Paper ID #35221Improving Student Outcomes with Final Parallel Program Mastery Approachfor Numerical MethodsDr. Sam B Siewert, California State University, Chico Dr. Sam Siewert has a B.S. in Aerospace and Mechanical Engineering from University of Notre Dame and M.S., Ph.D. in Computer Science from University of Colorado. He has worked in the computer engineer- ing industry for twenty-four years before starting an academic career in 2012. Half of his time was spent on NASA space exploration programs and the other half of that time on commercial product development for high performance networking and storage systems. In 2020
University Purdue University, Indianapolis Dr. Miller is the Undergraduate Program Director and Clinical Associate Professor of Biomedical Engi- neering at Indiana University-Purdue University Indianapolis (IUPUI). After earning her BS in Materials Science and Engineering from Purdue University (West Lafayette), she earned her MS and PhD degrees at the University of Michigan (Ann Arbor). Her current roles include teaching, assisting in program assess- ment, student advising, and helping oversee undergraduate curriculum development and enhancement. c American Society for Engineering Education, 2020 Biomedical Engineering Students Gain Design Knowledge and Report Increased Confidence When
of a product; then developbusiness and marketing plans for the product, while gaining an understanding of thepatent process. All of these activities are part of a capstone project that is alreadyincluded in the curriculum at ASU‘s Polytechnic campus, Department of ElectronicSystems.Introduction ASU defines entrepreneurship as “the spirit and process of creative risk takingand innovation that leverages university knowledge to spur social development andeconomic competitiveness.”1 Additionally, in a contributed article to Mechanical Engineering Magazine,Ephraim Suhir, President and CEO of ERS/Siloptix Co. in Los Altos, CA, wrote that “atechnological professional with entrepreneurial skills has a better chance than a
Paper ID #35917Work in Progress: Developing Disambiguation Methods for Large-ScaleEducational Network DataMr. Adam Steven Weaver, Utah State University Adam Weaver is a B.S. Mechanical Engineering student at Utah State University. His research is focused on developing explicit disambiguation methods for large-scale social network studies. In addition, he works with applications of Particle Image Velocimetry (PIV), and wrote curriculum using PIV to teach energy conservation to high school students.Mr. Jack Elliott, Utah State University Jack Elliott is a concurrent M.S. in Engineering (mechanical) and Ph.D. in Engineering
foreducational purposes. And though denial of service attacks will always haunt wireless networksincluding Wireless Local Area Networks (WLANs), other risks can be mitigated such ascompromise of confidentiality and integrity through authentication, authorization and encryptionmechanisms.14Security over wireless networks has matured greatly since the original 802.11 standard wasratified. Privacy had been of great concern as the signals were originally broadcast over theshared medium sans encryption. The Wired Equivalent Privacy (WEP) encryption algorithm wasintroduced to overcome the initial privacy issues. Not only was it discovered to be flawed, but itwas also only a one-factor authentication mechanism.15 As wireless networks grew, key sharingbecame an
, see Section3.4.2.1 Learning and Engagement Strategies (LESs)Collaborative learning is where two or more people work in groups mutually searching for under-standing, solutions, or meanings, or creating a product [11]. Smith et al. [11] state that there is awide variation in the collaborative learning activities, but they must be centered on the students’ ex-ploration or application of the material. Collaborative learning promotes several education goals,including: involvement - students participate more in their learning, interact with other studentsand interact with the teachers; cooperation and teamwork - students recognize different views andwork together to build consensus to resolve these differences; and civic responsibility
., the graphical user interface or GUI) of the application in a systems context. It then iteratively refines these components, typically into object classes with their attributes, methods, and associations, until a level of detail is reached that allows implementation to begin. 5. Test Plan: The final document in the first semester is the test plan. It is due at the same time as the SDD. The test plan identifies what mechanisms and procedures the team will use to ensure software is evaluated before being submitted to the application build. 6. Initial Presentation: The final deliverable for the first semester is a presentation on the software’s semester-end capability. In addition to a demonstration of the
administrative direction for the Center for Engineering Outreach and Inclusion through the cultivation of partnerships with corporations, alumni, university con- stituents and organizational alliances.Dr. Pradip K Bandyopadhyay, Penn State University (Berks Campus)Mark Johnson, Pennsylvania State UniversityDr. Mikhail KaganDr. Ann Marie SchmiedekampDr. Peter J. Shull, Pennsylvania State University, Altoona Campus Dr. Peter J. Shull is an associate professor of engineering at Penn State University. He received his under- graduate degree from Bucknell University in mechanical engineering and his graduate degrees from The Johns Hopkins University in engineering science. Dr. Shull’s research has two main foci—nondestructive
