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Paul D Adams, University of Arkansas; Carol S Gattis, University of Arkansas; Xochitl Delgado Solorzano, University of Arkansas; Jennie S Popp Ph.D.; Wenjuo Lo, University of Arkansas

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dissatisfied (1).AcknowledgmentThis material is based upon work supported by the National Science Foundation under Grant No.1742496. Any opinions, findings, conclusions, or recommendations expressed in this material arethose of the author(s) and do not necessarily reflect the views of the National Science Foundation.References[1] Rogers, R., & Sun, Y. (2018), Engaging STEM Students from Rural Areas: Emerging Research and Opportunities. IGI Global. DOI: 10.4018/978-1-5225-6341-9.ch003[2] Harris, R. S., & Hodges, C. B. (2018), “STEM Education in Rural Schools: Implications of Untapped Potential.” National Youth-At-Risk Journal, 3(1). https://doi.org/10.20429/nyarj.2018.030102[3] U.S. Department of Agriculture. (2023, November

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Authors

Marilyn Barger P.E., FLATE (Florida Advanced Technological Education Center of Excellence); Ron Eaglin, Daytona State College; Sam Ajlani; Mori Toosi; Sidney E Martin III, Saint Petersburg Junior College; Richard Gilbert, University of South Florida; Susan Frandsen

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advisory board need to be recruited.AcknowledgmentThis work was funded in part by the National Science Foundation award 2148138. Any findings, conclusions, orrecommendations expressed in this material are those of the authors and do not necessarily reflect those of theNational Science Foundation.Bibliography[1.] Barger, M, Gilbert, R; Centonze, P; Ajlani, Sam; What’s Next? The Future of Work for Manufacturing Technicians, 2021 ASEE Annual Conference Proceedings (Virtual) (https://peer.asee.org/38053)[2.] Barger, M, M Boyette, R Gilbert - Florida’s Engineering Technology Associate of Science Degree Program: A Model for Technical Workforce STEM Based Education, Journal of Engineering Technology, Spring (2014). - See more at: http

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Jaejin Hwang, Northern Illinois University; Mohammad Faizan Sohail, Northern Illinois University

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afterexperiencing the AR educational tool. 3.2.Number of rest and achievementsFollowing the AR educational tool experience, there was a substantial reduction in the averagenumber of resets for path-finding layouts among students who gave up on solving the path andattempted new layouts. The average number of resets decreased from 7 to 1.4, reflecting asignificant improvement. Four students notably decreased their number of resets by 10, asillustrated in Figure 2. Additionally, there was an increase in the average number of achievements,rising from 5 to 9 gems. The number of achievements represents the gems students were able tocollect, and all five students achieved more gems, with an increase of up to 4 compared to the pre-test, as shown in Figure 2

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Varun K Kasaraneni, Gannon University; Scott Steinbrink, Gannon University; Lin Zhao, Gannon University; Saeed Tiari, Gannon University; Karinna M Vernaza, Gannon University

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journeys.AcknowledgmentThis material is based upon work supported by the National Science Foundation under Grant No.1107015, 1153250, 1643869 (past three grants), and 2221052 (active grant). Any opinions,findings, and conclusions or recommendations expressed in this material are those of the authorsand do not necessarily reflect the views of the National Science Foundation.References[1] Vernaza, K. M., Vitolo, T. M., Steinbrink, S., Brinkman, B. J. (2011). Scholars of Excellence inEngineering and Computer Science Program Phase I: Development and Implementation. Proceedings ofthe 2011 American Society of Engineering Education Annual Conference, June 26-29, Vancouver, BritishColumbia, Canada.[2] Vernaza, K. M., Steinbrink, S., Brinkman, B. J., Vitolo, T. M. (2014

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Eric Davishahl, Whatcom Community College; Anna Fay Booker; Petra Shea McDonnell-Ingoglia, Whatcom Community College; Pat Burnett, Whatcom Community College

