2015 - The Effects of Gender and Race Intersectionality on Student Learning Outcomes in Engineering

Attribution: Ro, Hyun K., & Loya, Karla I.
Researchers: Hyun K. RoKarla I. Loya
University Affiliation: Carnegie Mellon University; Bowling Green State University; Pennsylvania State University; University of Virginia
Email: hro@bgsu.edu
Research Question:
This study examines engineering students' self-reported learning outcomes by their gender, race/ethnicity, and the intersections of gender and race/ethnicity. This study focuses on the relationship between students' pre-college characteristics and their learning outcomes.
Published: Yes
Journal Name or Institutional Affiliation: The Review of Higher Education
Journal Entry: Vol. 38, No. 3, Pp. 359-396
Year: 2015
Findings:
  1. Whites, Asians, and men are generally more academically prepared in high school in comparison to Blacks, Latino/as, and women.
  2. Women assessed their engineering learning outcomes (particularly design and fundamental skills) lower than men, but assessed their professional learning outcomes (specifically communication and teamwork skills) higher than their male peers.
  3. Blacks and Latino/as also lag behind Whites and Asians in their self-reported GPAs in the engineering programs.
  4. The authors did not find any gender differences in regards to contextual competence.
  5. The impact of gender on learning outcomes varies by race/ethnicity.
  6. Black women tend to rate their design, contextual competence, and communication skills lower than their White counterparts. Even though Black men also rated these skills lower than Whites, these were not statistically significant differences. This finding might imply that Black women might be suffering a double effect because of their gender and race, which places them in twice a disadvantage, compared to Black men.
  7. There are no differences in self-assessed learning outcomes between Latinos/as and their White counterparts, with the exception that Latinas rated their leadership skills higher than Whites.
  8. The authors found that there are no differences in self-assessed learning outcomes between Latino/as and their White counterparts, with the exception that Latinas rated their leadership skills higher than Whites.
  9. Asian men and men from other racial/ethnic backgrounds assessed their fundamental skills and all three professional skills lower than White men.
  10. Women and men of color in engineering fields often hold lower self-rates of their learning, when compared to White students.
  11. Minorities in STEM majors self assess their STEM skills lower than their White counterparts.
Scholarship Types: Journal Article Reporting Empirical ResearchKeywords: EngineeringGenderIntersectionalityLearning OutcomesMinoritiesRaceSelf-conceptRegions: NationalMethodologies: QuantitativeResearch Designs: Secondary Survey DataAnalysis Methods: Descriptive StatisticsLinear Regression Models Sampling Frame:Engineering Students
Sampling Types: NationalAnalysis Units: StudentData Types: Quantitative-Cross Sectional
Data Description:
  • The authors utilize we use Feminist Intersectionality as their analytical lens, because it provides the scope and flexibility to examine both gender and race simultaneously. Authors also draw from the College Impact Model.
  • This paper stems from a larger study entitled Prototype to Production: Conditions and Processes for Educating the Engineer of 2020 (P2P). The P2P dataset contains 5,249 students that was collected from 32 four-year colleges that are representative of all four-year US engineering schools offering two or more ABET-accredited programs in seven engineering disciplines. The stratified sample design of institutions was also representative on three levels of highest degree offered (bachelor’s, master’s, or doctorate), and two levels of type of control (public or private).
  • This sample does not include first-year engineering students.
  • Six student-learning outcomes were chosen as criterion measures, three of them are core competencies and three are professional skills. The first ability of interest, fundamental skills, was chosen because it is the keystone of any engineering program. The second scale of interest assesses students’ design skills. The third ability of interest is contextual awareness, meaning that all engineering undergraduates must be prepared to solve engineering problems in real-world contexts.
  • The authors also included engineering professional skills through students’ self-assessments of their teamwork, communication, and leadership abilities. Teamwork skills, Communication skills, Leadership skills.
  • The key independent variables were race and gender.
  • Controls were in place to minimize the potential confounding effects of selected pre-college student characteristics, such as mother’s education; father’s education; transfer status; first math course after high school, and high school achievement as reflected in students’ total SAT scores and high school Grade Point Average. We also include class year. We created a dummy variable with two categories of students’ academic majors based on the relatively higher percentage of women students in some academic programs.
  • While this paper focuses on individual student-level analysis, the authors also include three institutional-level control variables: undergraduate enrollment size, highest-degree awarded, and Historically Black College and University (HBCU) and Hispanic Serving Institutions (HIS) institution status. The data include three HBCUs and three HSIs. They categorize undergraduate enrollment size as small, medium, or large using the intervals developed for the 2005 Carnegie Classification. “Small” was defined as an undergraduate enrollment of 1,000-3,000; “medium” as 3,000-10,000; and “large” as more than 10,000.
  • After cleaning the data, analyses used the weighted responses of 5,017 students in 31 colleges of engineering during the 2009 spring and summer terms. The weighted sample includes 2,323 White men, 469 White women, 185 Black men, 418 Latino men, 114 Latina women, 445 Asian men, 173 Asian women, and 654 men and 143 women students classified as Other.
Theoretical Framework:
Relevance:STEM Persistence and Retention
Archives: K-16 STEM Abstracts