Laboratory, Haque, Mohammed E., 31st ASEE/IEEE Frontiers in Education Conference, Session T1C, 20012. Visualization Techniques for Complex Processes in Solid State Engineering, Scott, C., Wake, D., ASEE Annual Conference Proceeding, Sec 3532, 19973. Documentation from URL: http://www.vrco.com, website of the software company that supports CaveLibTM4. Solid State Electronic Devices, Streetman, B., Banerjee, S., 5th Edition, 1999NIKHIL MODIMr. Modi is a graduate student at the College of Engineering, Southern University, Baton Rouge. He hasalso been a Teaching Assistant at the Department of Electrical Engineering. A proficient VC++programmer, he has great interest in computer graphics, computational fluid dynamics, and
blended project based learning (sbpbl) model implementation in operating system course. International Journal of Emerging Technologies in Learning (IJET), 15(5): 202–211, 2020.[19] Divya Kundra and Ashish Sureka. An experience report on teaching compiler design concepts using case-based and project-based learning approaches. In 2016 IEEE Eighth International Conference on Technology for Education (T4E), pages 216–219. IEEE, 2016.[20] Marc Dahmen, Luis Quezada, Miguel Alfaro, Guillermo Fuertes, Claudio Aballay, and Manuel Vargas. Teaching artificial intelligence using project based learning. Technical report, EasyChair, 2020.[21] D Anitha, C Jeyamala, and D Kavitha. Assessing and enhancing creativity in a laboratory course with
using a system thinking approach to support teachers and develop professional learning experiences around cre- ating conceptual models, designing coaching systems, developing frameworks and lessons, and preparing professional development. Her research interests include STEM education, system thinking, conceptual modeling, and coaching.Olivia LancasterDr. Nancy Ruzycki, University of Florida Dr. Nancy Ruzycki is an Instructional Associate Professor, Director of Undergraduate Laboratories, and the Principal Investigator on the EQuIPD Grant at the University of Florida within the Department of Materials Science and Engineering in the Herbert Wertheim College of Engineering. She has received over 7 million dollars in
Paper ID #39311Board 167: Exploring Elementary Pre-service Teachers’ PersonalEngineering Efficacy and Engineering Teaching Efficacy in a ScienceMethods Course Incorporating Engineering Design Activities (Work inProgress)Mr. Miracle Moonga, Montana State University - Bozeman Miracle Moonga is a graduate student in the Curriculum and Instruction program at Montana State Uni- versity (MSU). He also works as a teaching assistant in the department of education at MSU where he teaches a science methods course and a laboratory safety course. His research interests are in K-12 science and engineering education.Dr. Rebekah J. Hammack
, testing its movements, andpicking up/dropping off/transporting objects using the Workcell. The laboratory work wascarried out by the students in groups of two. The school of engineering provided completesupport in terms of equipment and software required for the program.The weekly plans of the robotics program are shown in Table 2. Students worked onAutonomous Vehicle for four times (12 hours), Robotics modeling for five labs (15 hours), andeight labs for VEX Robot (24 hours). One of the challenging factors that we encountered wasfaculty involvement. Since the participating faculty already had a full teaching load during theSummer, it was difficult to arrange lab content in a way that was both meaningful and coherent.As a result, the program
research interests lie in the applications of materials science and advancedmanufacturing techniques. © American Society for Engineering Education, 2022 2022 ASEE Midwest Section ConferenceHan HuHan Hu is an Assistant Professor in the Department of Mechanical Engineering at the Universityof Arkansas. He leads the Nano Energy and Data-Driven Discovery (NED3) Laboratory and hisresearch interests cover experimental characterization and multi-scale modeling of two-phaseheat transfer enhancement on micro-/nano-structured surfaces, immersion cooling of powerelectronics, diffusion kinetics in high-entropy alloys, and multimodal data fusion. © American Society for Engineering
collaborativeefforts to advance both AHPCC and scientific computing on campus. Jeff has been the recipientof nearly $500,000 in NSF funding as part of his work with the National research computingeffort.Han HuHan Hu is an Assistant Professor in the Department of Mechanical Engineering at the Universityof Arkansas. He leads the Nano Energy and Data-Driven Discovery (NED3) Laboratory and hisresearch interests cover experimental characterization and multi-scale modeling of two-phase heattransfer enhancement on micro-/nano-structured surfaces, immersion cooling of power electronics,diffusion kinetics in high-entropy alloys, and multimodal data fusion. © American Society for Engineering Education, 2022
