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1. The Engineering of Climate Engineering

   https://doi.org/10.1146/annurev-control-053018-023725  

   MacMartin, Douglas G. ; Kravitz, Ben ( May 2019 , Annual Review of Control, Robotics, and Autonomous Systems)

   While reducing anthropogenic greenhouse gas emissions remains the most essential element of any strategy to manage climate change risk, it is also in principle possible to directly cool the climate by reflecting some sunlight back to space. Such climate engineering approaches include adding aerosols to the stratosphere and marine cloud brightening. Assessing whether these ideas could reduce risk requires a broad, multidisciplinary research effort spanning climate science, social sciences, and governance. However, if such strategies were ever used, the effort would also constitute one of the most critical engineering design and control challenges ever considered: making real-time decisions for a highly uncertain and nonlinear dynamic system with many input variables, many measurements, and a vast number of internal degrees of freedom, the dynamics of which span a wide range of timescales. Here, we review the engineering design aspects of climate engineering, discussing both progress to date and remaining challenges that will need to be addressed. 

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2. Prediction of Engineering Identity in Engineering Graduate Students

   https://doi.org/10.1109/TE.2019.2901777  

   Choe, Nathan Hyungsok ; Borrego, Maura ( March 2019 , IEEE Transactions on Education)

   Contribution: This study shows that identification with engineering for engineering graduate students is positively and significantly predicted by engineering interest, competence, recognition, and interpersonal skills competence. Background: Prior studies of engineering identity on undergraduates identified several factors (e.g., engineering interest, engineering recognition) as positive predictors of identification of engineering. Engineering competence, achieved by participating in design projects, is a crucial part of students’ efforts to become more innovative engineers. Identity theory is used to understand undergraduates’ persistence in engineering, as students with stronger engineering identification are more likely to persist. More work is needed focusing on graduate students. Research Questions: Do engineering identity measurement frameworks studied for undergraduate students also apply to graduate students? Do they correlate with intention to complete the degree? What predicts the engineering identity of engineering Master's and doctoral students? Methodology: Interviews informed development and adaptation of a multi-scale survey instrument. Factor analyses identified four factors that relate to graduate engineering identity: engineering interest, engineering recognition, engineering competence, and interpersonal skills competence. Three sequential multiple linear regression models were used to predict engineering graduate students’ engineering identity. Findings: The final regression model, which includes student characteristics and the four factors resulting from Confirmatory Factor Analysis, predicts 60% of the variance in engineering identity—substantially more than similar undergraduate engineering identity models. All four factors were significant and positive predictors of graduate students’ engineering identity. The engineering recognition factor in particular needed adaptation to emphasize peers and faculty members over family, although family remained important. 

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3. Engineering Allies: The Personalities of Cisgender Engineering Students

   Rohde, J.A. ; Kirn, A. ; Godwin, A. ( June 2017 , ASEE Annual Conference & Exposition)

   https://peer.asee.org/28248 The research draws from a larger study conducted at four large public universities examining the non-normative attitudes of first-year engineering students and how these attitudes might affect their collegiate experience and the development of their engineering identity. Within the survey demographics section, students were asked to report their gender with as many options as they felt appropriate to describe themselves. Students were given the option to respond “male,” “female,” “cisgender,” “transgender,” “agender,” “genderqueer,” and/or “a gender not listed.” Of the students surveyed, 2,697 identified themselves as male or female. Of this population, 55 students additionally identified themselves as cisgender. A Welch’s t-test revealed that factors relating to engineering identity were significantly different between cisgender students who self-identified and those who did not. Self-identified cisgender students possessed higher scores on factors measuring components of engineering identity, such as Physics Performance/Competence beliefs (p = 0.001, Cohen’s d = 0.412). These students were also rated as higher on Openness from the “Big 5” personality measures (p = 0.006, Cohen’s d = 0.403), and scored significantly lower on Conscientiousness from the “Big 5” personality measures (p = 0.028, Cohen’s d = 0.343). These data highlight the differences between cisgender identified and non-identified students. Higher Openness results indicate that cisgender students are significantly more attentive of individuals’ inner feelings and may seek out more variety in their experiences than their non-cis-identified peers. Lower Conscientiousness scores reveal that cisgender students, on average, are less likely to conform to traditional cultural norms. Additionally, stronger scores relating to engineering identity indicate that cisgender-identified students feel that they belong in engineering. Together, these findings suggest that cisgender students possess traits and attitudes that could position them as ambassadors to or changemakers within engineering culture. Future research will work to understand these differences qualitatively to inform ways in which these individuals may serve as allies or “bridgers” for individuals within engineering who do not conform to gender and sexual orientation binaries. 

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4. Professional Aspects of Engineering: Improving Prediction of Undergraduates’ Engineering Identity

   https://doi.org/10.1061/(ASCE)EI.1943-5541.0000413  

   Choe, Nathan H. ; Martins, Luis L. ; Borrego, Maura ; Kendall, Meagan R. ( July 2019 , Journal of Professional Issues in Engineering Education and Practice)
5. First-year engineering students’ identification of models in engineering

   Shah, Nishith ; Thaker, Pujan ; Rodgers, Kelsey J. ; Verleger, Matthew A. ( April 2020 , Discovery Day presented by The Office of Undergraduate Research at Embry-Riddle Aeronautical University)

   Background To succeed in engineering careers, students must be able to create and apply models to certain problems. The different types of models include physical, mathematical, computational, graphical, and financial, which are used both in academics, research, and industry. However, many students struggle to define, create, and apply relevant models in their engineering courses. Purpose (Research Questions) The research questions investigated in this study are: (1) What types of models do engineering students identify before and after completing a first-year engineering course? (2) How do students’ responses compare across different courses (a graphical communications course - EGR 120 and a programming course - EGR 115), and sections? Design/Methods The data used for this study were collected in two introductory first-year engineering courses offered during Fall 2019, EGR 115 and EGR 120. Students’ responses to a survey about modeling were qualitatively analyzed. The survey was given at the beginning and the end of the courses. The data analyzed consisted of 560 pre and post surveys for EGR 115 and 384 pre and post surveys for EGR 120. Results Once the analysis is complete, we are hoping to find that the students can better define and apply models in their engineering courses after they have completed the EGR 115 and/or EGR 120 courses. 

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