Undergraduate admissions serves as a gatekeeper in higher education and often includes measures of secondary school academic performance, including standardized exams (e.g., SAT, ACT, AP, IB) and grade point average, which have weak to modest correlations with undergraduate academic performance. Additionally, these measures have been critiqued as biased and prioritize students from privileged backgrounds. More recently, non-cognitive and affective (NCA) factors—psychosocial constructs spanning behaviors, feelings, and emotions—of accepted students have emerged as stronger predictors of future academic performance compared to conventional admissions data. NCA factors also provide a multifaceted understanding of students that can direct actions for addressing representation and inclusion issues in engineering. In this paper, we conducted a$k-\text{means}$clustering of admissions metrics and NCA factors (i.e., belonging, identity, the Big Five) to understand if there are patterns among these variables within a large sample of engineering undergraduate students from two national surveys$(\boldsymbol{n} =\mathbf{6,050})$. Second, we evaluated the differences between students of varying backgrounds (i.e., gender, race/ethnicity, first-generation status) on these metrics and by cluster. Finally, we assessed the influence of the type of institution (e.g., public or private, doctoral degree granting, tuition guarantee, etc.) by cluster. Understanding how commonly-used admissions metrics relate to NCA attributes may reveal whether such a relationship is appropriate to consider in a holistic admissions review process that facilitates the matriculation of a more diverse engineering study body. Our results indicate that readily-available admissions data signifies the need for tailored support for matriculated students in order to support persistence of the incoming students through to an engineering degree.

This WIP paper describes the development, implementation, and preliminary lessons learned from co-creation workshops with engineering design instructors. Co-creation is a generative process to collect and integrate diverse perspectives and offers a novel approach to engineering education research. Empathy is also a relatively new concept in engineering education, but literature has shown empathy can lead to improved engineering design outcomes. The primary objective of our study is to use co-creation to develop a model that depicts how empathy manifests in engineering design. We engaged in co-creation with instructors at universities across the United States to generate a collective understanding of how empathy manifests across engineering design contexts, and we will use these findings to iterate on an extant empathy in design model. The model will inform instructional assessments and pedagogies for integrating empathy in engineering design, which will enable (1) instructors to understand the extent to which their students empathize in ways that instructors hope they will and (2) have needed strategies to respond effectively to promote empathy's use in design.

This full research paper investigates how faculty understanding and preparation to discuss diversity, equity, and inclusion in the classroom affects students” understanding of these topics and abilities to create inclusive teaming cultures. Inclusive teaming is an essential part of engineering education and one of the key ABET student outcomes. However, students are rarely given the skills needed to effectively support truly equitable teaming environments. This ethnographic case study uses data from a single-institution with a core mission of diversity, equity, and inclusion embedded in the vision, mission, practices, and pedagogy. Multiple sources of data were collected including observations, interviews, surveys, and artifacts. This study focuses on the faculty$(\mathrm{n}=6)$and student interviews$(\mathrm{n}=12)$conducted in Spring 2019. Together, these multiple streams of data provide key insights into particular faculty attitudes, philosophies, and practices that support students” development of DEI capacity.

