Multiple stakeholders are interested in measuring undergraduate student success in college across academic fields. Different metrics might appeal to different stakeholders. Some metrics such as the fraction of first-time, full-time students who start in the fall who graduate within six years, the graduation rate, are federally mandated by the U.S. Department of Education, Integrated Postsecondary Education Data System (IPEDS). We argue that this calculation of graduation rate is inherently problematic because it excludes up to 60% of students who transfer into an institution, enroll part-time, or enroll in terms other than the fall. By expanding the starters definition, we propose a graduation rate definition that includes conventionally excluded students and provides information on progression in a specific program. Stickiness is an even more-inclusive alternative, measuring a program's success in graduating all undergraduates ever enrolled in the program. In this work, programs are grouped into six academic fields: Arts and Humanities, Business, Engineering, Other, Social Sciences, and STM (Science, Technology, and Mathematics. Stickiness is the percentage of students who ever enroll in an academic field that graduate in the same field. We use the Multiple Institution Dataset for Investigating Engineering Longitudinal Development (MIDFIELD) 2023 which contains unit-record data for over 2 million individual students at 19 institutions. For the academic fields studied, Engineering has the highest graduation rate and third highest stickiness. Social Sciences and Business also have higher graduation rates and stickiness than the other fields. We also track the relative fraction of students migrating to and from each academic field. This paper continues our work to derive better metrics for understanding student success.

As part of a larger project to assess what marginalization looks like in engineering student teams in the classroom, an opportunity evolved to measure gender and race/ethnicity more authentically and more safely than is commonly done. This paper describes the design of these authentic questions and how students responded to them. In the case of the race/ethnicity question, the paper compares student responses to the new question to their responses to an earlier question that had no option to select multiple identities and no opportunity to write in a free-text response. This process makes visible the students who were likely harmed by the old question design, emphasizing the importance of an authentic measurement.

This research full paper explores the academic outcomes of undergraduate engineering students who leave their native countries and pursue their education in the USA. These “international students” are defined as students who were not citizens or permanent residents of the USA who enrolled in engineering programs in the USA. In this paper, we quantitatively analyze metrics for international and domestic students pursuing undergraduate degrees in one of the five most popular engineering disciplines in the USA: chemical, civil, electrical, industrial/systems, and mechanical using the Multiple-Institution Database for Investigating Engineering Longitudinal Development (MIDFIELD). MIDFIELD includes institutional records from over 1.7 million undergraduate, degree-seeking students in 21 programs at nineteen universities in the USA with over 85,000 men and 21,000 women enrolled in one of the most popular five engineering disciplines in the USA. Metrics used include representation at the start of university studies, initial engineering major choice, six-year graduation rate, and stickiness (the number of students graduating in a major divided by the number of students who ever enrolled in that major). Results are disaggregated by origin (domestic or international), sex (female and male), and major (chemical, civil, electrical, industrial/systems, and mechanical). Results show that there are more men than women in these disciplines and this is more pronounced for international students. In these disciplines, international students graduate at higher rates and have higher stickiness than domestic students. International females have the highest graduation rates. Industrial/Systems Engineering has the highest graduation rates and stickiness for all populations. Insights from this work can inform student services personnel and others committed to international student success.

Monitoring perceived psychological safety in engineering project teams helps instructors better manage student teams to lead to students’ positive learning experiences and outcomes, especially for teams with minoritized and culturally diverse students. Teams with diverse backgrounds are found to experience reduced cohesiveness and more interpersonal and task conflict as people are less likely to work well with self-identified out-group members. Meanwhile, teams with diversified members have the potential to benefit from a richer pool of resources and experiences to produce more creative and higher-quality outcomes. Thus, diverse team composition could carry both positive and negative influences towards student perceived psychological safety across the team life span. Using multilevel models of change, we investigate how the diversity at individual and team levels influences psychological safety across time for 1463 first-year engineering students in 390 teams conducting team projects. Future work will explore how students’ demographic and academic ability and the team composition affect perceived psychological safety to better inform engineering student team management for the instructors.

This study focuses on quantitative analyses of international and domestic students pursuing undergraduate degrees at institutions in the USA. Metrics used include representation at start of university studies, representation at graduation and six-year graduation rate. Results are disaggregated by origin (domestic or international), sex (female and male), and major (engineering or non-engineering). Results show that more international students choose engineering than other majors. There are more men than women in engineering and this is more pronounced for international students. International students graduate at higher rates in engineering than domestic students by about 5%. This may reflect a tension between their higher academic qualifications but challenges of adjusting to studying in another country. These insights can be used to support student success.

The Multiple Institution Database for Investigating Engineering Longitudinal Development (MIDFIELD) is a unique research resource offering student record data at an unprecedented scale. This special session aims to introduce participants to MIDFIELD including the data that it contains and some key results from research using MIDFIELD, explore how to conduct research with such a resource, and explain how participants can access MIDFIELD. Understanding what data is available in MIDFIELD and how to access it will help researchers decide if this is a useful resource for their own research.

