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Background: Increasing the persistence of engineering transfer students can help meet the US national priority of increasing the number of engineering graduates. Many transfer students experience a decrease in their grade point average (GPA) at their receiving institution, known as transfer shock, which can lead to them leaving the institution. This GPA decrease is found to be more prevalent in engineering transfer students. Purpose/Hypothesis: The purpose of this study is to analyze a single institutional dataset to determine when transfer shock occurs, how it differs among engineering transfer student subgroups, and if transfer shock is a predictor of graduation within 4 years in engineering. Design/Method: A 10‐year dataset with 789 engineering transfer students was used in this study, and the engineering transfer students were split into four subgroups. Multiple statistical analyses were conducted, including Welch's F‐test, chi‐square, and logistic regression, to understand differences in transfer shock during the first three terms of enrollment as well as 4‐year graduation rates among each subgroup. Results: Transfer shock extends through the first three post‐transfer terms, resulting in transfer norming. The engineering transfer student subgroups experience different levels of transfer norming; however, the subgroups were not predictors of graduation. The predictors were the transfer GPA and the transfer norming in the first three post‐transfer terms of enrollment. Conclusions: Engineering transfer students are not a homogeneous population; there are key differences between lateral and vertical transfer students. More strategic, longitudinal programming and decision‐making should be considered by institutions. [ABSTRACT FROM AUTHOR]

Background: Calls to improve learning in science, technology, engineering, and mathematics (STEM), and particularly engineering, present significant challenges for school systems. Partnerships among engineering industry, universities, and school systems to support learning appear promising, but current work is limited in its conclusions because it lacks a strong connection to theoretical work in interorganizational collaboration. Purpose/Hypothesis: This study aims to reflect more critically on the process of how organizations build relationships to address the following research question: In a public–private partnership to integrate engineering into middle school science curriculum, how do stakeholder characterizations of the collaborative process align with existing frameworks of interorganizational collaboration? Design/Method: This qualitative, embedded multiple case study considered in‐depth pre‐ and post‐year interviews with teachers, administrators, industry, and university personnel during the first year of the Partnering with Educators and Engineers in Rural Schools (PEERS) program. Transcripts were analyzed using a framework of interorganizational collaboration operationalized for our context. Results: Results provide insights into stakeholder perceptions of collaborative processes in the first year of the PEERS program across dimensions of collaboration. These dimensions mapped to three central discussion points with relevance for school–university–industry partnerships: school collaboration as an emergent and negotiated process, tension in collaborating across organizations, and fair share in collaborating toward a social goal. Conclusions: Taking a macro‐level look at the collaborative processes involved enabled us to develop implications for collaborative stakeholders to be intentional about designing for future success. By systematically applying a framework of collaboration and capitalizing on the rich situational findings possible through a qualitative approach, we shift our understanding of collaborative processes in school–university–industry partnerships for engineering education and contribute to the development of collaboration theory. [ABSTRACT FROM AUTHOR]

Background: Determining the root causes of persistent underrepresentation of different subpopulations in engineering remains a continued challenge. Because place‐based variation of resource distribution is not random and because school and community contexts influence high school outcomes, considering variation across those contexts should be paramount in broadening participation research. Purpose/Hypothesis: This study takes a macroscopic systems view of engineering enrollments to understand variation across one state's public high school rates of engineering matriculation. Design/Method: This study uses a dataset from the Virginia Longitudinal Data System that includes all students who completed high school from a Virginia public school from 2007 to 2014 (N = 685,429). We explore geographic variation in four‐year undergraduate engineering enrollment as a function of gender, race/ethnicity, and economically disadvantaged status. Additionally, we investigate the relationship between characteristics of the high school and community contexts and undergraduate engineering enrollment across Virginia's high schools using regression analysis. Results: Our findings illuminate inequality in enrollment in engineering programs at four‐year institutions across high schools by gender, race, and socioeconomic status (and the intersections among those demographics). Different high schools have different engineering enrollment rates among students who attend four‐year postsecondary institutions. We show strong associations between high schools' engineering enrollment rates and four‐year institution enrollment rates as well as moderate associations for high schools' community socioeconomic status. Conclusions: Strong systemic forces need to be overcome to broaden participation in engineering. We demonstrate the insights that state longitudinal data systems can illuminate in engineering education research. [ABSTRACT FROM AUTHOR]