This research paper explores how students' motivation from family influences and family recognition may provide particular support for students' certainty of an engineering major. This outcome has been linked to higher retention rates in engineering and is a useful way to understand students' pathways early on in their undergraduate careers. Family has a significant role in shaping a student and developing their values, skills, and socialization. For example, a family of engineers may emphasize math and physics, while a family of authors may emphasize creative writing and reading. Furthermore, in the United States, socioeconomic status is a major determiner in students' opportunities to engage in STEM outside of formal education and the types of careers with which families may be familiar. Prior studies indicate that talking about science at home is a particularly important predictor of students' STEM interests. Additionally, first-generation college students and students from lower socioeconomic backgrounds may have higher family pressure to choose engineering as a track for upward mobility. However, much of the prior work examining familial influences on STEM or engineering students' career pathways has focused on K-12 or students' decisions about engineering as a major in college. In contrast, this study explores the role of family on students' career pathways during college through a variety of related constructs and answers the research question, “What family and background factors predict undergraduate engineering students' surety of major?” In this work, we draw on Yosso's framework of Community Cultural Wealth to understand how familial capital can support student pathways through engineering. Familial capital refers to those cultural knowledges nurtured among family or kin that support a sense of community history, memory, and cultural intuition. The data for this study comes from a larger mixed-methods project focused on characterizing latent diversity in engineering. A national survey of 3,711 students from 32 ABET-accredited first-year engineering programs measured over a dozen underlying attitudes, beliefs, and mindsets including epistemic beliefs, motivation, innovation self-efficacy beliefs, personality, STEM role identity, and demographics. We used multiple linear regression to predict engineering students' surety of major as influenced by their motivation (i.e., controlled or autonomous), reported family recognition of them as engineers, and demographics characteristics. Additionally, we included whether students had family members, particularly parents with STEM degrees to understand how knowledge of STEM careers might support students' pathways. The results of this work provide insights into how a family may function as particular supports for students even from afar in a university setting.

This full research category paper examines how first-generation college students' mathematics and physics identity support the development of an engineering identity and how the three STEM identities support students' commitment to choose an engineering major. This study focuses on first-year, first-generation college students in engineering ($n=616$). The purpose of only focusing on first-year students was to understand how their decision to pursue engineering is shaped before engaging in engineering or college coursework. Structural equation modeling was used to test direct and indirect paths of students' STEM identities on engineering major commitment. First-generation college students' perceptions of themselves as capable and interested mathematics learners supported their views of themselves as capable physics and engineering learners. Forming an identity as a math and physics person supported the development of an engineering identity. First-generation college students' engineering identity supported their confidence of choosing an engineering major. However, female and Latinx first-generation college students were less likely to see themselves as physics people. Female first-generation college students were also less confident about their choice to pursue engineering. The findings elucidate the difference each subject-related role identities have on first-generation college students' developing engineering identity and confidence in their major choice.

In this full, research category paper, we examined the differences in subject-related role identities of first-generation and continuing-generation college students by gender. Subject-related identities have been linked to important educational outcomes and consist of identifying as a math person, physics person, and an engineer. These identities are formed through interrelated factors such as interest in the subject, beliefs about being able to understand the subject material (i.e., performance/competence beliefs), and internal/external recognition. The data came from a large-scale survey administered in introductory to engineering courses at 32 four-year ABET accredited institutions. Women in particular were significantly more likely to be interested in mathematics compared to men. Additionally, our study indicates that women first-generation and continuing-generation college students were less likely to be recognized externally and internally as a physics person, while men continuing-generation college students were more likely to have external and internal recognition in physics. Both men first-generation and continuing-generation college student groups were more likely to feel confident in their abilities to understand and do well in physics. Men in both groups were more likely to feel confident in their abilities to understand and do well in engineering compared to women in either group. Both women and men who are first-generation college students were less likely to feel like engineers in their first-semester of their engineering program. These results illustrate the areas of strength with which first-generation and continuing-generation college students enter engineering programs, as well as the areas of continued support for their developing identities.

This full research paper examines how first-year engineering students' recognition beliefs differ by household language (English versus non-English). An Exploratory Factor Analysis of 18 survey items identified two factors grouping students' recognition experiences into leadership-based and knowledge-based categories. An analysis of variance (ANOVA) showed that the First Language Not English (FLNE) students generally felt less recognized as an engineer than their peers. We present multiple excerpts from four "restoryed" case summaries of one student to provide insight into why differences in recognition may occur for FLNE students and how these students describe their identity development. The results of this study may indicate important ways to recognize students in the classroom and promote identity development and persistence.