’ academic backgrounds are notable challenges and we expect to encounter in futuresemesters. We also found that even though the NRT capstone offered sessions about teamcollaboration, students still faced challenges with team logistics. Therefore, to better support thenext cohort, in the spring 2023 NRT capstone course, the NRT faculty will offer more teambuilding activities at the beginning of the semester. In addition, we found that even though thescheduled team workdays were useful, successful teams needed to meet outside of course time.We also found that one semester might not be sufficient to develop and submit a final researchproduct for journal publication, especially if it includes laboratory experiments. Literature reviewpapers and
development of a laboratory manualto guide earth science students through the process of exploring the history and nature of planetEarth. Since it is the beginning stages of a work in progress, only a simple first draft of thelearning objectives and lab procedures for this unit have been developed by engineering andeducation students at ORU. The current learning objectives are as follows: 1. Describe the methodologies of retrodictive thought experiments and affordance-based reverse engineering 2. Starting with the Big Bang, summarize the process (from science) by which planet Earth came into existence, and identify the natural laws that govern these processes. 3. Describe the measurements that assist in determining the age of the
the industry upon graduation in May 2023.Hari PandeyHari is a Ph.D. Candidate in the Department of Mechanical Engineering at the University ofArkansas. His research focus includes prediction and mitigation of boiling crisis using acousticemission and high-speed imaging, improving boiling heat transfer using wicking structures, andimmersion cooling of power electronics.Han HuHan Hu is an Assistant Professor in the Department of Mechanical Engineering at the Universityof Arkansas. He leads the Nano Energy and Data-Driven Discovery (NED3) Laboratory and hisresearch interests cover experimental characterization and multi-scale modeling of two-phase heattransfer enhancement on micro-/nano-structured surfaces, immersion cooling of power electronics
viability Artifacts: Product Test Results (OEM) Dimensional Results (OEM and SMM) © American Society for Engineering Education, 2022 2022 ASEE Illinois-Indiana Section Conference Proceedings | Paper ID 35927 Cumulative Costs7. OEM issues PPAP (Production Part Approval Process) and releases that to SMM. Artifacts: PPAP Level III instructions from OEM Signed Warrant (OEM)8. SMM develops tools for PPAP. Artifacts: Qualified Laboratory Documentation Validation of Fixtures/Gauges/Measurement Aids Measurement System Analysis (MSA) Process Capability Study
© American Society for Engineering Education, 2022 2022 ASEE Illinois-Indiana Section Conference Proceedings | Paper ID 36054number of ‘best practices’ have been suggested, which were used in designing a peermentorship program at Anderson University.In 2017, Coller, et. al. used peer mentors for teams in a first-year engineeringdesign-build-test-communicate course at the University of Michigan, and the authors provide aframework for assessment of their mentorship program [5]. They were able to report severalbest practices from their experience. Suggestions for successful peer mentorship programsinclude recruiting excellent former students, assigning mentors at a laboratory (TA) level,gathering regular updates from mentors, and providing
the universities he joined. He is the recipient of the ”Distinguished Professor of the Year”, University of Bridgeport, academic year 2006-2007. He supervised hundreds of senior projects, MS theses and Ph.D. dissertations. He developed and introduced many new undergraduate/graduate courses. He also developed new teaching / research laboratories in his area of expertise. His students have won more than twenty prestigious national / international awards from IEEE, ACM, and ASEE. Dr. Elleithy is a member of the technical program committees of many international conferences as recog- nition of his research qualifications. He served as a guest editor for several international journals. He was the chairperson of the
grimydays of the past. Prospective students tour manufacturing programs and their laboratories, andmention what they want to do after graduation – basically defining manufacturing engineering.But, when they are asked to choose a program, they prefer mechanical engineering or other fieldsover manufacturing. Table 1. ABET Accredited Programs in Manufacturing Engineering4 as of 02/09/2022 Manufacturing Engineering (21) Arizona State University, Bradley University (IL), Bachelor’s of Science Brigham Young University (UT), California Polytechnic State University - San Luis Obispo, California Polytechnic State University – Pomona, Central
curriculum. This project did not tie to any specific course nor bear any college credit. It was a purely extra-curriculum activity.• Teaming up with one of the student engineering clubs, GUBotDev starting the second year improved students’ participation and expanded the resource. The GUBotDev mobile lab (a modified full RV) acted as the onsite testing laboratory for the team during 2021 competition as shown in Figure 6.• It is an excellent experience for the team to enter the competition and meet with other teams from all over the world. It was a fruitful experience for the key project members with one of 7 Proceedings of
