students are paired with nursing studentsto develop assistive devices for a specific client with a physical disability. The teamwork skillsand mindset developed in the Program are brought into a much sharper focus when students mustnavigate working in such diverse teams and with a real-life end user.It should be noted that this approach to teaching teamwork and developing teamwork lends itselfto other classes. For instance, Business Writing at University of Detroit Mercy uses the TeamLists and Team Reflection activities as does the Professional Communication class at OaklandCommunity College. See Appendix B for a sample student reflection on teamwork.Conclusions and next stepsA sustained approach to teaching teamwork supports learning of this key
“other”and 23/81 from the “none” category). The percentage withdrawal for each category is representedin Figure 4 and demonstrates that the withdraw rate for students with no prior coding experiencewas 30 to 50% higher than those with some level of experience. The scores for the first practicumand final course grade were therefore collected for the remaining students that completed thecourse (N = 104). Figure 5 (a and b) represent scores based on the year of high school graduationand prior computer science experience (note: students that graduated in 2016 or earlier wereassigned the year 2016). Although there was no significant trend observed with the year of highschool graduation, it was found that all students that had taken an AP computer
North Central Section Conference Copyright © 2024, American Society for Engineering Education 2Fig 1. Diagrams of RHEED patterns corresponding to (a) flat, monocrystalline ZnO sample, (b)partially uneven, monocrystalline ZnO, and (c) fully uneven, monocrystalline ZnO sample. For every available RHEED image, the binary classification corresponding toepitaxially–grown ZnO sample surface quality was paired with the complete set of PAMBEoperating parameters that were in place when the image was acquired. This includes values forsubstrate temperature, zinc effusion cell temperature, oxygen gas flow rate, plasma sourceforward power level, and growth duration. Statistical metrics for the input variables over
of plasma assisted oxidation and ignition of ethylene–air flows by a repetitively pulsed nanosecond discharge. Proceedings of the Combustion Institute, 2009. 32(2): p. 3181- 3188.18. Ombrello, T., et al., Flame propagation enhancement by plasma excitation of oxygen. Part I: Effects of O3. Combustion and flame, 2010. 157(10): p. 1906-1915.19. Ombrello, T., et al., Flame propagation enhancement by plasma excitation of oxygen. Part II: Effects of O2 (a1Δg). Combustion and flame, 2010. 157(10): p. 1916-1928.20. Starik, A., B. Loukhovitski, and A. Chernukho, Comprehensive analysis of combustion enhancement mechanisms in a supersonic flow of CH4–O2 mixture with electric-discharge-activated oxygen molecules
how students incorporateempathy into their engineering designs and the quality of the information sources that studentsintegrated into their personas and other stakeholder activities. In addition, future course deliverywill also include a greater emphasis on the VIC as opposed to the technical design componentwhich will be completed solely in the technical design course. Finally, the authors look forwardto continuing to participate in the research around stakeholder empathy development in CivilEngineering design.Bibliography[1] H. Zhu and B. E. Mertz, “Work In Progress: Incorporation of the Entrepreneurial Mindset into the Introduction to Engineering Course,” presented at the 2017 ASEE Annual Conference & Exposition, Jun. 2017
, and online availability of support from instructors.Przybyla et al. [7] designed and built their own platform for the teaching of a remote powerelectronics laboratory. It consists of a reconfigurable power converter board, microcontroller-based control board, Raspberry PI 4, model B, oscilloscope, control and viewing applications,remote control application, and the PCs of connected students. Students connect to the systemfrom their computers via a remote-control application such as Zoom. The instructor is logged into the same Zoom session and can guide a group of students, giving screen control to one studentat a time. The Raspberry PI enables connection to the Internet. It hosts the GUI application tointerface with the user. It communicates
; Exposition, 2023.[12] R. LaFarge and C. Abdallah, “The diversity programs’ graduate bridge program,” in 2003 Annual Conference, 2003, pp. 8–1123.[13] A. L. Rudolph, “Cal-bridge: Creating pathways to the phd for underrepresented students in physics and astronomy,” Physics Today, vol. 72, no. 10, pp. 50–57, 2019.[14] A. Wright, R. Brent, C. R. Jackson, E. C. Dickey, K. S. Weems, and B. J. Reich, “A bridge to the ph. d. for urm students,” in 2019 CoNECD-The Collaborative Network for Engineering and Computing Diversity, 2019.[15] R. G´amez, B. W.-L. Packard, and T. M. Chavous, “Graduate bridge programs as nepantla for minoritized students in stem: Navigating challenges with non-bridge peers and faculty.” Journal of Diversity in Higher