This research category work-in-progress paper describes a beginning examination of how to adapt the identity trajectory theory from its original use with graduate students and early career faculty to understand how early career undergraduate students develop identities as engineers over time. This study focuses on students who have diverse attitudes, beliefs, and mindsets, i.e., latent diversity, to understand how engineering education and culture may support or hinder students' identity development in and out of the classroom. In this paper, we use the identity trajectory theory to explore students' stories about their background, pathway into engineering, and first-year engineering experiences. We are adapting the three strands of this framework (institutional, intellectual, and networking) in addition to identifying additional or supplementary strands to make meaning of the students' identity trajectories in engineering. We probed the aforementioned strands through narrative interviews with 26 engineering students. This preliminary work describes the challenges and affordances of translating this framework into narrative research with undergraduates and provides new ways of understanding identity development.

This Special Session will engage engineering and computing education professionals in an interactive discussion of how to find and use the expertise of an advisory board when writing and executing funded projects. Our recent research of effective practices for supporting early career faculty in engineering education has shown that grant administration is an area that many faculty feel unprepared to manage. Beyond writing an excellent grant proposal, the skills required to carry out the planned grant activities are different from those addressed in existing professional development opportunities and are essential the success of a grant. This session will provide an interactive discussion and development of tools on one specific aspect of grant proposal writing and management-advisory boards. Advisory boards are an essential part of leveraging the expertise in the wider engineering education community, but there are various ways of strategically building and engaging advisory boards in grant work. The outcomes of this session will be a set of tools for faculty to use in building and leveraging the expertise of an advisory board in grant submissions.

This work-in-progress research paper stems from a larger project where we are developing and gathering validity evidence for an instrument to measure undergraduate students' perceptions of support in science, technology, engineering, and mathematics (STEM). The refinement of our instrument functions to extend, operationalize, and empirically test the model of co-curricular support (MCCS). The MCCS is a conceptual framework of student support that explains how a student's interactions with the professional, academic and social systems within a college could influence their success more broadly in an undergraduate STEM degree program. Our goal is to create an instrument that functions diagnostically to help colleges effectively allocate resources for the various financial, physical, and human capital support provided to undergraduate students in STEM. While testing the validity of our newly developed instrument, an analysis of the data revealed differences in perceived support among College of Engineering (COE) and College of Science (COS) students. In this work-in-progress paper, we examine these differences at one institution using descriptive statistics and Welch's t-tests to identify trends and patterns of support among different student groups.

This research category full paper explores National Science Foundation (NSF) Faculty Early Career Development (CAREER) Program awardees from the Division of Engineering Education and Centers. The NSF CAREER Award distinguishes researchers as promising future leaders who are advancing the frontier of engineering education research (EER). Additionally, the multidisciplinary rise of EER has resulted in a diverse community of researchers from many backgrounds and academic departments. Given the recognition associated with the CAREER award, it is crucial that all early career faculty members possess the knowledge and support to create high quality CAREER applications. In this study, we investigated the educational backgrounds, institutional affiliation, and public abstracts of CAREER awardees to document prevailing patterns in recognition through CAREER awards. This knowledge informs future work to provide additional support for early career faculty planning on applying to the program.

In this work in progress research paper, we investigated whether non-cognitive and affective (NCA) factors that predict academic success through GPA may relate to other forms of success such as student retention in engineering programs. Studies show that most students leave engineering within the first two years, making national retention rates in engineering less than 50%. Furthermore, the students who leave engineering are often academically talented, indicating a need to examine other success measures beyond GPA such as non-cognitive and affective (NCA) factors. Using data from a single institution (n = 540), we explore the NCA differences between students who remained in engineering after their first year and those who are no longer enrolled in engineering, or even in college at all. Results show that only one demographic and five NCA measures are statistically significant predictors of continued enrollment. Overall, a better understanding of student success as measured by retention using NCA profiles might assist researchers and practitioners with developing interventions and supportive environments that promote students' academic success and thriving in engineering.

