Download PDF Winter Issue of The Bridge on Frontiers of Engineering December 25, 2021 Volume 51 Issue 4 The NAE’s Frontiers of Engineering symposium series forged ahead despite the challenges of the pandemic, with virtual and hybrid events in 2021. This issue features selected papers from early-career engineers reporting on new developments in a variety of areas. Invisible Bridges: Mirror, Mirror on the Wall Monday, January 3, 2022 Author: Beth Cady Inspired by the name of this quarterly, this column reflects on the practices and uses of engineering and its influences as a cultural enterprise. Engineering education in the United States has undergone periods of reform for many years, often in response to reports predicting a loss of technological innovation and global leadership that prompt calls to increase the numbers of engineers in this country. And the numbers of students earning bachelor’s degrees in engineering have increased dramatically over the past 20 years. This is encouraging news. Yet White men still earn the vast majority of those degrees and constitute the vast majority of engineers working in industry and academia. The reasons for this are numerous and varied, but rather than address the underlying systemic issues that maintain the status quo, one of the most popular responses to the problem is to “increase the pipeline.” This approach calls for getting more young people from populations that have been traditionally marginalized and minoritized in engineering interested and prepared for undergraduate study in engineering and then having them graduate with an engineering degree. Increasing the input to the system, the rationale goes, will cause a corresponding increase in the output from that system. The pipeline metaphor is flawed, and is itself leaky, on many levels; it assumes only one entry point (generally middle school), and does not allow for complexities along engineering education and career pathways such as starting later in life, stopping for a period of time, or moving into engineering from another field. Many have written about these problems with the pipeline metaphor. But there is another, deeper problem with the pipeline metaphor: it ignores the culture, climate, and curricula of engineering education. The pipeline functions like Skinner’s black box—we observe the inputs (entering college students) and outputs (those with engineering bachelor’s degrees) without considering or examining what happens to the students between those two milestones. It’s important to retire that metaphor from use. To effectively diversify engineering and engineering education, we must delve into that box. Simply bringing more Black and Brown people, White women, LGBTQIA+ individuals, and people with disabilities into institutions and programs with a long tradition of excluding individuals from those populations will, at best, drive them to disciplines with more welcoming cultures. At worst, those who manage to complete their degree and enter engineering work are more likely to end up with negative experiences and possibly deleterious impacts on their health and wellbeing as well. Words like grit, rigor, resilience, and fit are used to signal to anyone whose identity or identities are excluded from engineering that they must either change or ignore that part of themselves in order to fit into the mold of an engineer. Thus, even for capable students excited about studying engineering, it can be difficult to reconcile these aspects of one’s identity with an “engineering identity” (typically male, White, heterosexual, and nondisabled). Having to constantly monitor one’s behavior to hide or minimize parts of identity is exhausting and diverts energy from what Sam Florman rightly called “the existential pleasures of engineering.” Encouraging people to change themselves in order to be an engineer has significant consequences. It discourages the participation and retention of those who do not “fit” the majority type and, as former NAE president Bill Wulf explained in an NAE report two decades ago, it has important opportunity costs: Without diversity, the life experiences we bring to an engineering problem are limited. As a consequence, we may not find the best engineering solution. We may not find the elegant engineering solution. As a consequence of a lack of diversity, we pay an opportunity cost, a cost in designs not thought of, in solutions not produced. Opportunity costs are very real…. Those concerns remain as true today as when they were written. One area of change needed is in the culture and perceptions of who is and can be an engineer. We can begin by acknowledging the heuristics and biases that we all bring to the table and that often unconsciously inform how we make sense of the overwhelming amount of information that we encounter daily. These cognitive shortcuts make decisions easier by reducing the amount of information processing needed. But they also increase errors because important information may be overlooked or stereotypes activated. For example, the fundamental attribution error and the related correspondence bias lead us to greatly overestimate how much personal characteristics like innate intelligence and motivation contribute to behavioral outcomes like test scores (e.g., “I did well on the test because I am smart”—or “I did not do well because I am not smart”). Conversely, we greatly underestimate the role of situational context in those outcomes (e.g., it is less typical for an individual to crow that “I did well on the SAT because I attended a well-resourced school that offered test prep sessions,” or to acknowledge that “I did not do well on the SAT because I needed to work to help support my family and could not study as much as I needed”). Relatedly, actor-observer