Paper ID #22588Designing a Sustainable Large-scale Project-based Learning (PBL) Experi-ence for Juniors in Electrical and Computer EngineeringProf. Stephen Schultz, Brigham Young University Stephen M. Schultz has received B.S. and M.S. degrees in electrical engineering from Brigham Young University, Provo, UT, in 1992 and 1994, respectively. He received a Ph.D. in electrical engineering from the Georgia Institute of Technology, Atlanta, GA, in 1999. He worked at Raytheon Missile Systems from 1999-2001. He has taught at Brigham Young University since 2002 and is currently a Full Professor. He has authored or coauthored over
at California State University, Los Angeles. He is pursuing his career as an entrepreneur in the field of Civil Engineering. c American Society for Engineering Education, 2019Design of Flipped Classroom Model for a Computer Aided Structural Analysis Design and Experimentation Course AbstractEngineering course redesign with educational pedagogy is gaining widespread acceptance. Thereis a move from teacher-centered lectures to student-centered active learning strategies that willbenefit student learning. It is important that students develop critical thinking and analytical skillsthat will form the basis of lifelong learning. In this
wasconducted as a part of an experiential learning portion of an undergraduate engineering lab in arequired computer-integrated manufacturing course for two engineering programs, mechatronicsand industrial engineering. In the lab, students designed and implemented digital logic-basedcontrols for a typical manufacturing operation. The students participating in the lab experimentswere seniors majoring in mechatronics and/or industrial engineering. The mechatronics studentshad previous experiences with building digital circuits while their fellow students from industrialengineering did not. First, the students were divided into pairs where each industrial engineeringstudent was paired with a mechatronics student. As the students were creating and
Paper ID #27218Analysis of Students’ Personalized Learning and Engagement within a Cy-berlearning SystemDebarati Basu, Virginia Tech Dr. Debarati Basu is an Assistant Teaching Professor in the College of Computing and Informatics at the University of North Carolina at Charlotte. She earned her Ph.D. in Engineering Education from Virginia Tech (VT) in 2018. She received her bachelors and masters in Computer Science and Engineering. Her research areas are in the Cyberlearning or online learning, computer science education, and experiential learning including undergraduate research. She is also interested in curriculum
for this course are • Demonstrate an understanding of the mechanics of accelerating bodies. • Analyze and solve dynamic problems related to Engineering applications. • Use computer-aided tools to study the dynamics of moving bodies • Improve presentation skills and generate a technical design reportAdditional teaching goals and objectives through the intervention pursued in this study are thefollowing: • Engaging students in real-world, hands-on tasks and improve cognitive learning of students: By incorporating this hands-on laboratory experiment in the aforementioned course, the goal is to provide a platform for students to test engineering concepts learned through lectures. In doing so, the project
running through the truss’s two-force members (2FMs). This scenario does not lend itself to a holistic understanding of howtrusses behave under loads of various magnitudes and locations. It does not facilitate acomparison of the relative strengths and weaknesses of different truss designs, nor aconstructivist learning style driven by curiosity.TrussVR© carries out the computations of solving a truss almost instantaneously. What thisaffords is a new way to learn about trusses, and a way to learn features of trusses that have beenpreviously impractical to learn through conventional lab techniques. Build a truss, apply anexternal force, and see the distribution of forces within the truss. This cycle can be repeatedquickly in VR, allowing learners to
Paper ID #25845Relating Level of Inquiry in Laboratory Instructions to Student LearningOutcomesSpencer Rosen, Harvey Mudd College Spencer Rosen is a student at Harvey Mudd College pursuing a BS in Engineering with an emphasis on Electrical and Computer Engineering. He expects to graduate in May of 2020.Sabrine Griffith, Harvey Mudd College Sabrine Griffith is pursuing a BS in Engineering with a focus on Biomedical Devices Engineering at Harvey Mudd College and a BS at Claremont McKenna College in Economics. She expects to graduate with these two degrees in May of 2020.Eli Byrnes, Harvey Mudd College Eli Byrnes is a
Paper ID #21046Optimizing Students’ Learning Experiences in Instrumentation and Mea-surement LaboratoryDr. Emine Celik Foust, York College of Pennsylvania Emine Celik Foust is currently an Associate Professor at York College of Pennsylvania. In 2008, she worked as a Postdoctoral Research Associate in Mechanical Engineering Department at Johns Hopkins University. She received her Master of Science and Ph.D degrees in Mechanical Engineering from Lehigh University. Emine Celik Foust’s research interests include design and development of engineering systems using ana- lytical and experimental approaches (advanced global
