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degree plan choices: A qualitative study with engineering and communication students," submitted to the International Communication Association's Annual Conference, 2025.6. E. L. Deci and R. M. Ryan, "Self-determination theory," in Handbook of Theories of Social Psychology, vol. 1, pp. 416-436, 2012.7. M. S. Eickholt, "The effect of superiors' mentoring on subordinates' organizational identification and workplace outcomes," Master’s Thesis, West Virginia University, 2018.8. K. Kricorian, M. Seu, D. Lopez, and others, "Factors influencing participation of underrepresented students in STEM fields: Matched mentors and mindsets," International Journal of STEM Education, vol. 7, no. 16, 2020.9. S. L. Kuchynka, A. E
Health, Volume 28, 2023, 100395, ISSN 2352-6483, doi: 10.1016/j.smhl.2023.100395 for successful implementation of AI in educational systems. P = (K × U)/2 (1) C = 5 - (D + R + S + L)/4 (2) educational initiatives aimed at increasing AI literacy could be effective in [6] Z. Xiong, C. Wang, Y. Li, Y. Luo and Y. Cao, "Swin-Pose: Swin Transformer Based Human Pose Estimation," 2022 IEEE where Where improving student perceptions. 5th
in a fluid flowbalance equation and the Colebrook friction equationsimultaneously, using an iterative method prone to numerical CD: Dimensionless drag coefficient of an object of well-errors. A better way is a graphical method where the equations defined geometryare plotted on a Moody’s chart and the solution derived by A: Planform or frontal area of an immersed body subject tolocating the intersection(s) of relevant curves. This paper fluid flowintroduces a new Matlab app for such purpose and demonstratesits capability to find (i) flow velocity and (ii) pipe diameter, given There are pragmatic engineering problems that requiresall other relevant parameters. The
Paper ID #49764GIFT: Formative Lecture Quizzes to Help Students Improve Their UnderstandingDr. Kathleen A Harper, Case Western Reserve University Kathleen A. Harper is the assistant director of the Roger E. Susi First-year Engineering Experience at Case Western Reserve University (CWRU). She received her M. S. in physics and B. S. in electrical engineering and applied physics from CWRU and her Ph. D. in physics, specializing in physics education research, from The Ohio State University.Dr. Kurt Rhoads, Case Western Reserve University Kurt Rhoads, Ph.D., P.E. is the faculty director of the Roger E. Susi First-Year Engineering
learning, alternative grading, and design thinking, he also co-founded the STEPS program (funded through NSF S-STEM) to support low-income, high-achieving engineering students. Budischak holds a Doctorate in Electrical Engineering and enjoys outdoor activities with his family. FYEE 2025 Conference: University of Maryland - College Park, Maryland Jul 27Work In Progress: Enhancing Student Collaboration Through Growth-Based Assessment PracticesIntroductionBackgroundIn a broad literature review, Geisinger and Raman summarized many factors related to studentattrition from engineering majors [1]. The authors noted that competitive grading environmentscommonly found in STEM disciplines have been linked with
. AcknowledgmentsSpecial thanks to the Undergraduate Engineering Office and the First-Year Advising team, whosupported this research.VII. References[1] R. J. Waddington, S. Nam, S. Lonn, and S. D. Teasley, “Improving Early Warning Systems with Categorized Course Resource Usage,” Learning Analytics, vol. 3, no. 3, pp. 263–290, Dec. 2016, doi: 10.18608/jla.2016.33.13.[2] R. S. Newman, “How Self-Regulated Learners Cope with Academic Difficulty: The Role of Adaptive Help Seeking,” Theory Into Practice, vol. 41, no. 2, pp. 132–138, 2002.[3] K. Shaaban and R. Reda, “Effectiveness of intrusive advising of engineering first-year students using tailored freshman seminars,” EURASIA J Math Sci Tech Ed, vol. 18, no. 5, p. em2106, Apr. 2022, doi
. 10.18260/1-2--21641[2] Zarske, M. S., & Gallipo, M. J., & Yowell, J. L., & Reamon, D. T. (2014, June), STEM High School: Do Multiple Years of High School Engineering Impact Student Choices and Teacher Instruction? Paper presented at 2014 ASEE Annual Conference & Exposition, Indianapolis, Indiana. 10.18260/1-2--23035[3] Weis, S., & Yakubovsky, M., & René Coté, B. B., & Kelly, J. (2021, December), Integrating Engineering Ideas into High School and Middle School Curricula Paper presented at 2009 GSW, unknown. 10.18260/1-2-370-38622[4]Wang, M., & Degol, J. (2020). Gender and STEM: Understanding the persistence gap through expectancy-value theory. Journal of Educational
