Schupbach, University of Colorado Denver William is working towards a PhD in Mechanical Engineering at the University of Colorado Denver and is a research assistant and a part time instructor.Prof. Tom Altman Dr. Altman received his Ph.D. in Computer Science from the University of Pittsburgh. He specializes in optimization algorithms, formal language theory, and complex systems. He has published a book and over 90 journal/refereed papers. He received numerous research and teaching awards. Tom has been a PI/co-PI on over 20 external grants, including the NSF(4) and DARPA(2). An ABET CAC Program Evaluator, Dr. Altman has expanded his research interests into STEM and, in particular, Engineering Education.Dr. Michael S
every spring semester since.One research-cited reason that collegiate students leave engineering is a lack of engineering-related experiences during the first year of the program. Conventional first-year engineeringcurricula require students to complete multiple gateway courses prior to beginning disciplinarycoursework. These courses oftentimes deal with abstract material with little perceivedengineering context. As a result, students end up believing that all engineering courses will besimilar, and some ultimately leave for other professional arenas where applications can beunderstood much earlier in academic career(s). A key motivating factor in developing ENGR 111was to augment student desire to persist in engineering degree pursuit, by
: A survey. Heliyon, 4(11).6. Kaveh, A. (2024). Applications of artificial neural networks and machine learning in civil engineering. Studies in computational intelligence, 1168, 472.7. Wu, B., Xu, J., Zhang, Y., Liu, B., Gong, Y., & Huang, J. (2024). Integration of computer networks and artificial neural networks for an AI-based network operator. arXiv preprint arXiv:2407.01541.8. Fanni, S. C., Febi, M., Aghakhanyan, G., & Neri, E. (2023). Natural language processing. In Introduction to Artificial Intelligence (pp. 87-99). Cham: Springer International Publishing.9. Khan, A. A., Laghari, A. A., & Awan, S. A. (2021). Machine learning in computer vision: a review. EAI Endorsed Transactions on Scalable Information
furtherrefinement to the plan, and to overcome some limitations such as controlling for differencesbetween coaches. The hope is that the implementation of this plan will make an impact both interms of outcomes and in the future trajectory of individual participants, especially for first-yearstudents who struggle in their first semester.References[1] T.G. Carter, R.H. Jarman, S. Fenwick, T.O. Schrader, C.M. DiCarlo. “Improving StudentSuccess in STEM with a Student Success Coach and Intrusive Advising.” Proceedings of 2020ASEE Annual Conference and Exposition, 2020.[2] J. Ingham, W.R. McShane “Academic Skills Seminar: A Two-Year Analysis of an IntrusiveIntervention for Freshmen on Probation.” Proceedings of 1998 ASEE Annual Conference andExposition, 1998.[3
comparisons to validate these findings across different contexts. Investigation ofspecific intervention strategies could help identify the most effective approaches for developingboth team skills and intercultural competence. Development of standardized assessment toolsand examination of industry outcomes would also provide valuable insights for improving STEMeducation practices.References[1] S. Majid, Z. Liming, S. Tong, and S. Raihana, “Importance of Soft Skills for Education and Career Success,” Int. J. Cross-Discip. Subj. Educ., vol. 2, no. Special 2, pp. 1036–1042, Dec. 2012, doi: 10.20533/ijcdse.2042.6364.2012.0147.[2] P. Bahrami, Y. Kim, A. Jaiswal, D. Patel, S. Aggrawal, and A. J. Magana, “Information Technology Undergraduate
building andcommunication, as well as better project management.References[1] ABET, *Criteria for Accrediting Engineering Programs*, 2020. [Online]. Available:https://www.abet.org/accreditation/accreditation-criteria/criteria-for-accrediting-engineering-programs-2020-2021/. [Accessed: Jan. 16, 2025].[2] N. P. Gaunkar, N. Fila, and M. Mina, “Broadening engineering perspectives by emphasizingthe human side of engineering,” in *Proc. 2020 IEEE Frontiers in Education Conf. (FIE)*,Uppsala, Sweden, 2020.[3] C. A. Roberts and S. M. Lord, “Making engineering socio-technical,” in *Proc. 2020 IEEEFrontiers in Education Conf. (FIE)*, Uppsala, Sweden, 2020. [Online]. Available:https://doi.ieeecomputersociety.org/10.1109/FIE44824.2020.9273957[4] S. H
Paper ID #49227Exploring changes in metacognition, time management, and wellbeing amonggen Z first-year undergraduate engineering students.Matilde Luz Sanchez-Pena, University at Buffalo, The State University of New York Dr. Matilde S´anchez-Pe˜na is an assistant professor of Engineering Education at the University at Buffalo – SUNY where she leads the Diversity Assessment Research in Engineering to Catalyze the Advancement of Respect and Equity (DAREtoCARE) Lab. Her research focuses on developing cultures of care and well-being in engineering education spaces, assessing gains in institutional efforts to advance equity and
