys, and other data. Our study shows signals designed to change beliefs can have real, lasting impacts on market outcomes.

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Lauren C. Russell, Michael J. Andrews.

We exploit historical natural experiments to test whether universities increase economic mobility and equality. We use "runner-up’" counties that were strongly considered to become university sites but were not selected for as-good-as-random reasons as counterfactuals for university counties. University establishment causes greater intergenerational income mobility but also increases cross-sectional income inequality. We highlight four findings to explain this seeming paradox: universities hollow out the local labor market and provide greater opportunities to achieve top incomes, both of which increase cross-sectional inequality, and increase educational attainment and connections to high-SES people, which prevent inequality from perpetuating into intergenerational immobility.

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Veronica Minaya, Judith Scott-Clayton, Rachel Yang Zhou.

Graduate education is among the fastest growing segments of the U.S. higher educational system. This paper provides up-to-date causal evidence on labor market returns to Master’s degrees and examines heterogeneity in the returns by field area, student demographics and initial labor market conditions. We use rich administrative data from Ohio and an individual fixed effects model that compares students’ earnings trajectories before and after earning a Master’s degree. Findings show that obtaining a Master’s degree increased quarterly earnings by about 12% on average, but the returns vary largely across graduate fields. We also find gender and racial disparities in the returns, with higher average returns for women than for men, and for White than for Black graduates. In addition, by comparing returns among students who graduated before and under the Great Recession, we show that economic downturns appear to reduce but not eliminate the positive returns to Master’s degrees.

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