marriage and family 82, 892-910 (2020).8 López-Iñesta, E., Botella, C., Rueda, S., Forte, A. & Marzal, P. Towards breaking the gender gap in Science, Technology, Engineering and Mathematics. IEEE Revista Iberoamericana de Tecnologias del Aprendizaje 15, 233-241 (2020).9 Lewis, S. & Humbert, A. L. Discourse or reality?“Work‐life balance”, flexible working policies and the gendered organization. Equality, Diversity and Inclusion: An International Journal (2010).10 Kong, S., Carroll, K., Lundberg, D., Omura, P. & Lepe, B. Reducing gender bias in STEM. MIT Science Policy Review 1, 55-63 (2020).11 Marín-Spiotta, E. et al. Hostile climates are barriers to diversifying the geosciences. Advances in
Program.Prof. Haoyong Lan, Carnegie Mellon University Haoyong Lan is the Engineering Librarian at Carnegie Mellon University, where he provides library in- struction, research assistance, data support, and collection development to students, faculty, and staff. He received a Bachelor’s degree in Electrical Engineering and a Master’s degree in Library and Informa- tion Science both from the University of Illinois at Urbana-Champaign. His research interests include explainable artificial intelligence, engineering research competency, scientometrics, digital library, and information retrieval. ©American Society for Engineering Education, 2024 Finessing the Introductory Standards Workshop
rubric, employing a quality scale ranging from 0(Unacceptable) to 3 (Exceptional), is utilized to assess students' technical writing skills[4]. ThisProceedings of the 2024 ASEE North Central Section Conference 4Copyright © 2024, American Society for Engineering Educationrubric is bifurcated into two main sections: a) Report Mechanics: This aspect of the rubricfocuses on the structural and presentation quality of the report, including the organization ofcontent, aesthetic layout, adherence to the specified format, and the correctness of spelling,grammar, and punctuation; b) Report Content: This section delves into the substantive elementsof the technical report. Evaluated components include the abstract or
students’ backgroundpreparation and additional factors prior to enrolling in the IC Engines course.Since a strong foundation in thermal-fluid sciences is required for the course, an initialevaluation was conducted on the number of students who earned a B or better inThermodynamics I (a course prerequisite). The aim was to determine whether a significant Proceedings of the 2024 ASEE North Central Section Conference Copyright © 2024, American Society for Engineering Education 8number of Fall 2021 students had benefited from a stronger foundation in Thermodynamics I atthe time of enrollment in IC Engines
comprises wireless sensors configured in the CupCarbon simulator [12]. The sensorsare arranged in scaled topologies like those used in the hardware environment. The sensors areprogrammed to (a) function in stand-alone or virtual mode (b) respond to the corresponding sensorin the hardware environment.Section 2 identifies the hardware environment. Section 3 describes the simulator environment.Section 4 discusses the integration of the hardware and software environments. Section 5 outlinesconclusions and future work.Section 2: Hardware environmentFigure 1 illustrates one of the WSN configurations on a rectangular grid comprising fivetransmitting nodes and five receiving nodes. Each configuration comprises sensor nodes mountedon 3-D printed stands. The
learning in traffic flow modeling andintelligent transportation systems. Encouraged by early success, the program plans to apply forrenewal, with potential updates to lectures, projects, field trips, and integration with MichiganState University’s Indy Autonomous Challenge race team to attract and engage new students inautomated vehicle research.AcknowledgementsThis work is supported by NSF Grants 2150292 and 2150096.References[1] N. Paul, M. Pleune, C. Chung, B. Warrick, S. Bleicher and C. Faulkner, "ACTor: A Practical, Modular, andAdaptable Autonomous Vehicle Research Platform," 2018 IEEE International Conference on Electro/InformationTechnology (EIT), Rochester, MI, USA, 2018, pp. 0411-0414, doi: 10.1109/EIT.2018.8500202.[2] Nicholas Paul and
; Chadwick, S., & Shaffer, R., & Cone, M., & Helbling, J. (2005, June), Interdisciplinary FreshmanExperience Paper presented at 2005 Annual Conference, Portland, Oregon. https://peer.asee.org/153316. Green, M., & Leiffer, P., & Hellmuth, T., & Gonzalez, R., & Ayers, S. (2007, June), Effectively Implementing TheInterdisciplinary Senior Design Experience: A Case Study And Conclusions Paper presented at 2007 AnnualConference & Exposition, Honolulu, Hawaii. https://peer.asee.org/29127. Allenstein, J. T., & Whitfield, C. A., & Rhoads, B. (2012, June), From the Industry to the Student: ProjectManagement of an Industry-sponsored Multidisciplinary Capstone Project Paper presented at 2012 ASEE AnnualConference &