This research category work-in-progress paper uses cross-sectional data, collected in the fall of 2017, to understand first-generation and continuing-generation college students' intended choice of an engineering major. Data for this analysis came from a large-scale survey of 3,711 first-year engineering students from 32 U.S. institutions of which 790 students identified as first-generation college students and 2,072 identified as having one or more parent(s) with a bachelor's degree or higher (continuing-generation college students). A Welch's t-test was used to examine the differences in engineering major selection between and within groups. Results from the within-group comparison show that men and women, who are first-generation college students, have similar disciplinary interest as reported in the ASEE Engineering by the Numbers. Most notably women first-generation college students were more likely to choose biomedical, chemical engineering, and other STEM-related degree compared to men first-generation college students. When analyzing the data by gender and examining college generation group differences, we found that women first-generation college students were more likely to choose, civil, computer, construction management, electrical engineering, computer science and, information technology compared to women in the other group. While men first-generation college students were more likely to choose construction management, electrical engineering compared to men in the other group. Enrollment trends of first-generation college students in engineering are difficult to determine, this study provides a first step towards understanding the fields that attract these students.

In this full research paper, we bring into focus the interplay of conformity to masculine social norms and demographic characteristics (i.e., gender, race/ethnicity, institutional settings) among undergraduate engineering students in the United States. We approached this study with an exploratory, non-experimental design that involved examining patterns of relationship between the conformity to masculine social norms and demographic characteristics of respondents. Our data were obtained from of survey responses by engineering students (n=128) in first-year general engineering courses at three universities in the Southeastern United States. We operationalized conformity to masculine social norms using the Conformity to Masculinity Social Norms Inventory (CMNI-22). Our results revealed moderate to low conformity to masculine social norms among engineering students in first-year general engineering courses. Overall, student demographic characteristics appeared to have weak to limited influence on levels of conformity. However, the institutional setting interacted significantly with both gender and race/ethnicity such that male students at the public research university setting and white students in the same setting reported significantly higher levels of conformity to masculine social norms than students in other demographic categories. We discuss these findings as they enrich understanding about how institutional contexts might affect gendered social norms related to engineering professional formation.

This research category full paper examines the attitudes and beliefs that first-year engineering students have about the stereotypes of engineers and what it means to fit in engineering. We explored the attitudes and beliefs of 12 first-year engineering students, who may or may not identify with certain aspects of the stereotypical engineer, to understand their initial perceptions of engineering and what it means to fit in engineering. Most of the students' descriptions of an engineer aligned with the widely-accepted stereotype of an engineer, but they were also careful to state that that image was not true of all engineers. Several students expressed how they fit in engineering as a matter of “sticking it out” because engineering requires hard work, motivation, and commitment, along with other attributes that were not descriptive of a stereotypical engineer. In this paper, we explore the tensions in how students describe the role of “an engineer” generally and their own identities and fit as engineers.

This research-to-practice full paper describes the deliberate and arduous process we recently went through to develop a national survey to study the non-cognitive traits of undergraduate engineering and computing students. The goal of this survey is to characterize student profiles in order to develop and examine particular interventions to guide students toward success in engineering and computing majors. This survey measures non-cognitive attributes including personality, sense of belonging, engineering or computing identity, study skills, well-being, and a variety of other constructs that are not routinely measured in engineering populations nor integrated into admission decisions, advising processes, or academic curricula. Prior research indicates that these non-cognitive attributes are important for students' academic success and retention. However, no studies have examined a comprehensive set of non-cognitive traits holistically to understand how they influence student success. This collaborative project, funded by three linked NSF grants, merges the interests of researchers at three campuses in understanding and supporting students with varied non-cognitive profiles. As part of this research, we negotiated the content of a national survey, suitable for use on our own campuses as well as with other national partners, to probe more than a dozen constructs collectively describing student non-cognitive attributes. The construction of the survey itself was non-trivial, and involved significant negotiations among the researchers including initial collection of instruments with validity evidence to serve as a basis for discussion; an in-person kick-off meeting; multiple follow-up teleconferences; multiple rounds of inclusion/exclusion decisions based upon mutually-agreed upon guiding principles; pilot survey testing; pilot data evaluations such as exploratory factor analysis; and final decisions about instruments/items to include in the final version, all while considering survey length, distribution channels, and key IRB concerns. This paper details the 10-month effort to construct a survey that meets the research needs and intellectual curiosity of partners at three diverse campuses. In this process, we had to balance the different institutional contexts of the funded partner sites while also maintaining flexibility for national distribution. The deliberate processes we used may serve as a template for future survey creation, starting from constructs of interest, to selection of specific instruments (or sub-scales thereof), and factor analysis to consider further down-selection of individual items to include in the final survey. The outcomes of this paper may serve the engineering education community by highlighting previously undocumented processes in collaborative survey construction that introduce intellectual complexity or time delays into the development timeline.