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presented the results ofyear 1 work, the background and theoretical underpinning and motivation for the project, and ourresearch and assessment plan in 2023 [3]. This current paper reflects on our experience recruitingand piloting the learning community courses for the first time in Fall 2023 and Winter 2024. Wepresent the demographics of the first cohort in comparison to students in a non-linked version ofour Introduction to Engineering course (ENGR 101). We also describe a few examples ofinterdisciplinary curriculum and projects that we have developed and share some studentfeedback on their experience.Student Recruitment, Demographics, and RetentionWe took the following steps to recruit students for the new learning community. A new page onthe

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2024 ASEE Annual Conference & Exposition

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Emma Treadway, Trinity University; Jessica E S Swenson, University at Buffalo, The State University of New York

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authors and do not necessarily reflect the views of the National ScienceFoundation.Bibliography[1] J. R. Morelock, “A systematic literature review of engineering identity: definitions, factors, and interventions affecting development, and means of measurement,” Eur. J. Eng. Educ., vol. 42, no. 6, pp. 1240–1262, Nov. 2017, doi: 10.1080/03043797.2017.1287664.[2] A. Godwin, “The Development of a Measure of Engineering Identity,” in 2016 ASEE Annual Conference & Exposition Proceedings, New Orleans, Louisiana: ASEE Conferences, Jun. 2016, p. 26122. doi: 10.18260/p.26122.[3] Z. Hazari, G. Sonnert, P. M. Sadler, and M.-C. Shanahan, “Connecting high school physics experiences, outcome expectations, physics identity, and physics career

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George Kow Quainoo, North Park University

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data, making direct comparisons at each time point more difficult.However, quantitative data and qualitative data demonstrate gains in program objectives forcohort members. Students, despite a pandemic, showed growth in professional skills and careernetworks through the support of their S-STEM mentor, program guidance, tutoring, andinternship opportunities.IV AcknowledgementsThis material is based upon work supported by the National Science Foundation (NSF) underGrant No. 1833769. Any opinions, findings, and conclusions or recommendations expressed inthis material are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation. The authors would like to acknowledge Eric Brown, Yoojin Choi, ReneeCox

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Jennifer Cromley, University of Illinois Urbana-Champaign; Karin Jensen, University of Michigan; Joseph Francis Mirabelli, University of Michigan

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conclusions or recommendations expressed in thismaterial are those of the authors and do not necessarily reflect the views of the National ScienceFoundation. The authors thank our project evaluator, Dr. Liz Litzler. We thank advisory boardmember Diana Gonzalez for her support with recruitment on this project. The authors also thankthe year 2 and year 3 participants for supporting this work by sharing their experiences in oursurveys. References[1] T. M. Evans, L. Bira, J. Beltran-Gastelum, L. T. Weiss, and N. L. Vanderford, Evidence for a mental health crisis in graduate education, The FASEB Journal, vol. 36, pp. 282- 284, 2018.[2] J. L. Lott, S. Gardner, and D. A. Powers, Doctoral student

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Alexandra Coso Strong, Florida International University; Adam Kirn, University of Nevada, Reno; Kaitlyn Anne Thomas, University of Nevada, Reno; Mais Kayyali, Florida International University; Kelsey Scalaro, University of Nevada, Reno

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the GPDs to reflect on thelived experiences of graduate students in their program. As part of these questions, we inquiredabout the extent to which students were experiencing trauma during the time in graduate schooland the actions taken by the GPD when a student was experiencing trauma. The interview alsoincluded questions about the role of the department and institution in handling traumatic events.All the interview audio was transcribed by Rev.com for analysis purposes.Preliminary Data AnalysisLeveraging trauma-informed frameworks of care and systems analysis techniques, the dataanalysis has focused on the first two research questions noted in the Project Overview section.To this end, the initial data analysis process involved examining

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Diana Arboleda, University of Miami; James Giancaspro P.E., University of Miami; Aaron Heller, University of Miami

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analyzedalong with data from the other survey instruments to explore the relationships between cognitive,motivational, and emotional processes on self-efficacy as it relates to academic persistence.6. AcknowledgementsThis material is based upon work supported by the National Science Foundation under Grant No.2204892. Any opinions, findings, and conclusions or recommendations expressed in thismaterial are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation.7. References[1] H. N. Haron and A. M. Shaharoun, "Self-regulated learning, students' understanding and performance in engineering statics," presented at the IEEE