Understanding how psychological dynamics in teams influence the effectiveness of students' teamwork behaviors improves instructors' ability to manage student teams. This research study explored the relative importance of three measures of team dynamics in predicting five behavioral dimensions of effective teamwork. Data were collected from 1780 students in a first-year engineering course in Spring 2020, and 1638 students' data remained after removing multivariate outliers. Relative weight analysis via RWA-Web was conducted for this study as it revealed the pure and independent contribution of each predictor for criterion variables. Results showed that the combination of conflict ($\mathrm{R}2=0.00293,\ \mathrm{p} < .05$), cohesiveness ($\mathrm{R}2=0.00126,\ \mathrm{p} < .05$), and psychological safety ($\mathrm{R}2=0.00254,\ \mathrm{p} < .05$) explained 0.0067 of the variances in five teamwork behavior constructs. On the one hand, these results show that compared to psychological safety and cohesiveness, conflict was the most significant factor influencing teamwork behavioral effectiveness. On the other hand, the results also reveal that all three of these measures have extremely low predictive power. Therefore, while this work might suggest that instructors need to pay closer attention to monitor the conflict in student teams to improve their teamwork skills, the results are confounded by the low variability in ratings overall. Most teams report high ratings - a mean greater than 4 on a 5-point scale once the behavioral scale is converted to numeric values. Noting that our greatest concern lies with identifying and remediating dysfunctional teams, the RWA analysis will be repeated on a sample restricted to teams showing some evidence of dysfunction, which will be reported in the full manuscript.

Although computing occupations have some of the greatest projected growth rates, there remains a deficit of graduates in these fields. The struggle to engage enough students to meet demands is particularly pronounced for groups already underrepresented in computing, specifically, individuals that self-identify as a woman, or as Black, Hispanic/Latinx, or Native American. Prior studies have begun to examine issues surrounding engagement and retention, but more understanding is needed to close the gap, and to broaden participation. In this research, we provide quantitative evidence from the Multiple-Institution Database for Investigating Engineering Longitudinal Development—a longitudinal, multi-institutional database to describe participation trends of marginalized groups in computer science. Using descriptive statistics, we present the enrollment and graduation rates for those situated at the intersection of race/ethnicity and gender between 1987 and 2018. In this work, we observed periods of significant flux for Black men and women, and White women in particular, and consistently low participation of Hispanic/Latinx and Native American men and women, and Asian women. To provide framing for the evident peaks and valleys in participation, we applied historical context analysis to describe the political, economic, and social factors and events that may have impacted each group. These results put a spotlight on populations largely overlooked in statistical work and have the potential to inform educators, administrators, and researchers about how enrollments and graduation rates have changed over time in computing fields. In addition, they offer insight into potential causes for the vicissitudes, to encourage more equal access for all students going forward.

This paper focuses on how a small sample of people with disabilities perceives the usability of web interfaces designed to meet current standards for people with disabilities. Developing accessible interfaces for online educational tools is necessary in providing an inclusive learning environment. Seeking the perceptions of people with disabilities is a logical design step, but it is even more critical due to the emerging evidence on the limitations of Web Content Accessibility Guidelines (WCAG), the standard currently used in the design process. In this work, we report the perceptions of people with disabilities on an example web interface designed according to WCAG standards. In this work-in-progress, we employed 43 workers from Amazon Mechanical Turk to compare the existing interface for CATME (an educational platform for team formation and peer evaluation) to an interface implemented according to web content accessibility guidelines while giving why they might prefer the features of either interface. The majority of the participants preferred the WCAG-compliant designs, a few participants provided useful reflections on their preference for the original interface. For example, WCAG criteria 1.4.11 require that hovering over a button results in a color change of the button from blue to white. Approximately half of the participants supported this feature, but the rest preferred a different method of highlighting a target button. We infer that WCAG criteria should be followed with continued reflections on user-centered design, particularly given that several WCAG criteria apply on a case-by-case basis according to the overall design of the web interface. In this paper, we perform a detailed analysis on the feedbacks and reasons given by the participants on the implementation of various accessibility criteria and examine their reasoning to understand the rationale of this small sample of people with disabilities in web designs. The input from this study will guide further exploration with a larger sample of participants. We hope that our research findings will provide further insights into the development of accessible educational tools.

This Work-In-Progress (WIP) research paper summarizes and compares institutional demographic and financial trends among five Southeastern engineering institutions through 2000-2015. This WIP is part of a larger study investigating the effect of institutional characteristics on first- to second- year retention among undergraduate engineering students. Using two databases, we compared institution demographics, number of degrees granted, and institution expenditure both at the university level and engineering college level. The authors will use the results of this WIP to further investigate the effects of these variables on engineering students' academic performance by using these results and applying additional quantitative models to a longitudinal and multi-institutional database.

This work-in-progress presents an overview of current research with the Multiple-Institution Database for Investigating Longitudinal Development (MIDFIELD) and strategies for inviting and supporting other researchers to use this database in their own research. MIDFIELD is a resource for the study of students that includes longitudinal, de-identified, whole population data for multiple institutions. This enables researchers to examine student characteristics (such as race/ethnicity, sex, socioeconomic indicators) and curricular pathways (including coursework) by institution and over time. Because the dataset contains records of all students matriculating over a period of time, researchers can study students across all disciplines, not just engineering. The MIDFIELD team aims to educate the broader research community, expand the network of researchers capable of conducting this research, and share innovative research methods in addition to the actual data. We have offered workshops at several conferences as well as the MIDFIELD Institute. The inaugural MIDFIELD Institute brought together researchers from across the USA for two days in 2019. In an evaluation at the end of the Institute, participants were pleased with the Institute and rated it highly. There was high agreement about the value of the content and delivery. Most participants reported that the instituted lived up to their expectations and was a good way to learn about how to use MIDFIELD data. Areas of improvement suggested by participants included making it longer and more challenging. Several of the MIDFIELD Institute attendees are presenting works-in-progress together at FIE 2020 to provide attendees with a range of examples of research that is possible with MIDFIELD.

