Decisions to choose and persist in a career or to change careers, jobs, or organizations are made from adolescence to middle age and are influenced by a number of factors. These factors may be internal to the individual, such as interests or skills, or external, such as influences by families, the economy, or even certain policies. Programs or activities that increase exposure to, understanding of, or experiences in engineering also play a role in these decisions.
This chapter examines the factors that influence the decision making of engineering students and graduates, starting with K–12 preparation and then considering experiences through college and into the workforce. A theoretical model, called social cognitive career theory (SCCT), is used to identify the factors that affect an individual’s educational and career decisions as well as potential points for interventions to increase the likelihood that individuals will complete an engineering degree and use the skills and knowledge gained in their education throughout their career. The focus here is primarily on studies of women1 in engineering because of a dearth of studies, sample sizes, and literature on other marginalized groups, which include other races, nationalities,2 and ethnicities; persons with disabilities; and LGBT3 persons; data for these groups are presented when they are available. The committee addresses this lack of research in its recommendations.
The chapter presents descriptions of interventions that target educational and work environments or attempt to reduce bias in teaching or managing, with the goal of increasing the number of women and underrepresented minority (URM) engineers. It concludes with some general summary observations about the career and work choices of young engineers, remaining questions about these choices, and the needs for more data—especially for underrepresented populations—to elucidate future directions for research and practice.
As documented in chapter 1, women and certain minority populations are severely underrepresented among engineering degree holders at all levels and even more so in the engineering workforce. There are at least two
1 In general, these studies compare women and men in engineering and do not take race or ethnicity into account. Federal datasets count underrepresented minority women in both gender and race/ethnicity categories.
2 Although Asians overall are overrepresented in engineering compared to their representation in the US population, differences in attainment of bachelor’s degrees exist across groups with different national origins. For example, Southeast Asians and Pacific Islanders have lower rates of college completion than Chinese, Japanese, Indian, or Korean students, so interventions designed for some subgroups may not work for others, and because the demographics of the US population change constantly it is important to not view minority groups as homogeneous and to examine differences within those populations (NAE 2014) as well as compared to majority populations. However, little research examines these nationality differences in engineering education or the workforce (Ing and Victorino 2016).
3 LGBT stands for lesbian, gay, bisexual, and transgender.
highly compelling reasons why the nation should be concerned about engineering’s diversity challenge, and they are summed up by the words “innovation” and “equity.”
First, research has shown that a diverse workforce—whether a function of gender, ethnicity, socioeconomic, or other factors—is more creative and innovative than a homogeneous one (Chubin et al. 2005; Corbett and Hill 2015; Emerson 2014; NAE 2002; Phillips 2014) and that groups with equal gender representation exhibit better collaboration and teamwork (Bear and Woolley 2011). As former NAE president Bill Wulf observed two decades ago, the creativity and innovativeness so critical to engineering stem from the life experiences of the people who do it, so without diversity “we limit the set of life experiences that are applied, and as a result, we pay an opportunity cost—a cost in products not built, in designs not considered, in constraints not understood, in processes not invented” (Wulf 1998, p. 9). Moreover, assuming that the distribution of students with the intelligence, creativity, curiosity, and other abilities to become productive, innovative engineers is blind to gender, race, ethnicity, or other externally visible differentiators, the inability of engineering to attract and retain more women and underrepresented minorities denies employers and the nation access to a large and, given demographic trends, growing share of the engineering-capable talent pool.
Second, as shown in chapter 1, the knowledge, skills, and abilities gained during an engineering education are versatile and highly relevant to a variety of occupations and fields. Since only a small fraction of the nation’s workforce has this combination of skills and knowledge, graduates from engineering programs are in high demand and have higher starting salaries and lifetime earnings and lower unemployment rates than graduates in other disciplines. Moreover, engineering graduates report high levels of career and work satisfaction. As shown in this chapter, research and practice have identified strategies that are consistently effective in overcoming issues of recruitment and retention, where efforts have been made to implement them; these practices are known to break down barriers that deny significant numbers of the workforce access to the income and quality of life afforded by the engineering profession. For all of these reasons, it is a matter of social justice and equity that individuals from all backgrounds be encouraged and supported to study engineering and obtain an engineering degree.
Finding: There are at least two compelling reasons why the nation should be concerned about engineering’s diversity challenge: the creativity and innovation costs of unused skills and talent, and equity/social justice.
Many factors lead to students’ initial choice of an engineering major, and several theories can help predict or explain individuals’ career choices based on these factors. Two theories in particular have influenced research on engineering as a career choice: the general expectancy value model (Eccles-Parsons et al. 1983; Eccles 2007) and the social cognitive career theory (SCCT) model (Lent et al. 1994). Their terminology is somewhat different, but there is significant overlap in the two models’ psychological and environmental constructs that predict choice behavior. The expectancy value model considers experience and socialization as factors in an individual’s expectation of success in an endeavor (Eccles 2007). The SCCT model includes two aspects of social cognitive theory (Bandura 1997): self-efficacy beliefs and outcome expectations.
Because social cognitive career theory is the most recent and most comprehensive model that explicitly incorporates contextual supports and barriers that shape career choices, and most of the research across age groups has been based on SCCT whereas the expectancy value model focuses primarily on choices made in early adolescence, the committee uses SCCT as the principal framework for the analysis in this chapter.
The SCCT model (Lent et al. 1994) relates to academic and career development by explaining how interests develop and affect career choices and by helping predict an individual’s initial career choices as well as persistence and performance in a career. It is used throughout this chapter to explain (1) the factors that act on individuals as they make choices about their education and career in engineering and (2) differences in the impacts of those factors based on an individual’s background and characteristics. Figure 3-1 presents a simplified diagram of the SCCT model.
The model takes account of individual differences (person inputs; e.g., gender, race/ethnicity, health, personality traits) and background contextual affordances (or distal factors; e.g., home and school environment and
experiences, family socioeconomic status) that affect opportunities to learn a task or set of tasks associated with a field (e.g., math and problem solving associated with engineering), including one’s learning experiences. People learn by performing a task themselves (personal accomplishment or mastery experiences) or by observing a friend or role model accomplish the task (vicarious learning), but learning experiences also include encouragement from others (social persuasion) or feelings of excitement about performing the task (or conversely, anxiety about not performing it) (physiological states). Learning experiences in turn shape self-efficacy expectations and outcome expectations, which then shape interests, goals, and actions. An individual’s actions might be matriculation in engineering as an undergraduate student, graduation with a degree in engineering, and entry and persistence in the engineering profession. Internal and external factors (person inputs and contextual influences) affect the elements of the SCCT model as well as how they interact with one another. They may serve as supports or barriers to an individual’s decisions throughout the pathway.
Self-efficacy is the confidence that one can successfully engage in a particular activity or task.4 It predicts both how much effort an individual will put into a task and whether s/he will try to cope with obstacles to persist in the task or give up when faced with an obstacle such as a low quiz grade in math class. It is specific to the domain of the task and does not extend to other domains, so self-efficacy in math does not necessarily translate to self-efficacy in science. It is also highly subjective; how a person evaluates her own confidence and abilities affects her behavior far more than an objective assessment of her abilities. Self-efficacy is affected by personal and background characteristics, so it follows that individuals with different characteristics will be affected differently by and react differently to the same obstacle.
Outcome expectations refer to what one expects from engaging in a task. They include self-evaluation (e.g., increased happiness, expectation of high salary), feedback from others (e.g., praise), or physiological effects (e.g., reduced anxiety). Outcome expectations are distinct from self-efficacy. One may, for example, have confidence in performing an activity but not expect to engage in it (and thus not expect outcomes from it). Conversely,
4 The difference between self-efficacy and confidence is explained as follows: “Confidence…refers to strength of belief but does not necessarily specify what the certainty is about…. [S]elf-efficacy refers to belief in one’s agentive capabilities, that one can produce given levels of attainment. A self-efficacy assessment, therefore, includes both an affirmation of a capability level and the strength of that belief….” (Bandura 1997, p. 382). In addition, self-efficacy is domain-specific for the individual.
one can expect outcomes (positive or negative) from participating in an activity even if confidence in one’s performance is low. If both self-efficacy and outcome expectations are high, it is likely that the individual will develop interest in the area, form goals to pursue the interest, and take actions necessary to achieve those goals. Actions may include choosing to major in engineering, finishing a college degree in engineering, entering an engineering job, and persisting in an engineering career.
Contextual influences can be characterized as barriers or supports—both near to the individual (such as family) or in the larger economic climate (such as a recession)—that hamper or support engineering-related interests, career choice, and associated actions, either directly or indirectly by influencing self-efficacy and outcome expectations.
If individuals have positive self-efficacy in their engineering-related tasks and expect positive outcomes from their career, it is likely that their interest in engineering work will remain high and that they will persevere in their career. But career-related self-efficacy, and thus career choice behavior, can be undermined or enhanced by contextual influences (e.g., financial barriers or teacher support). This chapter reviews barriers to, and supports for, choosing and staying in an engineering career, with a focus on populations historically underrepresented in engineering, specifically women and underrepresented minorities, because opportunities, access, and experiences in engineering differ significantly for these populations.
One factor that tends to differ for men and women and underrepresented minorities is the extent to which individuals feel they belong in engineering. Even if a student is interested in the subject and has an aptitude for it, a view of engineering as a solitary effort that does not help society may discourage her from pursuing a degree in the field (this perception of engineering is more discouraging to female students than to males; Eccles 2007). Alternatively, stereotypes held by families or teachers may, whether openly or inadvertently, send a message to some students that they should not pursue engineering. Stereotypes and bias can function implicitly (e.g., operating below the level of consciousness but still affecting behavior), but research has shown that directing attention to implicitly held beliefs can reduce their influence (Greenwald and Banaji 1995).
Regardless of intent, messages based on implicit or explicit bias may discourage students of any age from entering, or feeling that they belong in, engineering. Furthermore, individuals who are aware of a stereotype about themselves relative to engineering (e.g., a girl who has heard a teacher say that girls are not good at math) may fear that they will confirm the stereotype when taking an assessment (e.g., a math test) and perform poorly on it regardless of their actual knowledge of the subject, a phenomenon known as stereotype threat (Steele 1997).
Interventions are activities or programs designed to provide positive learning experiences that lead to improved self-efficacy, optimistic outcome expectations, or both, with the overarching goal of encouraging interest, actions, and goals in engineering (Bakken et al. 2010; Luzzo et al. 1996; Sullivan and Mahalik 2000) or developing coping skills to overcome negative experiences or stereotypes (Yeager and Dweck 2012). They can act at any point of the SCCT model (e.g., interventions can be designed for learning experiences, classroom environments, or outcome expectations). Most research on self-efficacy has emphasized interventions at the individual level, focusing on the promotion of interest as a way to facilitate the choice of a career major or path (Singh et al. 2013).