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Homero Murzi, Virginia Polytechnic Institute and State University; Yi Cao, Virginia Polytechnic Institute and State University; Natali Huggins, Virginia Polytechnic Institute and State University; Andres Nieto Leal, Virginia Polytechnic Institute and State University

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recommendations expressed in this material arethose of the author(s) and do not necessarily reflect the views of the National ScienceFoundation.References[1] I. Direito et al., “Diversity, Equity, and Inclusion in Engineering Education: an Exploration of European Higher Education Institutions’ Strategic Frameworks, Resources, and Initiatives,” in SEFI 49th Annual Conference Proceedings 2021, SEFI - European Society for Engineering Education; Brussels, Dec. 2021, pp. 189–193. Accessed: Feb. 08, 2024. [Online]. Available: https://lirias.kuleuven.be/3635850[2] K. Fu et al., “Broadening participation: A report on a series of workshops aimed at building community and increasing the number of women and minorities in engineering design,” in

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Syed Hassan Tanvir, University of Florida; Gloria J Kim, University of Florida; Jing Guo, University of Florida; Philip Feng, University of Florida; Wanli Xing, University of Florida

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instructor's reflection on the overall EEE 4423 course experience.Student Exit Survey: The fundamental purpose of the exit survey was to record students’perspectives on lecture content, homework assignments, overall course experience, and thechallenges they encountered during the EEE 4423 course. The survey also aimed to assess theperceived difficulty of the workload and homework assignments. In the end, students self-assessed their current level of understanding of the 9 key concepts introduced in the course.Additionally, the survey aimed to identify any barriers that might have posed challenges tounderstanding these 9 key concepts of QIS.Student Exit Interview: Following this student exit survey, a 45-minute semi-structured interviewwas conducted

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Michael Johnson, Texas A&M University; Amarnath Banerjee, Texas A&M University; Bimal P. Nepal, Texas A&M University; Rutwik Dehade, Texas A&M University; Glen Miller

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questions.The project anticipates expanding the scope of the E3 program by recruiting a higher number ofhigh school teachers and provide them training in developing ethics curriculum for their studentsalong with relevant practical examples so that a larger number of prospective first-generationstudents can receive exposure to the education required to help improve their ethics self-efficacy.Acknowledgement: This work was supported by the National Science Foundation’s Ethical andResponsible Research (ER2) grant (SBE # 2124888). Any opinions, findings, conclusions, orrecommendations presented are those of the authors and do not necessarily reflect the views of theNational Science Foundation.References: 1. R. Thornberg, “The lack of professional

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Elisa Bravo, University of Michigan; Jesse Austin-Breneman, University of Michigan

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relationships and create connections in thesocial fabric of the makerspace [11], [13]. To have an inclusive makerspace, all studentparticipants must have a strong sense of belonging [11], [14]. Fostering a culture that engendersbelonging in participants requires makerspace leaders and administrators to critically questionhow the environment and culture of the makerspace systematically marginalize certain groupsfrom participating and succeeding in these spaces [15]. To ensure that the makerspace does notreinforce a “closed loop” culture, makerspace designers should reflect on who is not present inthe makerspace and the potential barriers to participation and belonging present in the currentmakerspace design [11]. This can be difficult to achieve because

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Authors

Leo C. Ureel II, Michigan Technological University; Laura E Brown, Michigan Technological University; Michelle E Jarvie-Eggart P.E., Michigan Technological University; Jon Sticklen, Michigan Technological University; Laura Albrant, Michigan Technological University; Mary Benjamin, Michigan Technological University; Daniel Masker, Michigan Technological University; Pradnya Pendse; Joseph Roy Teahen, Michigan Technological University

