blocks on a table inside a work cell located in the engineering laboratory inthe School of Engineering. Through the internet, a user can send orders to the robot and see itlive using a set of web cameras installed inside the work cell. The objective of the project is todevelop a recruiting tool to attract prospective students to engineering. Robot Controls Local Internet Server Video
the other hand,laboratory courses and engineering design courses are often used to teach communication andteamwork skills 1. Typical communication skills include, but are not limited to, maintaininglab/design notebooks, writing technical reports, and oral presentations. A project-based coursemay also include writing a proposal.On-line collaboration tools, also known as groupware, are widely used in many organizations toimprove their productivity and the quality of their products. Currently, Wikipedia includes over95 software tools 2. Types of collaboration tools include bulletin (discussion) boards for threadeddiscussions, public folders for sharing documents, and version control systems for concurrentediting software source codes or CAD
Paper ID #27039Proven Professional Development Strategies: Data from an ENG ASAP Trans-fer Student ProgramDr. Armando A. Rodriguez, Arizona State University Prior to joining the ASU Electrical Engineering faculty in 1990, Dr. Armando A. Rodriguez worked at MIT, IBM, AT&T Bell Laboratories and Raytheon Missile Systems. He has also consulted for Eglin Air Force Base, Boeing Defense and Space Systems, Honeywell and NASA. He has published over 200 tech- nical papers in refereed journals and conference proceedings – over 60 with students. He has authored three engineering texts on classical controls, linear systems, and
havethe opportunity to earn academic credit for their engineering design work. A key difference in thisframework as compared to other typical capstone designs, independent studies, or research creditcourses is that undergraduate TAs and project managers within the project teams are responsiblefor developing many of the assignments distributed to those students enrolled the course as theproject progresses. The methods of student assessment within this framework include: individualor small-group weekly assignments, design notebook checks, peer and self-evaluations,participation, summative technical reports, and the Humanitarian Library. Additionally, unlikemany traditional problem set or laboratory courses, student skills are developed through
Science on their engineering exhibits and works to improve the facilitation and design of the exhibits. Her research focuses on how science center visitors engage and tinker at engineering activities and the impacts of these open-ended tinkering activities in terms of STEM learning and engineering understanding.Dr. Alice Merner Agogino, University of California, Berkeley Alice M. Agogino is the Roscoe and Elizabeth Hughes Professor of Mechanical Engineering and affli- ated faculty at the Haas School of Business in their Operations and Information Technology Management Group. She directs the Berkeley Expert Systems Technology /Berkeley Energy and Sustainable Technolo- gies (BEST) Laboratories and is a member of the
Research (ONR), United States Navy, NASA Jet Propulsion Laboratory (JPL)] and industry partners [Blue Origin, Lockheed Martin, Sun Nuclear, Northrop Grumman, Rockwell Collins, PTC, Alstom]. Dr. Morkos received his Ph.D. from Clemson University. His Ph.D. dissertation was awarded the 2014 ASME CIE Dissertation of the year award for its transformative research on the development of non- traditional representation and reasoning tools for requirements analysis. Dr. Morkos was a postdoctoral researcher in the Department of Engineering & Science Education at Clemson University performing NSF funded research on engineering student motivation and its effects on persistence and the use of advanced technology in
and the application of artificial intelligence in the design of composite structures. Additionally to his research, he has been working as a teaching assistant at Stevens. Pitz holds a Master’s degree in Polymer Technologies and Science from Johannes Kepler University, Austria.Mr. Louis Oh, Stevens Institute of Technology Louis Oh is a Design Laboratories Manager of Stevens Institute of Technology and a student of the Mechanical Engineering Masters program. Louis has 10 years of experience in CNC machine spindles, and his expertise includes failure inspection, spindle condition analysis, and monitoring using vibration signals and sound emissions. American c
teaching. He teaches a variety of thermo-fluid and energy conversion courses, as well as design and professional component courses. He has coordinated the freshman, sophomore, junior, and senior project team-taught courses in the WKU ME program. He has presented a variety of conference papers on energy conversion initiatives and engineering design initiatives in education.Prof. H. Joel Lenoir, Western Kentucky University Joel Lenoir is the Layne Professor of Mechanical Engineering at WKU, and for 33 years has taught primarily in the mechanical systems and design areas of the curriculum. His industrial experience includes positions at Michelin Research and Oak Ridge National Laboratory, as well as extensive professional