third village (El Convento). In recognition of their success in bringing sustainable cleanwater and sanitation solutions to villages in the Yoro region, the Environmental ProtectionAgency (EPA) awarded EWB-LC a $75,000 P3 grant for these efforts to be used between 2006and 2008.Project Management ConceptsAccording to Oberlender, project management can be defined as the “art and science ofcoordinating people, equipment, materials, money, and schedules to complete a specified projecton time and within approved cost.”8 Oberlender consolidates 20 key concepts of effective projectmanagement into five basic functions: planning, organizing, staffing, directing, and controlling7.However, Oberlender’s theory is intended for a professional organization
] [20].In ENGR 101, we feel that the rubrics help us stay focused on the learning goals and purpose ofthe assignment and not get lost in peripheral elements. For example, during the first two years ofassigning technical memos we did not use an analytic rubric, but instead let instructors choosehow to evaluate the submissions. After a few semesters using this method, we realized that wehad inadvertently been focusing too much on sentence structure, grammar, and spelling in ourevaluation, and the technical understanding had become undervalued. This prompted us todevelop an analytic rubric that still had us provide assessment about writing mechanics, butrefocused the bulk of the assessment on the students’ achievement of the technical learning
at Harvey Mudd College. His research interests include experi- ential and hands-on learning, and integrating mechanical, chemical and quantum devices into circuits and communication links. American c Society for Engineering Education, 2021 Engineering Identity, Slackers and Goal Orientation in Team Engineering ProjectsAbstract -- This research paper will describe the results from a qualitative investigation oflong-running, team-based engineering projects at a small liberal arts college. Long-running,team-based engineering projects are projects in which groups of students perform an engineeringtask over three or more weeks
Paper ID #40058Work in Progress: Research on Engineering Students’ EpistemologicalBeliefs in Design Decision Making; Conceptual Issues and a NewMethodological ApproachDr. Trevion S Henderson, Tufts University Trevion Henderson is Assistant Professor of Mechanical Engineering at Tufts University. He earned his Ph.D. in Higher Education at the University of Michigan. ©American Society for Engineering Education, 2023 (WIP) Research on Engineering Students’ Epistemological Beliefs in Design Decision Making: Conceptual Issues and a New Methodological ApproachThis work-in-progress paper reports on an
school students, and selectingappropriate flooring materials and designing a floor layout for a house occupied by a family withdogs and small children. MethodsWe audio-recorded two engineering units taught by each of the two teachers, for a total of about810 minutes of classroom instruction. The audio-recordings were transcribed into writing. Todetermine whether a dialogic spell occurred, we identified all instances in which students spokewithout the interjection of a new question posed by the teacher. After identifying these instancesin the data set, we then went back and identified what teacher oral discourse moves immediatelyproceeded the dialogic spell. We then used constant comparative analytic
University, studying student engagement and post-structural philoso- phy in the Mary Lou Fulton Teachers College.Ms. Noa Bruhis, Arizona State University Noa Bruhis is a doctoral student in the School for the Future of Innovation in Society at Arizona State University. She earned a B.S. in Mechanical Engineering from UC Davis, and received her M.S. in Water Resources Engineering from Oregon State University. She spent several years in industry, developing research-grade environmental sensors, and has returned to school for a Ph.D. in the Human and Social Dimensions of Science and Technology Program at ASU.Dr. Nadia N. Kellam, Arizona State University Nadia Kellam is Associate Professor in the Polytechnic School of the Ira
Technological University Mary Raber currently serves as Chair for the Engineering Fundamentals Department in the College of Engineering at Michigan Technological University.Dr. A.J. Hamlin, Michigan Technological University AJ Hamlin is a Principle Lecturer in the Department of Engineering Fundamentals at Michigan Technological University, where she teaches first-year engineering courses. Her research interests include engineering ethics, spatial visualization, and educatioDr. Matt Barron, Michigan Technological University Dr. Barron’s teaching interests include solid mechanics, engineering fundamentals, and transitional mathematics. His research interests include educational methods, non-cognitive factors, and bone tissue