In this paper, we discuss efforts to collect and analyse data at the local level to prompt reflective teaching in large foundational engineering courses. The work is in direct response to the growing demands and constraints of teaching in large classes that compromise the educational environment. We feel that motivated improvement-seeking institutions and academics must strive to innovate within the constraints. To do this, we argue that locally rooted data analytics offers unique opportunities to infuse data back into decision-making processes. As a demonstration of our claims, we discuss summaries of our team's efforts within large foundational engineering mechanics courses at a public research institution in the United States. Specifically, we report on work to examine (1) Student Engagement and Performance (analysis of student surveys and course grades); (2) Performance Patterns Not Performance Points (analysis of course-level data); and (3) Understanding Courses in Context (analysis of existing institutional data). [ABSTRACT FROM AUTHOR]

Post-course instructor ratings are a common practice at universities in Europe, Australia, and North America. Rather than solely describing teaching practice, however, such ratings may be associated with a range of non-pedagogical factors. We explored engineering students’ instructor ratings at a large United States institution, investigating relationships between overall instructor rating and some of those non-pedagogical factors, including subject area, class size, and students’ course grades. Instructor ratings were more favourable in humanities courses than in science or math courses, and students gave higher ratings to instructors who taught smaller class sizes. The strongest relationship existed between overall rating and students’ course grades: students who received A’s rated instructors an average 0.84 points higher on a 6-point scale than students who received F’s. Students who withdrew from a course provided the lowest instructor ratings. When instructor ratings are used as metrics of teaching ability in discussions related to promotion, tenure, or salary adjustments, there is an inherent inequity in the system that must be acknowledged beyond already well-documented biases, as non-pedagogical factors often outside of the instructor’s control may be significantly associated with those ratings. [ABSTRACT FROM AUTHOR]

Abstract: Temperature and humidity fluctuations in operating fuel cells impose significant biaxial stresses in the constrained proton exchange membranes (PEMs) of a fuel cell stack. The strength of the PEM, and its ability to withstand cyclic environment-induced stresses, plays an important role in membrane integrity and consequently, fuel cell durability. In this study, a pressure loaded blister test is used to characterize the biaxial strength of Gore-Select® series 57 over a range of times and temperatures. Hencky''s classical solution for a pressurized circular membrane is used to estimate biaxial strength values from burst pressure measurements. A hereditary integral is employed to construct the linear viscoelastic analog to Hencky''s linear elastic exact solution. Biaxial strength master curves are constructed using traditional time–temperature superposition principle techniques and the associated temperature shift factors show good agreement with shift factors obtained from constitutive (stress relaxation) and fracture (knife slit) tests of the material. [Copyright &y& Elsevier]

As higher education institutions look to educate and graduate degree earners that have the skills and knowledge necessary to design, communicate, and collaborate in ways that allow for innovative solutions to complex socio-technical challenges, new approaches to educational efforts are being considered and implemented. Institutional responses have included new courses that have a transdisciplinary focus and embedded course experiences that use problem-based approaches coupled with cross-disciplinary team exposure. Often these initiatives have a singular thematic focus (i.e., sustainability). Little is known about the efficacy of transdisciplinary learning initiatives, especially those that encompass a breadth of thematic areas, as it relates to development of complex thinking skills and whether these learning environments provide for similar benefits across student majors. This study, conducted at a Research I university, was designed to address this gap in the literature by examining whether a university level learning initiative using transdisciplinary approaches was achieving desired goals to advance undergraduate students' complex thinking skills. Findings among the respondents (n = 592) indicate that the initiative is advancing fundamental complex thinking skills in that specific courses allow students to learn about other disciplines and provide exposure to different disciplinary perspectives. However, results reveal that across all majors courses would benefit from increased real-world problem-based exposure and opportunities to interact with community stakeholders. Additionally, results suggest that undergraduates may need opportunities to develop a deeper understanding of the complexities that exist in cross-disciplinary collaboration, including how to develop integrated solutions that leverage the strengths of technical and non-technical approaches. [ABSTRACT FROM AUTHOR]