Paper ID #32979Participation and Learning in Labs Before and During a PandemicMs. Madalyn Wilson-Fetrow, University of New MexicoDr. Vanessa Svihla, University of New Mexico Dr. Vanessa Svihla is a learning scientist and associate professor at the University of New Mexico in the Organization, Information and Learning Sciences program and in the Chemical and Biological En- gineering Department. She served as Co-PI on an NSF RET Grant and a USDA NIFA grant, and is currently co-PI on three NSF-funded projects in engineering and computer science education, including a Revolutionizing Engineering Departments project. She was
expected that VR and/or combined AI will have significant increase offunding opportunities from the federal governments.VR has the potential to improve learning outcomes and student engagement in an active learningenvironment. VR is the use of three dimensional (3D) computer graphics in combination withinterface devices to create an interactive, immersive environment[3]. Due to improvements intechnology and reductions in cost, the use of VR in education has increased greatly over the pastten years [4], [5]. Emerging consumer VR devices are starting to provide sufficient quality andaffordability for home and school use, and this will eventually make educational VR experiencesbroadly available. Future consumer VR headsets are expected to include
makes, without argument,conceptual designs using paper and pencil, computer modeling, and implementation of the designsin the physical world essential elements of learning. It is not surprising that KLC has been appliedin civil engineering [3-5], mechanical engineering [5], chemical engineering [3, 4, 6], aeronauticalengineering [5], industrial engineering [7], and manufacturing engineering [3, 4, 8].This work addresses a small laboratory project. Project based learning (PBL), as a part ofexperiential learning, is also well-researched [10-12]. In addition, since students work in pairs, PLis implemented. PL methods are well described and justified in education and psychology literature[13-17]. In engineering education, PL is applied in
was selecting a project that had real-world applicability, integrated knowledge fromseveral different engineering subjects, resulted in a functional device, and would be appropriatefor sophomore-level biomedical engineering students. The vein finder device project met all ofthese requirements. Students worked in teams and applied various skills such as programming,circuit design, soldering, computer-aided design, and rapid prototyping to develop a functional,inexpensive vein finder device, which could be used by nursing students to learn how to locatesuitable veins for intravenous insertion. Student feedback from course evaluations indicated thatthe design project was effective in increasing student motivation and learning. The study
trying to learn online using new technology. In some cases, students lived in areas withlimited bandwidth. Some students lacked the use of laptops or other computing resources and oftenattended classes via mobile phones.While working in an office environment was risky and discouraged, the lack of faculty interaction withpeers left many faculty feeling a sense of isolation. Normal hallway discussions were restricted, makingcollaboration such as co-teaching multiple sections of the same course much harder. Similarly, notbeing able to come to campus not only limited faculty-student interactions (office hours, recitations,etc.), it also inhibited student-peer interaction (group projects, teamwork, etc.) and stopped most ofextracurricular experience
year, I plan to integrate computer science and mechanical engineering into my curriculum in aspiration of becoming a mechatronics engineer in the future.Dr. Prudence Merton, Dartmouth CollegeDr. Vanessa Svihla, University of New Mexico Dr. Vanessa Svihla is a learning scientist and assistant professor at the University of New Mexico in the Organization, Information & Learning Sciences program, and in the Chemical & Biological Engineering Department. She served as Co-PI on an NSF RET Grant and a USDA NIFA grant, and is currently co-PI on three NSF-funded projects in engineering and computer science education, including a Revolutioniz- ing Engineering Departments project. She was selected as a National Academy
Conner, Qinang Hu, Brian Norton, and Tony Ivey, ”Oklahoma State University’s ENDEAVOR: Transformation of Undergraduate Engineering Educa- tion through the Experience-based learning.” 2020 ASEE Annual Conference & Exposition. June 21-24, 2020. Montreal, Quebec, Canada. Abstract submitted on Oct 14, 2019. Abstract accepted on October 28, 2019. Draft paper submitted on Jan 31, 2020. • Lead Author: B. Smyser, Reviewer and contributor: J. Conner, ”Measurements and Analysis for Mechanical Engineers”, 2nd Edition TopHat Publishing [ISBN: 978-1-77330- 957-6] 2019 • Lee, S., Conner, J. Arena, A. ”Aspects of Autonomous Recovery System for High Altitude Payloads by Using a Parafoil” AIAA Aviation and Aeronautics Forum and