Finding: Many interrelated internal and external (personal and societal or cultural) factors influence the decision making of students and graduates in ways that contribute to engineering’s diversity challenge.
Students’ developing interests in particular career paths are supported by individual (personal), experiential, and institutional factors such as learning experiences, self-efficacy and outcome expectations, interests, barriers and supports, and even policies.
Learning Experiences: K–12 Preparation
Initial STEM career choice in high school has been shown to predict later career choice, although boys were overall more interested in engineering and girls more interested in medical and health-related STEM careers (Sadler et al. 2012). Initial career choices start with opportunities for learning experiences both in and out of the classroom (e.g.,
tinkering or building things at home, an interactive museum exhibit) that help shape an individual’s confidence to do the work associated with that career. Engineering experiences in K–12 education can provide real-world context to enhance learning of math and science, improve technological literacy, develop critical thinking skills, increase awareness of engineers and their work, and prepare students for further engineering education (NAE/NRC 2009). These learning experiences aim to provide individuals with accomplishments related to the career, role models, encouragement, and ways to reduce anxiety and increase excitement. But about four times as many boys as girls opt to pursue a college engineering education. For students—mostly girls and underrepresented minorities—whose learning experiences do not provide positive effects, interventions can support their interest and performance and thus increase the likelihood that they will consider further studies and a possible career in engineering.
High School Preparation
Research indicates that URM individuals are more interested in high school science and math subjects, and have equal or greater intentions to major in science or engineering, than their White counterparts (Hanson 2009; NSF 2014), yet many more White men major in engineering than White women or URM men and women. HERI data on first-year students who wish to earn an engineering degree show nearly identical percentages of women and underrepresented minorities (20.6 percent and 20.5 percent, respectively), significantly lower percentages for both than in the general college population, where women are over 50 percent and African Americans, American Indians/Alaska Natives, and Hispanics of any race constitute almost a third of enrolled college students. Clearly, ability and interest are not the only contributing factors in pursuing a degree in science, technology, engineering, or mathematics (Seymour and Hewitt 1997).
Concerns about inequality of opportunity and the selection of engineers from a restricted pool that cannot guarantee the highest possible quality are vividly illustrated by the disparate access to mathematics and science courses in high school: 71 percent of White students and 81 percent of Asian students have access to a full set of such courses (Algebra 1 and 2, geometry, calculus, biology, chemistry, and physics), whereas only 57 percent of African American students and fewer than half of Native American students do (Morones 2014). Box 3-1 provides insights into the high school students who might enroll in engineering bachelor’s degree programs.
Math Preparation and Performance
Math preparation is a key variable for those entering engineering and must be considered all along students’ educational pathway. In elementary school boys and girls have equivalent math and science achievement; differences begin to be seen in middle school, when boys outperform girls in science, but not in math (Hill et al. 2010). Boys are also more likely than girls to indicate that they like math or science and believe that they are good at the subject
(Pajares 2005; Turner et al. 2008). These disparities become most evident among high school seniors, when scores on tests of math and science achievement show the most gender divergence (Hill et al. 2010). In addition, girls and boys differ not in the amount of mathematics they take in high school but in the number and type of science courses and Advanced Placement (AP) tests taken (e.g., boys are more likely to take the physics and Calculus BC tests).
Crucially, the K–12 educational experience varies for students of different backgrounds. URM students are more likely than White students to live in high-poverty neighborhoods with low-resourced schools (Annie E. Casey Foundation 2012), which tend to have fewer science facilities and other resources (Smith et al. 2013), less effective teaching (Max and Glazerman 2014), and teachers with less experience and preparation than schools with fewer disadvantaged and URM students (Smith et al. 2013).
At the high school level there may be discrepancies in access to courses, specifically AP programs, which provide advanced coursework and possible college credits for high school students who both complete the course and earn a high score on the AP exam. AP programs are available to a majority (85 percent) of US high school students, but are not equally accessible to all groups. African American students are less likely to attend a school with an AP program than White, Asian, or Hispanic students. Economically disadvantaged students (those eligible for a free or reduced lunch) are also less likely to have access to AP programs. And even when their high school offers one or more AP courses, URM and low-income students are less likely than their peers to take the course and the exam (Handwerk et al. 2008).
Interventions for Girls and Underrepresented Minority Students
One way to alleviate discrepancies in math preparation has been the systematic development of extracurricular programming, much of it funded by federal agencies such as the National Science Foundation (NSF) or the US Department of Education. Research shows that math self-efficacy can be enhanced by intervention (Betz and Schifano 2000; Hackett 1995). And most of the programming has been aimed at developing (and assessing) learning interventions designed to increase math self-efficacy and ultimately the choices of middle and high school girls and underrepresented minorities about entering STEM fields (OSTP 2013).
Extracurricular interventions include summer camps, Odyssey of the Mind,5 and other out-of-school activities. For example, a racially diverse group of high school students in a 2-week summer STEM program continued to explore STEM careers up to 18 months afterward and began to consider resources that could assist their progress toward that career as well as impediments they might face (Blustein et al. 2013). And participation in the after-school robotics program For Inspiration and Recognition of Science and Technology (FIRST) positively affects STEM-related interests and abilities in both girls and boys, both White and non-White, and from both high- and low-income families (Melchior et al. 2015). Other after-school programs have been shown to increase interest in engineering for low-income Hispanic students (e.g., Blanchard et al. 2015).
Girls’ self-efficacy and participation in engineering increase with interventions that promote math/science interests (O’Brien 1996), highlight the social value of engineering (Eccles 2007), increase families’ explicit support for math classes (Burgard 2000), promote positive environments (Dooley 2001), emphasize the potential positive outcomes of taking math and science classes (Edwardson 1998; Nauta and Epperson 2003), and explicitly work to increase math/science and engineering self-efficacy (Mau 2003).
A review of interventions to promote female and URM students’ pursuit of STEM careers showed that the interventions vary in content, intensity, and level of selectivity (Valla and Williams 2012). The authors called for more effective evaluations of such programs and offered recommendations for extracurricular programming: mentoring or guidance (particularly for high school students), help for students with challenging coursework, longer and more intensive programming, cultural sensitivity in program content, social components and peer-to-peer interactions, and financial assistance for field trips to colleges and industries.
Interventions can also promote resilience and coping skills so that students who experience academic challenges will persist. For example, some interventions teach that intelligence is flexible and can change over time, known as a “growth mindset” (Dweck 2007), rather than being fixed at birth. When students believe that intelligence is not fixed and that effort can help them overcome academic challenges, they are more likely to work harder and try different strategies to meet a challenge, and they also believe that they will learn and grow from the experience. Students who believe that intelligence cannot be changed tend to give up when challenged (Yeager and Dweck 2012). Teachers can promote the growth mindset by encouraging students to learn from failure and
5 Odyssey of the Mind is an international online problem-solving program targeted to teams of K–12 students.
try new solutions, and they can also help by praising students’ effort and learning process rather than their intelligence in solving a problem. Interventions that teach students to think of their brain as malleable and capable of growth have been shown to improve grades for all students and to lessen achievement gaps between students from different backgrounds (Yeager et al. 2013).
Research is needed to (1) determine whether K–12 interventions need to be better designed to attract capable students from all backgrounds; (2) expand the use of interventions shown to be effective; and (3) enhance understanding of the impact of deterrents such as the “masculine culture”—defined as the “features of a field (e.g., beliefs, norms, values, structures, interactions) that can cause women to feel a lower sense of belonging or be less successful than their male counterparts” (Cheryan et al. 2017, p. 6)—associated with engineering (Seron et al. 2016) as well as the history of engineering being dominated and defined by White men (Riley et al. 2014).
Role of Teachers
Discussion of student preparation must include the critical importance of the training and professional development of K–12 teachers, particularly those who teach math, science, or engineering at the high school level. The National Research Council’s Committee on Highly Successful Schools or Programs for K–12 STEM Education (NRC 2011) identified effective instruction as a key ingredient for strengthening STEM participation. The committee highlighted teacher-student engagement throughout the report, and specifically noted that “effective instruction capitalizes on students’ early interest and experiences, identifies and builds on what they know, and provides them with experiences to engage them in the practices of science and sustain their interest” (NRC 2011, p. 19). The report made the following recommendations for effective teachers: they should have (1) deep knowledge of their discipline, (2) a supportive system of accountability to support their professional development, (3) adequate instructional time, and (4) equal access to high-quality learning opportunities (this applies to both teachers and students).
It is also critical that primary and secondary teachers acknowledge and address any conscious or implicit biases or stereotypes they hold about groups, especially concerning academic performance, as well as stereotypes of engineers and engineering as a field. Teachers’ biases can affect their interactions with students (Dee and Gershenson 2017; Greenwald and Banaji 1995) and may cause some students to lose confidence in their ability to become engineers. Programs exist to help teachers and others acknowledge and overcome their biases, and can help participants not only learn to be aware of and minimize bias but also gain skills and the motivation to act to improve diversity (Moss-Racusin et al. 2014). Some programs include training in cultural competency, perspective taking, or empathy; others encourage interactions with individuals in social groups other than one’s own (Dee and Gershenson 2017). Further examples of promising practices include decorating classroom spaces to avoid stereotypical portrayals of STEM professionals (Cheryan et al. 2009) and promoting high standards of performance for all students and displaying confidence that each student can meet those standards (Eschenbach et al. 2014).
From a systematic review of the literature on STEM education for girls and women, researchers identified seven practices to help teachers create gender-inclusive STEM education (Scutt et al. 2013). Four of the practices focus on areas for teachers to emphasize in instruction: a foundation in calculus; spatial skills; communication skills in math, science, and engineering; and resilience in math and science. The other three practices are teacher efforts in what the authors call “building scaffolding to implement” this skill development: encouraging students to take an active expert role (e.g., teaching to their classmates), clear and fair grading policies, and reconsideration of group work, especially if girls are quiet in such groups. A subsequent study confirms the importance of such activities; it assessed teachers’ perception of their influence on students’ decisions to pursue STEM majors and students’ perception of their teachers’ influence, and found that teachers systematically underestimated their influence as well as the effect of engaged instruction (Lichtenstein et al. 2014b).