Self-report assessments are used frequently in higher education to assess a variety of constructs, including attitudes, opinions, knowledge, and competence. Systems thinking is an example of one competence often measured using self-report assessments where individuals answer several questions about their perceptions of their own skills, habits, or daily decisions. In this study, we define systems thinking as the ability to see the world as a complex interconnected system where different parts can influence each other, and the interrelationships determine system outcomes. An alternative, less-common, assessment approach is to measure skills directly by providing a scenario about an unstructured problem and evaluating respondents' judgment or analysis of the scenario (scenario-based assessment). This study explored the relationships between engineering students' performance on self-report assessments and scenario-based assessments of systems thinking, finding that there were no significant relationships between the two assessment techniques. These results suggest that there may be limitations to using self-report assessments as a method to assess systems thinking and other competencies in educational research and evaluation, which could be addressed by incorporating alternative formats for assessing competence. Future work should explore these findings further and support the development of alternative assessment approaches. [ABSTRACT FROM AUTHOR]

Background: Prior researchers developed an instrument to measure perceived design thinking ability of first‐year students interested in engineering, and they validated the instrument through exploratory factor analysis. Purpose/Hypothesis: Our study uses the previously developed instrument to evaluate perceived design thinking ability of senior engineering students. We make a cross‐sectional comparison of this measure on a national scale. Design/Method: We surveyed a national sample of senior engineering students in 2018 and conducted a cross‐sectional comparison with results from a 2012 national sample of first‐year students who were interested in declaring an engineering major. Two‐way analysis of variance tests compared average design thinking scores across sample groups. Confirmatory factor analysis was conducted to improve the design thinking instrument. Results: First‐year students who intended to declare an engineering major score significantly higher (2.80) on the design thinking scale than senior engineering students (2.59) with a medium effect size of 0.4. The senior engineering sample performs significantly worse on the feedback seeking and experimentalism instrument items, but significantly better on the integrative thinking and collaboration items. We found no significant differences in perceived design thinking ability among engineering disciplines among senior students. Conclusions: Feedback seeking and experimentalism are traits that engineering educators should develop in their students to improve perceived design thinking ability. Incorporation of user‐centered design and divergent thinking in the engineering classroom are recommended as avenues to foster feedback seeking and experimentalism. We also offer recommendations to improve the design thinking instrument for future research. [ABSTRACT FROM AUTHOR]

Sustainable development is a systems problem that requires a shift in thinking from individual parts to the relationships between them. Enabling those involved in the development process to more quickly think in systems is therefore vital to create more sustainable solutions. However, measuring the ability to think in systems is a challenge because of the limited methods to observe behavior or measure outcomes. Recent advances in neuroimaging offer a radically new approach to measure one's ability to think in systems. The specific technique, called functional near-infrared spectroscopy (fNIRS), captures the change in oxygenated blood in the cortical region of the brain, which is a proxy for elevated cognitive activation. In this study, engineering students (n = 28) performed both concept mapping (i.e., labeling concepts and drawing directional connections between them) and concept listing (i.e., generating a list of concepts without indicating relationships) related to grand challenges for sustainability. fNIRS captured the increase in oxygenated blood along the prefrontal and parietal cortex during both concept mapping and listing tasks. Self-evaluation and concept mapping scores were also captured and compared. Concept mapping led to significantly more concepts compared to concept listing. Concept mapping also required less cognitive resources (i.e., oxygenated blood) to generate more concepts. The region of the brain that received more cognitive resources is also significantly different when participants were using concept listing and mapping. Concept mapping directed more cognitive resources to the regions of the brain associated with cognitive flexibility and decreased cognitive resources in regions associated with visuospatial processing. Self-evaluation of systems thinking was negatively correlated with concept mapping scores, meaning students with high perceived ability produce worse concept maps. Global efficiency of brain networks was positively correlated to concept map scores and more accurately measure performance compared to self-evaluation. This study provides neurocognitive evidence to support the benefits of concept mapping and also demonstrates the added advantages of neuroimaging to study systems thinking. • Methods from neuroscience are applied to measure cognition during concept generation. • Empirical evidence describes the neurocognitive benefits of concept mapping for sustainability problems. • Self-evaluation is negatively correlated with actual performance while patterns of neuro-activation are positively correlated. [ABSTRACT FROM AUTHOR]