Paper ID #26418How Research Informs Teaching and Learning Models: Case Studies in Build-ing Solar Cell and Bioengineering Technology in the Lab and ClassroomDr. Anas Chalah, Harvard University Dr. Anas Chalah Assistant Dean for Teaching and Learning Lecturer on Engineering Sciences Director of Lab Safety Program Harvard University John A. Paulson School of Engineering and Applied Science Pierce Hall G2A, 29 Oxford Street Cambridge, MA 02138 (617)-495-8991 achalah@seas.harvard.eduDr. Fawwaz Habbal, Harvard University Fawwaz Habbal has served as the Executive Dean for the Harvard School of Engineering and Applied Sciences
, 2021 Anytime-Anywhere Engineering ExperimentationAbstract: This work examines the delivery of quality, hands-on engineering experimentation in a homeor remote environment. The course was designed to develop experimental skills in engineeringmeasurement methods, based on electronic instrumentation and computer-based data acquisitionsystems, using the microcontrollers Raspberry Pi and/or an Arduino. The learning outcomesinvolved developing student confidence, proficiency in data acquisition, statistical assessment ofdata, experimental setup and implementation. There were 6 formative modules to developconfidence in making engineering measurements with a variety of sensors and a summativemodule that involved a student-created
might be too expensive for students toperform physically [3], for distance learning [3], and for students with mixed-abilities andspecial needs [21]. They also provide an opportunity for research and education collaborationsamong institutions around the world [21]. Remote laboratories have most often been used toteach electrical and mechanical engineering [22].Virtual laboratories (or simulations) are computer software/models, which provide simulateddata [3], [15]. They provide an opportunity to demonstrate unobservable phenomena such aselectromagnetic fields, laminar flow in pipes, heat transfer, and electron flow [5], [7], [10], [16],[17]. Virtual laboratories also allow students to conduct more experiments faster and cheapercompared to hands
Paper ID #29397Work-in-Progress: A modular course on sensors, instrumentation andmeasurement: Supporting a diversity of learners’ agency of self-directionDr. Brian D. Storey, Franklin W. Olin College of Engineering Brian Storey is professor of mechanical engineering at Olin College.Dr. Bradley A Minch, Olin College of Engineering Bradley A. Minch received the B.S. degree with distinction in Electrical Engineering from Cornell Uni- versity in May 1991. In June 1997, he received the Ph.D. degree in Computation and Neural Systems from the California Institute of Technology (Caltech) where he worked under the supervision of
BS and PhD in Computer Science from the University of Illinois at Urbana-Champaign.Dr. Cynthia Marie D’Angelo, University of Illinois at Urbana Champaign Cynthia D’Angelo, Ph.D., is a researcher specializing in science education, technology-enhanced learning environments (including simulations and games), and collaborative learning. She focuses on leveraging data gathered through innovative technologies to better understand student learning of STEM concepts and practices. She has a background in physics and science education.Mr. Daniel Cermak, Illinois Informatics; University of Illinois at Urbana ChampaignMiss Mei-Yun Lin, University of Illinois at Urbana Champaign Mei-Yun Lin is a Ph.D candidate in the department of
: Robotics Technology in the department of Computer Engineering Technology atCUNY-New York City College of Technology is offered as a technical elective to its senior students. Inaddition to introducing fundamental subjects in both Autonomous Mobile Robot [1] and RoboticManipulator [2], another goal is to prepare students with necessary knowledge and skills for roboticprogramming and design. The course is structured to have a 2.5-hour lecture session and a 2.5-hour labsession each week. When teaching onsite the school (i.e., in-person), students were given physical robotsfor implementation of the algorithms discussed during lectures. When access to laboratory facilities wasimpossible under e-learning (for example, during the COVID-19 pandemic
students “work as an engineer,” the courseinstructors took a backward design approach to redesign this course. First, learning outcomesfor the course were redefined to highlight problem-solving skills, which are essentialoutcomes according to the ABET criteria. Second, a comprehensive assessment plan wascreated to measure student progress in each of the learning outcomes. Rubrics-based gradingfocuses on assessing five dimensions of student work: the solution’s efficacy, quality oftechnical writing, oral communication, completion of prototypes, and testing plans and results.Finally, the newly developed learning outcomes and assessment plan were aligned withlearning activities in the course, including design, prototyping, testing, as well as
video quality.Last, the efficacy of online laboratories as an impactful student experience has limited coveragein the literature. Assessing student learning must be accomplished from the perspective ofcomparing practical, live laboratory exercises with their on-line, remote alternatives. As digitalexperiences engage more students in new ways, those new ways can be applied to education, butthey must be built well. There is very little information available concerning best practices inimplementing on-line labs as few educators develop or use them. This work seeks to add to thatlibrary of best practices.ReferencesAsraf, H., Dalila, K., Zakiah, M., Amar Faiz, Z., & Nooritawati, M. (2018). Computer assistede-laboratory using LabVIEW and internet