Self-Efficacy in Math and Science
Strong self-efficacy in math and science is likely to provide students with the wherewithal to overcome setbacks and persist in the face of obstacles, leading to interest in and consideration of an initial career choice in engineering.
Most studies of self-efficacy at the middle and high school levels have examined self-efficacy not for engineering per se but for math and/or science, or more broadly for STEM careers (e.g., a biologist or a mathematician). A retrospective study of over 2,000 first-year college students, for example, found that strong predictors of a STEM major were a parent in a STEM career, math self-confidence, high combined SAT scores and GPA, more time spent studying in high school, and high academic self-confidence (Moakler and Kim 2014). Similarly, a study of over 18,000 first-year students intending to major in engineering found that they were more likely to have a mother with at least a college degree and/or a parent employed in engineering (appendix C).
More learning experiences and more opportunities for performance accomplishments in math and science should lead to high self-efficacy in these areas, which may, in turn, lead to greater consideration of an engineering major. Indeed, more first-year students intending to major in engineering had completed four or more years of math courses and had at least two years of physics (appendix C). They also had higher high school GPAs and higher average SAT scores than those intending to pursue other STEM majors, and the students who completed an engineering degree had more engineering-related preparation in their primary and secondary education.
Examination of these variables by gender and race/ethnicity reveals differences among those planning to major in engineering (table 3-1). White students planning to major in engineering were more likely than URM students to have completed four or more years of high school math and two or more years of physics, and they had higher GPAs and higher SAT scores. Female students were slightly more likely to have completed two or more years of biology and had higher GPAs and SAT scores than males.
Math and science self-efficacy is a powerful predictor of math grades and achievement for both boys and girls (Hackett and Betz 1989; Lent et al. 1991; Schunk and Pajares 2001), and there is evidence that it is highly predictive of persistence in STEM fields (Hackett 1995; Schunk and Pajares 2001). For example, among 8th grade girls who had aspired to STEM careers, general academic proficiency predicted persistence six years later, but math self-efficacy was a greater predictor of entry into a college program in engineering (Mau 2003). A study of 2004 high school graduates surveyed in 2002 and again in 2006 found that their choice of a STEM major was influenced by exposure to math and science in high school, math ability, and math self-efficacy, but these experiences increased the motivation of White students more than that of URM students toward STEM majors (Wang 2013).
|Percent completing courses or earning A– or better GPA; average SAT scores|
|Among other STEM and engineering majors||Among engineering majors|
|Other STEM major n=58,186||Engineering major n=18,128||White/Asian n=13,340||URM n=2,398||Significance||Male n=14,011||Female n=4,117||Significance|
|4 or more years HS matha||89.6||94.3||95.0||91.5||***||94.2||94.9||*|
|2 or more years HS physicsa||61.9||71.6||73.7||64.4||***||71.8||71.1||*|
|2 or more years HS biologya||60.8||42.2||42.0||42.6||**||40.4||48.8||***|
|HS GPA: A− or bettera||56.0||62.1||66.8||43.5||***||58.8||74.6||***|
|Average SAT scoreb||1148||1231||1260||1104||***||1228||1243||***|
Source: 2012 CIRP Freshman Survey, Higher Education Research Institute, UCLA.
a Compared using crosstab/chi square.
b Scores represent means rather than percentages; scores compared using a t-test.
* p < .05, ** p < .01, *** p < .001.
K–12 Student Engineering Outcome Expectations
Many interventions that focus on learning experiences also seek to help students develop realistic and positive outcome expectations about pursuing an engineering degree. Interventions can address expectations of self, others, and/or physiological experience; for example, students will be more likely to enter an engineering major if they believe their family and friends will approve, if they feel excited about the major, and if they anticipate accruing positive benefits, such as a high salary (Wiswall and Zafar 2015b).
Financial outcome expectations (e.g., believing that engineers are well paid and that an engineering degree will guarantee a job) positively predict engineering-focused studies and plans. Occupations that appear to offer high lifetime earnings generally appeal more to students than those with low likely lifetime earnings, and this expectation can affect choice of college major. In fact, in some cases students who were misinformed about earnings associated with a particular major changed their intended major when correctly informed (Wiswall and Zafar 2015b).
But the earnings-major effect is weak relative to other factors, such as perceived enjoyability of the work, expectation of success, or feeling of belonging in the field (Arcidiacono et al. 2012; Beffy et al. 2012; Long et al. 2014; Montmarquette et al. 2001; Wiswall and Zafar 2015a). For women more than men, personal beliefs about how enjoyable engineering coursework would be for them affect decisions to major in engineering (Zafar 2013). Interventions to correct negative expectations about potential success or feeling of belonging in engineering include interacting with engineers (Sweeder and Strong 2012), presenting accurate media information about an engineering career (Shoffner and Dockery 2015), and countering gender and racial stereotypes about engineers (Deemer et al. 2014).
Families play an essential role in helping to set outcome expectations about engineering. An intervention to increase parents’ perception of the utility of STEM courses increased course taking for high-achieving girls and low-achieving boys. The authors hypothesized that parents of boys—whether low or high achieving—expect them to be capable of success in STEM courses, whereas parents of low-achieving girls assume they will not be successful in such courses (Rozek et al. 2015).
Although most US adults think they know what engineers do, and more men than women think they know about the field, they do not consider themselves knowledgeable about engineering. Overall, most US adults do not think that engineers care about societal concerns or improving quality of life and that engineering as a field is not inclusive for women or underrepresented minorities. Almost half believe that engineers invent products that harm people and society. Despite these negative perceptions, over 75 percent of parents would be equally pleased if their child chose to be an engineer, doctor, or scientist. However, their reasons differed somewhat for boys and girls,6 suggesting that parents might communicate different outcome expectations to their children.
Gender-Related Differences in Interests
Six vocational personality types have been identified, determined by scores on an inventory of interests: Realistic (working with things), Investigative (scientific work), Artistic (creative self-expression), Social (working with people), Enterprising (leading/influencing), and Conventional (detail oriented) (Holland 1997). Individuals may be one or a combination of types, and work environments can also be categorized by these types. The assumption underlying the assessment of interest types to help people choose occupations is that if an individual is similar in interests to the people in that occupation, s/he is predicted to be more satisfied in the occupation, a prediction that has been supported in several studies since the mid-1950s (Hansen 2013). This is helpful for individuals in confirming that a career choice is a good fit for them, or helping undecided individuals to explore career options.
Engineering occupations are usually categorized as Realistic or Investigative (Donnay et al. 2005); individuals who have a Realistic and/or Investigative personality would be expected to be interested in an engineering occupation. Men tend to score higher than women on the Realistic and Investigative interests, and women higher on the Social and Artistic interests (Hansen 1978; Su et al. 2009), which may account in part for the lower entry of women into engineering (Su et al. 2009). Although disparities exist between men and women on the Things--
6 Information from an April 2014 Harris Interactive Poll on American attitudes on engineering, conducted on behalf of the NAE.
People dimension of interests—men generally prefer to work with things and women with people—the gender gap in these interests is smaller than the STEM employment gap, suggesting that other factors affect career choice (Su et al. 2009). Mean disparities in interests have also been observed across racial and ethnic groups, although these are relatively small and have little practical effect (Fouad and Kantamneni 2008; Tracey and Sodano 2013).
A study of over 200,000 first-year college students planning to major in STEM areas found that both ability (as measured by ACT scores and high school GPA) and interest predict both the choice of and persistence in a STEM major for men, and predict STEM major choice more strongly for women than for men (Le et al. 2014). Echoing other researchers, the authors note that obstacles such as social and cultural norms affect females’ choices of a STEM or non-STEM field independent of the students’ interest or academic abilities.
Taken together, these results suggest that even women and URM students who are interested in STEM fields do not enter them because of other factors, which are discussed in the next section.
Contextual Influences at the K–12 Level: Barriers and Supports
Contextual influences are “variables that enhance or constrain” progress toward a career (Lent et al. 2000, p. 36; 2003). Background (distal) influences, such as family socioeconomic status, may enhance or limit learning opportunities over the long term. Proximal factors that hinder or facilitate the individual’s implementation of a choice are likely to be more temporally specific and may be particular to the individual (such as family) or the larger economic climate (such as a recession) at the time of the decision. Chapter 1 reviews distal factors; this section discusses barriers and supports closer to the individual.
Positive variables could be supportive family members, mentors, or financial assistance, while barriers might be financial constraints, family obligations, or discrimination. These factors do not affect an individual’s decisions equally (e.g., discrimination may be more strongly felt as a negative factor than having financial assistance is felt as a positive one) and may be related to each other (e.g., mentors could provide learning opportunities as well as advice for seeking financial assistance) (Lent et al. 2003). They affect individuals differently, and it is important to understand this in order to develop appropriate interventions.
The choice to major in engineering is influenced by barriers and supports that correlate significantly with outcome expectations, self-efficacy, coping efficacy (resilience), and interests (Lent et al. 2003). They indirectly influence choice goals and actions in engineering by affecting self-efficacy, which shapes interests, goals, and persistence in an engineering major. They are distinct constructs (not opposite ends of a continuum), so strongly felt barriers do not necessarily accompany weak supports and vice versa (Fouad et al. 2010).
A study of high school students created a scale for students to assess anticipated educational and career-related barriers and found that, in general, female and Mexican American high school students expected to face more potential barriers to their educational (e.g., financial situation) and career (e.g., discrimination on the job) pursuits than did male and European American high school students (McWhirter 1997). Examination of sources of internal and external barriers and supports—families, teachers, stereotypes about who is good at math or science, social circles, or the students themselves (e.g., individual interest in math or science, test anxiety)—shows that they differ across grade levels, gender, and subject area (Fouad et al. 2010).
Female students in math in middle school, high school, and college reported that teachers were both a barrier (e.g., “did not give advice on careers”) and a support (e.g., “my teachers expect me to do well”). Boys, on the other hand, reported the following barriers in math: lack of role models in middle school, uninspiring teachers in high school, and lack of opportunities in college. They considered math teachers a support in middle school and college, but in high school having clear goals was the greatest support.
In science, teachers were a strong support for middle and high school girls, while college women were strongly supported by their own interest. Lack of inspiration and lack of advice from teachers were barriers for middle school and college females, while high school girls reported test anxiety as the highest barrier. For middle and high school boys, teachers were the strongest source of support, whereas for college men it was an interest in science. For middle school boys, the highest barrier was that their friends were not interested in science; for high school boys, it was ineffective teachers, and for college males lack of support from parents was the strongest barrier (Fouad et al. 2010).
