between simulated neurons, the average and maximum message size and bandwidth requirements, prevented collisions per thousand move commands, and unprevented collisions per thousand move commands. The number of random commands would start at 1000 and increase until the results stop significantly changing from the previous tests.7. Step 6 would be repeated with varying arm lengths and geometries. Parameters for testing would include the arm's total number of joints, frequency of branching, and sensor density between joints. A8. The data from step 6 would be used to calculate a maximum safe angular speed for each joint of the B
Appendix B). Thefocus of this paper is on the first three phases.Plan: The plan phase focused on determining if case study methodology is compatible with theproposed study and forming the research questions. Based on these findings of the scopingreview, multiple-case study was chosen as the methodology. This study will examine a widearray of course types, focus on individual courses as opposed to the whole curriculum, andincorporate interviews of faculty of the courses examined. Given the varying types ofengineering courses within the curriculum (i.e., first-year, technical, elective, design, etc.), thisapproach allows for a more complex and nuanced understanding of how different courses shapethe curriculum, as each course type may require
Intelligence, vol. 4, p. 100118, 2023. 11 Work-in-Progress: Gen AI in Engineering Education and the Da Vinci Cube [3] P. Denny, J. Prather, B. A. Becker, J. Finnie-Ansley, A. Hellas, J. Leinonen, A. Luxton- Reilly, B. N. Reeves, E. A. Santos, and S. Sarsa, “Computing education in the era of generative ai,” Communications of the ACM, vol. 67, no. 2, pp. 56–67, 2024. [4] E. Latif, G. Mai, M. Nyaaba, X. Wu, N. Liu, G. Lu, S. Li, T. Liu, and X. Zhai, “Agi: Artificial general intelligence for education,” arXiv preprint arXiv:2304.12479, 2023. [5] J. Prather, P. Denny, J. Leinonen, B. A. Becker, I. Albluwi, M. Craig, H. Keuning, N. Kiesler, T. Kohn, A. Luxton-Reilly et al., “The
opportunity topractice new concepts and expand their problem-solving capabilities in a low-stakesenvironment. Unfortunately, the importance of homework is often not impressed upon incomingfreshman as 56.7% of them report spending less than six hours per week working on homeworkduring their last year of high school, a behavior of which was sufficient since 97.5% had anaverage grade of an A or B [1]. The disconnect of earning good grades while not needing to putin meaningful work towards achieving them is a learned behavior which can harm students inhigher education, and it’s a difficult behavior to correct. The problem is exacerbated sinceassigned grades in high school are poor indicators of content knowledge because grades areawarded not just for
Transfer Credit Loss Completed Transferred Difference Percentage Category Credits (A) Credits (B) (A-B) (A-B)/A All Courses 23,985 22,523 1,462 6.1% Engineering Total 2,122 1,924 198 9.3% Courses URM Yes 1,039 929 110 10.6% No 1,083 995 88 8.1% First-Gen Yes 1,377 1,246 131 9.5% No 745
successes byrecruiting additional mentee-mentor matches and responding to the survey results by offeringmore purposeful connection points between all parties.Funding AcknowledgmentThis research is sponsored by a National Science Foundation (NSF) Broadening Participation inEngineering (BPE) Track 3 award (#22-17745). Any opinions, findings, conclusions, orrecommendations are those of only the authors and do not necessarily reflect the views of theNSF.ReferencesAmerican Society for Engineering Education. (2024). Engineering and engineering technology by the numbers, 2023. Engineering & Engineering Technology by the Numbers, 2023Buzzanell, P. M., Long, Z., Anderson, L. B., Kokini, K., & Batra, J. C. (2015). Mentoring in academe
).Figure 2: a) Experimental Apparatus used; b) Variation of the motion sensor position tomaximize the signal; and c) Typical measurement obtained with the Pasco motion sensorand Pasco Capstone program. (a) (b) (c)MethodologyThe work was divided into three stages: pre-class, in-class, and post-class.Pre-class (individual)The pre-class material provided: laboratory instructions, a conventional 2D videoexplaining the physical concepts involved, and an immersive video.The immersive videos showed: the steel ball’s trajectory from different angles; launcheswith different angles (20 degrees, 30 degrees, and 40 degrees) and the respective heightthe ball reached
the fundamentals required for 2D and 3D static systemanalysis and introduce 3D vectors in a statics course using social and financial designconsiderations [31]. The module presents participants with the challenge of locating the supportsfor a stayed energy generation system (nominally the balloon in Figure 1(b). A map of acommunity is provided that drives participants to consider the impact of their solution on peoplewhile they are also grappling with the ideal technical arrangement of the cables. Equilibrium of apoint in 3D space is also explored with 3D-printed pulley systems to ensure the participants havethe technical ability to solve a 3D statics problem.Styrofoam Beam DesignThe objective of the Styrofoam Beam Design project is to