course organizationPrior to enrolling in these courses, students should pass two courses on digital logic and Cprogramming. Assuming the students have mastered these prerequisites, the microcontrollerarchitecture courses can build upon this foundation.In the microcontroller architecture course, students will continue to learn more about VerilogHDL using FPGA boards. Students will learn from the Computer Organization and Design MIPSedition Textbook [1]. This book gives a good foundation and understating of computerarchitecture. Learning MIPS architecture is not the ultimate goal; however, this book and itslessons will give good understanding of intermediate level computer architecture, which helpsthe transition to ARM. After learning the
, he earned a PhD in Electrical and Computer Engineering in 2011 at the University of Virginia. His current research interests include machine learning, embedded systems, electrical power systems, and engineering education. c American Society for Engineering Education, 2018 BYOE: Circuit Modules for Visualizing Abstract Concepts in Introductory Electrical Engineering CoursesPresenter Information:The author welcomes the opportunity to collaborate on the development of courseware related toundergraduate laboratories for electrical and computer engineering. Design files and printedcircuit fabrication for these experimental setups are open-source and available from the author.Contact
Paper ID #21097Student Reflections on Experiences Gained from an Open-ended Problem-solving Bio-signals LaboratoryDr. Renee M. Clark, University of Pittsburgh Dr. Renee Clark serves as research assistant professor focusing on assessment and evaluation within the University of Pittsburgh’s Swanson School of Engineering and its Engineering Education Research Center (EERC), where her interests center on active and experiential learning. She has 25 years of experi- ence as an engineer and analyst, having worked most recently for Walgreens and General Motors/Delphi Automotive in the areas of data analysis, IT, and manufacturing
. Currently, he is an Assistant Professor with the same department, since August 2019. Dr. Hassan’s primary focus is on education development and innovation. His Research interests include, but not limited to: Machine Learning, es- pecially Deep Learning, for Image Processing and Video Prediction, Neuromorphic Computing Systems and its applications.Prof. Ahmed Dallal, University of Pittsburgh Dr. Dallal is an assistant professor at the department of electrical and computer engineering, Unversity of Pittsburgh, since August 2017. Dr. Dallal primary focus is on education development and innovation. His research interests include biomedical signal processing, biomedical image analysis, and computer vision, as well as
research laboratory as context for graduate students’ training: The role of lab structure and cultural climate in collaborative work,” Learn. Cult. Soc. Interact., vol. 13, no. March, pp. 113–122, 2017.[6] N. D. Fila and M. C. Loui, “Structured Pairing in a First-Year Electrical and Computer Engineering Laboratory : The Effects on Student Retention , Attitudes , and Teamwork *,” Int. J. Eng. Educ., vol. 30, no. 4, pp. 848–861, 2014.[7] Engineers Australia, “Document G02—Accreditation Criteria Guidelines,” Engineers Australia, Accreditation Board, 2008. [Online]. Available: https://www.engineersaustralia.org.au/sites/default/files/content-files/2016- 12/G02_Accreditation_Criteria_Guidelines.pdf.[8] Engineers
. Research indicates that involving students in hands-onactivities can enhance STEM education and the overall quality of the learning experience 3 .STEM education exposes students to explore complex topics that can be reinforced through alaboratory experience. A positive hands-on laboratory experience can also have a significantimpact on retention in engineering students. Knight et al. identified an over 15% increase inretention when first year engineering students are exposed to a hands-on project-basedcurriculum 4 . Although the benefits of a hands-on laboratory experience are apparent, thesignificant cost of laboratory equipment can be prohibitive for some institutions 2 .Computer simulation has been shown to be an effective tool that can be a
(Arduino or Raspberry Pi), boards, costeffective sensors, actuators, and transducers. The class is structured to have six experimentationmodules and an open-ended experimentation project. The contents of the experimentationmodules are designed to educate the student on the most essential and fundamental skillsnecessary to construct complex experimentation setups. These experiments involve integrationof several measurement sub-systems. In each formative module one experimental technique isaddressed. Module one teaches students the fundamentals of microcontrollers and dataacquisition with these cost effective devices. Module two focuses on temperature measurementsthrough the use of a variety of temperature sensors. Students also learn about the