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2016 - Math-Oriented Fields of Study and the Race Gap in Graduation Likelihoods at Elite Colleges

Attribution: Gelbgiser, Dafna, & Alo, Sigal
Researchers: Dafna GelbgiserSigal Alo
University Affiliation: Cornell University; Tel-Aviv University
Email: dg432@cornell.edu
Research Question:
This study examines the relationship between chosen field of study and the race gap in college completion among students at elite colleges.
Published: Yes
Journal Name or Institutional Affiliation: Social Science Research
Journal Entry: 58(2016), 150-164
Year: 2016
Findings:
  1. Fields of study influence the graduation likelihoods of all students, above and beyond factors such as students’ academic and social backgrounds. This effect, however, is asymmetrical: relative to white students, the negative effect of the institutional arrangements of math-oriented fields on graduation likelihood is greater for black students.
  2. Black students, relative to whites, enroll in more math intensive fields.
  3. The authors find no evidence that the selection regime channeling students to math-oriented fields is different for Black students. For example, in both groups, students with stronger academic preparation are more likely to enroll in math-oriented fields.
  4. Enrolling in math-oriented fields, like STEM fields, is detrimental to the graduation likelihoods of all students, but especially to those of black students, net of personal attributes, academic preparation, propensity to enroll in these fields, and institutional characteristics. Consequently, the race gap in graduation rate in math-oriented fields is larger than in other fields, which contributes to the overall race gap in graduation likelihoods at these selective schools.
  5. In fields characterized by low math intensity, the race gap is not significant.
  6. The main conclusion from this analysis is that the size of the race gap varies by field math intensity, regardless of student characteristics.
  7. These results indicate that a nontrivial share of the race gap in college completion is generated after matriculation, by the environments that students encounter in college.
Scholarship Types: Journal Article Reporting Empirical ResearchKeywords: Academic AchievementAchievement GapCollegeCollege Major ChoiceElite CollegesFields of studyGraduation RatesPersistenceRaceRegions: NationalMethodologies: QuantitativeResearch Designs: Secondary Survey DataAnalysis Methods: Descriptive StatisticsMultilevel ModelsOLS (Ordinary least-squares) Sampling Frame:Undergraduate Students in Elite Colleges
Sampling Types: Non-Random - PurposiveAnalysis Units: CollegeStudentData Types: Quantitative-Longitudinal
Data Description:
  • College and Beyond (C&B) database. This database has an exceptionally large sample size of around 24,000 students. It includes the individual records of all undergraduate students who enrolled in one of 28 academically selective four-year colleges and universities in the fall of 1989. The authors analyses focus on the sample of 2,012 black students and 21,625 white students for whom graduation status and college major information is available.
  • The dependent variable, college graduation, is a dichotomous variable for students who obtained a bachelor’s degree within 6 years of matriculation.
  • The authors use 26 distinct categories of college majors, including math and physics, engineering, psychology, foreign languages, music and theater, art and art history, and sociology. The authors used the average math SAT score of all students in a major to classify the math intensity of fields.
  • Student’s race was a dichotomous variable for non-Hispanic Black and non-Hispanic White.
  • The authors control for social background factors including gender, family income, parental education, high school type, eligibility for financial aid status, and home region. Academic preparation factors include high school class rank, and math and verbal SAT scores. Institutional factors include institutional selectivity level and the share of women in an institution.
  • The authors estimated a series of logit and OLS models, which predict a student’s major from the comprehensive set of back-ground and institutional factors. The authors fit these models to the entire sample, and then by racial groups in the sample. Second, they examine how graduation likelihood is influenced by the institutional arrangements within fields of study by fitting several multilevel models that predict six-year graduation likelihood, while taking into account the variability associated with the math orientation of majors, and with individual and institutional characteristics.
Theoretical Framework:
Relevance:Factors Related to STEM Readiness
Archives: K-16 STEM Abstracts
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