-cost and versatile hardware kit for a remote first-year mechanical engineering design classI. IntroductionEngineering design courses with hands-on laboratories are a critical component of an engineeringundergraduate curriculum. In particular, incorporating design courses early has been shown tohelp with retention rates in engineering, as well as with improved ability of students to solve open-ended problems [1, 2]. These courses have also shown student progress in academic achievementby helping to build confidence in their engineering skills, and by expanding their perspective onproblems and solutions [3, 4]. Introduction to Engineering Graphics and Design is an introductorylevel course, usually taken by
BCOM coursesrepresented in this study, they were generally quite experienced working in teams on open-endedprojects. The engineering students, in contrast, typically had far less experience working in teamson open-ended projects. By the time the engineering students began their Senior Design capstonecourse, their previous team experience was limited to a few clearly defined class projects with alimited scope or partnering with one or two other students in a laboratory class.A fourth difference between the engineering and BCOM groups in this study is the greaterexposure to leadership, teamwork, management, and similar concepts that the business studentshave received throughout their prior coursework. From the freshmen seminar to upper
Science Foundation (NSF), Office of Naval Research (ONR), United States Navy, NASA Jet Propulsion Laboratory (JPL)] and industry [Blue Origin, Lockheed Martin, Sun Nuclear, Northrop Grumman, Rockwell Collins, PTC, Alstom]. Dr. Morkos received his Ph.D. from Clemson University. In 2014, he was awarded the ASME CIE Dis- sertation of the year award for his doctoral research. He graduated with his B.S. and M.S in Mechanical Engineering in 2006 and 2008 from Clemson University and has worked on multiple sponsored projects funded by partners such as NASA, Michelin, and BMW. His past work experience include working at the BMW Information Technology Research Center (ITRC) as a Research Associate and Robert Bosch
required and focus heavily on the engineeringdesign process. The juniors in the study follow the NASA systems engineering handbook [39] toguide them through the process of designing and building a laboratory experiment. The seniorsloosely follow the engineering design processes prescribed by Otto & Wood and Ulman [40, 41],and received formalized functional modelling instruction [42] with related homeworkassignments prior to the start of the study (not as an intervention). The juniors involved in thestudy were not taught any formalized functional modelling processes prior to the study.3.2 Mechanics of the StudyData was collected at two different points during the semester (three weeks apart) for both thejuniors and the seniors (approximately at
computer-based models at theexpense of physical models. This fact is behind a general trend of teaching applied engineeringsubjects with minimal students’ involvement with physical set-ups including laboratoryexperiments. Carrying out laboratory experiments and generating experimental data, visiting aproject site, and using pencil and paper to produce a schematic, are gradually fading away. Thesetraditional tools were instrumental in developing an engineering common sense. It is argued herethat generating data from physical models is potentially a great learning tool, particularly whenthe model is built by the students. Building a model, testing a model, generating physical datafrom the model, and analyzing said data, help students alternate
thecontextual needs assessment method as published, followed by section 3.2 describing how theteam customized the method for the micro-hydro project. Section 3.3 provides results includingsamples of an interview transcript, customer needs, and specifications.3.1 The Contextual Needs Assessment Method (as Published)The Contextual Needs Assessment Method17,18 summarized in Figure 3 improves taskclarification through a new focus on context. The contextual focus is especially critical for needswhich are “frontier” or foreign to the designer. Testing under both laboratory and normalclassroom conditions shows the new method is extremely effective, easy to use, and wellreceived by students19.The contextual needs assessment method incorporates traditional
manufacture and contact information ‚ Place of manufacture ‚ Any patenting information, e.g., a patent number ‚ Any evidence of standards satisfied, e.g., UL (Underwriter’s Laboratory) plus the identification (number) of the standardAt least two appliances should have patent information and at least two should haveevidence of standards satisfied. For the two (or more) with patent information lookup the patent on the PTO website or on the Google Patent website. (If the claim is“patent pending” (pat. pend.) look up the final patent number (if it exists) usingGoogle Patent Search). Copy the first page of the patent for your report and thendescribe what part of the patent claim seems to apply to your particular appliance.For the ones