This work-in-progress paper builds on research that has found disciplinary differences in culture, demographics at initial enrollment ("starters"), demographics of students migrating later, and various student outcomes for both groups. An earlier longitudinal study using the Multiple-Institution Database for Investigating Longitudinal Development (MIDFIELD) showed no disciplinary stratification of grades in common early engineering courses based on the discipline in which a student matriculates (or first enrolls after a first-year engineering program). In contrast, this study finds that disciplinary differences in introductory courses emerge on the path to graduation. This can only be explained by a bias with respect to introductory course grades of students entering and leaving each major- students with lower grades in introductory courses are more likely to leave or be attracted by some majors than others. Citing prior research regarding cultural differences among the engineering disciplines, the authors propose that disciplines establish and enforce cultural norms regarding student performance in these introductory courses.

This research full paper investigates how much the type of leadership role and the type of team leadership structure that engineering students prefer before teamwork will affect students' perception of team processes and outcome. Team processes are team-level attributes that influence team effectiveness and reflect team members' collective attitudes, values, cognitions, and motivations. Many factors can affect these team processes, including leadership role and structure. In this study, we explored how engineering student preferences about leadership structure are related to the perception of students about team processes and outcome. We used a one-way ANOVA, dividing students by leadership role into three groups: prefer following, prefer leading, and balanced. We also divided students by preferred team structure: one strong leader, one leader who gets lots of team input, and shared leadership. We considered other team processes including conflict, psychological safety, cohesion, and the team outcome satisfaction. In the preferred leadership role, students with balanced preference reported most positively regarding all team processes and outcome. Similarly, students with a preference for shared leadership reported most positively regarding those variables.

This Work in Progress research focuses on the peer ratings behavior of students in liberal arts and business, versus engineering or the sciences and is relevant wherever teams are used as part of the pedagogy, We examine whether there are differences in patterns of peer rating behavior due to differences in their particular learning experiences and learning style preferences, as measured by their patterns in evaluations in peer ratings surveys. Our hypothesis is that engineering students (“hard discipline students”) will have significant differences in the patterns of peer evaluation scores as opposed to liberal arts or business students (“soft discipline students”). This analysis will use convergence in self and peer ratings, dispersion in ratings across peer evaluation dimensions, and the variances examined in the Social Relations Model as statistical analysis methods.The goals of this research are to discover if peer ratings patterns are significantly influenced by learning styles or learning preferences. And, if peer ratings behavior is influenced by learning styles or preferences then we plan to aid instructors in managing learning for doing/receiving peer ratings and improving teamwork behavior for students taking their courses based on their students' differences in learning styles/preferences. Our preliminary findings confirm our hypothesis that such peer ratings behavior differences exist.

This full paper aims to investigate students' academic outcomes based on their rurality classification. Despite the large number of studies investigating students' demographics across engineering disciplines, few studies consider how rurality - coming from a rural area - influences students' academic performance. This study also aims to study the variety of demographic variables and pre-college characteristics including home zip code at matriculation as a proxy for point of origin among engineering undergraduate students. Moreover, this study investigates the effects of these characteristics, on undergraduate students' likelihood of graduation and academic success across seven institutions.This is a quantitative study using a longitudinal data from multiple institutions. Students' home zip code is used to classify students to four rurality classifications using the urban-centric locale codes defined by U.S. Census Bureau. The study applies a logit regression on a dataset that includes 30,763 students to investigate the likelihood of graduation of engineering undergraduate students from seven institution. The study then applies an ordinary least squares linear regression model to a subset of 21,311 students who managed to graduate from the same institutions to investigate students' graduation GPA as a proxy of student success based on students' rurality classification. This study also analysis the results disaggregating students based on their institutions. Although the result show that there are different patterns among institutions, but generally, rural students seem at a disadvantage for both GPA and graduation at most institutions.

This workshop, similar to our 2018 FIE workshop but revised to reflect participant feedback, introduces data and tools for investigating undergraduate persistence metrics using R. Student record data are from MIDFIELD, a database of registrars’ data from US institutions. The stratified data sample includes demographic, term, course, and degree information for 98,000 students from 1987 to 2016. The midfieldr package provides functions for determining persistence metrics such as graduation rates and for grouping findings by institution, program, sex, and race/ethnicity. The goal of the workshop is to share our data, methods, and metrics for intersectional research in student persistence. The workshop is designed for R beginners.