creativity, experience and knowledge to solve problems to help people. Engineers design electric cars, mobile phones, bridges and processes to clean environment and mass transportation systems to move people and goods. Engineers can choose different types of jobs such as design, manufacturing, research, testing or sales etc. A student interested in discovering new knowledge can consider a career in research. If you are imaginative and creative, design engineering may interest you. If you like computers, you can be a CAD engineer. If you like laboratory and experiments, you may choose development engineering. Engineering is also organized in traditional fields such a mechanical, electrical, civil, chemical, biomedical or computer
advancementof faculty and student research, curriculum development through courses, laboratory experiments,course projects, as well as STEM outreach with pK-12 schools. The hardware requirements of theplatform are inexpensive, and the setup is portable as well as easily extended to larger grids. Thesoftware for each node is created in the Arduino environment and the RSS data collection programis written in Python which is compiled and executed with tools accessible online. In the future, theuser interface will implement advanced inverse mapping algorithms and deep learning models torefine the display of visual details and statistical analysis of the RSS data
-grade FPGAs ADASand Electric Vehicle embedded system requirements are met. Textbook used in the course islisted in Appendix A.The topics covered include • Elements of Embedded Systems Design • Real Time systems Requirements • Field Programmable devices • VHDL based design and design of Logic modules • Matlab to generate HDL code • Schematic design for FPGA • Simple CPU design • Design with embedded processors • Softcore processors NIOS II implementation inside FPGA • Use of Hardcore ARM processor inside SOC-FPGAs • Automotive applications and software standards. • Laboratory exercises with Intel DE1 SOC boards and projectCatalog Course Description:Topics covered include the use of hardware
students from threeconcentration areas of civil engineering (structures, construction, and transportation) to work in asmall group or six students. Some of the example projects students worked in the past few yearsinclude Building project for a university that includes classroom and laboratory facilities;Building project for a university that includes student services facilities and an auditorium;Indoor sports complex in a local community; and Ash recycling facility for a local township. Asample project along with the scope the required guidelines provided below:Scope of a Sample ProjectThe assigned project is a Center for Innovation and Collaboration at a local university. This newcenter is currently in the process of being revised, since the
Multidisciplinary Course Collaboration," Entrepreneurship Education and Pedagogy, vol. 3, no. 1, pp. 14-40, 2019, doi: 10.1177/2515127419856602.[8] B. Harold and H. S. Sam, "Petroleum and Natural Gas," in The Mining Industries, 1899–1939: A Study of Output, Employment, and Productivity. New York, NY: National Bureau of Economic Research, Inc, 1944, ch. 10, pp. 188-208.[9] L. Arscott "Sustainable Development in the Oil and Gas Industry," Journal of Energy Resources Technology, vol. 126, no. 1, pp. 1-5, 2004, doi: 10.1115/1.1653768.[10] P. Šprljan, D. Pavković, M. Klaić, T. Staroveški, and M. Cipek, "Laboratory prototyping of control system retrofitting designs for oil drilling applications," in Proceedings of 10 th
Paper ID #40352Case Study: Using AI&ML to Generate Well Logs in Santa-Fe Field, KansasProf. Mehrdad Zamirian, West Virginia UniversityProf. Shahab D. Mohaghegh, West Virginia University Shahab D. Mohaghegh, a pioneer in the application of Artificial Intelligence and Machine Learning in the Exploration and Production industry, is a Professor of Petroleum and Natural Gas Engineering at West Virginia University and the president and CEO of Intelligent Solutions, Inc. (ISI). He is the direc- tor of WVU-LEADS (Laboratory for Engineering Application of Data Science). Including more than 30 years of research and development in
averageengineering student may want to use the path of least resistance and go for the seemingly easiestpath to follow. This may come in the form of that 17 syllable Haiku, we talked of above. Thinkof assigning students a lab report or a final paper. Each of these require a structure that must befollowed, but these are long and cumbersome. The Haiku is only 17 syllables, but it is teachingstructure. Using that required lab report, we can see a need to choose the right words to describethe laboratory that was investigated. When you think of the Haiku, we find that the writer mustreally think about the way they create the text. It has to be investigated carefully or it won’t fitthe prescribed structure 5-7-5. This also lends itself to choosing the right word
