the previous semesters.References [1] Olivia S Anderson and Cynthia Finelli. A faculty learning community to improve teaching practices in large engineering courses: Lasting impacts. In 2014 ASEE Annual Conference & Exposition, pages 24–46, 2014. [2] Russell Benford and Julie Gess-Newsome. Factors affecting student academic success in gateway courses at northern arizona university. Online Submission, 2006. [3] Rebecca Butler and Orly Buchbinder. Learning assistant-student interaction in calculus: A critical discourse analysis. North American Chapter Int. Group Psychol. Math. Educ., 2023. [4] Fadhilah Fadhilah, Z Mawardi Effendi, and Ridwan Ridwan. Analysis of contextual teaching and learning (ctl) in the course of applied
,and effective assessment strategies in maximizing the educational value of reflection inengineering courses.AcknowledgementsThis work was made possible by grants from the National Science Foundation (NSF REU 2244323, NSFIUSE 2235227). Any opinions, findings, and conclusions or recommendations expressed in this materialare those of the authors and do not necessarily reflect the views of the National Science Foundation.References[1] ABET. “Criteria for accrediting engineering programs, 2024-2025.” Date Accessed. January 5, 2025. [Online]. Available: https://www.abet.org/accreditation/accreditation- criteria/accreditation-policy-and-procedure-manual-appm-2024-2025/[2] M. S. Knowles, The Modern Practice of Adult Education
learning outcome stating, “It just depends a lot on whatyou're doing and what you're using it for, and like what the role, what theassignment is actually like asking you to accomplish…what skills they want tohelp grow”. All of the participants echoed P1’s belief that GenAI use in anacademic setting was situational.Thanks to the interventions in place in this study, the students could persevere andreach new understanding. Consistent with Anderson’s findings [5], studentresearcher persistence provided opportunities for understanding. The interviewsrevealed that the “turning point” was not limited to the assignment's learningobjectives but also created an understanding of GenAI. Despite five of the sixparticipants feeling skeptical initially about
positive[THE SHIFT TOWARDS INCLUSION AND ACCESSIBILITY] 15social change. This study serves as a model for educators seeking to incorporate accessibility andinclusive design into their curricula, offering insights into structuring courses that combinetheory, practice, and real-world engagement. The outcomes of this course demonstrate theprofound impact of inclusive design education in shaping the next generation of designers andtechnologists, ensuring that accessibility remains at the forefront of innovation and development.[THE SHIFT TOWARDS INCLUSION AND ACCESSIBILITY] 16 ReferencesBarteaux, S. (2014
Students in Introductory College Chemistry Courses. Chem. Educ. 2014, 91, 1538−1545.7. Swarat, S., Light, G., Jung Park, E., and Drane, D. A Typology of Undergraduate Students’ Conceptions of Size and Scale: Identifying and Characterizing Conceptual Variation. J. Res. Sci. Teaching. 2011, 48:5, 512–533.8. National Research Council. A Framework for K−12 Science Education: Practices, Crosscutting Concepts, and Core Ideas; The National Academies Press: Washington, DC, 2012.9. Bybee, R. W.; Buchwald, C. E.; Crissman, S.; Heil, D. R.; Kuerbis, P. J.; Matsumoto, C.; McInerey, J. D. Science and technology education for the elementary years: Framework for curriculum and instruction; The National Center for Improving
core state standards for mathematics. TechnicalReport. Center for Mental Health in Schools at UCLA.[15] Hoepfl, M. (2016). Teaching and learning in project-based learning, technology andengineering education, and related subjects. Exemplary teaching practice in technology andengineering education, 1-32.[16] Hsu, M., Purzer, S., & Cardella, M. E. (2011). Elementary Teachers’ Views about TeachingDesign, Engineering, and Technology. Journal of Pre-College Engineering Education Research(J-PEER), 1(2), Article 5. https://doi.org/10.5703/1288284314639[17] International Technology and Engineering Educators Association (ITEEA). (2020).Standards for technological and engineering literacy: the role of technology and engineering inSTEM education.[18
points, with Group 1's average being5.81 and Group 2's being 4.91. This indicates that, on average, Group 1 achieved higher gradesthan Group 2.Applying ANOVA to compare performance (final grade) between Group 1 and Group 2 yieldsan F-statistic value of 116.8963 and a p-value of approximately 7.411684e-13. The p-value isextremely low (much lower than any standard significance threshold, such as 0.05), indicating astatistically significant difference between the two groups' final grades. This suggests thatacademic performance (measured by final grade) significantly differs between Group 1 andGroup 2.Analysis of Students' Work ExperienceBoth groups belong to the evening session, mainly consisting of students working during the day.Additionally