Research on student preference in team formation has led to the work in progress of algorithmic integration into an existing team formation algorithm. Forming student teams that are more likely to be successful is a goal of every teacher or instructor using teams as a part of their pedagogy. CATME is a team formation and team management website tool. It contains team formation, peer evaluation and teamwork training tools to help an instructor make and manage student teams. CATME’s team building algorithms include validated teamwork research with practical constraints provided by instructors.CATME’s Team-Maker algorithm uses a heuristic score based on instructor-determined criteria to form teams that optimize the student team composition. The tool includes 20 built-in questions for the instructor to choose from with the option to create individual questions. One question type not accounted for in the current CATME algorithm is a preference ranking question.Augmenting the Team-Maker algorithm to include student project preference as a part of the heuristic score will ease the time struggle of instructors while still forming well-balanced groups. Given that the problem at hand is very similar to the stable marriage problem, the Gale-Shapely algorithm was determined as the best possible options. The Gale-Shapley algorithm, better known for its implementation in the Medical Residency Matching Program, matches entities based on ranked preference lists. Once the algorithm terminates, no two unmatched resident/residency entities prefer each other over their current assignment.This paper documents the testing of the Gale-Shapley algorithm, illustrating methods to use student/instructor/ sponsor ranked preference lists for project selections. These techniques will be used to form teams in the 2018/2019 academic year and results included in final paper versions.

In this research-to-practice paper we provide the context for our research and review our process for conducting our engineering innovativeness factor analysis using Bayesian statistical approaches rather than using the traditional principal components analysis (PCA). Our purpose in discussing this analysis approach is to demonstrate that we found the Bayesian analysis approach to be a superior way to refine factors and reduce survey items when developing our instrument for assessment of engineering innovativeness characteristics.

This research-to-practice paper describes the results of 12 experiments using different combinations of peer evaluation trainings on the quality of peer evaluations of teamwork skills provided by first year engineering (FYE) students in an introduction to engineering course in a large Midwestern University. Our research question was: Which combination of peer evaluation trainings most significantly improves the quality of peer evaluations in this FYE course as measured by using data collected by the CATME (Comprehensive Assessment of Team Member Effectiveness) system's peer evaluation exercise? The five training interventions combined in the 12 experiments were Frame-of-reference teamwork training, Video-based teamwork training materials, Rater practice, Rater accuracy training and In-class teamwork reflections. The training intervention combinations that included Video based training and Rater accuracy training had the most significant effects on improving rater and target variances or the quality of peer evaluations.

This work-in-progress research-to-practice analysis examines whether using a more game-like practice tool for learning a peer rating schema significantly improves the quality of peer evaluations in a team-based course. Peer evaluations in our study are defined as the peer evaluations of teamwork behavior as measured by the CATME peer evaluation system. Data samples in this study include students in teams from introduction to engineering courses in a large Midwest university's engineering program who used the previous version and the current more game-like version of the rater practice tool. We found significant differences in the mean ratings of our intervention group and in the distribution of variances versus our control group in the first peer evaluation of the semester.

This workshop introduces data and tools for investigating undergraduate persistence metrics using R. Student record data are from MIDFIELD, a database of registrars' data from US institutions. The stratified data sample includes demographic, term, course, and degree information for 98,000 students from 1987 to 2016. The midfieldr package provides functions for determining persistence metrics such as graduation rates or program stickiness and for grouping findings by institution, program, sex, and race/ethnicity. The goal of the workshop is to share our data, methods, and metrics for intersectional research in student persistence. The workshop is designed for R beginners.

How successful are undergraduate students who begin in another major and migrate into engineering disciplines after matriculation? In this work in progress, we present quantitative data on outcomes for engineering migrators disaggregated by discipline, race/ethnicity, and sex. The study includes over 73,000 engineering students from nine U.S. universities, including first-time-in-college and transfer students who ever majored in the most common engineering disciplines: Chemical, Civil, Electrical, Industrial, and Mechanical Engineering. Adopting an ecosystem mindset, we have developed metrics including the graduation rate of migrators and “migration yield” to uncover dynamic information, not afforded by the conventional pipeline model, about the successes of students who migrate among the top five engineering disciplines. Our data show that the graduation rates of migrators are typically higher than those of starters for all engineering majors studied. Migration yield varies by race/ethnicity-sex as well as discipline. Migration yield for Chemical, Electrical, Industrial and Mechanical Engineering shows a sex-based effect, whereas Civil shows a race/ethnicity-based effect.

The Multiple Institution Database for Investigating Engineering Longitudinal Development (MIDFIELD) is expanding from 14 to about 100 institutions across the USA. This special session aims to introduce participants to MIDFIELD, explore how to conduct research with such a resource, and explain how participants can access MIDFIELD.

An engineer's ability to work in teams is critical to their engineering career and often a significant factor in a corporate hiring process. Recognizing this need, and motivated to demonstrate outcomes required for accreditation by ABET, most U.S. undergraduate engineering programs include team-based courses in their curricula. Hundreds of these engineering programs use the CATME application (the Comprehensive Assessment of Team-Member Effectiveness), which asks students to assess the teamwork behaviors of their peers. Our goal was to determine how effectively engineering students rated their peers and whether a proven method for improving the use of a rating schema, Frame of Reference training, would improve engineering students' peer rating behavior. We discovered that engineering students do not materially change their peer ratings based on their teaming experiences and we verified that repeated Frame of Reference trainings have a significant impact on peer rating dispersion and potentially the quality of engineering students' peer ratings.