there, we begin building larger pieces which ultimately are assembledinto a computer.As Figure 3 shows, the labs follow a day or two behind the lecture content. Because labsgenerally run four days a week and prelabs are due before students arrive in lab, we need a fewdays of buffer between students’ first exposure to the material and using it in lab.Lab kitsEvery student receives a lab kit containing the FPGA along with a breadboard, USB cable, and allof the discrete components they will need to complete the labs. The kit fits in a small containerabout the size of a pencil box, which is easy for students to carry and bring each week to lab. Thebox is also just deep enough for an assembled circuit to be packed away and remain intact. Anitemized
validation of structuring a course this way. 2 A good measure of validation came during the summer of 2010 when a discarded librarytextbook lumped in a pile of books to be thrown away caught my eye. The textbook is entitled“The Science of Engineering Design”, written by Percy Hill and published over 40 years ago in1970. Hill asserts in the Preface, page vii: … long experience with freshman students has convinced the author that material of the type presented in this book must be conveyed to the student as early as possible in the engineering curriculum …. This book … does not concern itself with the science of solid mechanics, fluid mechanics, integrated
calledinduced demand [1], [2]). Adding a new road lane brings new drivers, and over time (typicallywithin five years) leads to more traffic, more pollution, and contributes to a reduction incommunity quality of life [3], [4]. Similarly, viewing energy efficient building materials inisolation to how they perform within a system may lead to less than optimal solutions. Forinstance, windows with a low U-value typically cost more but produce less heat transfer, whichcan equate to reduction in HVAC loads, leading to a net positive benefit for both financialinvestors and the environment.Unfortunately, civil engineering practice still too frequently ignores these dynamicrelationships between system components. For example, rating systems like Leadership
their goals and providing them with opportunities to realize that. He also focuses on their personal development and on improving their abilities to be critical thinkers, better communicators, and active members of their community and the world. More information can be found on his personal website: www.rabihyounes.com. ©American Society for Engineering Education, 2024 Predicting Student Performance Using Discussion Forums’ Participation Data Abstract A significant gap in education lies in the need for mechanisms that enable earlydetection of potentially at-risk students. Through access to an earlier prediction ofstudent performance
, videoconferences, andpresentation materials were ranked as being used daily to weekly as well. From an academicstandpoint, at Montana State University, the laboratory and design courses required writtenreports that were longer in length (8 pages or more), which from the industry perspective, reportsthey used were ranked in the order of: short reports (less than 3 pages), proposals, lab reports,and then formal reports (more than 3 pages), but noted that the job role plays a large part in theimportance. For example, when asked to elaborate on which communications do they considerthe most important and why one respondent stated “Proposals, feasibility studies, and technicalinstructions…have the greatest impact on our operating system, growth, and
communication function. 7. Two neodymium ring magnets in the bottom part of Ceiling Robot. 8. A motor controlling a telescoping arm moves up or down. 9. A telescoping arm. 10. A webcam providing vision function for Ceiling Robot. 11. A microphone receives the voice from the classroom. 12. Two speakers broadcast the voice from a distance user’s talking. 13. Five ultrasonic range sensors, used to avoid bumping into people or objects in the room. 14. Four ultrasonic range sensors, used to prevent Ceiling Robots crashing into each other when several users control them. Figure 2. The hardware architecture of Ceiling Robot2.3 Key materials of Ceiling RobotThe key
refine the mesh near the walls; however,mesh refinement close to the walls increases the computational time and cost tremendously. Analternative round-about technique to obtain realistic flows without refining mesh close to theground is to use the standard wall functions [7]. However, Verma et. al. [1] did not consider eitherthe law of the wall or mesh refinement near the walls. Thus, in this work, wall functions are usedin the wall boundary faces to capture steep velocity gradients near the walls.1.7. ObjectivesFollowing teaching module components will be provided as hands-on material for students:1. OpenFOAM as part of the CFD course to consider turbulence in the flow.2. Applying standard wall function to use coarser mesh and save