This work-in-progress paper presents emerging results from a research study aiming to develop and gather validity evidence for an instrument that can be used by college administrators and student-support practitioners to assess the magnitude of undergraduate students' perceived institutional support received in science, technology, engineering, and mathematics (STEM). Our goal is to provide stakeholders with a validated tool to diagnose areas of strength and opportunities to better support students, particularly those from underserved populations. Over the past year, we have engaged in a systematic process of instrument development. We began by developing a prototype based on the newly developed Model of Co-Curricular Support (MCCS). We refined it by reviewing existing literature and instruments germane to student support, and soliciting stakeholder feedback. During the spring of 2018, we distributed the instrument to STEM undergraduate students at three U.S. institutions. In this paper, we report our process of instrument development and preliminary results.These results will inform the next revision of our instrument, ultimately providing the STEM education community with novel and theory-based ways to measure students' perceptions of support in STEM.

This full research paper focuses on a systematized review of the literature on low-socioeconomic students in engineering. Increasing the diversity of engineering cannot be addressed without acknowledging the necessity for equity across socioeconomic groups. An important step to developing equitable pathways that allow low-socioeconomic students to engage in engineering education is by identifying barriers to participation. Because little is known about the “invisible” population of engineering, a literature review regarding low-socioeconomic students' participation in the larger STEM education context provides an opportunity to begin making the population visible. This work identifies barriers that may make participating in engineering difficult and provides suggestions for researchers and practitioners to work to remove them.

This research category full paper seeks to understand if feelings of belonging differ according to student demographics for first-year engineering students. Engineering has maintained a stable profile (i.e., white, masculine, and male) for many years, despite national trends in higher education. Multiple researchers have demonstrated that increased diversity leads to improved communication skills, creativity, and problem-solving capabilities, all goals that directly align with engineering's core values. The lack of diversity within engineering has resulted in a culture which produces engineers that are underprepared and lacking the skills required to work in an increasingly diverse and global engineering market. Engineering's cultural attitude towards diversity has created environments where students, especially underrepresented minorities (URM), feel that they do not belong despite meeting the academic requirements. To better understand feelings of belongingness within engineering education, the research team set out to answer the question: How do feelings of belongingness differ across demographic characteristics for new (second week) engineering students, enrolled in a first-year first-semester engineering course? Our results demonstrate that neither disability status, race or sexual identity significantly affect how new engineers report their perception of belonging. Female students entered engineering feeling that they belong but at a level significantly lower than their male peers. This suggests that there is still much work to be done in the K-12 environment to cultivate female students' interest and confidence in engineering, as well as room for improving the welcoming of all students into engineering education.

This research-category full paper investigates the relationship between first-year engineering students' career aspirations and attitudes towards engineering. Career aspirations describe students' beliefs about professional roles they might perform in the future. Attitudes towards engineering were measured using engineering identity, belongingness within engineering, and specific motivation constructs. Examining the intersection of aspirations and attitudes allows educators to understand how students' intended career choices are related to their perceptions of their educational experience. Using survey data from 2,916 students at four large public universities, we found that an interest in industry-based careers was associated with high engineering identity, belongingness, and motivation scores. We found that gender had a moderate effect on aspirations and attitudes. Additionally, we found that an interest in mechanical engineering was associated with increased certainty in an engineering/industry career, while interests in biomedical engineering, non-engineering STM majors, and non-STEM majors were associated with decreased certainty in an engineering/industry career. These results have implications for the current discourse around how engineering students make decisions about their future careers.