This study uses longitudinal, student record level data from eleven public research universities in the United States over a period of twenty-eight years to investigate nontraditional and traditional undergraduate students who ever declared engineering as a major. A nontraditional student is defined as a person who is older than 24 years of age or attends college part-time for at least part of the academic year. A traditional student is defined as a student who matriculates into a baccalaureate degree program in the summer or fall after high school graduation, is younger than 25 years of age, and pursues college on a continuous, full-time basis during the academic year. The research questions addressed in this paper are: How do nontraditional students enter the engineering curriculum? Are there differences with traditional students' entry into engineering by transfer status? Are there differences in precollege academic preparation? Is the collegiate academic performance of nontraditional students different than traditional students by transfer status? Is there a difference in the graduation or withdrawal rates between nontraditional and traditional students by transfer status? Nontraditional students are very similar to traditional students. Once students choose engineering as a major, there are no differences in mean engineering grade point average (GPA) or final cumulative GPA between nontraditional and traditional students. Nontraditional and traditional students have similar SAT scores, similar high school GPAs, choose an engineering major in similar patterns, and have similar six-year graduation rates. Being a transfer student plays a larger role than being a nontraditional student.

The Multiple Institution Database for Investigating Engineering Longitudinal Development (MIDFIELD) is expanding to include 113 institutions and is being redesigned and archived to be more accessible to researchers. This special session will describe how researchers can better use or gain access to MIDFIELD. At the conclusion of the session participants should be able to: describe MIDFIELD including common data elements, discuss how new variables can be derived from MIDFIELD, understand what is necessary to access the data on the Interuniversity Consortium for Political and Social Research, and define quantitative and qualitative data types and structures and outline research questions and methods of personal interest to them.

Research on nontraditional students in engineering is sparse. We use longitudinal data from eleven public, research universities in the United States to investigate nontraditional (NTS) and traditional (TRS) students who ever declared engineering as a major. Nontraditional students could help fill the national call for more science, technology, engineering, and mathematics (STEM) degrees in the United States. The researchers focus specifically on engineering students because it has been found that they are different from the other disciplines under the STEM umbrella. The research questions addressed in this paper were: Is the peer socioeconomic status different for nontraditional students compared to traditional students? What choices are nontraditional students making for their major, and are these different from or the same as those made by traditional students? Is the pathway different for nontraditional students compared to traditional students? This paper shows that socioeconomic status of nontraditional students in engineering is lower than traditional students in engineering. We show some different choices that nontraditional students make for their engineering major. This research also shows that nontraditional students who start in engineering are less likely to switch to and graduate in other majors than traditional students - non-traditional outcomes are more binary, resulting in either graduation in engineering or leaving the university without a degree, so non-traditional students lead traditional students in both of those outcomes.

With the increased acceptance and inclusion of engineering as an area of study at the K-12 and the proliferation of outreach activities intended to increase students' interest in pursuing degrees and careers in engineering, first-year engineering students are increasingly arriving in university engineering programs with significant prior exposure to engineering content and practices. In this study, using a combination of a survey and follow-up transcript analysis, we explored the relationship between students' participation in pre-college engineering activities and their academic performance in their first year of studying engineering at a large research university. We found no significant relationships between either the type of pre-college engineering activity or the level of participation and students' grades in their first-year engineering classes. We did identify several trends in the data that suggest other areas of study, as well as changes to the data we request from students regarding their pre-college experiences.

Cooperative education programs alternate education and practice, resulting in increased grade point averages, greater confidence in choice of career, and relatively higher post-graduation salaries. This study examines perceived benefits and barriers for students who choose not to participate in co-ops. Since students who participate in co-ops are more likely to persist in STEM fields, and there are differences in participation rates by race/ethnicity (i.e. Black and Hispanic students participate at lower rates), it is critical to understand the reasons for non-participation. Co-op and non-co-op students from a large Midwestern U.S. research university were surveyed and the responses are disaggregated by gender and race/ethnicity. Choice Theory provides a theoretical framework to model perceived benefits and costs of co-op participation. Decision tree modeling is used to describe the different pathways to co-op participation and examine relationships between student backgrounds and pathways. Constant comparative analysis is used to study open-response questions. Future work will include follow up interviews with students from this survey to gain a more nuanced understanding. Findings have implications for the diversification for the engineering labor force.

Students who qualify for Calculus credit via the Advanced Placement (AP) exam often have the choice of accepting the credit, and starting in Calculus II or III, or declining the credit, and retaking Calculus I in a university setting. This study investigates and reports success metrics for students who make a choice of accepting or declining AP Calculus credit. The 2014 College Board National Report states when compared to similar peers, students who receive a score of 3 or higher in an AP exam tend to earn higher college grade point averages (GPAs), have higher graduation rates, and have the opportunity to take more discipline course work in college. This report is based on all the AP courses offered by College Board. It is not certain what the outcomes are for an individual course, i.e. AP Calculus, or how the markers of success translate to engineering students and engineering programs. By analyzing 3,600 engineering students academic records from Fall 2012 and 2014 (i.e. gender, ethnicity, residency, grade received in Calculus I course, AP Calculus exam score, High School GPA, SAT/ACT Math and Verbal score), this study seeks to describe patterns of success in students' subsequent Calculus courses from those who accepted AP Calculus credit, skipping Calculus I, as opposed to those who did not accept their AP Calculus credit and took Calculus I. Students ask for recommendations from their first year engineering advisors on whether to retake Calculus I in college or accept their AP Calculus credit, which consists of a score of 4 or 5 at this university. As research in this specific topic is absent, advisors in a first year engineering program must advise in the absence of concrete data. This paper offers insight based upon previous student academic records, which may inform advisors and incoming first year students on whether or not to accept AP Calculus credit.