, attitudes, and self-reported skills related to generative AI, coding, robotics, andengineering tasks. Self-reported likert scale responses of coding ability and robotic skill werealso collected. This was triangulated by asking implicit questions about student coding ability.More specifically student responses to questions such as “If you do have prior programmingexperience: when you "get stuck" and need help, what online resource(s) would you use to figureout how to move forward?” helped assess their prior coding knowledge. For instance,generalized responses that referred to use of a search engine or asking others for help wereindicative of lesser prior knowledge in comparison to student responses that referred to StackOverflow, open source
. 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
seven features: (1) First-year or sophomoreengineering vs. non-first-year or sophomore; (2) hands-on vs. non-hands-on; (3) whether thestudy was on first-year curriculum design (4) types of microcontroller use (5) If the study involvesmicroelectronics, (6) Identify the goal(s) of the study, and (7) Present the findings andconclusions. The three identified themes were (1) curriculum design, (2) student learningoutcomes, and (3) challenges and limitations. The thirty-two papers in the study providedinformation on each theme except “challenges and limitations,” which only included 31 papers,as one did not mention any challenges.Table 1: Differentiation of articles based on curriculum designs, Device Type, and Level
://www.shrm.org/topics-tools/news/employee- relations/employers-say-students-arent-learning-soft-skills-college[4] “Workplace Conflict Statistics 2024 | Pollack Peacebuilding.” Accessed: Jan. 05, 2025. [Online]. Available: https://pollackpeacebuilding.com/workplace-conflict-statistics/[5] P. Bahrami, Y. Kim, A. Jaiswal, D. Patel, S. Aggrawal, and A. J. Magana, “Information Technology Undergraduate Students’ Intercultural Value Orientations and Their Beliefs about the Influence of Such Orientations on Teamwork Interactions,” Trends High. Educ., vol. 2, no. 2, Art. no. 2, Jun. 2023, doi: 10.3390/higheredu2020014.[6] I. Hensista, S. Guddeti, D. A. Patel, S. Aggrawal, G. Nanda, and A. J. Magana, “Transformative Pedagogy as a
this study can be utilized to enhance the effectiveness of summer bridge programs,thereby producing engineers who meet the projected workforce demand.References[1] B. L. Yoder, “Engineering by the numbers: ASEE retention and time-to graduation benchmarks for undergraduate engineering schools, departments and programs,” 2016.[2] B. N. Geisinger and D. R. Raman, “Why they leave: Understanding student attrition from engineering majors,” in International Journal of Engineering Education, 2013.[3] A. Kodey, J. Bedard, J. Nipper, N. Post, S. Lovett, and A. Negreros, “The U.S. Needs More Engineers. What’s the Solution?,” Dec. 2023. Accessed: Jan. 14, 2025. [Online]. Available: https://web-assets-pdf.bcg.com/prod
the educationalexperience for first-year students in the introductory mining engineering course.References[1] N. Nelavai and S. Ramesh, "An Insight into the challenges faced by First Year Engineering Students: Poor Foundational Knowledge," Procedia Computer Science, pp. 823-830, 2020.[2] D. Kolb, Experiential Learning: Experience as the source of Learning and Development Second Edition, Pearson Education, 2015.[3] D. Rae and D. E. Melton, "Developing an entrepreneurial mindset in US engineering education: an international view of the KEEN project," The Journal of Engineering Entrepreneurship, vol. 7, no. 3, 2017.[4] M. Peel, "Nobody Cares: The challenge of isolation in school to university transition," Journal of
, understand and thus determine if they define themselves asbelonging to identities such as FLI, is explicitly defining what ‘first-generation’ and‘low-income’ means, and providing examples. The wording of these definitions should be givenin plain language, such as defining ‘first-generation student’ meaning the completion of a degreeby participants' parents', not just partial completion. In the AACRE pre-program survey, thesequestions include a plain language definition to explain and give example of any jargon, such as: Question 27: “Are you a first generation college student? (Meaning your parent(s) / caregiver(s) have NOT completed a bachelor's degree)These small but significant details are important to explain, so that
sharing their insights.This material is based upon work supported by the National Science Foundation under Grant No.(2128895). Any opinions, findings, conclusions, or recommendations expressed in this materialare those of the author(s) and do not necessarily reflect the views of NSF.References[1] H.-Y. Chiu et al., “Development of a social cognitive career theory scale for measuring the intention to select surgery as a career.,” Heliyon, vol. 9, no. 11, p. e21685, Nov. 2023, doi: 10.1016/j.heliyon.2023.e21685.[2] R. W. Lent, S. D. Brown, and G. Hackett, “Social Cognitive Career Theory,” in Career Choice and Development, Wiley, 2002, pp. 255–311.[3] S. D. Brown and R. W. Lent, “Social cognitive career theory.,” in Career