instructions on usage of the designed gAI-PCT platform. (a) Module 1: Home Scene (b) Module 2: Factory Floor Tour (c) Module 3: Capping Station Tour (d) Module 4: PPE Inspection Training Figure 4: Learning Interface build with Unity • Module 2 - Factory Floor Tour: The second scene called the Factory Floor Tour, is a walk around tour of a smart manufacturing environment. In this module, the students are giving tour of a realistic Industry 4.0 manufacturing floor, introducing them to all the key components of such an environment. The students can interact with the information boxes by clicking on the ‘Pink boxes’. Figure 4b below shows the Factory Floor Tour
,” The Journal of rheumatology, vol. 21, no. 3, p. 454—461, 3 1994. [Online]. Available: http://europepmc.org/abstract/MED/8006888[2] T. Audino, A. Pautasso, V. Bellavia, V. Carta, A. Ferrari, F. Verna, C. Grattarola, B. Iulini, M. D. Pintore, M. Bardelli, and et al., “Ticks infesting humans and associated pathogens: A cross-sectional study in a 3-year period (2017–2019) in northwest italy,” Parasites & Vectors, vol. 14, no. 1, 3 2021.[3] Unity Technologies, “Unity real-time development platform — 3d, 2d vr &; ar engine,” [online]. [Online]. Available: https://unity.com/[4] D. S. D¨uzkaya, G. Bozkurt, S. Ulupınar, G. Uysal, S. Uc¸ar, and M. Uysalol, “The effect of a cartoon and an information video about intravenous
information 2 Stage 1 + Circuit Analysis 3 Stage 2 + Programming + Digital DesignFor the prediction target, we classify students’ performance in ECE 301 into two categories: gradesA and B are labeled as good performance (“0”), while grades C, D, F, and W are labeled as poorperformance (“1”). By including grade C in the “poor performance” category, the program canproactively target a larger group of students for intervention, ensuring that the students who are onthe borderline receive the resources needed to improve their performance before facing academicdifficulties. With the designed stages and prediction targets, machine learning tools are applied toclassify and analyze both
correspondinggraduation rates. Some of those categories, notably the lower grades in Calculus 2 and 3, had a small numberof individuals and were categorized as “low N” because there wasn’t enough data on which to baseconclusions.The resulting analysis is shown in Table 6 below. Graduation rate follows the expected overall pattern ofbeing higher for students with higher grades in first-semester math courses. It can be seen that students whoreceive an A in precalculus in the first semester are in the second-highest category and have a significant(63%) probability of earning an engineering degree, but that there is a large gap between this and other gradesin precalculus (B=35%, C=15%, D=8%, E=1.5%, W=0%). Students receiving D, E, or W in precalc or an Ein Calc1 had
did not meet their [the TA’s]self-determined length.In this example the dissent came in both the form of legitimate dissent [33] (the quiz was overlycomplicated—it covered too much disparate material) and personal attacks (the coordinatorneeded instruction from the TA about how to be an instructor) [30]. To help resolve the dissent,the two-step strategy was deployed as follows: 1. Provide an avenue for dissent to occur and be addressed. a. Distribute the quiz in advance of the meeting for the TAs to review and provide comments. b. Encourage comments/criticism on the materials at the weekly meeting. 2. Establishing leadership boundaries between that emphasize both authority and respect. a. Do not
setting, a peer-mediated intervention strategy isutilized to help integrate a preschool target student, who is socially isolated, into the classroom bypairing them with two designated peers. Socially isolated refers to students who are not engaged inthe classroom. This strategy is employed alongside two observation methods: IDEAS and SocialNetwork Observation (SNO). 3 (a) Bluetooth beacon (b) Beacon in vest Figure 1: Beacons worn in a vest by the studentsSNO is a more traditional approach to observations, where a researcher observes the interactionsbetween the target student and their designated peers and then takes notes on the
developinginstructional tools to facilitate model-based inquiry in a physical science course for prospectiveelementary teachers. Any opinions, findings, conclusions, or recommendations expressed in this materialare those of the authors and do not necessarily reflect the views of the National Science Foundation. REFERENCESBaumfalk, B., Bhattacharya, D., Vo, T., Forbes, C., Zangori, L., & Schwarz, C. (2018). Impact of model‐ based science curriculum and instruction on elementary students' explanations for the hydrosphere. Journal of Research in Science Teaching, 56(5), 570-597. https://doi.org/10.1002/tea.21514Braun V, Clarke V. (2006). Using thematic analysis in psychology. Qualitative Research