The transfer pathway, particularly from two- to four-year colleges, is often seen as a vehicle to expand the science and engineering workforce by increasing college participation of underrepresented groups, such as black or African American students. In an earlier study, after controlling for credits earned, we found that black transfer students are more likely to persist in engineering than non-transfer black students - a finding that does not hold for students of other ethnicities. In this paper, we study this somewhat puzzling difference in outcomes for black transfer students. Using an updated version of the longitudinal data set used in the earlier study that enables us to distinguish transfers from two- versus four-year institutions, we find that (1) black students in engineering are more likely to transfer from other four-year institutions than from two-year institutions, and (2) transfers from two- versus four-year institutions differ on several key characteristics, including gender, full- versus part-time enrollment status, and education outcomes including six-year graduation in engineering. Observing that our earlier results were driven by transfer students from four-year institutions, we focus this analysis on transfers from two-year colleges to identify factors associated with their performance and persistence in engineering. We find that gender and academic achievement (engineering GPA) - not transfer status - are driving graduation outcomes for two-year black transfer students. Black women are 28 percent less likely to drop out, IS percent less likely to fail an engineering course, and 25 percent more likely to graduate in engineering in six years than black men. In terms of performance, for every tenth of a grade point increase in engineering GPA, the odds of a black student graduating with an engineering degree in six years improves by 13.7 percent. These results should inform debates regarding the effectiveness of the two-year transfer pathway in engineering for black and other minority students.

There is a growing interest in understanding innovative behavior in engineers. However, there are a limited number of empirical studies that describe innovative characteristics that are unique to engineers. In this research we are conducting a modified Delphi Study to examine the complex constructs associated with engineering innovativeness. The first round survey was developed based on data from a prior qualitative study. The participants in our Delphi study were a group of 102 recognized engineering innovators averaging over 25 years' experience and drawn from academic, corporate, and entrepreneurial organizations. At the conclusion of the Delphi Study, participants will have completed three anonymous rounds of online surveys asking them to clarify and rank order characteristics of innovative engineers by phases of the innovation process. This paper discusses our methodology, initial round one Delphi Study results and the next steps in our research, which include the second and third round surveys. The findings will inform the development of surveys designed to measure innovativeness among engineering.

Cooperative education programs (co-op), also referred to as Work-Integrated Learning (WIL), provide students with relevant professional experiences in industry. This industry-focused environment presents an opportunity for students to clarify academic and career objectives prior to finishing their studies. This first stage of a four-phase research project explores undergraduate engineering students' interest and decision-making process related to participation in cooperative education at a large mid-western U.S. university. Students who showed initial interest in co-op by attending an information session in 2013-2014, but did not participate in a co-op experience are interviewed. This paper provides an overview of the methods used to accomplish this objective, as well as discusses the future directions and implications of the work. Social Cognitive theory provides a framework for students' reasons for non-participation in the context of factors, such as campus environment, pre-collegiate work experiences, academic course selections, peer interactions, and career intentions. Through the use of phenomenological inquiry, information obtained directly from the students who have expressed interest, but chosen not to pursue co-op provides information to co-op administrators and stakeholders to consider how the program and its recruiting processes may be strengthened.

Various technological, economic, and social developments may radically reshape engineering and computer science education in the next 20 to 30 years. Leaders in engineering education, such as IEEE, that play key roles must decide how they will innovate and support initiatives to improve engineering education. Decisions must be guided by both historical trends and potential future evolutions of engineering education. Since the future cannot be predicted, the organizations may be interested in methodologies to help make decisions. IEEE's Curriculum and Pedagogical Committee (CPC), which is charged with helping IEEE make solid decisions, engaged in a scenario planning exercise to help understand how various influences and trajectories could influence engineering education. Scenario planning methodology has been used by many organizations making long-term investments, to understand how future developments could be taken into account when making key decisions. The purpose of the workshop is to allow participants to experience some aspects of the scenario planning methodology and to compare their results with the results generated by the CPC.

Various technological, economic, and social developments may radically reshape engineering and computer science education in the next 20 to 30 years. Leaders in engineering education, such as IEEE, that play key roles must decide how they will innovate and support initiatives to improve engineering education. The IEEE's Curriculum and Pedagogical Committee (CPC), which is charged with helping IEEE forecast the future of engineering education and make decisions about IEEE's roles in preparing for and crafting that future, engaged in a scenario planning exercise to help understand how various influences and trajectories could influence engineering education. Scenario planning methodology has been used by many organizations making long-term investments. After considering influencers in the engineering education environment; important stakeholders and their roles; goals, constraints, and outcomes for key stakeholders; and potential uncertainties, the CPC identified two critical uncertainties over the next five years: (i) How will engineering programs innovate and adapt? (ii) What will be the values and competencies of engineering faculty? By considering two extremes for each of these uncertainties, the CPC crafted four scenarios, which are described in this paper, to characterize potential future trends and how different scenarios will influence the evolution of engineering education.