, theiracademic records exhibit significant differences that warrant careful consideration. First, directlymatriculated students typically completed ECE 301’s core pre-requisites (such as Physic II andCircuit Analysis) at the focal institution. This provides a detailed record of their proficiency, re-flected through a range of letter grades. In contrast, transfer students often bring in credits for pre-requisites (shown in Figure 3), which are recorded as a “T” (transfer) on their academic records.This limits insights into their knowledge acquisition and retention. Second, the academic record’sability to capture students’ academic histories differs between groups. Transfer credits are recordedin the semester they are recognized by the focal institution
: Springer International Publishing, 2018, pp. 217–239. doi: 10.1007/978-3-319-66659-4_10.[11] S. Baker, P. Tancred, and S. Whitesides, “Gender and Graduate School: Engineering Students Confront Life after the B. Eng.,” J. Eng. Educ., vol. 91, no. 1, pp. 41–47, 2013, doi: 10.1002/j.2168-9830.2002.tb00671.x.[12] K. J. Jensen and K. J. Cross, “Engineering stress culture: Relationships among mental health, engineering identity, and sense of inclusion,” J. Eng. Educ., vol. 110, no. 2, pp. 371–392, 2021, doi: 10.1002/jee.20391.[13] “How To Meet the Increasing Demand for Engineers | National Society of Professional Engineers.” Accessed: Apr. 29, 2025. [Online]. Available: https://www.nspe.org/career- growth/pe-magazine/spring-2021
and spatial visualization skills.Dr. Jennifer Mullin, UC San Diego Jennifer S. Mullin is an Associate Professor of Teaching in the Department Mechanical and Aerospace Engineering, and Faculty Director of Experience Engineering (E4) in Jacob’s School of Engineering. Her work is focused on engineering education research and curriculum development with an emphasis on creativity, design thinking and project-based pedagogy. She utilizes informed instructional choices through a ”learn-by-doing” approach to enhance and enrich the undergraduate educational experience, specifically at the intersection of engineering design, technical communication and problem-solving. ©American Society for
technology adoption or avoidance, andthe targeted framework interact and present.AcknowledgementsThis material is based upon work supported by the National Science Foundation under AwardNumber 2346881. Any opinions, findings and conclusions or recommendations expressed in thismaterial are those of the author(s) and do not necessarily reflect those of the NSF.References[1] D. Baidoo-Anu and L. O. Ansah, "Education in the Era of Generative Artificial Intelligence (AI): Understanding the Potential Benefits of ChatGPT in Promoting Teaching and Learning," SSRN, 2023.[2] M. Flavin, "Disruptive technologies in higher education," Research in Learning Technology, vol. 20, 2012.[3] J. Qadir, "Engineering Education in the Era of ChatGPT: Promise and
), pp. 45, 2022.[2] S. Malik, K. Muhammad and Y. Waheed, "Artificial intelligence and industrial applications-A revolution in modern industries," Ain Shams Engineering Journal, pp. 102886, 2024. .[3] A. B. Rashid and A. K. Kausik, "AI revolutionizing industries worldwide: A comprehensive overview of its diverse applications," Hybrid Advances, pp. 100277, 2024.[4] S. Azhar, "Building information modeling (BIM): Trends, benefits, risks, and challenges for the AEC industry," Leadership and Management in Engineering, vol. 11, (3), pp. 241–252, 2011.[5] T. O. Olawumi and D. W. Chan, "Development of a benchmarking model for BIM implementation in developing countries," Benchmarking: An
received the Ph.D. degree in electrical engineering from the University of Western Ontario, London, ON, Canada in 2006. She received the B.Sc. and M.Sc. degrees in electrical engineering from Shandong University, Jinan, China, in 1993 and 1996 re ©American Society for Engineering Education, 2025Community Partner and Institutional Stakeholder Perspectives on the Impact of the NSF-STEM Scholars of Excellence in Engineering and Computing Studies ProgramAbstractThe Scholars of Excellence in Engineering and Computing Studies (SEECS) program, funded byan NSF S-STEM grant, delivers engineering solutions that tackle community challenges whileproviding students with opportunities for
insightsgained from this analysis will be used to inform the development of future data collectionprotocols aimed at conducting interviews with university students, faculty, and administrators inthe subsequent phases of the project.AcknowledgementsThis material is based upon work supported by the National Science Foundation through AwardNo. 2340778. 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.References[1] AIR, “Broadening participation in STEM (science, technology, engineering, and mathematics),” American Institutes for Research. Accessed: Jul. 21, 2022. [Online]. Available: https://www.air.org/project
itsmanufacturer, is not guaranteed or endorsed by the author(s).Acknowledgement and Material AvailabilityWe would like to thank Julia Chamberlain, Kathleen Cruz, Sara Dye, Rob Furrow, Irene Joe,Bwalya Lungu, Hannah Minter Anderson, Ali Moghimi, and Patricia Turner from the PCIDiversity, Equity, and Inclusion Faculty Learning Community at UC Davis. We will make ourcurrent learning module available at https://cube3.engineering.ucdavis.edu.References[1] U.S. Food and Drug Administration. Artificial Intelligence and Machine Learning (AI/ML)-Enabled Medical Devices [Online] Available: https://www.fda.gov/medical- devices/software-medical-device-samd/artificial-intelligence-and-machine-learning-aiml- enabled-medical-devices[2] V. Binson