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Conference on Innovation and Technology in Computer Science Education, pp. 325–325, 2019. [6] M. L. Walther, “Matlabta: A style critiquer for novice engineering students,” Master’s thesis, Michigan Techno- logical University, Houghton, MI, 2020. [7] J.-M. Robert and E. Brangier, “What is prospective ergonomics? a reflection and a position on the future of ergonomics,” in Ergonomics and Health Aspects of Work with Computers: International Conference, EHAWC 2009, Held as Part of HCI International 2009, San Diego, CA, USA, July 19-24, 2009. Proceedings, pp. 162–169, Springer, 2009. [8] R. Oshana, “Human factors and user interface design for embedded systems,” in Software Engineering for Em- bedded Systems, pp. 417–440, Elsevier

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Gina Ristani, University of Minnesota, Twin Cities; Keisha Varma, University of Minnesota, Twin Cities; Seth Thompson, University of Minnesota, Twin Cities

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aspect of the projectis to improve the communication of the broader impacts and societal benefits provided by thecommunity’s research in engineering. The project focuses its mission not only on the engineeringresearch necessary to advance the field, but on the need to educate an engineering workforce thatis a demographic reflection of the current and future nation so we may maximize the impact ofengineering technologies on society. This investigation was undertaken through two approaches.Primarily, we sought to understand to what extent researchers are communicating the broaderimpacts of their work. In addition, we explored the ways in which researchers communicatethose impacts. Theoretical Background

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Ahatsham Hayat, University of Nebraska, Lincoln; Sharif Wayne Akil, University of Nebraska, Lincoln; Helen Martinez, University of Nebraska, Lincoln; Bilal Khan, Lehigh University; Mohammad Rashedul Hasan, University of Nebraska, Lincoln

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: at-risk or prone-to-risk (grade below B-), and average or outstanding (grade B- or above) • Three types: at-risk or prone-to-risk (grade below B-), average (grade B- or above but below A-), and outstanding (grade A- or above) • Four types: at-risk (grade below C-), prone-to-risk (Grade C- or above but below B-), average (Grade B- or above but below A-), and outstanding (grade A- or above)Addressing RQ2, we delve into the impact of integrating students’ background andnon-cognitive features on the predictive accuracy of LLMs. We hypothesize that a richer featureset, reflecting both the academic and experiential learning trajectories of students, cansignificantly enhance LLM forecasting capabilities.Our contributions are

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Nolgie O. Oquendo-Colón, University of Michigan; Xiaping Li, University of Michigan; Laura Carroll, University of Michigan; Cynthia J. Finelli, University of Michigan

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interviews to understand the role classroom teachingpractices play in the academic success of engineering students with ADHD. Collectively, thisresearch allows us to explore students’ perceptions of how active learning and lecture-basedclasses influence their classroom experiences, academic adjustment, and sense of belonging.AcknowledgmentsWe would like to acknowledge Cooperative Institutional Research Program (CIRP), the HigherEducation Research Institute (HERI), and the University of California, Los Angeles (UCLA). This research is supported by the U.S. National Science Foundation (2043430). Any opinions,findings, and conclusions, or recommendations expressed in this material are those of theauthor(s) and do not necessarily reflect the views of

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Authors

Sarah M. Ryan, Iowa State University; Robert Brown; Amy Kaleita, Iowa State University; Sergio Horacio Lence; Cynthia Lidtke, Iowa State University; Cameron Alexander MacKenzie, Iowa State University; Michelle Lynn Soupir, Iowa State University

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• GLC workshop model graduate students Industry Advisory Board Community (GLC) model • GLC small group reflections to work effectively Diversity Advisory Board • Implement & adjust GLC activities • Trainees' ePortfolios in multidisciplinary • Interdisciplinary based on feedback loop • Symposium content teams, Faculty/Mentors Institutional • Hold annual symposium • Professional & communication communicate Support/Infrastructure • Develop ePortfolio structure core competencies matrix effectively with Investigators' • Develop recruiting practices and

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David Reeping, University of Cincinnati; Kenneth Reid, University of Indianapolis; Matthew W. Ohland, Purdue University, West Lafayette; NAHAL RASHEDI, University of Cincinnati