From K–12 through college, a variety of interactions and experiences can cause girls and women to feel less sense of belonging in engineering than their male contemporaries. Influential factors in this cultural makeup include stereotypes about the sorts of people who work in engineering, negative perceptions about the engineering abilities of girls and women, lack of women engineers who can serve as role models, and “negative interpersonal relations, subtle and overt denigration of skills,…[and] favoritism toward male and majority students” (Lichtenstein et al. 2014a, p. 321). These factors all constitute what several authors have called “a chilly climate.”
To offset the “masculine culture” and chilly climate, teachers “must signal to girls and boys equally that they belong in the field. If learning opportunities reinforce rather than counteract the current masculine culture of these fields and do not give girls the knowledge that they can achieve success in these fields, then providing girls with more experience may widen rather than lessen gender gaps” (Cheryan et al. 2017, p. 15, italics in original). Fortunately, faculty strategies exist to increase women’s and URM college students’ consideration of engineering as a career: they involve encouragement of respectful classroom interactions among peers, positive faculty-student interactions both in and out of the classroom, and innovative instructional strategies to engage students, such as cooperative learning (Lichtenstein et al. 2014a).
Policies Affecting Undergraduate Engineering Enrollment
Policies can affect undergraduate enrollment in engineering programs by explicitly aiming to increase STEM enrollments or through indirect measures. They may also aim to equalize math and science education facilities and resources across schools, especially those that serve a high proportion of low-SES students and families.
Policies can be effected through vehicles such as federal funding. For example, an aim of the NSF initiative on Improving and Understanding STEM Education: Education and Human Resources is “increasing the number and diversity of STEM [undergraduate] students.”7 And the US Department of Education’s Upward Bound Math-Science (UBMS) program provides enhanced instruction in math and science topics to students from low-income families or whose parents do not have bachelor’s degrees; a majority of participants are URM students. UBMS has been found to improve participants’ high school grades, bolster enrollment in high school chemistry and physics courses, and increase the probability of participants’ enrolling in and completing a bachelor’s in science, engineering, or mathematics (US Department of Education 2007).
Policies can also be implemented through colleges and universities that adopt federally funded comprehensive interventions, such as the NSF’s Model Institutes for Excellence (Rodriguez et al. 2005), which included the following key elements: plans for recruitment and supporting transitions from other institutions, undergraduate research, faculty and curriculum development, infrastructure improvement (classrooms and labs), advising for graduate school or employment, and academic, financial, and social support for students (Fouad and Singh 2011). Because the project was available only to minority-serving institutions, it provided targeted funding and programming to increase STEM enrollment and graduation of URM students as well as a model that could work at other institutions to increase degree attainment (Rodriguez et al. 2005).
Institutional policies also play a role in undergraduate engineering enrollments. For example, many engineering schools rely more heavily on math ACT scores as an admissions criterion than on high school GPA, a practice that favors White and Asian male applicants, who are more likely both to take these tests and to score well on them. But as mentioned above, for some underrepresented groups, high school GPA may better predict success in an engineering program: Individuals with a high GPA in high school but low standardized test scores were more likely to graduate with an engineering degree in six years than those with high ACT math scores but a low high school GPA (Myers 2016). More URM and female students are in the high GPA/low test score category, and admissions policies that place more weight on math ACT scores than other factors may keep these students out of engineering programs. In addition, some research suggests that considering candidates’ affective and cognitive traits rather than test scores in application decisions increases the number of women who enter engineering programs (Holloway et al. 2014).
Other institutional policies take a systems view of admissions and retention efforts to increase diversity in engineering, combining flexible admissions policies with support and community for students once they arrive on campus. For example, the GoldShirt program began in 2009 at University of Colorado (CU) Boulder and is now replicated in five other US engineering institutions. Before launching the program, GoldShirt staff analyzed admissions ratings of URM engineering graduates in 2003–2008 to determine the profile of a successful student. They then worked with the university’s admissions office to identify URM applicants who fit that profile whether or not their test scores met the institution’s current admissions requirements, which had increased over the same period. Students admitted directly to the engineering school (rather than accepted elsewhere in the institution and expected to transfer) complete, as needed, a performance-building GoldShirt year of math, physics, and other courses that prepare them for the engineering curriculum. They live on campus with other engineering students and participate in tutoring and other academic support programs. After completion of the GoldShirt year, they move into their discipline-specific courses (Ennis et al. 2010). The majority of GoldShirt students are underrepresented minorities, first-generation students, and/or low-SES students—who all succeed in engineering.
The literature provides some cautionary tales on unintended consequences of well-meaning policies. For example, the increase in state-provided merit-based scholarships has had an unexpected negative effect on the numbers of US students obtaining a STEM degree (Sjoquist and Winters 2015). Although the mechanism is not known, one possibility is that the need to obtain a high GPA in high school and to maintain it in college (to ensure continued scholarship funding) leads students who receive low grades in introductory courses (as more often happens in objectively graded STEM courses than in subjectively graded non-STEM introductory courses) to avoid upper-level courses in those disciplines (Achen and Courant 2009; Sabot and Wakeman-Linn 1991).
In considering the factors that influence students’ study of engineering in college, the committee looked beyond the SCCT model to explore other influences and the associations between them. One outcome of interest to educators and employers is persistence: remaining in an engineering program and earning a degree. Also known as retention, persistence is affected by self-efficacy and relates to actions in the SCCT model.
Studies have begun to identify characteristics of students who leave an engineering major and those who persist to complete an engineering degree. A number of students earn their degree after attending two or more 2- or 4-year institutions or not attending school for some portion of time.8 In fact, the traditional model of full-time students entering and graduating from the same 4-year institution is not true for a majority of STEM students (NASEM 2016), although most research has focused on them.
Analysis of data from the Multiple-Institution Database for Investigating Engineering Longitudinal Development (MIDFIELD; https://engineering.purdue.edu/MIDFIELD) showed that engineering had the highest rate of persistence of matriculated students among the majors studied (listed in table 3-2)—57 percent of students who matriculated in engineering persisted in the field through their eighth semester (Ohland et al. 2008).9 Demographically, the students in this database are similar to other college students except for the low proportion of women. Among nontransfer students, the proportion of URM students in engineering is similar to other majors (Ohland et al. 2008). Among transfer students (from 2- and 4-year schools), those who enter engineering programs are less likely to be ambivalent about their commitment to graduate in engineering (Litzler and Young 2012).
Engineering students’ engagement—their involvement and attention in class, time spent studying or in other educational interests, and other academic activities (Chen et al. 2008)—is similar to that of students in other majors
8 These students are difficult to track through their educational career because data systems at the institutional, state, and national levels do not connect well with each other.
9 Migration from another major into engineering is low—only 7 percent of students begin in another major and switch into engineering, which contrasts with other majors that have large populations of students who transferred into them (Ohland et al. 2008).
TABLE 3-2 Multiple-Institution Database for Investigating Engineering Longitudinal Development (MIDFIELD) data showing persistence and enrollment in various majors to eighth semester, 1987–1999 cohorts.
|Major group (in decreasing order of PG8)||Matriculated in major group||Students enrolled in same group in the eighth semester||Total enrolled in each group at eight semesters||Persistence in group to eighth semester (PG8)|
A&H = arts and humanities; bus = business; NA = not applicable; PG8 = persistence to 8th semester; STM = science, technology, math. Reprinted with permission from Ohland et al. (2008).
and declines over time (Ohland et al. 2008). The highest risk of students leaving engineering is in their third semester (compared to the rest of their school years), although women are at higher risk of leaving engineering in semesters 3 to 5 than men (Min et al. 2011). Women who make it through that risk period are more likely to earn a degree in engineering relative to their male peers (i.e., men are more likely than women to drop out of engineering after their fifth semester), and White and Asian American students of both sexes complete engineering and STEM degrees at higher rates than their URM peers (see appendix C).
Students with lower SAT math scores are more likely to leave engineering than those with higher scores. In contrast, students with comparatively low verbal scores (between 200 and 500 out of 800) are slightly more likely to persevere than students with scores between 500 and 600 (Min et al. 2011).
Interestingly, students who leave engineering are more likely to persist to graduation in their new field than are students who begin in but leave other majors (Ohland et al. 2008). Former engineering students find success in many different majors, but commonly choose business (Ohland et al. 2008), economics, finance, psychology, integrative physiology, biochemistry, or math (Forbes et al. 2015).
Students’ decision to leave engineering or stay to complete their degree may be due to a variety of factors, internal (perceived cost and utility, self-efficacy, academic and social self-concept, and engineering identity or sense of belonging) and external (participation in a cocurricular experience, contextual supports or barriers, classroom culture, and institutional and programmatic climate). These factors are reviewed below.
Students’ decisions about engineering are swayed by internal factors that may be characterized as nonacademic (Marra et al. 2012), individual (compared to institutional factors; Meyer and Marx 2014), or characteristics and perceptions (compared to experiences; Litzler and Young 2012). Whatever the category, research results agree that decisions about engineering in college involve deeply personal choices. For example, engineering students in their senior year most often list intrinsic (i.e., not salary-based) motivations as their primary reason for choosing the field (Sheppard et al. 2010). In fact, internal factors—particularly outcome expectations, self-efficacy,
academic and social self-concept, and identity or sense of belonging—may have greater influence than external factors (Marra et al. 2012).
Outcome Expectations (Social Cost and Utility of a Degree)
Compared to other majors, engineering majors face a greater workload demand (as measured by self-reported time spent preparing for class) that often requires them to choose between pursuing an engineering degree and having additional and alternative educational and social experiences such as taking classes outside their major or participating in activities that are not engineering-related (Lichtenstein et al. 2010). Engineering students weigh the perceived costs in time, effort, and psychological impacts alongside the perceived utility of their future degree (Matusovich et al. 2010) in their decision making.
Self-efficacy not only influences college completion (Brown et al. 2008) and career decisions (Betz and Hackett 1981) but is a key predictor of persistence in STEM fields (Rittmayer and Beier 2009) and in engineering specifically (Brainard and Carlin 1998). Students’ confidence in their professional expertise is also directly related to the likelihood of their persistence in engineering majors (Cech et al. 2011).
Four types of experiences affect self-efficacy: personal accomplishments (or mastery experiences), vicarious learning, social persuasion, and physiological states, of which personal accomplishments have the strongest impact for engineering students. These four types of experiences have been shown to influence engineering students’ self-efficacy more than academic success, institution, year in school (i.e., first year or senior), and race/ethnicity (Marra et al. 2009).