performance verbally & graphically 3. Integrate prior coursework & university resources: 3.1. apply concepts, models, formulas and methods learned in prior courses, 3.2. develop and conduct physical and/or numerical experiments, tests or simulations, 3.3. implement available computer, laboratory and library resources, 3.4. develop expertise relationships with faculty mentors, and 3.5. communicate engineering information verbally & graphically. Page 13.141.8Teamwork Evaluation SystemA teamwork evaluation system, using an Excel spreadsheet, has been developed over the lastyear and a half in the Sr. Design sequence
, fabricate, and test devices. Some needs were modest and could be accommodated in theteam rooms or existing laboratories. However, the handbook had no guidelines for requestingrooms or other types of spaces, nor did the program have any significant predefined spaceallocated in advance. As is with most other colleges, excess space is rarely available. The processwas therefore ad-hoc and required the involvement of many college administrators to help “find”space. This lack of immediate space influenced the student team’s ability to develop anappropriate statement of work in partnership with the sponsor liaison as they could not make anassumptions about having dedicated facilities.A lesson learned here is that if at all possible, the program and
a bachelor’s in communications from the University of Cali- fornia at Santa Barbara. Prior to joining UTD in 2013, I worked in corporate communications, marketing communications and public relations.Dr. Jeanne SluderDr. Robert Hart P.E., University of Texas, DallasDr. Joe Pacheco Jr., University of Texas, Dallas Dr. Joe Pacheco Jr is a member of the teaching faculty in the Bioengineering Department at The University of Texas at Dallas (2014 to present) where his teaching includes freshman-level introductory bioengineer- ing courses, upper-division circuits and microcontroller programming courses, and senior level capstone courses. Previously, he was a member of the technical staff at MIT Lincoln Laboratory (2004-2013
TechniquesTwo common methods used to explore neural processes of decision-making and problem solvingunder laboratory conditions are electroencephalography (EEG) and functional magneticresonance imaging (fMRI). EEG involves a head cover (e.g., cap or net) which places electrodeson the scalp and measures electrical changes in the brain. Temporal resolution is very good(detects quick changes) though spatial resolution (where the change occurs) is poor becausesignals often interfere with one another and make it difficult to pinpoint specific brain regionsinvolved in the processing. EEG methods are mainly of value when stimuli are simple and thetask involves basic processes (e.g., target detection) triggered by task stimuli (Eysenck & Keane,2015
land and marine environ- ments and ship design for the U.S. Navy.Dr. Stephanie Sheffield, University of Michigan Dr. Sheffield is a Lecturer in Technical Communication in the College of Engineering at the University of Michigan.Mr. Magel P. Su, California Institute of Technology Magel P. Su is a PhD student in the Department of Applied Physics and Materials Science at the California Institute of Technology. He earned a B.S.E in materials science and engineering and a minor in chemistry from the University of Michigan. At Michigan, he was a member of the Ultrafast Laser - Material Interac- tion Laboratory and the Engineering Honors Program. He also served as an instructor for several courses including
produce computer-based models at theexpense of physical models. This fact is behind a general trend of teaching applied engineeringsubjects with minimal students’ involvement with physical set-ups including: laboratoryexperiments. Carrying out laboratory experiments and generating experimental data, visiting aproject site, and using pencil and paper to produce a schematic, are gradually fading away. Thesetraditional tools were instrumental in developing an engineering common sense. It is argued herethat generating data from physical models is potentially a great learning tool, particularly whenthe model is built by the students. Building a model, testing a model, generating physical datafrom the model, and analyzing said data, help students
, Canada, 2019.[19] D. I. Hanauer, J. Frederick, B. Fotinakes, and S. A. Strobel, "Linguistic analysis of project ownership for undergraduate research experiences," CBE-Life Sciences Education, vol. 11, no. 4, pp. 378-85, Winter 2012.[20] A. Haapasaari, Y. Engeström, and H. Kerosuo, "The emergence of learners’ transformative agency in a Change Laboratory intervention," Journal of Education and Work, vol. 29, no. 2, pp. 232-262, 2016.[21] V. Svihla, J. R. Gomez, M. A. Watkins, and T. B. Peele-Eady, "Characterizing framing agency in design team discourse," in Proceedings of the ASEE 126th Annual Conference and Exhibition: ASEE, 2019.[22] J. P. Gee, An introduction to discourse analysis: Theory and method