,women, and elderly. As engineers, sometimes it may be difficult to have different conversationswith certain groups. For example, related to women hygiene, it would be better if a doctor or apsychologist gives support, rather than an engineer.References[1] World Bank Group, “Water Supply and Sanitation,” 2009, [Online]. Available: http://go.worldbank.org/GJ7BOASPG0[2] World Health Organization and United Nations Children’s Fund Joint Monitoring Programme for Water Supply and Sanitation, “Progress on Drinking Water and Sanitation: Special Focus on Sanitation,” 2008.[3] B. Amadei, R. Sandekian, and E. Thomas, “A Model for Sustainable Humanitarian Engineering Projects,” Sustainability, vol. 1, no. 4, pp. 1087–1105, Nov. 2009, doi
selected based on the needs of the study and should depend onwhether the goal of the research is to capture fine grained distinctions between responses orprioritize comparison of items relative to one another.AcknowledgementsThe work was a part of the National Science Foundation under IUSE Grant # 2013504. The authorswould also like to thank Dr. Maria Yang and Dr. Barry Kudrowitz for sharing supplementalmaterials from their studies that were not found in their original papers.References[1] E. Hilton, B. Williford, W. Li, T. Hammond, and J. Linsey, “Teaching engineering students: freehand sketching with an intelligent tutoring system,” in Inspiring Students through Digital Ink: Impact of Pen and Touch Technology on Education, T. Hammond, M
thisarticle has been critically reviewed and further refined by the authors, ensuring that the contentaligns with the authors' intended scope and scholarly rigor.References[1] A. Hamad, B. Jia, “How Virtual Reality Technology Has Changed Our Lives: An Overview of the Current and Potential Applications and Limitations,” Int. J. Environ. Res. Public Health, 19, 11278, 2022. https://doi.org/10.3390/ijerph191811278[2] B. Birckhead, C. Khalil, X. Liu, S. Conovitz, A. Rizzo, I. Danovitch, K. Bullock, B. Spiegel, “Recommendations for Methodology of Virtual Reality Clinical Trials in Health Care by an International Working Group: Iterative Study,” JMIR Ment Health, 6(1):e11973, Jan. 31, 2019. doi: 10.2196/11973. PMID
score, first-term math grades (either Calculus or remedialmath), and AP credit are strongly correlated with student retention. Because calculus anddifferential equations are foundational to fluid mechanics, heat transfer, circuit analyses, andmany other core engineering courses, inadequate math preparation has repercussions throughoutthe curriculum.Figure 1: (a) Incoming first-year Calculus Readiness Exam (CRE) scores declined since thepandemic. (b) CRE is the primary predictor of first-year retention. Data: Dr. Ian Marcus,Director of Analytics, College of EngineeringInsufficient technical/mathematical training is a major barrier, but students who score poorly onthe Calculus Readiness Exam also typically lack adequate study habits and
Standards (NGSS) emphasize the role of pre-college engineering, andsince public school teachers rarely have familiarity with engineering concepts, they need moreknowledge of engineering. Further, the number of multilingual learners in US public schoolclassrooms are rapidly increasing, necessitating new practices by teachers and support structuresto better assist these students’ learning. A major motivation for our work is to counter theassumption often made within formal education in the US that these emergent multilingualstudents do not have the capacity or linguistic skills to engage in conceptually challenging topicssuch as science, engineering, or STEM inquiry.Our work emphasized a sustained professional development project with elementary
Van Treuren (BaylorUniversity) and funding from the Kern Family Foundation.References:[1] A. L. Zydney, J. S. Bennett, A. Shahid, and K. W. Bauer, “Impact of Undergraduate Research Experience in Engineering,” Journal of Engineering Education, vol. 91, no. 2, pp. 151–157, 2002, doi: 10.1002/j.2168-9830.2002.tb00687.x.[2] A.-B. Hunter, S. L. Laursen, and E. Seymour, “Becoming a scientist: The role of undergraduate research in students’ cognitive, personal, and professional development,” Science Education, vol. 91, no. 1, pp. 36–74, 2007, doi: 10.1002/sce.20173.[3] D. Lopatto, “Survey of Undergraduate Research Experiences (SURE): First Findings,” CBE, vol. 3, no. 4, pp. 270–277, Dec. 2004, doi: 10.1187/cbe.04-07-0045.[4
Paper ID #46314Programming as an Engineering Tool in K-12: e4usa+Programming. Introducingthe Purple ThreadDr. Kenneth Reid, University of Indianapolis Kenneth Reid is the Associate Dean and Director of Engineering at the R. B. Annis School of Engineering at the University of Indianapolis. He and his coauthors were awarded the Wickenden award (Journal of Engineering Education, 2014) and Best Paper award, Educational Research and Methods Division (ASEE, 2014). He was awarded an IEEE-USA Professional Achievement Award (2013) for designing the B.S. degree in Engineering Education. He is a co-PI on the ”Engineering for Us All