fly ash particles settling for different ranges ofparticle sizes as shown in Figure 4 and Figure 5. Figure 4 (A, B) and Figure 5 (A, B) show theyearly settlement amount in (Kg) of coal fly ash particles of the size range of (0.5m to 10m),(10.5m to 20.0m), (20.5m to 30m), and (30.5m to 50.0m) respectively.The maps presented in Figures 4 and 5 highlight the significant environmental concern associatedwith the settling of coal fly ash particles. This concern extends to regions both near and far fromcoal-fired power plants. The impact is particularly pronounced in the northcentral and northeasterncounties of West Virginia. This concentration suggests that atmospheric conditions and prevailingwind patterns play a crucial role in the
SUSTAINABILITY DAY 2023.Results are normalized to 100%. Evaluation scale was 1-5. Team Presentation Technical project poster Outreach project poster Overall A 85.63 86.67 90.00 88.15 B 61.25 73.33 80.00 70.00 C 78.13 78.33 77.50 79.23 D 82.50 84.62 85.38 85.00 E 66.88 80.00 84.00 76.67 F 58.75 68.00 76.00 69.64 G 94.38 90.00 89.09 91.67 H 86.88
21st century. John Wiley & Sons.[4] Eden, R., Burton-Jones, A., Casey, V., & Draheim, M. (2019). Digital transformation requires workforcetransformation. MIS Quarterly Executive, 18(1), 1-17.[5] Sandhu, K. (2021). Advancing Cybersecurity for Digital Transformation: Opportunities andChallenges. Handbook of Research on Advancing Cybersecurity for Digital Transformation, 1-17.[6] Pandey, A. B., Tripathi, A., & Vashist, P. C. (2022). A survey of cybersecurity trends, emerging technologies andthreats. Cybersecurity in Intelligent Computing and Communications, 19-33.[7] ABET. (2023). ABET Web Site. Online: https://www.abet.org/ (Accessed 30 Nov. 2023).[8] Arora, S., & Ahlawat, A. (2022). An Innovative Approach to Establish, Maintain
diverse disciplineshave created a need to develop educational material for AI-readiness of the workforce. In thiswork, we focus on the problem of designing and developing machine learning (ML) models withease. This paper thus undertakes an investigation into the automatic development of machinelearning models with minimal user expertise through the use of AutoKeras, an automatic MLpython library. AutoKeras streamlines the typically intricate ML development process whichtraditionally demanded the expertise of ML engineers. This paper will first walk through thetypical ML model development process. After this process is understood, AutoKeras’ role inmaking this process simpler and more accessible will be discussed and showcased with anapplication
. https://www.shrm.org/topics-tools/news/hr-magazine/how-leaders-can-foster-better-collaboration[8] A. De Brún, L. Rogers, A. Drury, and B. Gilmore, “Evaluation of a formative peer assessment in research methods teaching using an online platform: A mixed methods pre-post study,” Nurse Education Today, vol. 108, p. 105166, Jan. 2022, doi: https://doi.org/10.1016/j.nedt.2021.105166.[9] J. D. Kibble, “Best practices in summative assessment,” Advances in Physiology Education, vol. 41, no. 1, pp. 110–119, Mar. 2017, doi: https://doi.org/10.1152/advan.00116.2016.[10] Wilson, Z. S., Holmes, L., deGravelles, K., Sylvain, M. R., Batiste, L., Johnson, M., McGuire, S. Y., Pang, S. S., & Warner, I. M. (2011). Hierarchical
Figure 1:General Shape of the Tensile Test SampleFigure 2 shown below represents the lattice structure for printing. Two different cross-sectionalstructures used as two levels of lattice structure, parallel to the base and 450 to the base. a b Figure 2: Lattice Structure for the Tensile Test Sample: a) parallel to the base, b) 450 to the baseEight experiments were carried out to examine factors and interactions, each with threeiterations, and the mean of the results was chosen. To compute the fracture strength, the fractureforce was divided by the cross-sectional area of each specimen, and the strength was divided bythe mass of each specimen to
Paper ID #44596Curriculum Design for Wind and Solar Energy EducationDr. Mohammed Ferdjallah, Marshall University Dr. Mohammed Ferdjallah is an Assistant Professor in the Department of Computer Science & Electrical Engineering at Marshall University. Dr. Mohammed Ferdjallah received his PhD degree in Electrical and Computer and MS degree in Biomedical Engineering from The University of Texas Austin. He also received his MD degree from the International University of the Health Sciences. He has a multidisci- plinary expertise in image & signal processing, computational modeling, and statistical data analysis. As
initialization scriptdescribed below. B. The set up filesThe cdsplotinit, cdsenv, cdsinit and simrc files were downloaded along with the gpdk045 libraryfrom the Cadence website. And included in the library folder provided for the students to copy.As a student will source the initialization script, these files will be copied along with thegpdk045 library into the student’s work directory. C. Initialization ScriptThe primary objective of the initialization script is to facilitate copying the 45nm technologydevelopment kit within the student work directory without manually handling the library, filesand license information. The file is written using scripting language. In 180nm technology, thisscript referenced the Cadence and Synopsys licenses