ve egat e gat egat ositi P o ely N h at N nor N h at P ely m w ve ew e m tre me siti om xtr Ex So P o S E t h er
properties (𝑃𝑃, 𝐿𝐿, 𝐸𝐸, 𝑎𝑎𝑎𝑎𝑎𝑎 𝐼𝐼) and deflection behavior (𝛿𝛿). • Develop skills in setting up and conduct beam deflection experiments and read deflections from the dial gauges.Challenges: • Making sure that students calculate the moment of inertia correctly. In our case all the beams are of rectangular or square cross section. • Proper alignment of support between span length and incremental load application to minimize experimental error. • Accurate measurement of small and large deflections, especially for stiffer and flexible materials like steel and wood(s) respectively. • Addressing variability in material properties, particularly for natural materials like wood (various
other variables thatcan be freely controlled. These variabilities provide a wide range of investigation and datacollection. Important parameters that can be studied are summarized below: 1. The yaw angle represents the relative angle between the turbine axis and the flow direction. The yaw angle ranges from -50 to +50 degrees with fine increment. 2. The pitch angle represents the relative angle between the turbine blades and the flow direction. The pitch angle ranges from -5 to 40 degrees with fine increment. 3. Fan speed represents the average speed of air flow into the tunnel. The fan produces air flow from zero to about 15 m/s or 33.5 mph. This is more than sufficient to mimic realistic wind speed, particularly
environmental benefits,eliminating the use of leaded Avgas faces numerous challenges and introduces greateruncertainty to the fueling process, especially during the transition phase. The FAA has approvedtwo unleaded Avgas: Swift’s fuel UL94 and General Aviation Modifications, Inc.’s fuelG100UL [12]. Swift’s fuel has been commercially available for nine years and meets the ASTMInternational Standard, ASTM D7547, Specification for Hydrocarbon Unleaded AviationGasoline [12]. While G100UL holds an FAA Supplemental Type Certificate, it does not have anindustry consensus standard specification yet, such as ASTM D910 or ASTM D7547 [12]. Asmost FBOs do not have the tanking capability to have two or more grades of Avgas, if an FBOswitched to Swift’s UL94 fuel
. Wiley Online Library.[5] J. Collofello, et al. (2021), “Dissemination and adaptation of the EPICS (EngineeringProjects in Community Service) model,” Advances in Engineering Education, 9, 3.[6] S. Bechara. “Engineering with purpose: The impact of community service-based seniordesign projects,” ISEE Pulse, December 16, 2024. [Online]. Available:https://www.embs.org/pulse/articles/engineering-with-purpose-the-impact-of-community-service-based-senior-design-projects/[7] D. Staudacher. “ECE students use senior design projects to help community organizations,”Electrical and Computer Engineer, University of Illinois – Chicago, January 25, 2018. [Online].Available: https://ece.uic.edu/news-stories/ece-students-use-senior-design-projects-to-help
, improving retention predictions' accuracy and reliability.References1. Sean Kim, Eliot Yoo, Samuel Kim. Why Do Students Drop Out? University Dropout Prediction and Associated Factor Analysis Using Machine Learning Techniques. 2023. https://arxiv.org/abs/2310.109872. W. M. Attiya and M. B. Shams, "Predicting Student Retention in Higher Education Using Data Mining Techniques: A Literature Review," 2023 International Conference On Cyber Management And Engineering (CyMaEn), Bangkok, Thailand, 2023, pp. 171-177.3. N. S. Sani, A. F. M. Nafuri, Z. A. Othman, M. Z. A. Nazri, and K. Nadiyah Mohamad, “Drop-Out Prediction in Higher Education Among B40 Students,” International Journal of Advanced Computer Science and Applications, vol. 11, no. 11
1965/66.[3] L. Musser. “Atomic Energy Commission Depository Collection: Shining a Light on a HiddenResource,” Presented at the Special Libraries Association Annual Meeting, Baltimore, MD,2018. Poster. DOI:10.18113/S14D18. [Online]. Available:https://scholarsphere.psu.edu/resources/d740783e-76f2-48b1-bee6-08c3cd21916d[4] J. Kirk, S. Wood, and L. Sare, “Filling in the Gaps, Doing What We Have Always Done inTRAIL,” Documents to the People, vol. 51, no. 4, 2023, [Online]. Available:https://journals.ala.org/index.php/dttp/article/view/8151/11353[5] “National Technical Reports Library”. [Online]. Available: https://ntrl.ntis.gov/NTRL/[6] “OSTI.GOV”. [Online]. Available: https://www.osti.gov/[7] “International Nuclear Information System (INIS