the science experiences of successful women of color: Science identity as an analytic lens. Journal of Research in Science Teaching, 44(8), 1187–1218.Forest, C. R., Moore, R. A., Jariwala, A. S., Fasse, B. B., Linsey, J. S., Newstetter, W. C., & Quintero, C. (2014). The Invention Studio: A university maker space and culture. Advances in Engineering Education, 4(2), 1–32.Godwin, A. (2016). The development of a measure of engineering identity. In 2016 ASEE Annual Conference & Exposition Proceedings. New Orleans, LA: ASEE.Hazari, Z., Sonnert, G., Sadler, P. M., & Shanahan, M.-C. (2010). Connecting high school physics experiences, outcome expectations, physics identity, and physics career
Prospects. National Academies Press, 2009.[2] P. S. Lottero-Perdue, “Elementary teacher as teacher of engineering: Identities in concert andconflict,” in ASEE Annual Conference & Exposition 2013, Atlanta, GA, USA, June 23-26, 2013.https://peer.asee.org/19487[3] S. M. Nesmith and S. Cooper, “Connecting engineering design and inquiry cycles: Impact onelementary preservice teachers’ engineering efficacy and perspectives toward teachingengineering,” School Science and Mathematics Association, vol. 121, pp. 251-262, 2021.[4] D. J. Sherfnoff, S. Sinha, D. M. Bressler, and L. Ginsburg, “Assessing teacher education andprofessional development needs for the implementation of integrated approaches to STEMeducation,” International Journal of STEM
agreeReferencesBorrego, M., Knight, D. B., Gibbs Jr, K., & Crede, E. (2018). Pursuing graduate study: Factorsunderlying undergraduate engineering students' decisions. Journal of Engineering Education,107(1), 140-163.Gilmartin, S. K., Thompson, M. E., Morton, E., Jin, Q., Chen, H. L., Colby, A., & Sheppard, S.D. (2019). Entrepreneurial intent of engineering and business undergraduate students. Journal ofEngineering Education, 108(3), 316-336.Lattuca, L., Terenzini, P., Knight, D., & Ro, H. K. (2014). 2020 Vision: Progress in preparingthe engineer of the future.Lee, W. C., Hall, J. L., Godwin, A., Knight, D. B., & Verdín, D. (2022). Operationalizing andmonitoring student support in undergraduate engineering education. Journal of
collaborative inquiry and dialogue. As we individually and collectivelyinterrogate our assumptions and beliefs and expand our knowledge about other ways of knowingand being, we have begun to see a quality of care emerge in our discussions – care about how wemight support each other and ourselves.AcknowledgementThis material is based upon work supported by the National Science Foundation under Grant No.2234256 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 ScienceFoundation.References[1] J. Butler, Giving an Account of Oneself. New York: Fordham University, 2005.[2] A. Comeaux, Change (the) Management: Why We as Leaders Must Change
degree program at a large, public, research-intensive(R1) university in the southern U.S.Data Collection Co-creators were recruited through emails sent by each university’s disability resourceoffice and engineering department(s) to undergraduate students. These emails outlined eligibilitycriteria, which required co-creators to be currently enrolled undergraduate engineering studentsat that university who identify as disabled or as a person with disabilities. The emails invitedeligible individuals to participate in the study by reflecting on their disability-related experiencesat their university. Additionally, the emails detailed the participation process and offered a $40gift card as compensation upon completing the interview. To ensure
sharing among educators, it aimsto make PBL a more accessible and appealing pedagogical approach for engineering education.AcknowledgmentThis material is based upon work supported by the National Science Foundation under Grant No.2117224. 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 ScienceFoundation.References[1] D. Jonassen, “Supporting Problem Solving in PBL,” Interdisciplinary Journal of Problem- Based Learning, vol. 5, no. 2, Sep. 2011, doi: 10.7771/1541-5015.1256.[2] W. Hung, D. H. Jonassen, and R. Liu, “Problem-Based Learning,” 2008, pp. 485–506.[3] D. Boud and G. Feletti, The Challenge of Problem-Based Learning
frontier, this study offers a glimpse of how Copilot can support course updates usingsimple prompts. Alternative AI tools with different capabilities may be more effective in creatingspecific technical content.References [1] Batista J, Mesquita A, Carnaz G. Generative AI and Higher Education: Trends, Challenges, and Future Directions from a Systematic Literature Review. Information. 2024; 15(11):676. https://doi.org/10.3390/info15110676 [2] Noroozi, O., Soleimani, S., Farrokhnia, M., & Banihashem, S.K. (2024). Generative AI in education: Pedagogical, theoretical, and methodological perspectives. International Journal of Technology in Education (IJTE), 7(3), 373-385. https://doi.org/10.46328/ijte.845 [3] Choi, G.W
