Metrics matter race gender and measures of success in engineering education
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Metrics Matter: Race, Gender, and Measures of Success in Engineering Education. Russell A. Long Purdue University Matthew W. Ohland Purdue University Catherine E. Brawner Research Triangle Educational Consultants Michelle M. Camacho University of San Diego

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Metrics Matter: Race, Gender, and Measures of Success in Engineering Education

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Metrics matter race gender and measures of success in engineering education

Metrics Matter: Race, Gender, and Measures of Success in Engineering Education

Russell A. LongPurdue University

Matthew W. OhlandPurdue University

Catherine E. BrawnerResearch Triangle Educational Consultants

Michelle M. CamachoUniversity of San Diego

Richard A. LaytonRose Hulman Institute of Technology

Susan M. LordUniversity of San Diego

Mara H. WasburnPurdue University


Background

Background

Women and men who matriculate in engineering are more likely to persist in engineering than students in other majors (Ohland et al., 2008);

For all races except Native American, women who matriculate in engineering persist to the eighth semester at rates comparable to those of men (Lord et al., 2009);

The metric used to measure success matters. While eight-semester persistence in engineering is a reasonable predictor of six-year graduation in engineering in the aggregate, institutional differences are noticeable and much greater than variation by gender (Ohland, Camacho, Layton, Lord, & Wasburn, 2009);

Institutional variation in persistence, as measured by either eight-semester persistence or six-year graduation, is much greater than the variation by gender (Ohland et al., 2009).


Measuring success in stem

Measuring “Success” in STEM

Six-year graduation rate

  • Xie & Schauman. Women in science (2003)

    Persistence to the eighth semester

  • Astin& Astin. Undergraduate science education: The impact of different college environments on the educational pipeline in the sciences (1992).

  • Seymour & Hewitt. Talking about leaving: Why undergraduates leave the sciences (1997).


Metrics matter race gender and measures of success in engineering education

Data from Multi-Institution Database for Investigating Engineering Longitudinal Development (MIDFIELD).

The Multi-Institution Database for Investigating Engineering Longitudinal Development (MIDFIELD)

  • 9 public research institutions in the southeastern United States.

  • 73,154 first-time-in-college students matriculating in engineering from 1988 through 1998.

    • 15,424 women (21%)

    • 12,928 under-represented minorities (18%)


Southeastern midfield institutions

Southeastern MIDFIELD Institutions

  • Clemson University

  • Florida Agricultural and Mechanical University

  • Florida State University

  • Georgia Institute of Technology

  • North Carolina Agricultural and Technical State University

  • North Carolina State University

  • University of Florida

  • University of North Carolina Charlotte

  • Virginia Polytechnic Institute and State University


Nine southeastern midfield institutions

Nine Southeastern MIDFIELD Institutions

6 of the 50 largest U.S. undergraduate engineering programs.

1/12 of all U.S. engineering undergraduate degrees.

1/5 of all U.S. African-American engineering B.S. degree recipients each year.

Graduation percentage of Hispanics (regardless of gender) is representative of other U.S. programs.

All other ethnic populations are representative of a national sample.


Limiting principles

Limiting Principles

  • Institutional data are provided on the condition that researchers using the data protect the identity of the partner institutions and each institution’s students.

  • While this study includes data for very large numbers of students, only nine institutions are represented, so institutional variation is treated using a case study approach.


Methods

Methods

  • Race is not examined dichotomously

  • Persistence rates of women through a critical race len.

  • Whole population data - our findings are fully representative of the institutions studied.

  • Can be generalized to other large public institutions to the extent that MIDFIELD institutions are representative of those.

  • To study the effect of the choice of metric to define success, our study includes two separate persistence metrics:


Eight semester persistence

Eight-Semester Persistence

The number or percentage of students matriculating in any engineering discipline who are still enrolled in an engineering discipline in their eighth semester (although not necessarily in the engineering discipline in which they originally matriculated).


Six year graduation

Six-Year Graduation

The number or percentage of students matriculating in any engineering discipline who have graduated in any engineering discipline within six chronological years (again, not necessarily from the engineering discipline in which they matriculated).


Yield

Yield

The number of students graduating within six chronological years as a percentage of those students who persist to eight semesters.

The product of the yield and the eight-semester persistence is the six-year graduation rate.


Metrics matter race gender and measures of success in engineering education

At first, eight-semester persistence in engineering appears to be a consistent predictor of six-year graduation.


Metrics matter race gender and measures of success in engineering education

Female and male populations aggregated by race with similar graduation rates may have widely varying experiences. Letters represent institutions; filled circles are female populations. Note that institutional differences outweigh gender differences.


Metrics matter race gender and measures of success in engineering education

B

A

D

C

Female and male populations aggregated by race with similar graduation rates may have widely varying experiences. Letters represent institutions; filled circles are female populations. Note that institutional differences outweigh gender differences.


Trajectories of asian engineering students

Trajectories of Asian Engineering Students


Trajectories of black engineering students

Trajectories of Black Engineering Students


Trajectories of hispanic engineering students

Trajectories of Hispanic Engineering Students


Trajectories of native american engineering students

Trajectories of Native American Engineering Students


Systematic majority measurement bias

Systematic Majority Measurement Bias

  • Asians and Whites - 82 percent of the total. undergraduate engineering population studied.

  • Masks the performance of the underrepresented populations.


Trajectories of white engineering students

Trajectories of White Engineering Students


Conclusions

Conclusions

At all institutions, women who persist to the eighth semester are more likely to graduate than men who persist to the eighth semester.

Using eight-semester persistence as a success metric can underreport the persistence of women to graduation. This is true for all aggregated populations of women and many racial subpopulations.

While we have demonstrated that persistence varies by institution, presumably because of institutional recruitment and retention practices, within each institution it is clear that an eight semester metric belies six year graduation persistence.


Conclusions1

Conclusions

Eight semester persistence metrics that do not disaggregate by race conflate data that heavily over-represents white males. These produce data that suggest men outpace their gendered counterparts at the eighth semester marker. Following these students to six year graduation, and disaggregating by race and gender, reveals that women in several racial/ethnic groups graduate at a higher rate.

Ultimately, our work demonstrates that trajectories of persistence are non-linear, gendered, and racialized, and that higher education has developed the way in which engineering persistence is studied based on the behavior of the majority, specifically the White, male population.


Acknowledgements

Acknowledgements

This material is based on work supported by the National Science Foundation Grant No. REC-0337629 (now DRL- 0729596) and EEC-0646441, funding the Multiple-Institution Database for Investigating Engineering Longitudinal Development (MIDFIELD) and a collaborative NSF Gender in Science and Engineering Research Grant (0734085 & 0734062). The opinions expressed in this paper are those of the authors and do not necessarily reflect the views of the National Science Foundation.


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