Practitioners in engineering education, in studying and presenting their quantitative data, typically seek meaning - an inherently rhetorical activity. Data displays are an important part of this discourse. Visual conventions (pie charts, bar charts, and line charts, for example) can help or hinder the discovery of meaning in a data set. Our work concerns the visual rhetoric of this community: we assess current conventions and promote contemporary approaches to more effectively discover and communicate stories in the data. In this work in progress, we present three data displays from the Journal of Engineering Education representing commonly encountered, conventional designs. We assess the rhetorical merits and shortcomings of the displays, redesign them using principles and practices from the data visualization community, and discuss the results. We conclude that intentional design of data displays can help researchers explore their data, discover questions that might not have arisen otherwise, and convey compelling messages to their audiences.

We are conducting a longitudinal, multi-institutional, and multivariate study of the trajectories of students in specific engineering disciplines in the U.S.A. to an extent never before possible. Focusing on the eleven partner institutions of the Multiple-Institution Database for Investigating Engineering Longitudinal Development (MIDFIELD), we examine trajectories of engineering students in five engineering disciplines by race/ethnicity and gender. This work-in-progress focuses on the largest fields: chemical (ChE), civil (CVE), electrical (EE), industrial (IE), and mechanical (ME) engineering. Our results show that all disciplines lose about half of their starters. However, when transfer students and others who switch into the majors are included, the results vary by race/ethnicity, gender, and engineering discipline. The metrics used are trajectories and stickiness in the major and in engineering. This work can inform educators, administrators, and policy makers about how engineering disciplines are racialized and gendered in different ways. Sharing this information can help engineering disciplines learn from each other.

There have been numerous calls to improve undergraduate teaching in engineering to attract and retain a larger and more diverse engineering student body. This work-in-progress paper will describe research that will explore the perceptions of engineering professors over the past 17 years to gain a better understanding of the climate for quality teaching in engineering. This study builds on surveys of faculty teaching practices that were collected from 1997, 1999, and 2002 in the Southeastern University and College Coalition for Engineering Education (SUCCEED). Faculty at the SUCCEED partner institutions were surveyed again in 2014. From the survey results, researchers will be able to analyze how engineering faculty perceive the climate for quality teaching at their institution and how this related to their individual teaching methods. The research considers a theoretical model proposed by Henderson and Dancy, 2007, which shows the relationship between the departmental climate and an individual's teaching methods. The model requires validation and possibly refinement.

This study uses longitudinal data from eleven public, research universities in the U.S. to compare grades in required courses, graduation rates, and final cumulative grade point average of traditional (TRS) and nontraditional (NTS) students who ever declared engineering as a major. There have been national calls for increasing the numbers of science, technology, engineering, and mathematics (STEM) degrees in the U.S., and nontraditional students represent a large potential source of STEM majors. Engineering is studied separately because it has been found to be different than other STEM disciplines. The participating institutions are representative of large public universities that offer a large majority of U.S. engineering degrees. Understanding the choices and outcomes of nontraditional students can inform the process by which the students earn their degrees. Our results show that NTS earn grades that similar (but consistently higher) to those earned by TRS in Science, Mathematics, Engineering courses and have similar cumulative final grade point averages. NTS also graduate in six years at higher rates than TRS. By recruiting and matriculating more NTS, engineering programs can increase six-year graduation rates and graduate more engineering students.

Cooperative education (co-op) programs in engineering provide students with relevant professional experience before they finish their undergraduate degree. Most programs and employers have academic eligibility requirements that make it difficult to infer whether successful employment outcomes are due to the selection of higher performing students or the causal effect of co-op participation. The goal of this study is to determine factors that are associated with participation in engineering cooperative education programs, controlling for eligibility. Longitudinal and multivariate data from six different institutions, each with large engineering programs where co-op participation is not mandatory, were studied with stepwise logistic regression. Results show that cumulative GPA at the end of the second semester is the strongest predictor of co-op participation. While institutional differences, year of matriculation, ethnicity, major discipline, and high school variables are also significant, gender is not related to co-op participation. The results from this paper will provide useful information for colleges, co-op administrators, and employers about who participates in co-op programs.

As a result of the growth of formal and informal pre-college engineering opportunities, many students are enrolling in university engineering programs with significant prior exposure to engineering ideas and practices. This study explores how participation in pre-college engineering programs and activities affects the experiences of students in a first-year engineering program. Twenty-three students selected for maximum variation in their experiences were interviewed and the resulting transcripts analyzed using a phenomenographic research framework. Preliminary results suggest seven broad categories of description encompassing a broad range of both positive and negative effects resulting from pre-college engineering experiences.