This work-in-progress research paper uses multiple regression of both cognitive and non-cognitive factors to model current GPA of engineering and computer science students. High school GPA and ACT/SAT scores are among the most common scores used as admission criteria, which result in a relatively homogeneous engineering population. Prior research, however, shows that these scores do not account for the variance in GPA once these students start undergraduate studies. In this work, we explore how students' cognitive (e.g., study skills, test performance, regulatory behaviors, etc.) and non-cognitive factors (e.g., identity, motivation, personality, etc.) predict student success in their engineering pathways. The data for this initial study comes from a pilot survey, deployed in the summer of 2017, of 490 engineering and computing students from two large, public institutions, one on the West Coast, the other in the Midwest. We used multiple linear regression to control for demographic variables while examining the predictive value of particular cognitive and non-cognitive factors for student academic achievement (i.e., GPA) in university. Our analysis shows, not surprisingly, that standardized test scores only explain a small portion of the variance of undergraduate GPA. Including non-cognitive and affective factors into a regression model produced a marked increase in the explained variance. Our work is novel in examining a constellation of possible factors that predict undergraduate student GPA, by combining both cognitive and non-cognitive factors as predictors. This analysis begins to unpack particular factors that have potential to predict GPA of engineering and computer science students.

This full, research category study examines how out-of-school experiences in Grades 9-12 predict first-generation college students' engineering possible selves and certainty of career path. The data for this study came from a large-scale survey on outreach programs which was distributed in first-semester English courses to capture an array of responses from students interested in STEM and non-STEM careers. We used structural equation modeling to examine a set of hypotheses: 1) out-of-school experiences would be mediated by interest and recognition in physics and STEM and no direct effect will be found for out-of-school experiences on physics and STEM identities, 2) these identities subsequently predict engineering possible selves, and 3) engineering possible selves will predict certainty of career path. The results of our structural equation modeling analysis supported our hypotheses, out-of-school experiences alone are not enough to develop an identity as a physics person or STEM person, rather they need to be mediated through recognition by others and an underlying interest. A physics identity and a broad STEM identity were found to significantly predict students engineering possible selves. Engineering possible selves were a significant predictor of first-generation college students' certainty of career path. Future possible selves for first-generation college students have important implications for academic development, integration into their community of practice, retention, and the formation of a future professional identity.

In this work-in-progress paper, we synthesize research from psychology, sociology, and engineering education, in order to consider the presence of masculine social norms in engineering. According to prior work, social norms represent collective expectations that are socially constructed by majority social groups about the proper role and conduct of different groups in society. Social norms related to masculinity are often associated with emotional regulation, the exertion of significant dominance over others, and the desire to win. Unfortunately, the social pressure to conform to traditional ideologies of masculinity has been shown to adversely affect individual's help seeking behaviors, sexual health, and self-esteem. In the interest of gaining a better understanding and promoting inclusivity in the culture of engineering degree programs, we explore in this paper how these collective expectations may be particularly relevant in the context of engineering - a field often critiqued as being governed by masculine norms.

This work-in-progress (WIP) research paper investigates contributing factors for how students describe what it means to be an engineer and what particular characteristics enable students to belong in engineering. We answer the research question, “What are the key contributing factors that influence how diverse students feel that they belong in engineering?” We used a semi-structured protocol to interview 12 diverse engineering students during Fall 2016 about their pathways into engineering, identities, and belongingness in engineering. The participants were selected from a pool of students who completed an attitudinal survey during Fall 2015 as a part of a larger study. They were purposefully recruited to maximize the number of women, students of color, first-generation college students, students with visible and non-visible disabilities, and LGBTQ+ students. The interviews were coded inductively to understand the emergent themes of how students described their social and individual identities and how they did or did not fit with what it means to be an engineer. The themes are emergent and this work-in-progress paper will describe our findings to date.