the CFAs (Social, Knowledge, and Encounter) organized chronologically.In contrast, Group B only had access to an unsorted spreadsheet of activities within the LMS.Group B, thus, did not receive any weekly reminders or LMS-posted information.Group A & B students registered for the CFAs through Google Forms (the links were provided inthe spreadsheet/LMS). Students were asked to provide information about their section, how theyheard about the event, why they wanted to attend it, and any specific question(s) they hoped toget an answer to. Upon completing the form, they received a Google Calendar invite to confirmtheir registration.After each event, students completed a reflection form to document their experiences andconfirm
transfer in biological systems. Students worked in teams to build confidence withexperimental and analytical skills while deepening their understanding of biological systems. Inthis project, students tested the properties of soils that emulated other permeable materialsrelevant to bioengineering.Forming Teams with CATMECATME’s Team-Maker software [19] was utilized to diversify teams of students in BIOE 120.Students completed a survey that requested data about their racial and ethnic identity, genderidentity, college (e.g., Engineering, Liberal Arts and Sciences, Business), major(s), and classyear (Table 2a). They were then asked to rate their experience level with various technical skillsas well as their preferred leadership style and if they
Journal of Engineering Education, vol. 32, no. 1, pp. 333–347, 2016.[6] N. L. Fortenberry, J. F. Sullivan, P. N. Jordan, and D. W. Knight, “Engineering education research aids instruction,” Science, vol. 317, no. 5842, pp. 1175–1176, 2007.[7] S. McGuire, S. Y. McGuire, and T. Angelo, Teach students how to learn: Strategies you can incorporate into any course to improve student metacognition, study skills, and motivation. Routledge, 2015.[8] A. Kramer, C. Wallwey, G. Thanh, E. Dringenberg, and R. Kajfez, “A Narrative-Style Exploration of Undergraduate Engineering Students’ Beliefs about Smartness and Identity,” in 2019 IEEE Frontiers in Education Conference (FIE), Covington, KY, USA: IEEE, Oct. 2019, pp. 1–9. doi
Pre + Post 1=Beginner to 5=Expert Attitude towards tech challenge How much did you enjoy the tech challenge project you Post 1=Did not enjoy at all to worked on all week? 5=Enjoyed it a lot How well did you work with your team? Post 1=Did not work well together at all to 5=Worked together very well Psychological safety (Cronbach’s α = .80) I felt comfortable talking to the project advisor(s) about Post 1=Not true at all to my questions
contexts. These objectivesalign with the principles of adaptive expertise, highlighting the importance of educationalstrategies that prepare students for dynamic professional environments.Despite its importance, adaptive expertise is often underemphasized in first-year engineeringcourses. Traditional curricula frequently focus on routine skills, such as machining or drafting,with limited opportunities for students to engage in open-ended, iterative design processes. Thispaper seeks to address this gap by demonstrating how the integration of Kolb’s ExperientialLearning Cycle, iterative prototyping, and structured coaching can foster adaptive expertise infirst-year students. By building on prior research, such as Larson et al.’s [3] work on
programs of choice) dominate as the primary stressors across all demographic groups,although statistically significant differences based on gender, nationality, and level of disabilityare observed. A new intervention to guarantee some students placement into their second-yearprogram of choice was expected to address one of the most significant stressors (second-yearprogram placement), but data collected to date shows these students have lower well-beingscores, higher stress scores, and no statistically significant difference in identify programplacement as a key stressor.References [1] Okanagan Charter: An International Charter for Health Promoting Universities and Colleges, 2015. [2] S. Fisher and B. Hood, “The stress of the transition to
. Eng. Educ., vol. 107, no. 4, pp. 556–582, 2018, doi: 10.1002/jee.20234.[3] I. R. Beattie and M. Thiele, “Connecting in class? College class size and inequality in academic social capital,” J. High. Educ., vol. 87, no. 3, pp. 332–362, 2016.[4] C. R. Glass, E. Kociolek, R. Wongtrirat, R. Jason Lynch, and S. Cong, “Uneven experiences: The impact of student-faculty interactions on international students’ sense of belonging,” J. Int. Stud., vol. 5, no. 4, pp. 353–367, 2015, doi: 10.32674/jis.v5i4.400.[5] B. K. Iverson, E. T. Pascarella, and P. T. Terenzini, “Informal faculty-student contact and commuter college freshmen,” Res. High. Educ., vol. 21, no. 2, pp. 123–136, 1984, doi: 10.1007/BF00975100.[6] A. Pitt, F. Oprescu, G