Sixty-one sophomores were interviewed at six large public institutions to learn why they chose their institution and their engineering major. The institutions were categorized as either requiring a first-year engineering (FYE) program or allowing students to matriculate directly into a major. At these institutions, the first-year experience either required a common introduction to engineering course, required introduction to engineering courses that were not common to all majors or included an optional introduction to engineering course. The impact of the matriculation mode on selection of the institution and the presence or absence of a required first year course are studied. We find that cost of attendance is far more important than matriculation mode for most students choosing their institutions. Required and optional first-year courses, when taken, do tend to help students either affirm their prior choice of major or select an engineering major that suits their interests.

Using longitudinal data from eleven institutions in the U.S., this study explores the persistence of students in the two largest engineering disciplines: Electrical (EE) and Mechanical (ME). These programs have large enrollments of students but small percentages of women. Despite these similarities, enrollment and persistence in these majors is qualitatively different. In this research, we adopt an intersectional framework and consider both race/ethnicity and gender. Our results show that ME attracts more White students while EE attracts more Black and Asian students. Hispanic men and women are attracted in similar numbers to EE and ME. Overall, ME has higher graduation rates than EE and women have higher rates than men in both disciplines. Transfer students of nearly all race/gender groups are more likely to persist to graduation than starters in the same disciplines. Black and Hispanic female transfer students are particularly successful in EE and ME, which suggests enhancing the transfer pathway as a strategy to improve diversity. The success of ME starters causes a shift in the demographic profile between starters and graduates. ME could learn from EE how to diversify its enrollment and EE could learn from ME strategies to retain its diverse students. These findings suggest that program factors affect each race-gender group differently. Therefore, the success of recruitment and retention strategies may depend on considering both the target population and the discipline.

The goal of this workshop is to introduce participants to tools that can help them manage teams in their classes effectively and efficiently. We review some of the factors that instructors may wish to consider when administering self- and peer-evaluations and how they might improve the quality of those evaluations using rater training. Attendees with wireless-network-capable laptop computers will interact with the system in real-time.

Building on the work of others, we propose a different approach to studying the influence of letter grades on engineering students' major choice and migration patterns. As this work progresses, we will improve understanding of the effects of course performance, grading distributions, and early major intentions on the likelihood that students will persist in a given field.

A new metric, “stickiness,” is proposed, tracking longitudinally all students who have contact with a discipline to determine the likelihood those students will “stick” to that discipline and graduate in it. This metric has the versatility to be relevant for students making contact with engineering through a variety of pathways. Stickiness exhibits significant disciplinary differentiation. Whereas earlier work has shown that Industrial Engineering is the most successful at attracting and retaining students, the disciplinary distribution of stickiness shows that Industrial Engineering is exceptional. Disaggregating by race/ethnicity and gender, much larger variations in stickiness are observed (as much as 48 percent), and positive and negative outcomes are identified where students in particular subpopulations are more or less likely to stick than expected. Aggregated by race/ethnicity and gender, the stickiness of transfer students ranks the disciplines in the same order as the stickiness of first-time-in-college students, but transfer stickiness exhibits less disciplinary variation and transfer students in all disciplines exhibit higher stickiness than first-time-in-college students.

Longitudinal data from ten U.S. institutions are used to characterize outcomes of three matriculation models: Direct Matriculation to a specific major (DM), First-Year Engineering programs (FYE), and Post-General Education Programs (PGE). Both DM and FYE programs show high persistence rates, but FYE programs are less likely to attract transfer students and switchers. FYE graduates are the most likely to stick with their first choice of major (after completing FYE requirements), followed by DM graduates who begin in undesignated engineering (taking extra time to decide), then DM graduates who choose their major as part of the matriculation process, and then PGE graduates. FYE students also have the shortest time to graduation. We conclude that encouraging students to associate with engineering or an engineering discipline from the start, yet maintaining the curricular flexibility to allow alternate entry points onto the engineering path improves persistence, accessibility, effectiveness of major choice, and time to graduation.

Transfer students make up a significant share of engineering college graduates, yet their persistence is seldom studied, largely because of the lack of longitudinal data. This analysis used longitudinal data from 11 universities enrolling large numbers of engineering students to investigate the demographic characteristics and educational outcomes of transfer students in engineering relative to non-transfers. We find that students who transfer to four-year engineering programs are more likely to come from under-represented minority groups (URMs) and less likely to be women, although both groups are over-represented at two-year colleges. The findings confirm existing research indicating that, on average, non-transfers outperform transfer students, and non-URMs outperform URMs. But we also find that URM transfers, and especially Black transfers, are no less successful than nontransfer students - indicating that the transfer pathway is an effective bridge to a four-year degree. This is partly true for women transfers who do as well as men but are outperformed by women non-transfers. Finally, we find significant variation in outcomes between full- and part-time students, which may be driving the observed differences by transfer status. Our results should inform debates regarding the efficacy of the transfer pathway in engineering, particularly for women and URMs.

The purpose of this study is to examine differences in student performance among engineering disciplines, as measured by term GPA's. Results indicate that: 1) Women outperform men in most engineering disciplines; 2) Student performance starts low at the freshman level, drops slightly at the sophomore level, and then increases over the junior and senior levels (without controlling for mortality); 3) Significant differences in GPA's remain between majors after controlling for relative SAT score, academic class level, race, and gender; 4) After controlling for major, relative SAT score, academic class level, and race, the gender gap in performance grows even larger.