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curriculum or areas wherestudents may veer off course. Interventions based on the results might entail adjustments tocurricular guidelines, enhanced academic advising, or the implementation of novel programs andinitiatives to bolster student progress. As this project continues to evolve, we expect to delivernew analytical potential to the community and create new strands of inquiry to connect toexisting persistent problems in engineering education. AcknowledgmentsThis material is based upon work supported by the National Science Foundation under Grant No.BPE- 2152441. Any opinions, findings, and conclusions or recommendations expressed in thismaterial are those of the authors and do not necessarily reflect the

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Hakan Gurocak, Washington State University, Vancouver; Xinghui Zhao, Washington State University; Kristin Lesseig

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, scalability can be achieved byholding the lectures in a large computer lab but usually these labs are set up for open access. As aresult, the flowerpots may need to be set up before each lecture and taken away after. Anotherpossibility is to hold multiple sections of the course with smaller section sizes.AcknowledgmentsThis material is based upon work supported by the National Science Foundation under Grant No.DUE-IUSE-2116226. Any opinions, findings, and conclusions or recommendations expressed inthis material are those of the authors and do not necessarily reflect the views of the NationalScience Foundation.References [1] P. Seeling, “Active learning moves programming students from novice to skilled,” https://www.pearsoned.com/active-learning

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Sarah Cooley Jones, Louisiana State University and A&M College; Elizabeth Michelle Melvin, Clemson University

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prioritize and schedule. We also gathered information about students’ experience of the workshop (the knowledge of the presenter, length of the session). Here we present the most salient results about student learning outcomes related to the workshop’s objectives. Learning Styles and Study Groups Workshop: The learning styles and study groups workshop seeks to increase student’s understanding of their results on the Felder/Solomon Engineering Learning Styles Index by learning about a) the different learning style indexes (e.g. active/reflective, visual/verbal, sensing/intuitive, and sequential/global), b) how these indexes manifest when learning new information, and c) what skills to use to adapt

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Authors

Rui Wu, East Carolina University; Sergiu Dascalu, University of Nevada, Reno; Zhen Zhu, East Carolina University; David Feil-Seifer; Marjorie Campo Ringler, East Carolina University; Bryan C. Hutchins; Laura Rosof; Ponkoj Chandra Shill, University of Nevada, Reno; Hossein Jamali, University of Nevada, Reno; Frederick C Harris Jr., University of Nevada, Reno

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theory, personalized learningpedagogies address the assumption that learners, especially college students, have an inherentneed to comprehend the purpose behind their learning endeavors, whether revisiting familiarconcepts or exploring new domains.Within the general framework of personalized learning, activities grounded in real-life scenariosenhance student engagement, particularly evident in fields such as robotics and computer science,where problem-solving and scenario-based learning align with adult learning principles. Derivedfrom andragogy, four key principles characterize adult-centered instruction and learning 10,9,11 :relevance to assignments, encouragement of critical and reflective thinking, acknowledgment andutilization of personal

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Authors

Angela R Bielefeldt, University of Colorado, Boulder; Lupita D Montoya, University of Colorado, Boulder; Andrea Ferro, Clarkson University; Cesunica E. Ivey, University of California, Berkeley; Shakira Renee Hobbs, University of California Irvine; Maya A Trotz, University of South Florida; Cliff I. Davidson, Syracuse University; Susan J. Masten P.E., Michigan State University; Sheryl H Ehrman, San Jose State University; Chang-yu Wu, University of Florida

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) and do not necessarily reflect the views of the National Science Foundation.DeclarationsThis project is being conducted in accordance with research reviewed by Institutional ReviewBoards for Human Subjects Research at Clarkson University (Protocol 23-31) and the Universityof Colorado Boulder (Protocol 23-0344).References[1] American Academy of Environmental Engineers (AAEE), Environmental Engineering Body of Knowledge, Annapolis MD: AAEE, 2009[2] D. Grasso, Chair; Environmental Engineering for the 21st Century: Addressing Grand Challenges. Consensus Study Report. Washington DC: The National Academies Press, 2018. https://doi.org/10.17226/25121[3] L. Blaney, A. MacKay, D. Rodrigues, K. Nelson, “Results from the 2022-2023 member