Females exhibit consistently lower self-efficacy than males (Cech et al. 2011; Marra et al. 2009; Schreuders et al. 2009). Even when males and females had equivalent high school preparation, females display lower confidence in engineering tasks (Schreuders et al. 2009). Similarly, females exhibit a disparity in their actual and perceived competence, doing well in their classes despite their beliefs to the contrary (Seymour and Hewitt 1997). Males in the same study did not reveal this disparity: although both men and women performed similarly in their classes, men were more confident in their abilities than women. However, there is evidence that gendered differences in engineering confidence decline as experience increases (Cech et al. 2011).
Although research shows a positive relationship between students’ self-efficacy and engineering persistence, confidence in various engineering skills relates to persistence differently. For example, confidence in math or technical skills is related to higher enjoyment and persistence in engineering studies (Brainard and Carlin 1998; Eris et al. 2010); among engineering students in their senior year high confidence in professional skills is related to intentions to pursue non-engineering work, although it is unknown whether there is a causal relationship between the two or if they are related through a third factor such as family income or network size (Sheppard et al. 2010). Because beliefs about important skills and abilities for engineering careers change over the course of one’s education and employment as experience is acquired (Winters et al. 2013), further domain-specific self-efficacy research may reveal more specific links between confidence in engineering skills and decisions about engineering education and careers.
Academic and Social Self-Concept
Hurtado and colleagues (appendix C) examined how students’ self-reported self-concepts changed from their first year in college (2004) to their fourth (2008). The authors examined academic self-concept (academic ability, drive to achieve, mathematical ability) and social self-concept (leadership, public speaking ability, social self-confidence), and compared scores among non-STEM, STEM, and engineering students. Engineering students reported the highest sense of academic self-concept and were significantly stronger in this domain than the other two groups at both college entry and senior year. Studying with classmates was correlated with gains in academic self-concept and also with persisting in engineering.
The engineering students also appeared to gain the most in their social self-concept relative to their non-STEM or other STEM peers. These gains strongly correlated with studying with other engineering students and faculty support and mentoring (appendix C).
Engineering Identity and Sense of Belonging
The extent to which engineering students identify as engineers or feel as though they belong in an engineering community (e.g., a classroom or department) plays a critical role in decisions about remaining in an engineering major (Danielak et al. 2014; Marra et al. 2012; Matusovich et al. 2010; Meyers et al. 2010, 2012; Pierrakos et al. 2009). Stevens and colleagues (2008, p. 365) credit identification as an engineer as “the compass that guides one to make a pathway through engineering” (italics in original). Creating an engineering identity involves not only gaining knowledge of the engineering practice (Pierrakos et al. 2009; Stevens et al. 2008; Tonso 2007) but also aligning one’s sense of self with engineering (Eccles 1994; Matusovich et al. 2010; Pierrakos et al. 2009).
One of the factors behind gender and other disparities in engineering and other STEM fields may be a perceived similarity to the people in an occupation—that is, whether one would fit in with others in that occupation. This is a stronger predictor than interest for an individual’s consideration of an occupation (Cheryan and Plaut 2010). Research on engineering identity reveals that the feeling of belonging in engineering is deeply tied to gender. Female students are less likely than males both to feel included in engineering environments (Cheryan et al. 2017; Marra et al. 2012) and to be identified by males as engineers (Tonso 2007), and they are more likely to report that they feel a need to deemphasize some parts of their identity in order to be accepted in engineering (Tonso 2007, 2014). Women’s experiences in engineering education also disrupt their ability to match their sense of self with the profession (Seron et al. 2016).
In fact, because engineering requires both technical and social competencies, “engineering identities” challenge both male and female stereotypes: males downplay their social skills and females feel they have to prove their technical skills (Faulkner 2007). But because technical skills have typically been valued over social skills in engineering, the barriers to engineering identities and belonging are felt more keenly by women (Faulkner 2007).
Moreover, because women tend to express interest in helping and people-oriented professions, which are not common perceptions of engineering careers, fewer females than males perceive engineering as a career that fits their sense of self (Eccles 2007). Greater recognition of engineering as a profession that serves society and requires social skills can encourage participation in engineering by women (Eccles 2007; Faulkner 2007; Hewlett et al. 2008), and efforts to highlight the importance of engineering for society call for actively promoting the idea that “engineering and engineers can make a difference in the world” (NAE 2008, p. 11). In addition to the message that engineering includes understanding, defining, and solving important societal problems using a mix of technical and professional skills, effective messaging about the field incorporates discussion of interdisciplinary work, social consciousness, creativity, and multicultural understanding. This recognition has the potential to improve gender diversity in engineering.
Finding: Lack of knowledge about the profession is a significant barrier for potential engineers from populations underrepresented in engineering. Messages that describe engineering as a field that involves understanding, defining, and solving important societal problems using a mix of technical and professional skills, interdisciplinary work, social consciousness, creativity, and multicultural understanding impart knowledge of the field to all students, and seem to be particularly important for female and URM students, who otherwise may not see engineering as a viable option for themselves.
Instructional strategies that use holistic, real-world applications of STEM tend to be more effective for attracting and retaining women and underrepresented groups (Margolis and Fischer 2002; Sadler et al. 2000). And outside the classroom, engineering service organizations, such as Engineers Without Borders (EWB-USA), have witnessed tremendous growth with roughly balanced gender populations (EWB-USA 2012). Inspired by the gender diversity of such organizations, a recent study sought to understand the personality traits and motivations of engineers involved in EWB-USA in order to help broaden participation in engineering (Litchfield and Javernick-
Will 2015). While both EWB-USA members and nonmembers exhibited well-developed engineering personality traits and intrinsic engineering interests, the members had significantly stronger personality traits for openness to experience and agreeableness, deeper motivations for social good, and broader interests than nonmembers (Litchfield and Javernick-Will 2015).
Finally, engineering identity is affected by external factors (discussed in the next section) that can in turn influence decisions about engineering. If identification with engineering—“the compass” that guides an individual student through engineering studies—is missing, the student may struggle to navigate through contextual challenges such as a chilly classroom climate (e.g., negative interpersonal relationships, intentional or unintentional disparagement of the abilities of women and minority students) (Stevens et al. 2008).
External Factors: Contextual Supports and Barriers
Career choices and even options can be importantly shaped by contextual experiences during students’ undergraduate years. Studies have found that, even more than grades or ability, students’ decision to persist in engineering is influenced not only by individual demographic characteristics (as discussed above) but also by contextual factors such as educational institution, attitudes of peers, faculty, or family, program structure, advising quality, curriculum, and instruction (Eris et al. 2005, 2007; Seymour and Hewett 1997). Even a single experience—an internship, faculty interaction, or mentor’s advice—can become the basis for overgeneralizations about career options (Danziger 2006; Roska 2005; Shauman 2006) and sway a career decision (Lichtenstein et al. 2009). Positive experiences can mediate the effects of individual characteristics and are therefore critical for students dealing with a negative interaction or climate at their institution (Litzler and Young 2012). In addition, students whose parents did not attend college (“first-generation students”)—a group that includes a higher proportion of women and underrepresented minorities (Nunez and Cuccaro-Alamin 1998)—have garnered recent research attention. They are of interest both because of their underrepresentation and because they may need more academic and social support than other students because they are unfamiliar with university life and procedures and do not know how to navigate them (Pascarella et al. 2004). Almost 20 percent of individuals majoring in engineering are first-generation students (Sheppard et al. 2010).
Extra- and Cocurricular Experiences
Engineering undergraduates participate in activities outside the classroom as much as their non-engineering peers, although they tend to focus on activities related to engineering (Chubin et al. 2008). About 85 percent of them have had an internship or cooperative experience by their senior year (Lichtenstein et al. 2010). These experiences, if
high quality, can improve students’ work self-efficacy (Raelin et al. 2014) and are positively related to retention in an engineering major: students who participate in internships and extracurricular activities like clubs or organizations related to their major are retained at a higher rate than students who do not have such experiences (appendix C) and they are more likely to pursue an engineering job after college (Brunhaver et al. 2012; Sheppard et al. 2010).
Engineering-related extracurricular experiences are related to higher confidence in professional skills as well (Sheppard et al. 201010). A comparison of engineers involved and uninvolved with Engineers Without Borders found that EWB-USA members perceived higher confidence in their professional skills (but similar confidence in their technical skills) than their peers not involved in engineering service organizations (Litchfield et al. 2016). It is worth noting that students who are more confident in their professional and interpersonal skills tend to have plans focused on non-engineering work or graduate school (Sheppard et al. 2010), while those with postgraduation plans in engineering tend to be less confident of their professional and interpersonal skills (Atman et al. 2010; Sheppard et al. 2010).
People: Families, Peers, Professors, Mentors
Most students who persevere in engineering were motivated to pursue the subject by a high school mentor; conversely, those who do not persist were pressured by their families to study the subject (Eris et al. 2010). Positive interactions with faculty also play a significant role in undergraduate students’ persistence in engineering, satisfaction, and career decision making (Lattuca et al. 2006; Pascarella and Terenzini 2005) by enhancing confidence in problem solving, engineering design, and interpersonal skills (Chen et al. 2008). Such interactions are a source of self-efficacy, and they are particularly important for female students in setting and pursuing career goals in engineering (Amelink and Creamer 2010). Women’s persistence in engineering is positively associated with attending office hours, meeting with teaching assistants, and receiving mentoring (Tate and Linn 2005); poor teaching and advising are associated with both women and men transferring out of engineering (Marra et al. 2012).
Participation in a mentoring program has led to higher retention of students, especially women, compared to those that did not participate (Marszalek et al. 2009; Sheppard et al. 2010). Mentors who provide images of futures (outcome expectations) and ways to obtain those futures are important for student decision making (Stevens et al. 2008). Mentors can also help students develop coping strategies: STEM switchers and nonswitchers faced similar structural and cultural barriers in their majors, but those who persisted used better coping strategies (Seymour and Hewitt 1997).
Peer study groups are positively correlated with retention. Women who participate in tutoring and peer study groups are significantly more likely to persevere in engineering (Tate and Linn 2005; appendix C). Students who felt a sense of community and collaboration with their peers had the lowest risk of attrition (Litzler and Young 2012).
Peers can also improve retention and student experience outside of study groups. The Posse STEM Program (www.possefoundation.org/specialized-initiatives) identifies and recruits students from diverse backgrounds who may not meet traditional college admissions criteria and forms 10-person multicultural teams who begin training together in high school and then attend the same undergraduate institution and continue working together. The program provides full-tuition scholarships to several partner institutions, supports the students during their studies, and works with the partner institutions to make the climate and community more accepting of students from all backgrounds. Posse scholars have a 90 percent graduation rate and receive continuing support from the community as they begin their careers.