averageengineering student may want to use the path of least resistance and go for the seemingly easiestpath to follow. This may come in the form of that 17 syllable Haiku, we talked of above. Thinkof assigning students a lab report or a final paper. Each of these require a structure that must befollowed, but these are long and cumbersome. The Haiku is only 17 syllables, but it is teachingstructure. Using that required lab report, we can see a need to choose the right words to describethe laboratory that was investigated. When you think of the Haiku, we find that the writer mustreally think about the way they create the text. It has to be investigated carefully or it won’t fitthe prescribed structure 5-7-5. This also lends itself to choosing the right word
Engineering and Computer Science, and directs the Neural En- gineering Laboratory at University of Missouri-Columbia. His research focus is presently in the area of computational neural engineering from a systems and control perspective. He is author of 170 refereed articles (100+ journals, books and book-chapters, 70+ conference), and 88 posters and abstracts. He is also active in educational training related to neural engineering (from a systems/control perspective) for audiences ranging from K-12 students to faculty to K-12 levels. American c Society for Engineering Education, 2021 Robotics-based Engineering Approaches in the G4-12 Curriculum1. Introduction
outreach programs to recruit young women toengineering. Age", Proceedings of the 2005 American Society for Engineering Education Annual Conference &Exposition, 2005[7] Robnett, R., "The Role of Peer Support for Girls and Women in STEM: Implications for Identity and AnticipatedRetention", International Journal of Gender, Science and Technology, 5(3), 232-253, 2013.[8] Akl, R. G., Keathly, D., and Garlick, R., "Strategies for Retention and Recruitment of Women and Minorities inComputer Science and Engineering", Innovations 2007: World Innovations in Engineering Education and Research,2007.[9] Feisel, L.D. and Rosa, A.J., "The role of the laboratory in undergraduate engineering education”, Journal ofengineering education, pp. 121-130, January
," J. Eng. Educ., vol. 93, no. 3, pp. 223–231, Jul. 2004.[11] M. T. H. Chi, "Active-Constructive-Interactive: A Conceptual Framework for Differentiating Learning Activities," Top. Cogn. Sci., vol. 1, no. 1, pp. 73–105, Jan. 2009.[12] S. Freeman et al., "Active learning increases student performance in science, engineering, and mathematics," Proc. Natl. Acad. Sci., vol. 111, no. 23, pp. 1–6, 2014.[13] C. E. Wieman, "Large-scale comparison of science teaching methods sends clear message," Proc. Natl. Acad. Sci., vol. 111, no. 23, pp. 8319–8320, 2014.[14] A. Dallal, A. Dukes, and R. M. Clark, "Student performance in partially flipped ECE laboratory classes," in ASEE Annual Conference and Exposition, Conference Proceedings
course has six objectives: 1. to become familiar with equipment and procedures to determine properties of engineering materials; 2. to learn to prepare metallographic specimens, examine the microstructures, and understand the effects of heat treatments; 3. to become familiar with the ASTM standards for materials testing; 4. to develop spreadsheet skills in processing, plotting and analyzing experimental data; 5. to interpret experimental results and compare them to expected results; and 6. to create professional and concise laboratory reports using spreadsheet and word processing software.In fall 2020, faculty at my university chose their own modality of instruction – in-person, online or ahybrid model. I chose
full of lessons and engineering applications.Above all, every university has a power plant and workers who are full of experience and readyto share their experience with students with enthusiasm and dedication. The power plant is ademonstration laboratory that can be used to teach many engineering programs including heattransfer, thermodynamics, machinery, water treatment and water quality, materials, structure,combustion, and, more importantly, all these are undergone under dynamic conditions.Managing this mentorship was difficult, due to the time constraints and the corona pandemic.One of the advantages is the proximity of the early college to the engineering building. Research,education, and outreach are involved in this mentoring at
throughout the entiresemester. These groups were arranged such that neither gender was placed in a minority. Afterthe completion of the semester-long data collection, researchers selected consented groups basedon complete attendance, meaning that no group member was absent from a week of datacollection. Participant demographics, such as age, race, and engineering major, were notcontrolled in this study. Groups were spread across four registered sections, each taught by threeteaching assistants. In this paper, we analyze data from two weeks of 50-minute discussionsessions held in a laboratory classroom.Data AnalysisGroups’ video and audio data were collected as they solved each task. This study analyzes datafrom 22 total video recordings, one from