Paper ID #28402Energy Consumption Trends for AC Systems in a Typical HouseDr. Maher Shehadi, Purdue Polytechnic Institute Dr. Shehadi is an Assistant Professor of Mechanical Engineering Technology (MET) at Purdue Univer- sity. His academic experiences have focused on learning and discovery in areas related to HVAC, indoor air quality, human thermal comfort, and energy conservation. While working with industry, he oversaw maintenance and management programs for various facilities including industrial plants, high rise residen- tial and commercial buildings, energy audits and condition surveys for various mechanical and
near-zero correlations on all measures. However, unlike Summer 2003, the Gain andNormalized Gain do not provide significant correlations for any courses. In fact, they are close tozero. These results imply that the SCI Post-Test measures the same basic material as the coursescover, which is the most important evidence for concurrent validity. Page 9.1292.4 Proceedings of the 2004 American Society for Engineering Education Annual Conference & Exposition Copyright © 2004, American Society for Engineering EducationPredictive ValidityFor Summer 2003, the SCI Pre-Test lacks predictive validity with respect to final
design and directinterventions addressing the mechanisms that seem to be disconnecting ability and interest inSTEM careers.Social cognitive career theory suggests that self-efficacy and expectancy-value are criticalfactors in an individual’s career choice and persistence.7 Self-efficacy is a person’s belief in theirability to complete tasks and affect events that impact their lives.8 Expectancy-value theoriescomplement self-efficacy theories in the investigation of a larger social cognitive model forcareer aspirations and persistence. Expectancy-value theories posit that individuals regularlyassess the likelihood of attaining specific goals and the value they would gain or lose from suchattainment.9, 10 How self-efficacy in traditional academic
National Cooperative Highway Research Program (NCHRP) panel. She advises the student chapter of the Society of Women Engineers (SWE) at SFSU.Dr. Xiaorong Zhang, San Francisco State University Xiaorong Zhang received the B.S. degree in computer science from Huazhong University of Science and Technology, China, in 2006, the M.S. and the Ph.D. degrees in computer engineering from University of Rhode Island, Kingston, in 2009 and 2013 respectivelFatemeh Khalkhal Dr. Khalkhal is an assistant professor in mechanical engineering at San Francisco State University (a primarily undergraduate and Hispanic-serving Institution). Her research experience is in developing structure-property relationships in complex fluids and polymer
undergraduate student studying Aerospace and Mechanical engineering. I contribute to two separate research projects and participate in multiple student organizations. My interest include flight dynamics, aircraft design, propulsions (aircraft and rocketry), and bringing positive opportunities to others.Antonio Garcia (Associate Dean of Engineering) © American Society for Engineering Education, 2022 Powered by www.slayte.com Engineering Education Enrichment (e3) Initiative: A Co-Curricular Program Intended to Improve Persistence and Career Success for Low-Income and First-Generation Engineering StudentsAbstract
Comparing learning outcomes and student experiences in Engineering Mathusing virtual and physical robotsDaniel GodrickDan Godrick, P.E., is a Teaching Assistant Professor with the Integrated Design Engineering program atthe University of Colorado, Boulder. He brings a wealth of experience to his teaching, including timespent as a buisness consutant, project manager, and as a engineering consultant in private practice.He holds degrees in Mechanical Engineering (BS Duke University, MS CU) and in Civil Engineering(MS George Washington University). He is a licensed P.E. in Colorado.Angela BielefeldtDr. Bielefeldt, P.E., is a Professor at the University of Colorado Boulder (CU Boulder) in the Departmentof Civil, Environmental, &
ProjectsI IntroductionFor a number of years the Department of Electrical and Computer Engineering (ECE) atTexas Tech University (TTU) has supported the BEST (Boosting Engineering Scienceand Technology) robotics program in area secondary schools. The BEST program isdifferent than many robotics type programs in that the cost to the schools is minimized.The local BEST Hub provides their schools with returnable kits and non-returnable kitsto be used to construct the robot for that year’s competition. The non-returnable kits, inthis case, consist of a relatively large box of materials to be used in construction. Theseare not robot kits that are assembled. The robots must be built from scratch with the rawmaterials provided. The game is different every
Building Council (USGBC). This system isreferred to as LEED, which stands for Leadership in Energy and Environmental Design7.USGBC LEED-NC Rating System and its application in Hydraulic/Hydrology Course:LEED-NC is subdivided into six groups for which there are prerequisites, subcategories, andcredits in place of possible points7. The six categories are: Sustainable Sites (SS), WaterEfficiency (WE), Energy and Atmosphere (EA), Material and Resources (MR), IndoorEnvironmental Quality (EQ) and Innovation and Design Processes (ID). These broad areas areassigned some specific points. Based on the satisfactory performance on those areas the projectmight score points. Cumulative score determine the level of certification based on the followingscale