Classroom Experiences and Climate
Satisfaction with instructors has been positively associated with both overall satisfaction with college experience (Chen et al. 2008) and plans to pursue an engineering career (Amelink and Creamer 2010; Chubin et al. 2008; Margolis and Kotys-Schwartz 2009). Conversely, research has consistently shown that reduced participation in
10 This study is based on data from the Academic Pathways of People Learning Engineering Survey (APPLES) administered to engineering students at 21 US engineering colleges and schools in spring 2008.
engineering is associated with a “chilly climate,” “an inhospitable environment” for women and underrepresented minorities (Lichtenstein et al. 2014a). As noted in chapter 2, some pedagogies have shown promise in decreasing performance gaps between majority and underrepresented groups and in retaining women and URM students in engineering education.
The inhospitable environment can include overtly discriminatory practices, subtle microaggressions, or implicit bias that suggests that individuals from underrepresented groups lack the ability to become engineers. Students who repeatedly experience these behaviors from peers or faculty begin to feel isolated and their academic performance suffers (NASEM 2016). For example, students who heard faculty convey stereotypes about racial or ethnic groups in class were less likely to remain in engineering (appendix C). An earlier study similarly reported that attrition from STEM majors was not based entirely on ability but that classroom climate and activities were major factors in choices to persist (Seymour and Hewitt 1997).
In addition, women and men have distinct experiences, and different interpretations of them, as they progress through their courses, internships, and other engineering activities. These professional socialization experiences serve to encourage men to enter engineering careers while deterring women (Seron et al. 2016), although a female role model (e.g., a faculty member in the same discipline) can help women students overcome negative attitudes toward the field as well as stereotype threats to their performance (Drury et al. 2011). Implicit biases held by faculty members may cause less effective mentoring of students from different backgrounds; for example, to avoid appearing biased toward a particular group, a majority-group faculty member might withhold all criticism from the student. This behavior both denies students quality feedback on their work and sends a message that they lack ability in the field (NASEM 2016). URM faculty are critical to the retention of underrepresented students both because they serve as role models and mentors (Chubin et al. 2005; May and Chubin 2003) and because minority students are more likely to have positive interactions with them (May and Chubin 2003).
Students who know how to navigate an academic pathway, thanks to coaching from a mentor or social support, may avoid these negative classroom experiences by taking courses with other faculty or at other institutions. The navigation of seemingly small programmatic decisions can make big a difference in decisions to stay in or leave engineering (Stevens et al. 2008).
Institutional and Programmatic Factors
An analysis of MIDFIELD data showed that institutional factors are a stronger predictor of persistence than individual racial differences (Ohland et al. 2011). A school’s mission affects its culture and opportunities, which, in turn, can undermine or support retention in engineering. For example, students who attend public technical schools with a mission to produce engineers and science technology majors often have fewer alternatives for nontechnical coursework and are more likely to complete their degree in and pursue a career in engineering (Lichtenstein et al. 2009). Conversely, students who attend schools that offer other majors and who have the latitude to take courses outside their major have more opportunities to explore and shift majors, correlating to a greater likelihood of migration out of engineering fields (Lichtenstein et al. 2009).
Finding: The low numbers of women and underrepresented minorities in engineering education and the engineering workforce dictate that the pathways and motivations of every group be considered fully and that the entire engineering community—educators, employers, research funders, policymakers, and engineering professionals—work collaboratively to improve diversity.
Students’ college experiences affect their postgraduation plans (Amelink and Creamer 2010; Margolis and Kotys-Schwartz 2009; Ro 2011), and the plans described by college seniors predict their career decisions (Astin 1993; Brunhaver 2015; Pascarella and Terenzini 2005).
What do the career plans of engineering students look like? A recent analysis of APPLES data shows that over 80 percent of engineering juniors and seniors reported that they were likely to work in an engineering occupation
(Gilmartin et al. 2017; see also Sheppard et al. 2014), although a quarter also expressed interest in non-engineering occupations. Commitment to these plans differs by gender: more women than men expressed interest in a non-engineering occupation and more men than women were interested in an engineering occupation.
However, the picture of these students’ plans is more complex: less than a third (28 percent) of engineering students are committed exclusively to an engineering path, and 65 percent have flexible and/or undefined postgraduation plans. This suggests that a majority of engineering students either see their career as including both engineering and non-engineering work (i.e., a combination of plans) or are uncertain about how their career might include engineering and/or non-engineering work (Gilmartin et al. 2017; Sheppard et al. 2014).
Intrinsic psychological motivation (e.g., feeling good when doing engineering-type activities, thinking that engineering is fun and/or interesting) is a strong positive predictor of engineering-focused plans. Other positive predictors include learning experiences and environmental factors (e.g., co-ops and internships, active involvement in engineering classes), contextual factors (e.g., likely salary based on the labor market), and institutional factors (e.g., public vs. private educational institution) (Gilmartin et al. 2017; Sheppard et al. 2014).
Positive predictors for non-engineering-focused plans include high self-efficacy in professional/interpersonal skills, involvement in non-engineering activities, and institutional factors (e.g., private institution). Compared with their peers, civil engineering majors are more likely to have engineering-focused plans, while chemical and biological/biomedical engineering majors are more likely to have non-engineering-focused plans (Gilmartin et al. 2017; Sheppard et al. 2014). Commitment to engineering-focused plans seems to vary along with the culture of disciplines (Brawner et al. 2012, 2015). It is worth noting that family income (taken as representative of socioeconomic status) and self-reported undergraduate GPA had no direct predictive power in differentiating engineering- vs. non-engineering-focused plans (Gilmartin et al. 2017; Sheppard et al. 2014).
Those with engineering-focused plans (as compared with “all other plans”) have greater intrinsic psychological motivation and involvement in engineering classes and less professional/interpersonal self-efficacy (similar to what was found by comparing students who have engineering-focused plans with those who have non-engineering-focused plans). Students with a higher self-reported GPA were more likely to have engineering-focused plans than “all other plans,” and URM women were more likely to have other plans (again, as compared with engineering-focused plans) than were their peers (the average among URM men, non-URM women, and non-URM men; Gilmartin et al. 2017).
A survey of engineering students in their senior year to identify factors influencing those who intended to leave the field (9 percent) and those who had reservations about entering it (34 percent) did not find any gender differences in either group (Margolis and Kotys-Schwartz 2009). Students in both groups felt less prepared, had poorer perceptions of their internship or capstone experience, were less satisfied with the instruction they received, and rated salary as less important and coworkers more important than those who intended to pursue a career in the field.
Engineering-related extracurricular experiences are generally positively associated with retention in engineering, whereas students who pursue non-engineering experiences, such as internships in non-engineering fields, may choose to leave engineering to pursue careers in the field of their internship; for instance, an engineering student who completed an internship in finance went on to pursue a job in that field (Lichtenstein et al. 2009). Studies have similarly found that participation in a non-engineering student organization has a negative and significant association with intentions to pursue an engineering career (Brunhaver et al. 2012; Sheppard et al. 2010). And engineering graduates who participated in a study abroad program were more likely to work in a non-engineering job than those who did not, which might be related to improved self-efficacy in non-engineering activities or more positive outcome expectations for non-engineering careers than for engineering careers. Alternatively, some companies may prefer employees with experience in an engineering internship, so those who interned outside the field would be less desirable candidates and might therefore be more likely to work in a non-engineering occupation (Brunhaver et al. 2012).
An engineering degree leads to a variety of career pathways and options, so there are no simple answers to questions about the postgraduation pathways of engineering majors. As illustrated in chapter 1, over 40 percent of engineering graduates seek additional education (e.g., an MS, MBA, PhD, or even an MD or LLD degree). With
their technical education, engineering majors head in a variety of professional directions, influenced by factors such as personal history and characteristics (e.g., race, socioeconomic status), experiences in undergraduate engineering (e.g., internship, study abroad), occupational values (e.g., earning potential, making a difference), and other related events (e.g., getting licensure, receiving a promotion; Brunhaver et al. 2012). They are evenly split between aiming for work that is closely vs. distally aligned with their degree (appendix C; Lichtenstein et al. 2009).
Recent graduates may choose to take on work that is not related to their engineering studies for a variety of other reasons. Table 3-3 sheds light on the reasons why roughly 11 percent of employed recent engineering graduates reported working in a field different from their degree (based on 2010 data). The state of the job market was an important factor, as almost half of these graduates reported not being able to find a job in the field of their highest degree, although men cited it more than women. Other differences between men and women existed; more women than men cited job location, while more men than women chose pay and promotion opportunities as a reason, which is consistent with prior research (Frehill 2008; Sheppard et al. 2014).
Over 57 percent of recent engineering graduates work in engineering two years after graduation. This number is higher for those who majored in civil and mechanical engineering, and lower for those in electrical and other engineering fields. In addition, some occupational differences exist between genders at the early career stage (2–3 years from degree), when men are slightly more likely than women to be employed in engineering occupations and women slightly more likely to be employed in non-S&E occupations.
An average of 19 percent of recent engineering graduates are in S&E-related occupations (the percentage varies by major), and some 8 percent pursue additional education. “Change in career or professional interests” was cited by 13 percent of engineering majors as the primary reason for working in a field different from their major.
It is instructive to look at the actual steps of recent graduates in light of what engineering students say about their career plans. About 80 percent of engineering juniors and seniors expressed interest in pursuing engineering occupations, and approximately 60 percent of them went into engineering work (Sheppard et al. 2010). Plans change, often due to unforeseen factors (table 3-3), and career paths evolve.
Predictors of Early Career Choices
Many early-career engineering graduates express a desire for stability in their general career plans, in that they would like to remain in the same industry for several years; those who expect to work right away in industry generally say the same when asked about their career goals (appendix C). Yet longitudinal data show that four years after graduation most engineering majors had held an average of 1.7 jobs (Cataldi et al. 2014). In-depth interviews
|Job in highest degree field not available||39.87%||45.65%||44.55%||*|
|Other reason for not working in occupation related to highest degreea||24.76%||18.75%||19.89%||*|
|Change in career or professional interests||13.45%||12.94%||13.04%||NS|
|Pay, promotion opportunities||3.55%||12.48%||10.78%||*|
|Working conditions (hours, equipment, working environment)||2.72%||4.30%||4.00%||*|
Source: NSRCG 2010.
a This is a write-in category on the NSRCG survey.
Note: Gender differences analyzed using independent samples t-test.