This work-in-progress research paper describes the initial findings of research on students' attitudes about diversity in first-year engineering teams. We used quantitative pre- and post-survey data and qualitative interviews with student teams to understand students' initial attitudes about diversity and teaming and how those were affected by engineering teaming experiences over a semester. The qualitative and quantitative data analyses interact throughout the project's iterations, with each informing the other. Here, we review the progress made through in-depth qualitative analysis when compared to survey data about changes in variance of students' attitudes towards teaming. By using an iterative mixed methods approach, we are able to explore the subtle distinctions in students' attitudes and experiences affecting diverse teaming experiences. In this paper, we will detail this iterative process and how it has produced more nuanced findings than a particular research paradigm alone.

Engineering culture has traditionally limited rather than fostered diversity in engineering. This culture serves to limit representation of diverse individuals within engineering and create environments that are detrimental to creativity, problem solving, and productivity. One way to address this issue is to understand how students align themselves with the cultural values of engineering and navigate their pathways through earning their engineering degrees. We present an analysis of ten participants previously identified through attitudinal survey data as belonging to a “normative” attitudinal group of engineering majors. These individuals provide a way to understand students who are attitudinally similar to the accepted norms and practices of what it means to be an engineer. Results indicate the importance of social resource experiences in engineering and on the widely held belief that success in engineering is born out of hard work, consistent with other studies. These findings outline ways in which engineering culture can shape student attitudes and actions towards learning engineering. Understanding this group may provide ways to change engineering culture to be more inclusive for all students. Our research begins to describe particular cultural practices and values to improve the recruitment, training, and retention of a broader population of engineering students.

This work-in-progress research paper begins to explore stories told by 12 diverse engineering undergraduates about how they chose engineering as a major in their studies. The students were interviewed during Fall 2016 about their pathways into engineering, their identities, and their belongingness in engineering. The participants were selected from a pool of students who completed an attitudinal survey during Fall 2015. They were purposefully recruited to maximize the number of women, students of color, first-generation students, students with visible and nonvisible disabilities, and LGBTQ+ students. These attributes were self-identified by students, and, in this work, we report them in their own words and in rich detail rather than binning students into fixed categories. We focused on multiple intersections of diverse and underrepresented identities to uncover and explore the counter-narratives that these students co-constructed with the researcher to answer the question, “What are the converging and diverging stories about particular influences on diverse students' choice of engineering in college?” We used narrative methods to identify where student stories share similarities and differences to understand some of the pathways underrepresented students take into engineering. These stories may provide insight into recruiting and supporting other diverse students.

This work-in-progress research study examines the response patterns of first-generation college students (FGCS) to the engineering identity measures compared to non-first-generation college students (non-FGCS). This work answers the following research question, “Do FGC and non-FGC engineering students interpret the engineering identity measurement items in a conceptually different manner?” We explore if FGCS respond to engineering identity items similarly to non-FGCS and the fairness of using these instruments for FGCS to make claims about this group. The data for this work are from a survey instrument completed by 2,916 first-year engineering college students from four U.S. institutions. We hypothesize that quantitative measures constructed for the general engineering student population (non-FGCS) may not function the same for a FGCS subpopulation in engineering. Using extensions to the confirmatory factor analysis, we tested for measurement invariance of engineering identity constructs between FGCS and non-FGCS. Our comparative analysis of FGCS and non-FGCS found weak measurement invariance within the engineering identity constructs (i.e. interest, recognition, and performance/competence) indicating a similar factor structure and factor loadings, but different uses of the identity item scale. This research raises questions on the use and fairness of normative measures in engineering education for populations that fall outside the majority engineering student population.