Conference Copyright © 2024, American Society for Engineering Education2024 ASEE North Central Section Conference[3] Cagliano, R., & Spina, G. (2000). Advanced manufacturing technologies and strategically flexible production.Journal of operations Management, 18(2), 169-190.[4] Juran, J. M., & De Feo, J. A. (2010). Juran's quality handbook: the complete guide to performance excellence.McGraw-Hill Education.[5] Dale, B. G., Dehe, B., & Bamford, D. (2016). Quality Management Techniques. Managing Quality 6e: AnEssential Guide and Resource Gateway, 215-267.[6] Besterfield, D. H., Besterfield-Michna, C. A. R. O. L., Besterfield, G. H., Besterfield-Sacre, M. A. R. Y.,Urdhwareshe, H., & Urdhwareshe, R. (2019). Total
distribution of data.Table 3. Longitudinal Comparison of Mind Map Scores. Prelim Team Final Team (Average) (-) (Average) A 43 72 108 B 65 144 161Teamwork and Collaboration – The Team mind maps scored higher, on average, than the Prelimmind maps created by the individual team member. This finding suggests a synergistic effectwhere the students cooperate to integrate their different perspectives and visions of the project.The change in the knowledge structure, as noted in Table 2, suggests that there was anopportunity for Surface Learning during this collaborative activity. Note, that Student X’s Prelimmind
Paper ID #44581The Service We Offer in Teaching About Common SenseProf. Craig J. Gunn, Michigan State University Craig Gunn is the Director of the Communication Program in the Department of Mechanical Engineer- ing at Michigan State University. He integrates communication skill activity into all courses within the mechanical Engineering program. He has co-authored a number of texts related to communication and poetry in engineering. ©American Society for Engineering Education, 2024 The Service we Offer in Teaching About Common Sense Craig James Gunn
Paper ID #44625Fault Recognition and Mitigation in Food Processing EquipmentDr. David R Mikesell P.E., Ohio Northern University David Mikesell is the Ella A. and Ernest H. Fisher Professor of Mechanical Engineering at Ohio Northern University. He joined the faculty after graduate work in automotive engineering at Ohio State, six years designing automated assembly machines and metal-cutting tools, and service as an officer in the U.S. Navy. His research interests are in land vehicle dynamics, autonomous vehicles, manufacturing, and robotics. Since 2015 he has served in leadership of the ASEE Mechanical Engineering Division
Paper ID #44636Photogrammetry System to Reconstruct Syndactyly Hand ModelsCaleb Edward Scheideger, Ohio Northern University Caleb Scheideger is a mechanical engineering student at Ohio Northern University with interests in bio- medical research.Dr. Hui Shen, Ohio Northern UniversityXiangyi Cheng, Ohio Northern UniversityAnna Dillenbeck, Ohio Northern University ©American Society for Engineering Education, 2024
Paper ID #44616Converting Text Into 3D Printable BrailleDax Amburgy, Ohio Northern University College of Engineering I am a Junior Computer Science major with a concentration in Cybersecurity.Dr. John K. Estell, Ohio Northern University An active member of ASEE for over 30 years, Dr. John K. Estell was elected in 2016 as a Fellow of ASEE in recognition of the breadth, richness, and quality of his contributions to the betterment of engineering education. Estell currently serves as chair of ASEE’s IT Committee; he previously served on the ASEE Board of Directors as the Vice President of Professional Interest Councils and as
: sam.ramrattan@wmich.edu & matthew.cavalli@wmich.eduAbstractThe metal casting industry has less than thirty certified Foundry Educational Foundation (FEF)university/colleges in North America. For this reason, it is important to support and maintainquality educational programs. For the past thirty-five years, metal casting simulation tools havebeen affiliated with academia primarily in research and development. At the same time metalcasting industry has adopted a digital approach to manufacturing where simulations play a majorrole. Educational institutes need to involve solidification and simulation technologies at theundergraduate level. Can solidification simulations be an effective tool to support studentunderstanding of metal casting concepts in
provided an overview of the new outcomes aswell as potential methods for teaching and assessing.Table 1: Current ABET student outcomes for engineering programs1. an ability to identify, formulate, and solve an ability to function effectively on a team complex engineering problems by applying whose members together provide leadership, principles of engineering, science, and create a collaborative and inclusive mathematics. environment, establish goals, plan tasks, and meet objectives. an ability to apply engineering design to an ability to develop and conduct appropriate produce solutions that meet specified needs