*p < .05, NS = not statistically significant
with a small sample of engineering graduates showed that slightly less than half were doing what they expected four years after graduation, and this divide was greater for women than men (Carrico et al. 2012).
Recent graduates may experience “culture shocks,” as they confront the complexity and ambiguity of real-world engineering (Korte et al. 2008), and barriers, such as lack of support from coworkers and managers or a frustrating work environment (Brunhaver et al. 2010). These shocks and barriers may prompt some recent graduates to seek employment elsewhere, whether in the same field at a different company or in a different field. Two studies of women engineers show that their relationships with managers and coworkers and the presence or lack of opportunities for advancement, training, or development significantly affect their career commitment to engineering (Buse et al. 2013; Fouad et al. 2016).
The longitudinal data presented in chapter 1 illustrate engineering degree holders’ job changes and migration into and out of the field, showing how graduates “live out” their engineering and non-engineering career interests (recall that some 65 percent of engineering juniors and seniors had interests in both). Most graduates commit to a specific career path as students and stay on that pathway for at least the first few years after graduation (Brunhaver 2015). Factors that seem to most affect recent engineering graduates’ choice of career pathway are:
- their type of undergraduate institution, level of technical interest, and major;
- whether they participated in an engineering internship/co-op; and
- their initial steps/plans (i.e., senior year plans, choice of first position).
Demographic characteristics, precollege experiences, engineering self-efficacy, and contextual factors did not directly influence their current employment (Brunhaver 2015).
Additional Learning Experiences
Over 60 percent of juniors and seniors in engineering have plans for additional education; nearly 43 percent report that they will definitely or probably attend engineering graduate school, and about 28 percent indicate plans to attend non-engineering graduate school (the overlap between these groups is 8 percent). There is no statistical difference in the percentages of women and men considering engineering graduate school, but women are more likely to express interest in attending non-engineering graduate school (Sheppard et al. 2014).
Students’ postgraduate degree goals vary by the type of institution (public or private, more or less selective) from which they received their bachelor’s degree. Students from less selective institutions tend to aspire to earn a master’s degree, compared to those from more selective schools who say they plan to seek a PhD, MBA, or even an MD or LLD degree. Degree goals also vary by gender: higher proportions of men aspire to earn a master’s and a slightly higher proportion of women indicate plans to pursue a doctoral or graduate business degree (appendix C).
These aspirations for further education are greater than actual graduate degree completion in the first years after graduation: although 60 percent of engineering juniors and seniors anticipate pursuing additional education, only about 40 percent of them do. As shown in table 3-4, by 2010 about 12 percent of engineering majors who graduated between 2006 and 2009 had completed a master’s degree in engineering. This rate is three times higher
TABLE 3-4 Early-career graduates (less than 3 years postdegree) with engineering bachelor’s degrees: Highest degree earned. PhD degrees are not included in this table because students are unlikely to finish a PhD program within three years of earning their bachelor’s degree. (n=143,655).
Source: NSRCG 2010.
than the 2003–2005 cohort surveyed in 2006 (Sheppard et al. 2014), perhaps reflecting the economic downturn of 2008, which may have encouraged continued schooling instead of entry in a poor job market.
Engineering graduates pursue advanced degrees in engineering and non-engineering for different reasons (table 3-5). Not surprisingly, most graduates enroll in engineering programs to acquire new skills and advancement opportunities; those who enroll in non-engineering programs do so for the same reasons as well as to change fields, obtain special certification, and broaden their knowledge base before embarking on a career.
Career Stability and Satisfaction
As illustrated in chapter 1, an engineering education provides graduates with a relatively high initial salary and significantly higher lifetime earnings than other disciplines (figure 1-16), low unemployment (about two-thirds the rate of unemployment for all college-educated workers), career versatility/flexibility, and a high degree of job satisfaction (similar to the 89 percent of US employees who state that they are very or somewhat satisfied with their jobs; SHRM 2017) whether they work in engineering or non-engineering occupations (figure 3-2 and appendix A). As explained in chapter 1, although nearly 90 percent of BS engineering graduates use the skills and knowledge of their degree, only 45 percent of recent BS engineering graduates and 35 percent of all degreed engineers work in engineering occupations narrowly defined.
|Reason for coursework||All graduates taking classes||Enrolled in engineering||Enrolled in non-engineering|
|Gain further skills in field||82.1%||90.8%||62.4%||*|
|Further education before career||77.6%||80.1%||72.1%||*|
|Increase advancement opportunities||72.6%||78.6%||59.3%||*|
|Prepare for graduate school/further education||37.4%||42.1%||26.7%||*|
|Change academic/occupational field||22.7%||13.2%||44.2%||*|
Source: NSRCG 2010.
Note: Differences between engineering and non-engineering analyzed using independent samples t-test.
*p < .05, NS = not statistically significant.
Finding: Engineering graduates working in engineering, engineering-proximate, and non-engineering-related occupations typically have high levels of career and work satisfaction.
As discussed in chapter 1, engineering graduates tend to shift fields throughout their careers (tables 1-12 and 1-13, figures 1-13 and 1-14). They move between engineering, engineering-proximate, and non-engineering occupations, although for people farther from graduation, the migration is greater out of than into engineering positions, and the most common career shift is into engineering management (see table 1-6 and figure 1-14).
Importantly, the participation rates of men, women, and underrepresented minorities in engineering occupations diverge. Although women represented more than 19 percent of BS engineering graduates in 2013, they accounted for only 15 percent of individuals working in engineering occupations. Similarly, African Americans, American Indians/Alaska Natives, and Hispanics of any race, who together constituted 14 percent of BS engineering graduates in 2013, represent only about 11 percent of those employed in engineering occupations (NSCG 2013). A number of studies have documented that women and underrepresented minorities leave engineering occupations at a higher rate than their White and Asian American male counterparts, and research has explored factors contributing to this divergence.
For example, several large-scale studies, most comparing women to men, have examined reasons for leaving engineering and science jobs. Women in engineering and science occupations are more likely than men in those occupations to change careers or to stop working (Hunt 2016; Preston 2006). Although some factors, such as loss of interest in the field (Frehill 2008), affect the decisions to leave of both women and men, frustration with pay and promotion opportunities explains much of the gender gap for leaving engineering (Fouad et al. 2016; Hunt 2016; Singh et al. 2013). Other factors—lack of flexibility in work hours and location that constrain choices of work-life balance, feeling isolated, inability to find mentors or support networks, and male-dominated culture—also contribute to women leaving science and engineering at a higher rate than men (Fouad and Singh 2011; Hall 2007; Hewlett et al. 2008; Preston 2006; Stephan and Levin 2005).
A study of the career advancement of nearly 1,800 men and women in mid-level technical jobs at seven large Silicon Valley companies found that, although all were highly educated and women were a third of the sample (a larger proportion than in the overall workforce), men were 2.7 times more likely than women to work in a high-level position (Simard et al. 2008). And although women and men viewed some aspects of their work environments similarly (e.g., both believed that mentoring and teamwork were not valued by the company), certain barriers to advancement influenced them differently. More women than men saw expectations of working long hours and stereotypes of women as less technically competent than their male counterparts as barriers to their advancement. Although both men and women felt that having a family was a barrier to advancement, more women than men reported either postponing or never having children or getting married in order to achieve career goals, and more women than men reported poor health due to work demands.
Men were significantly more likely than women to have a partner who stayed home full time to take care of children and household work, offering them the ability to choose to work long hours without experiencing negative consequences of avoiding obligations at home. Women, on the other hand, were more likely than men to have a partner who was also employed full time and thus took both their partner’s schedule and all shared family and household obligations into consideration when deciding to work long hours. Consequently, a lack of work-life balance and expectations of long hours at work affect a larger percentage of women in technical fields than men in those fields (Simard et al. 2008). Women report leaving their occupations for balance-related reasons more often than men (Frehill 2008) and do so throughout their careers (Fouad et al. 2016; Singh et al. 2013). Even current female engineers report heavy workloads and expectations to put work before family as reasons they have considered leaving (Fouad et al. 2016).
Overall, the masculine culture of engineering education in classes or other engineering experiences such as internships or team projects (Cheryan et al. 2017; Seron et al. 2016) discourages women from entering an engineering occupation (Fouad and Singh 2011), and behaviors such as incivility and undermining from supervisors and coworkers remain a factor throughout women’s careers (Fouad et al. 2016).
It is important to note that women who leave engineering do not differ from those who persist on measures of self-efficacy, vocational interests, perceptions of barriers related to the organizational environment, or expected
outcomes in the three domains: doing engineering tasks, managing multiple roles, and navigating organizational climates. However, women who remain in engineering perceive better support in the work environment (particularly managerial support for work and family balance and management-provided training opportunities), have a stronger commitment to the organization, and experience greater satisfaction with their jobs than those who leave (Fouad et al. 2016).
Interventions to Foster Retention in the Workplace
Research on attrition, retention, or advancement in engineering has focused on the differences between men and women, with limited research on interventions directed toward underrepresented minorities or other marginalized groups (e.g., persons with disabilities, LGBT individuals). However, research has suggested interventions that could reduce the disparities between men and women leaving engineering.
Because bias against women in engineering often leads to lower salaries, assignments of more menial or undervalued work (e.g., planning an office party, taking notes in a meeting), and other discouraging outcomes, one model of change includes an examination of where and how the bias has led to discrepancies, an interrupting force that mitigates the effects, and metrics to assess the effects of the intervention (Williams et al. 2014, 2016). And because workplace bias affects other marginalized groups in engineering, this intervention could also improve working conditions and retention in engineering for them. It is important to note, however, that individuals who fit more than one category of marginalization (e.g., a woman of color) may not benefit as much from interventions as those in only one group (e.g., White women, men of color). It is also important to not view groups of individuals as homogeneous (NAE 2014). However, research has not fully explored the experiences of these individuals, and few interventions to address bias against them have been developed or tested (Ong et al. 2011).
Interventions that foster engagement and retention in the workplace often focus on changing the organizational culture—the corporate values and customs, unwritten rules of the workplace, and social environment. Many businesses believe it is difficult to achieve a positive culture and engagement, although they realize that it can significantly affect their employees and bottom line (Bersin et al. 2015). Improvement in employee retention requires
commitment from the top leadership, simplification of the work environment (e.g., a reduction in burdensome procedures), investment in employees, and measures to assess where change is needed and how it is working to improve the company culture (Bersin et al. 2015).