This research paper describes the application of linguistic analysis through scaled co-occurrence networks to create visual representations of systematic literature reviews. This approach uses currently available and free tools in this new application. Co-occurrence networks are a method for visualizing relationships between concepts within written material. The results of a co-occurrence analysis are a network that reflects the relationships between words based on meaning similarities among words and text segments. To illustrate this approach, I applied the methodology of a systematic literature review search that resulted in 391 unique journal articles, books, and reports on identity published in the period from 1995 to 2015. The abstracts, titles, and keywords of these journals were analyzed via linguistic analysis to create a word co-occurrence network of these articles related to identity in science and engineering. Clusters within this network were identified based on word frequency. The results of this research illustrate a hole in the current identity literature in understanding diversity beyond traditional definitions of race, class, and gender. This method has the potential to powerfully convey and embed information about large amounts of data in a single image and offers a new way to report findings from a systematic literature review.

This paper introduces an alternative to singular performance measures through the creation of a scaled index incorporating a variety of performance factors indicating overall student success as well as the creation of similar sub-indices for performances in the particular areas of math, English, and science. These indices have been used in two studies based on nationally representative college student data: the Sustainability and Gender in Engineering (SaGE) and the Outreach Programs and Science Career Intentions (OPSCI) projects. The Academic Performance Index (API) is a scale constructed out of students' weighted high school GPA, available standardized test scores (ACT/SAT), AP test scores (if any), highest levels of various high school coursework taken, and college credit hours earned prior to enrolling in college. Importantly, the API uses any and all available data in these domains, which can be up to 42 different indicators for an individual student in the case of the SaGE project. This index shows less bias regarding race and gender, when compared with commonly-used standardized tests scores. Additionally, this item is psychometrically better at indicating variation across students' performance.

The U.S. government has called for more STEM professionals in order to remain competitive as a nation. Increased participation of women and minorities in these fields will capture the rich diversity of their lived experiences and contributions. Many studies examine these issues for women or minorities, but less frequently consider the intersection of gender and race. There have been quantitative studies conducted in recent years that attempt to capture why women leave engineering. However, they lack the rich description at the intersection of race and gender necessary to understand the impetus to leave engineering industry. Identity theory is the theoretical framework utilized for understanding how engineering industry culture fits with how these women see themselves and feel like they belong or do not belong in engineering. Identity theory can illustrate the meanings that Black women attribute to themselves as engineers and how they negotiate their perceived membership in engineering based on interpretations of status differences, legitimacy and stability of those status differences. This paper presents insight in to methods of data collection, analysis process, and preliminary research results.

This study investigates first-generation and non-first-generation engineering undergraduates' math/science identities, subject-related interests, and career plans. First-generation students are an understudied, but growing population. Understanding how these self-beliefs and background factors affect students' engineering choice can help widen pathways into engineering which continues to be defined as “pale and male.” Additionally, identity has predictive value for practical outcomes like engineering choice in college. The data for this study comes from the nationally representative Sustainability and Gender in Engineering (SaGE) survey completed by 6,772 college students who enrolled in first-year English courses at 2- and 4-year colleges across the U.S. Data were analyzed using t-test and chi-square tests for linear and dichotomous outcomes respectively. Our results show differences in first-generation students' identities, interests, performance/ competence beliefs, and family support for science. These differences can serve as a stepping stone towards understanding the trajectories of first-generation college students in engineering. By understanding underrepresented students' identities, performance, and backgrounds, specific strategies can be developed to support these students in our engineering programs.

Understanding students' self-ascribed engineering identity may be one way to understand engineering choices and to help recruit new students to the engineering pipeline. In our framework, identity is composed of students' perceptions of their performance/competence, recognition, and interest in a domain. This paper outlines the creation of a model of engineering choice based on this framework. The data utilized in this analysis come from the nationally-representative Sustainability and Gender in Engineering (SaGE) survey. Distributed during the fall of 2011, the survey was completed by 6,772 college students across the United States enrolled in first-year English courses. A structural equation model was built using previously validated constructs of mathematics, physics, and general science identities. These three constructs predict an engineering identity which, in turn, influences the choice of engineering in college. The model is a step towards a better understanding of the choice of an engineering major in college.