traditional, hierarchical methods of teaching and promotes a more inclusive,participatory, and student-centered approach. Feminist pedagogy, advocates for a learningenvironment where knowledge is co-constructed through interaction among all participants—students and instructors alike. This shift toward co-creation of knowledge is particularly valuablein engineering fields, where innovation thrives in environments that foster creativity, criticalreflection, and collaboration. Figure 4 presents survey results. For each question, the responses are broken down into threeoptions (Option a, Option b, and Option c) with corresponding to how many participants selectedeach option. Student survey 100 90 80 70 60 50 40 30
approach and an innovative, two-strand theoretical framework comprised ofsocial theories of identity [6], [7], [8], [9] in one strand and critical theories, including VeteranCritical Theory [10] and Community Cultural Wealth [11], in the second strand.. In doing so, itaims to critically examine higher engineering education structures and interpretively exploreSVSM professional identity development in engineering programs at 2- and 4- year publicinstitutions in the western United States. The research plan is guided by two research questions:1. How do SVSM participate and persist in undergraduate engineering education? a) How do personal and professional assets combine to create SVSM community cultural wealth in engineering? b) How do SVSM
traditional wayby the same instructors resulted in only 45% of the students receiving a “B-” or higher grade forthe course. In the past 2 years, with new developed laboratory exercises, the number of studentswho received a “B-” or better increased to 65%. Moreover, 83% of students “agree” or “stronglyagree” that application-oriented and hands-on design labs and projects helped them to better learnthe course content. 86% “of the students agree” or “strongly agree” that laboratory exercisesincreased their interest in the subject. Such improvements in the course help students stay engaged,strengthen their understanding, and prepare for their future courses and career.IntroductionSimilar to the curriculum at many universities, our program has a basic
score of 88.56%, equivalent to a letter grade of B+. Table 1: Performance of ChatGPT-4 in CSE 174. Course Assessment Grade ChatGPT-4 Jamieson’s LLM Assessment Count Weight Score Prompt Taxonomy Final Exam 1 20% 86% PR; CoT; zero-shot Midterm Exam 1 1 15% 91% PR: CoT; zero-shot Midterm Exam 2 1 15% 88% PR; CoT; zero-shot Labs 10 15% 84.90% PR: CoT; zero-shot Quizzes 13 10% 85.71% PR: CoT; zero-shot Projects
engineering success. A 28-year study conducted by Budny etal. [5] found a clear correlation between engineering success and a strong understanding ofmathematical principles. Their research also revealed that students earning an A in precalculushad the same retention probability as those who started in Calculus I and earned at least a B,suggesting that mastering foundation material provides the necessary groundwork to obtain anengineering degree. Similar results were reported by Gardner et al. [6], who found that the gradesof first-year engineering students in their initial mathematics courses were significantlycorrelated with their retention in engineering programs.Bridge programs are a common intervention designed to enhance retention. These
-ended questions. These are as follows: 1) Overall, how would you rate your experience in our embedded systems courses that incorporated hands-on learning through the MISL-ASE board? A. Excellent B. Good C. Fair D. Poor 2) How confident do you feel in applying the skills acquired from the embedded systems courses to research projects related to embedded systems design? A. Very confident B. Confident C. Somewhat confident D. No confident 3) Which aspects of hands-on learning and related research projects were most beneficial to your understanding of embedded systems? (Select all that apply) A. Practical experiments with the MISL-ASE board B. Final course projects C. Conducting research
model; and 2) configuring a realistic lighting condition. Technicaldetails of these investigations will be explained in Section 4.3. Figure 2. The proposed i360oVR framework: (a) 3D reconstruction; (b) VR model development; (c) VR scene creations; (d) hotspot integration; and (e) i360oVR.Once the VR model of the cliff is developed, the next step is to create 360o virtual scenes asshown in Figure 2c. To this end, a virtual 360o camera is placed at pre-selected locations in theVR model of the cliff. Camera parameters are tuned such that 2:1-ratio 360o images of the cliffmodel can be rendered for each camera location. The demonstration of VR scene creation will beillustrated in Section 4.4. Thereafter, the rendered 360o images are
& Psm-MProjectiles Psm-P Inclined Plane Psm-P B field of a Psm-P wireThe authors completed the lessons, watched the interviews, and categorized the modes in thevideos independently and met to discuss the choice of sense-making modes for each of thelessons. The evolution and construction of the modes is illustrated in the figures below. Thesemodes are based on the interviews with the students and represent how they interacted with thelessons and the AR Scenes. Each of the modes start out with a PSM-P mode where