Organizational cultures that benefit women and underrepresented minorities do not negatively affect male majority employees. Features of inclusive and supportive organizational cultures include leadership support and transparent policies for training and development, encouragement of collaboration rather than competition between employees, consistency in pay and rewards for all employees, and equal access to job flexibility and promotion paths (DeNisi and Smith 2014). On the other hand, perceptions that only certain groups have access to training and development opportunities, that bullying or incivility toward marginalized groups is acceptable in the workplace, that collaboration is not rewarded, or that opportunities for advancement and promotion are available only to majority males lead to a negative culture that decreases employee engagement and retention. This is true of all employees, but especially women and underrepresented minorities.
Finding: Because people with diverse gender and racial/ethnic identities may have different motivations and pathways in engineering it is imperative to consider which educational and programmatic interventions are most effective in welcoming, supporting, and advancing those from underrepresented backgrounds. It is essential to continue developing, implementing, and evaluating well-designed educational and training interventions to both attract and retain women and underrepresented minorities and support all individuals in engineering. It is equally important to change the perceived and real culture(s) of engineering to welcome all individuals regardless of gender, race, ethnicity, or background. Recognition and correction of bias, support for work-life balance, and equal opportunity for training and advancement will help create a supportive environment for all employees.
As noted in chapters 1 and 2, engineering education provides graduates with skills, knowledge, and abilities that allow them to apply their education and experience to a variety of rewarding tasks and occupations and lead to higher salaries and lifetime earnings. It is also evident, though, that engineering faces a diversity challenge. Certain groups are less likely to decide to enter or persist in engineering, and the factors affecting those decisions differ based on both individual characteristics (e.g., gender, race, ethnicity, disability, personality traits) and external factors (e.g., family socioeconomic status, local community, school experiences, parental education, perceptions of engineering culture). This chapter has explored the impacts of these internal and external factors on educational and career decision making of students and graduates, with a focus on populations underrepresented in engineering education and the workforce, women and URMs. Data show that efforts to increase the participation of these populations have been only marginally successful. However, research has identified and validated certain interventions at various education levels that are effective in increasing participation of these underrepresented populations, and they should be widely disseminated, further evaluated, and improved upon.
The following sections summarize the research findings reviewed in this chapter as they relate to interventions in K–12 education, higher education, and the workplace.
Interventions at the K–12 level, informed by an understanding of the internal and external factors that affect student decision making, can help develop interest and prepare students to succeed in engineering study at the postsecondary level. Early intervention, preferably in or before middle school, is critical to encourage young students to become interested in engineering and to take the math and science courses that are predictive of success in engineering in college.
Lack of knowledge about the profession and its practice is a significant barrier for potential engineers. Messages that describe engineering as a field that involves understanding, defining, and solving important societal problems using a mix of technical and professional skills, interdisciplinary work, social consciousness, creativity,
and multicultural understanding are attractive, impart knowledge of the field to all students, and seem to be particularly important for female and URM students, who otherwise may not see engineering as a viable option for themselves. Thus, they can help to offset negative perceptions of engineering’s culture by signaling that they belong in the field, which will increase gender and racial representation in engineering.
In addition, families are critical in the development of children’s interest in engineering, particularly during middle school, and should be enlisted to communicate positive messages to their children, emphasizing intrinsic rewards such as the opportunity to develop and use a mix of social and technical skills and the prospect of performing interesting work while solving big problems for people and society.
The following interventions have been shown to be effective, particularly for female and URM students, and should be widely disseminated, especially in low-income and other underserved communities. Although the interventions benefit many students, research is needed to determine the effects for other marginalized groups and those who fit more than one category of marginalization.
- Ensure that teachers have deep knowledge of their discipline, support for professional development, adequate instructional time, and access to high-quality learning opportunities.
- Ensure that all schools have adequate resources and facilities, especially schools that serve predominantly low-income children and communities.
- To address the abilities and interests of all students, use inclusive instructional practices that support students from different backgrounds and with different learning needs. Other effective teaching practices such as hands-on and active learning projects, especially in math and science classes, help prepare students to enter an engineering major by ensuring that they participate and are engaged in the activities.
- Promote participation in relevant out-of-school activities such as FIRST or STEM summer camps.
- Provide training to help K–12 educators recognize the possibility of their implicit bias and its ability to negatively affect their interactions with students and families. Training can help teachers both avoid sending subtle messages implying that certain populations are not capable of becoming engineers and gain skills to recognize and confront biased actions in others.
- Communicate clearly to K–12 educators, who can then convey to students and their families, the extrinsic (e.g., high salary) and intrinsic (e.g., rewarding work) benefits of engineering as a course of study and career. Students respond positively to messages about careers that include interesting work that makes a difference in the world, while their parents rate availability of jobs and interesting work as similarly important for career considerations (NAE 2008) and would also be pleased if their child chose an engineering career in part because of the high salary.11
- Provide students with accurate information about engineering, both to counter stereotypes of the nature of engineering work and the people who do it, and to prepare them to navigate their education and enter the workforce.
- Cultivate students’ positive outcome expectations of an engineering major and career by emphasizing the message that engineering encompasses social and professional as well as technical skills and equips graduates to do interesting work in a wide range of occupations, help define and solve important problems for people and society, and make a difference in the world.
- Help families understand the utility and rewards of an engineering degree and career, such as the high versatility of the technical and professional skills learned, accessibility to many different careers, and high initial and lifelong salaries.
As discussed in chapter 2, institutions of higher education have begun to adopt more active learning and student-centered approaches, which improve student learning and persistence to an engineering degree. However, although women persist to graduate at similar rates to men, URM students have a much lower retention rate than majority
11 April 2014 Harris Interactive Poll, American attitudes on engineering, conducted on behalf of the NAE.
students. Concerns also remain about the experiences of women in engineering education as well as the number of high-performing students, especially women, who switch to a non-engineering major. The following actions have been shown to improve retention for all students in undergraduate engineering education:
- Communicate clearly to students throughout their college experience that engineering is about understanding, defining, and solving important problems for people and society, and that it requires a mix of technical and professional skills, an ability to communicate and work effectively across disciplinary boundaries and with many different stakeholders, strong social consciousness, creativity, multicultural understanding, and business/entrepreneurial understanding. Make students aware of the potential near-term and lifelong rewards of an engineering degree, the high versatility of the technical and professional skills learned, the fact that an engineering degree is a pathway to many different careers, and the fact that individuals with engineering degrees earn high initial and lifelong salaries.
- Promote multiple high-quality engineering-related experiences for students, such as internships and cocurricular activities (e.g., Engineering Projects in Community Service, Engineers Without Borders, the Grand Challenges Scholars Program).
- Promote high-quality, frequent student-faculty interactions (e.g., through advising and mentoring) for discussions of outcomes and career pathways.
- Provide mastery experiences (e.g., design challenges, problem-based learning activities) to increase engineering self-efficacy, especially for women and underrepresented minorities.
- Encourage students to study with other students to promote their own sense of community and persistence in engineering.
- Use instructional techniques (e.g., active learning) that promote real-world applications of STEM concepts and engage marginalized students as well as majority students.
- Educate faculty about implicit biases and provide training for them to learn to avoid sending implicit (or explicit) messages that create a hostile climate for certain populations. Training should also provide faculty with the tools to address biased behavior they observe in others.
- Counteract a climate that is often chilly for women and URM students by encouraging respectful classroom interactions among peers, positive faculty-student interactions both in and out of the classroom, and innovative instructional strategies to engage students, such as cooperative learning.
- Offset the “masculine culture” of engineering education by ensuring that educators, curricula, and the broader “climate” of classrooms signal to girls and boys equally that they belong in the field.
Companies and institutions can promote job satisfaction, company commitment, and thus the retention of all employees by attending to their organizational culture. Recognition of bias, support for work-life balance, and equal opportunities for training and advancement will help create a supportive environment for all employees.
- Encourage organizationwide understanding of implicit bias and how it manifests in the workplace treatment of women and underrepresented minorities, establish a mechanism for managers to learn to identify actions that may perpetuate bias, and offer training to provide managers and employees with the knowledge and tools to recognize and address bias in themselves or others.
- Develop an institutional culture that focuses on practices that enhance employees’ skills, motivation, and opportunities for advancement. Ensure that all employees have equal access to opportunities for advancement, training, and development and advertise those opportunities throughout the workplace.
- Afford employees as much flexibility as possible with respect to where and when they conduct their work with a clear understanding of what constitutes effective work performance, thereby providing employees with greater latitude to manage their work-life balance.
- Put policies and practices in place to ensure that employees who take parental leave are onboarded effectively afterward and offered the same opportunities for advancement, training, and development as their peers.
Myriad factors influence an individual’s decisions to study and pursue a career in engineering. The impacts of these factors vary by demographic group; much research has been conducted on gender differences, but there is inadequate research on a number of underrepresented groups, especially at the intersection of underrepresentation (e.g., first-generation Hispanic students, women of color) or subpopulations of minority groups (e.g., individuals of Southeast Asian descent). Interventions have been implemented and researched to encourage women and underrepresented groups to participate in engineering, but in many cases the programs help only one group (e.g., White women or men of color) but not other marginalized populations such as women of color.
For many underrepresented populations, data are suppressed in national datasets to avoid identifying specific individuals (who may be the only person in a particular discipline who represents a specific population), so interventions cannot be accurately assessed using current research methods. New approaches, such as the use of administrative data (discussed in previous chapters and appendix E), are needed to expand research on the experiences of underrepresented groups and determine how and why targeted interventions encourage (or even discourage) them in their plans to enter and stay in engineering. Researchers using administrative data can follow individuals through their educational pathways by linking precollege activities, demographic information, and college transcripts to, for example, assess long-term impacts of a precollege summer engineering camp for low-income students by examining how many participants applied to, entered, and graduated from engineering programs.
In addition, while it is useful to conduct experiments that isolate the effects on one variable at a time in order to reliably develop an understanding of the underlying processes, it may be time to focus more on the relationships between external supports, barriers, and experiences and internal person inputs to develop a more holistic approach to designing interventions for underrepresented populations. Building on such research, efforts to improve diversity in engineering should take a systems approach that considers the interplay of internal and external influences on an individual when developing interventions aimed at increasing the representation of all populations in engineering.
Although single researchers may be able to design effective investigations that take a systems approach, it may be more effective for all stakeholders in the engineering education and workforce enterprise to develop “collective impact” initiatives. In such initiatives all partners, supported by an independent organization with staff dedicated solely to the effort, work together to structure processes and consolidate resources in order to develop an agenda, systemwide metrics, consistent and frequent communication, and “mutually reinforcing activities among all participants” (Kania and Kramer 2011, p. 38).
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