having a successful second run after only a few short days was a great success. Number of deliveries far exceeded expectations Meeting the project requirements4. What was your greatest challenge on the drone project? Time constraints and some minimally-performing team members Dropping accuracy Initial run failed Solving last minute technical problems5. What suggestion(s) do you have to improve the drone project? Making the competition even more challenging by adding an obstacle to the course More time Incorporating design originality into the scoring system6. Did your view of engineering change as a result of the drone project and if so how? The importance of time and project
] S. Ghanat and D. Ragan, “Implementing Entrepreneurial Minded Learning in a First-Year Seminar Course,” Proceedings of the 2014 ASEE Annual Conference, Portland, OR.[ 6] Pluskwik, Leung, & Lillesve, 2018 [7] N. Duval-Couetil, E. Kisenwether, J. Tranquillo, J. Wheadon, ”Exploring the Intersection of Entrepreneurship Education and ABET Accreditation Criteria,”The Journal of Engineering Entrepreneurship, vol. 6, Number 2, pp.44-57,June 2015. https://doi.org/10.7814/jeenv6n2p3. [Accessed Dec 17, 2017].[8] ABET, “Changes in Definitions, Criterion 3 and Criterion 5
instance, C1 performed near the average in Milestone5 and below average in Milestone 6, yet the team maintained a united approach throughout, reflectingtheir commitment to equity.Equity Concerns: F4, F7In contrast, teams F4 and F7 displayed consistently high grades with near-zero deviations in suggestedadjustments, raising potential concerns about collusion in the peer review process. F7’s dramatic drop inperformance during Milestone 3, while maintaining no deviations in peer review data, may indicate aprearranged agreement among members. F4 presents a subtler case, with no single milestone showingsignificant performance deviation that might reveal team inequities hidden by internal agreement, evenshowing a later increase in performance. These
Paper ID #47666Instilling Confidence and Belonging in a First Year Mechanical EngineeringRobotics CourseDr. 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 the Jacob’s School of Engineering at UC San Diego.Dr. Huihui Qi, University of California, San Diego Dr.Huihui Qi is an Associate Teaching Professor in the department of Mechanical and Aerospace Engineering, at the University of California San Diego.Prof. Nathan Delson, University of California, San Diego Nathan Delson
size of minority groups, which prevents a moredetailed empirical analysis by race, first-generation status, and economically disadvantagedstudents.References1 Clayton, A. B., & Worsham, R. E. (2024). Preparing Students for Postsecondary Success: The Effects of College Advising on College Readiness. Innovative Higher Education, 49(1), 1-24.2 2 Vedogbeton, H., Brown, C., Somasse, G. B., & Krueger, R. (2023, June). Improving the Experiences and Retention of Black Students in STEM Education. In 2023 ASEE Annual Conference & Exposition.3 Kurlaender, M., Reed, S., & Hurtt, A. (2019). Improving College Readiness: A Research Summary and Implications for Practice. Policy Analysis for California Education, PACE.4 Gottfried, M. A
_te/14158.htm[9] Skillfull Learning, 1 - What Is Metacognition and Why Should I Care?”, (2019).[10] P. C. Brown, Make it stick: the science of successful learning. Cambridge, Massachusetts: The Belknap Press of Harvard University Press, 2014.[11] P. Cunningham, H. Matusovich, D.-A. Hunter, S. Blackowski, and S. Bhaduri, “Beginning to Understand Student Indicators of Metacognition,” in 2017 ASEE Annual Conference & Exposition Proceedings, Columbus, Ohio: ASEE Conferences, Jun. 2017, p. 27820. doi: 10.18260/1-2--27820.[12] S. A. Ambrose, How learning works: seven research-based principles for smart teaching. in The Jossey-Bass higher and adult education series. San Francisco, CA: Jossey-Bass, 2010.[13] P. N. Van Meter, C. M
inDesign Process Experience a miniaturized design process, preparing pairs: each student designs for the them to experience a similar process in longer needs of a partner project(s) in the course A lecturette on design, design Understand that engineering design is one of many thinking, and engineering design Hyperlink design disciplines, and how all design disciplines share common processes, tools, and ways of reasoning about the world in order to create value2. Empathy & Students will
during the class session before each exam. In theactivity, students compete in teams to answer questions quickly. Background music plays forapproximately 1 minute while the teams work to find the correct response. Teams must agree onan answer and turn it in before the music stops. No points are awarded for late or incorrectresponses. Correct responses earn the number of points the team wagered on that response,usually indicating the level of confidence they have in their answer. During the first half, teamscan wager 5, 3, or 1 point(s) once in each round of three questions. During the second half, thewagers change to 6, 4, or 2 points per question per round. Points are recorded in a spreadsheet,and team point totals are announced at half-time