scientific and business authority in theengineering profession [1] in a metaphorical free body diagram, using Faulkner’s notion of “nutsand bolts” engineering identity [86] and Cruz et al.’s critical analysis of engineering ethicseducation [87]. Please see figure one for an illustration of this framework.Figure 1: Free body diagram of engineering professionalismBefore diving into the theoretical roots of this figure, I offer a brief explanation of my underlyingassumptions. Foundational to this image is the sociological tension between human agency andsocial structure. I view engineers as neither free agents nor objects living their lives according toa structurally determined script. Rather, I view them as individuals with some level of decision
explanation[s] of complex topics,” helping them understand information by summa-rizing key topics, explaining information in different ways, demonstrating “step by step walk-throughs for challenging problems,” or otherwise providing additional context and definitions ofterms. One respondent stated that they sometimes use AI to “understand a difficult phrase by past-ing it into the chatbot and asking it to explain it more clearly.” Respondents also noted the benefitof AI chatbots as a “24/7 teacher” and “free tutor” for students, allowing them “quick tutoringopportunities” to ask questions if there was not enough time in class or office hours, or if “a humanteacher is not available.” AI also has the capacity for “virtually unlimited follow up
framework for assessing and improving the project. Future work includes refiningdata collection methods, addressing limitations such as varying problems across cohorts, andfurther assessing research quality. Future efforts will focus on identifying student learningoutcomes, refining the project, and exploring new ways to introduce PROCESS andmetacognitive problem-solving to a growing cohort of engineering students.References[1] S. D. Sheppard, K. Macatangay, A. Colby, and W. M. Sullivan, Educating Engineers: Designing for the Future of the Field, vol. 9. San Francisco, CA: Jossey-Bass, 2009. [Online]. Available: https://files.eric.ed.gov/fulltext/ED504076.pdf[2] J. G. Donald, Learning To Think: Disciplinary Perspectives. The Jossey-Bass
that is brief, well-structured, and that takestheir psychosocial needs into account.Acknowledgements: This work was supported through funding by the National ScienceFoundation IUSE Grant No. 2111114/2111513. Any opinions, findings, and conclusions orrecommendations expressed in this material are those of the author(s) and do not necessarilyreflect the views of the National Science Foundation.Note: The first and last author share first authorship equally.References[1] Nat. Center for Science and Engineering Statistics (NCSES), “Diversity and STEM: Women, minorities, and persons with disabilities 2023,” Nat. Science Foundation, Special Report NSF 23-315, 2023. [Online]. Available: https://ncses.nsf.gov/wmpd[2] Nat.Center for Education
Technology Education, ASEE, 2024, https://mindset.ASEE.org. [Accessed: Jan. 14,2025].[6] S. Das, D. Kleinke, and D. Pistrui, “Reimagining engineering education: does Industry 4.0need Education 4.0?,” ASEE Annual Conference, Jun. 2020, Montreal, CA.[7] D. Pistrui, D. Kleinke, and S. Das, “The industry 4.0 talent pipeline: a generational overviewof the professional competencies, motivational factors & behavioral styles of the workforce,”ASEE Annual Conference, Jun. 2020, Montreal, CA.[8] D. Pistrui, J. Layer, and S. Dietrich, “Mapping the behaviors, motives and professionalcompetencies of entrepreneurially minded engineers in theory and practice: an empiricalinvestigation,” The Journal of Engineering Entrepreneurship, ASEE Special Issue, vol. 4
Vin G B S Vin B S B S B G S Fig. 4: The common source amplifier (left) and the resulting bugs from disconnecting thebody (center) and connecting a PMOS gate, drain, and source with the NMOS body (right) Page 1 Page 2
over adopting AI tool use in their curriculum. Per the framework,components contributing to a sense of agency include past experiences, expectations of thefuture, and present cultural, structural, and material conditions that can be opportunities, barriers,and resources [1].At the onset of the project, our team theorized several factors which might impact teacher’s AIuse based on Biesta et al.’s framework, including social supports or hindrances from otherteachers or administrators, school and community resources and access to use AI tools,perceptions of added value of AI tools on teaching outcomes, opinions and ethical concernsabout AI tools, and familiarity with AI tools from prior personal or professional use.Ecological Systems TheoryBiesta