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Craig O. Stewart, University of Memphis; Chrysanthe Preza, The University of Memphis; Stephanie S Ivey, The University of Memphis

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. These results are presented in Figures 1-4 below. FIGURE 1: Results for survey items 1-5.FIGURE 2. Results for survey items 6-10.FIGURE 3. Results for survey items 11-15. FIGURE 4. Results for survey items 16-20.DiscussionSTEM Identity, Self-Efficacy, Mindset, and Major/Career IntentionsOverall, participation in the VIP program did not seem to impact engineering identity, self-efficacy, mindset, or intentions to remain in the engineering major or pursue an engineeringcareer. Most participants scored highly on these measures, perhaps reflecting a selection bias,with the VIP program attracting students who already have strong sense of themselves as “STEMpeople.” It may also be the case that

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Lucy Arellano Jr., University of California, Santa Barbara

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. University of California, Santa Barbara Jaman Mohit Texas Tech University Montana Montez Texas Tech University Alyson Garcia Midwestern UniversityAcknowledgement:This material is based upon work supported by the National Science Foundation under Grant No.(1930037). Any opinions, findings, and conclusions or recommendations expressed in this materialare those of the author(s) and do not necessarily reflect the views of the National Science Foundation.Correspondence concerning this manuscript should be addressed to

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Authors

Emmanuella Obiageli Ejichukwu, University of Michigan, Dearborn; DeLean Tolbert Smith, University of Michigan, Dearborn; Hanadi Matar, University of Michigan, Dearborn

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share insights from the family narrative (synthesisof all the data generated from the family’s participation) and results of how the family enactedspecific engineering practices. Also, the authors will share a preliminary reflection on how thesepractices might serve as a vehicle to positively impact the sense of belonging of Blackengineering students.1 IntroductionThe academic success of Black students is linked to the familial cultural capital. The familymodel has been employed as a means of helping students adjust to the rigors of higher education[1]. Positive effects on academic accomplishment are produced when a child's academicendeavors are supported by their family [2]. Familial capital shows up in the form of motivatingthe student to

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Authors

Angela Minichiello, Utah State University; Hannah Wilkinson, Utah State University; Samuel Shaw, Utah State University; Allison Miles, Utah State University

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both the regional military student support community andnationally.AcknowledgementsThis material is based upon work supported by the National Science Foundation under Grant No.2045634. Any opinions, findings, and conclusions or recommendations expressed in this materialare those of the authors and do not necessarily reflect the views of National Science Foundation.References[1] “2020 Demographics profile of the military community,” Department of Defense, 2020.[2] K. A. Holder, “Veterans who have served since 9/11 are more diverse,” United States Census Bureau. Accessed: Feb. 07, 2024. [Online]. Available: https://www.census.gov/library/stories/2018/04/post-9-11-veterans.html[3] “VA College Toolkit, ‘Characteristics of Student Veterans

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Authors

Jeong Yang, Texas A&M University, San Antonio; Young Lee, Texas A&M University, San Antonio; Mohammad Abdel-Rahman, Texas A&M University, San Antonio; Zechun Cao, Texas A&M University, San Antonio

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is to determine whether or not the implementation of our new app willimprove rider experiences with the transit system. Additionally, the study would also look intoinsights on whether using SmartSAT app can increase the amount of people that took the publictransportation service.AcknowledgmentThis work is supported by the National Science Foundation under Grant No. 2131193. Any opinions,findings, conclusions, or recommendations expressed in this material are those of the author(s) anddo not necessarily reflect the views of the National Science Foundation.References[1] Transit Capacity and Quality of Service Manual-2nd Edition, http://onlinepubs.trb.org/onlinepubs/tcrp/docs/tcrp100/Part4.pdf.[2] Smartphone Applications To Influence Travel

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2024 ASEE Annual Conference & Exposition

Authors

Emma Sophie Stine, University of Colorado Boulder; Amy Javernick-Will, University of Colorado Boulder

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those of the authors and do not necessarily reflect the National Science