bias leads us to attribute others’ behavior to personal causes but use situational contexts to explain our own. Thus if I don’t do well on an exam, I may blame lack of sleep due to my job rather than my innate intelligence or study habits, but attribute others’ poor scores to their lower intelligence or lack of work ethic to study rather than their need to work instead of study. More insidiously, our perceptions of other people can be affected by ingroup-outgroup bias, which leads us to favor individuals we consider to be in our “ingroup,” whether we’re categorizing by gender, race, neighborhood, team, or any of a number of identities that we all hold. Because of the strength of these biases, we tend to give similar attributional consideration to members of our ingroup (this is called the group-serving bias or ultimate attribution error). So if all the students who look like me fail a test, I’m likely to think they also have contextual excuses, while simultaneously not giving that consideration to students who are dissimilar to me. We also tend to ignore or not carefully consider information that contradicts our existing beliefs while trusting evidence that supports those beliefs (confirmation bias). So if I believe that hard work and motivation are the only ingredients needed to become an engineer and thus everyone has an equal chance to become one (the myth of meritocracy), I might not consider evidence to the contrary, such as differences in access to quality education at all levels, bias (implicit or explicit) against individuals from minoritized populations, or historic systemic racism and sexism that studies clearly show mean that not everyone has an equal chance of being an engineer. This sense-making process also affects the ways we categorize people we meet for the first time. If I meet someone who seems similar to my idea of an engineer I use the representativeness heuristic to, correctly or not, classify them as an engineer. If a child asks what engineers are like I will likely describe the first known engineer that comes to mind (the availability heuristic). Without checking my reasoning, I could easily be contributing to stereotypes of who is and can be an engineer. This is where the compositional diversity of engineering education matters. When the discipline is overwhelmingly White and male, those individuals will give different attributional considerations to Black and Brown students than to White ones. They will likely think of individuals similar to them as being a better representation of an engineer, and because of confirmation bias may not acknowledge evidence showing that individuals from marginalized populations are great engineers. This could have negative effects on both peer and student-faculty relationships as well as, beyond the classroom, opportunity and economic costs to innovation. These heuristics and biases evolved as humans did. They helped our early ancestors recognize potential threats and act accordingly, making life or death decisions when confronted with unfamiliar people who could be enemies or friends or animals who could be prey or predators. Even today there is nothing inherently wrong with using these cognitive shortcuts to help us manage our behavior—without them we would not be able to whittle down all the information presented to us in order to make a decision. Acknowledging that inherent heuristics and biases can produce inequitable results for students is an excellent place to start to ensure that engineering education does not remain “stuck in 1955.”  According to the National Science Foundation’s 2019 Science and Engineering Indicators (https://ncses.nsf.gov/pubs/nsb20197/data), of the 118,000 engineering bachelor’s degrees awarded in 2017 White men earned 47 percent and White women earned 12 percent. Both Asian and Hispanic men earned approximately 8 percent, but Asian and Hispanic women earned less than 3 percent of degrees. Black men also earned 3 percent of those degrees, but Black women and American Indian men and women each accounted for less than 1 percent. According to Carnevale and colleagues (2021), 56 percent of working engineers are White men; women of all races are 16 percent, with White women the largest share of that group at 9 percent. While Asian men are 12 percent of that workforce, Asian women are only 3 percent. Black men (4 percent) and Black women (1 percent) as well as Hispanic men (8 percent) and Hispanic women (2 percent) constitute a very small proportion of the engineering workforce. Carnevale AP, Smith N, Quinn MC. 2021. Mission not accomplished: Unequal opportunities and outcomes for Black and Latinx engineers. Washington: Georgetown University Center on Education and the Workforce.  National Academy of Engineering. 2018. Understanding the Educational and Career Pathways of Engineers. Washington: National Academies Press.  Cech EA, Waidzunas TJ. 2021. Systemic inequalities for LGBTQ professionals in STEM. Science Advances 7(3):1–9.  Wulf WA. 2002. The importance of diversity in engineering. In: Diversity in Engineering: Managing the Workforce of the Future. Washington: National Academy Press, p. 9.  It should be noted that individuals from collectivist societies (like those of countries in Asia and South America) do this less than those from individualistic societies (like those of the United States, Germany, and Australia).  Sorby S, Fortenberry NL, Bertoline G. 2021. Stuck in 1955, engineering education needs a revolution. Issues in Science and Technology, Sep 13. Also see Chubin D. 2021. A revolution for engineering education. Issues in Science and Technology, Oct 5. About the Author:Beth Cady is director of the NAE’s Practices for Engineering Education and Research (PEER) program.