Recent News


Check out a video summary of our most recent findings:

Latinx in STEM Careers from Kindea Labs on Vimeo.



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Representation in Engineering


According to the NSF's Women, Minorities, and Persons with Disabilities in Science and Engineering report, engineering as a field continues to be dominated by White men, and women and Latino/as remain significantly underrepresented in engineering. The statistics from this report, given below, indicate that substantial changes need to be made to fully utilize our pool of talented, White women and Latino/as in engineering.

  • Of all undergraduate and graduate engineering degrees awarded in 2005-2006, 80.6% were awarded to men and 68% were awarded to Whites, with women and Latino/as receiving only 19.4% and 6%, respectively.
  • Among all Whites receiving engineering degrees, 83% were male and 17% female; among Latino/as, 78% were male and 22% were female.
  • Among all men receiving engineering degrees, 69.7% were White and 5.9% were Latino, and among women, 59.8% were White and 6.7% were Latina.
  • When data are disaggregated by gender and race/ethnicity, White women (11.6%), Latinos (4.7%) and Latinas (1.3%) receive a small percentage of bachelor’s degrees in engineering.


A Comparison of White and Latino/a Men and Women in Engineering


Women and Latino/as remain significantly underrepresented in engineering. To better understand this underrepresentation, we are working towards the identification of psychological variables that contribute to the persistence and satisfaction in engineering programs and entry-level engineering careers of women and Latino/as. Our project is grounded in Social Cognitive Career Theory (SCCT), which explains the interactions among personal, environmental, and behavioral variables in the development of career interests, choices, and persistence.


Current Project (2014 - 2019), NSF Award#1430614 and #1430640

In our current project, we collect data from engineering students at nine universities, including primarily white institutions as well as HSIs. This study is a potentially conclusive examination of the utility of the SCCT model in predicting satisfaction, engagement, and persistence in engineering for White women and Latino/as both during college and their early careers. Results from this work will inform the development of custom interventions to enhance relevant systemic supports and bolster the social cognitions that are the strongest predictors in engagement, persistence, and satisfaction in engineering for each group. The findings can also inform the development of supports at strategic points in students' educational training when they may be at higher risk for dropping out of engineering.


The study is a collaboration between researchers at the University of Missouri (MU), the University of North Dakota, the University of Denver, and Oklahoma State University.


Prior Projects (2010 - 2014), NSF Award #1036713

In our prior projects, we used a sample of engineering students at New Mexico State University (NMSU), a Hispanic Serving Institution (HSI). We hypothesized that the SCCT model could explain significant variance in students' academic satisfaction and persistence in engineering. In addition, we tested for group invariance of the SCCT model to assess the generalizability in the model based on gender and race/ethnicity.


Structural equation modeling (SEM) was used to examine the hypothesized SCCT model (both cross-sectionally and longitudinally), and a series of multigroup analyses using SEM was used to test for group invariance. Finally, we conducted interviews with Latino/a non-persisters in engineering to examine the salient factors in their decision to leave engineering.


The study was a collaboration between researchers at the University of Missouri (MU), New Mexico State University, and the University of North Dakota.