more advancedcourses. The survey will ask students to reflect on their interest in the topics, motivation in theircourses, and any impact the course had on their future plans.References[1] J. Wheadon and N. Duval-Couetil, “Elements of Entrepreneurially Minded Learning: KEENWhite Paper,” Journal of Engineering Entrepreneurship, vol. 7, no. 3, pp. 17-25, 2016.[2] J.S. London, J.M. Bekki, S.R. Brunhaver, A.R. Carberry, and A.F. McKenna, “A Frameworkfor Entrepreneurial Mindsets and Behaviors in Undergraduate Engineering Students:Operationalizing the Kern Family Foundation’s ‘3Cs’,” Advances in Engineering Education, Fall2018.[3] L. Bosman and S. Fernhaber, “Applying Authentic Learning through Cultivation of theEntrepreneurial Mindset in the
what else to do,” “we were all working at the sametime, not just one person moving.” These statements indicate the MR module was able to facilitatean interactive, collaborative, problem-based approach to learning for the course.Responses to the additional comments query were statements that the module was “fun” and“amazing” as well as requests for use of MR for other lab experiments with one exception. Thatexception was a party who returned to the theme of discomfort and noted s/he “wouldn'trecommend [MR] for people with motion sensitivity.”5.3 ECE Course DataDescription of the outcomes for each of the three forms of data gathering for the CHEG coursefollow.5.3.1 ECE Self-AssessmentLike for the CHEG course, the ECE self-assessment queries
enhances engagement but also nurtures the formation of a robust engineeringidentity, ultimately contributing to more confident and competent future engineers.Acknowledgements :This work was supported through funding by the National Science Foundation (Awards No.2138019, No. 2138106 and No. 2514040). 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.
Teamwork (e.g. leading, planning, contributing) (SO5) 8.5 + 1.7 Planning & conducting testing & analysis (SO6) 8.0 + 1.5 Learning & applying new information independently (SO7) 8.6 + 1.4 Average grades for overall course performance, final project reports, and peer evaluationsfor students in Capstone 1 and Capstone 2 are shown in Table III.2 for graduating classes from2020-2024. Each class enrolled 30-40 students. In the “Sem.” column, a prefix F indicates a fallsemester, while S indicates a spring semester. There is a marked increase in course and reportgrades from Capstone 1 to Capstone 2 for nearly every class, while peer evaluation averages arein the
in courses and curricula ontheir own campuses. The paper originally was submitted in January 2025. In revising, we haveadded an Appendix that discusses conditions in April 2025, which represent an abrupt change innational conditions related to DEIJ topics as compared to Fall 2024 when the teaching activitieswere conducted.IntroductionEngineering programs continue to adapt to changing stakeholder demands for better integrationof diversity, equity, inclusion, and justice (DEIJ) into both classrooms and curricula. Forexample, ABET’s approved new Criterion 5 will require programs to offer curricula “thatensure[s] awareness of diversity, equity, and inclusion for professional practice consistent withthe institution’s mission” [1] (note that this
2-year and 4-year degree programs to address this skilled employeeshortage.Bibliography 1. Li, L. “Reskilling and Upskilling the Future-ready Workforce for Industry 4.0 and Beyond”. Inf Syst Front (2022). https://doi.org/10.1007/s10796-022-10308-y 2. Acerbi F, Rossi M and Terzi S (2022). Identifying and assessing the required I4.0 skills for manufacturing companies' workforce. Frontiers in Manufacturing Technology, (2):921445. Doi: 10.3389/fmtec.2022.921445 3. 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) 4. National Science Foundation Advanced Technological
, June 2022. [Online]. Available: https://my.clevelandclinic.org/health/symptoms/23154-neurodivergent. [Accessed Jan. 4, 2025][2] N. Chown, “Neurodiversity,” in Encyclopedia of Autism Spectrum Disorders, pp. 3134–3135, Jan. 2021. [Online]. Available: https://doi.org/10.1007/978-3-319-91280-6_102298. [Accessed Jan. 4, 2025][3] S. Lindsay, M. Proulx, H. Scott, and N. Thomson, “Exploring teachers’ strategies for including children with autism spectrum disorder in mainstream classrooms,” International Journal of Inclusive Education, vol. 18, no.2, Jan. 2013.[4] P. Dwyer, E. Mineo, K. Mifsud, C. Lindholm, A. Gurba, and T. C. Waisman, “Building Neurodiversity-Inclusive Postsecondary Campuses