to fundamentaldesign principles (e.g., Computer Aided Design), concepts (e.g., fluid mechanics, controlsystems, circuitry, etc.) and skills (e.g. mechanical and electrical fabrication). Each week of thecourse included two-hour lecture and two-hour laboratory sessions in the first term, and one-hourlectures and two-hour labs in the second term.PBL was a central component of the course [23], [24]. Students were introduced to how a projectdeveloped in full cycle—planning, research and design, manufacturing, and evaluation. In thefirst term, students were introduced to engineering design fundamentals. Students continued thesecond term with an autonomous team project, where they applied manufacturing andprogramming skills to develop a product
projects.Program HistoryIn 2016, the Mechanical Engineering Department identified Additive Manufacturing (AM) as agrowing field and an important topic to incorporate into the Mechanical Engineering (ME)curriculum at Penn State Erie (Behrend). At that time, Behrend owned approximately five 3Dprinters, and we initially developed a course where the students could utilize the machinesowned by Behrend. The course was a 1 credit lab that the senior ME students could take to filltheir program requirements (two laboratory courses of their choosing). The machines werecentrally located in Innovation Commons at Behrend, which is a makerspace that was developedby Behrend to support innovation and early manufacturing of prototypes for all Behrend studentsand local
area of estimation theory with applications to mechatronics and aerospace systems. Andrew worked as a post- doctoral researcher at the Centre for Mechatronics and Hybrid Technology (Hamilton, Ontario, Canada). He also worked as a Project Manager in the pharmaceutical industry (Apotex Inc.) for about three years. Before joining the University of Guelph in 2016, he was an Assistant Professor in the Department of Mechanical Engineering at the University of Maryland, Baltimore County. Andrew worked with a num- ber of colleagues in NASA, the US Army Research Laboratory (ARL), US Department of Agriculture (USDA), National Institute of Standards and Technology (NIST), and the Maryland Department of the
in the fall. The course serves as a way for students to become familiar with theexpectations of college classes and to give them an idea of what mechanical engineering studentsdo. Students work in a team environment once a week on laboratory projects and open-endedmini-design projects where they incorporate elementary engineering design methodologies todesign some device within certain constraints. Once students begin working on their final designprojects, they meet outside of class to brainstorm ideas, build and test prototypes, and refine theirfinal designs. The final project typically lasts five weeks. Due to budgetary constraints, studentsconstruct their project out of common scrap/recycled materials. The final projects vary bysemester
monitoring methods Identify, formulate and solve an appropriate queueing model that applies IE4520 Stochastic Modeling to a given queueing system Formulate and solve problems using dynamic programming Carry out background research IE4522 Human-Machine Systems Conduct laboratory experiments in human response and performance, Interpret results statistically, use findings to design human-asset systems Apply concept of supply chain management IE4525
their support with the changes to the curriculum. Additionally,we are grateful to our scheduling office and laboratory managers who helped with organizationalaspects of running the course. Thank you, also, to Michael McCarthy and Derek Dunn-Rankinfor providing guidance on the history of MAE projects. Finally, thank you to the two anonymousreviewers for their helpful comments and feedback.ReferencesAdams, R. S., Turns, J., & Atman, C. J. (2003). Educating effective engineering designers: Therole of reflective practice. Design studies, 24(3), 275-294.American Association for the Advancement of Science [AAAS]. (2001). Atlas of science literacy.Washington, DC: National Science Teachers Association.Archer, L. B. (1965). Systematic method for
, manufacturing, and assembly processes. Since 2010, Lo- gan has worked as a private tutor; most recently he has moved from small in-person tutoring into electronic classroom learning as a consultant for an online tutoring service. In previous semesters, he has aided the teaching of introductory design and modeling classes at Florida Polytechnic University. As the operator of the Florida Polytechnic University Robotics Laboratory, he trains students to use fabrication machin- ery, 2D and 3D design software, and analytic methods to aid in student and research projects. Logan also provides 3D modeling, prototyping, and 2D design services to various local companies, and hopes to earn certifications for 3D design in the coming
process and design educational and research programs that bring the concepts of innovation and entrepreneurship into the classroom and the research laboratory. Dr. Christodoulatos is leading the implementation of academic entrepreneurship through the creation of innovative curric- ula and overseeing the commercialization of the Institute’s intellectual property. He has been teaching and performing research since 1988 and has managed over a hundred and fifty major research projects exceeding $30M. Dr. Christodoulatos has developed and delivered entrepreneurship curricula and special- ized innovation and entrepreneurship workshops for faculty, administration and technical entrepreneurs in Malaysia, Brunei and Taiwan. He