Academic Advisor (required), choose at least one Adventure from eachStudent Learning Outcome category. Peer Educators and Mentors may assign specific Adventuresfor their section(s), for example, a Fain Fine Arts section might require attendance at a performance.Students should complete the following assignments: Goal Setting Activity – Week 2, Study GuideActivity – Week 4, Wellness Inventory – Week 5, and Self-Assessment – Week 13. Summary and ConclusionsSuggestions from PEs (Peer Educators) include putting due dates on the syllabus, tracking adventurecompletion, including guest speakers, and something due each week to improve attendance. Theyalso suggested continuing the guidebook. The mentors asked for
/2024/resources/nace-career-readiness-competencies-revised-apr- 2024.pdf [7] Jang, S. (2021), “Redesign of a Large Statics Course for Neurodiverse Students in the Distance Learning Environment.” 2021 ASEE Virtual Annual Conference, https://peer.asee.org/37644Fig. 3. Reflection of result Q3. [8] Passow, H. J. (2012). "Which ABET Competencies Do Engineering Graduates Find
, “Design meetings and designneural network architectures, including transformers and notebooks as tools for reflection in the engineering design course”, IEEEgenerative models like GANs and VAEs, will further advance 36th Annual Conference, Frontiers in Education, pp. 165-184, Santhe capabilities of AI in education. As reported by HolonIQ, Diego, CA, USA, 27-31 October 2006.the global ed-tech market is projected to reach $404 billion by [3] Robin S. Adams, Jennifer Turns, and Cynthia J. Atman, “Educating effective engineering designers: the role of reflective practice,” Design2025, highlighting the growing impact of AI in this
REFERENCES possibility of cheating the game Neither we nor our testers have [1] Creative Classroom Challenges: Educational Puzzles for All. (2023, yet been able to find a way of cheating the game, short of using October 10). Brainy Casuals Puzzle. https://brainycasuals.com/educational-games/educational- excessive force. However, we recommend that only one switch puzzles/creative-classroom-challenges-educational-puzzles-for-all/ be flipped at a time to guarantee the stability of the internal [2] Olwan, S., & Connolly, M. (2024, July 26). Games and Activities to Suit digital logic
electronics.combination of 4 sequential bits set by player-2. After player-1makes their guess of the 4-bits, they receive instantaneous Students who investigate this game may also experimentfeedback from a row of LEDs telling them how many bits were with different configurations of logic gates and observe howchosen incorrectly, but not which ones were incorrect. Using this these changes affect the device's behavior. This process wouldinformation, player-1 makes a second guess for the 4 bits and help reinforce theoretical knowledge through practicalreceives second feedback from the LEDs. Player-1 gets a total of application. Due to the strategic nature of the game, studentsfour trial guesses to find player-2’s original 4
. language understanding,” NAACL-HLT, 2019. • However, both methods failed to generate relevant [13] S. Reimers and I. Gurevych, “Sentence-BERT: Sentence embeddings using Siamese BERT-networks,” EMNLP, 2019. responses for Queries 4 and 5, suggesting that [14] Q. Zhu et al., “Efficient context retrieval in dialogue systems using neural certain queries may require alternative embedding similarity,” ACL, 2021. optimization strategies or more comprehensive [15] H. Jeon et al., “Memory-efficient transformer architectures for long- training data. context NLP,” ICLR
, [10] https://hub.qmplus.qmul.ac.uk/group/chromium/cobalt-chromium-alloy Thierry Judet, Michel Bonnin, Jean-Alain, Colombier and Sheldon S. [11] Yi Lu, Wenshuang Li, Jianfeng Zhou, Yi Ren, Xuefen Wang, Jun Li, Lin, Foot Ankle Int 2008 29: 1117. Shu Zhu,Strengthening and toughening behaviours and mechanisms of[2] Total ankle replacement Design evolution and results Alexander VAN carbon fiber reinforced polyetheretherketone composites (CF/PEEK), DEN HEUVEL, Saskia VAN BOUWEL, Greta DEREYMAEKER. Composites Communications,Volume 37,2023,101397, ISSN 2452
model, the impact of the expert's decisions on it has to be made. The company refinements required to increase Fig. 8. X-ray of a pneumonia-affected lung and a healthy lung (Sample robustness in diverse clinical environments are promising. images) for model 2. Model 2 exhibits Greater accuracy, manages incomplete data,resilient. In model 2 ResNet18's advanced feature extraction on complete patient data and thus provides a more robust andsurpasses that of a basic CNN. Moreover, Bayesian reasoning interpretable AI-based healthcare solution. Real-case scenariosprovides clinically interpretable predictions