Virtually Hosted by the section
November 12, 2021
November 12, 2021
November 13, 2021
11
10.18260/1-2--38444
https://peer.asee.org/38444
706
Dr. Yu Wang received her Ph.D. degree in Electrical Engineering from the Graduate Center of the City University of New York in 2009. Currently, she is a professor in the Department of Computer Engineering Technology at New York City College of Technology. Her primary area of interest includes engineering education, formal methods for modeling real-time systems, digital design, FPGA hardware-based systems, Agile testing, Machine Learning algorithms, and the applications of neural networks.
Benito Mendoza is an Associate Professor of Computer Engineering at the New York City College of Technology (CITY TECH). Before he joined CITY TECH, he worked as a Postdoctoral Research Engineer at ExxonMobil Research and Engineering Company. His areas of interest include Multi-Agent Systems, Bio-Inspired Systems, Context and Situation Awareness, and Artificial Intelligence in Education and Intelligent Tutoring Systems. He holds a PhD. in Computer Science and Engineering from the University of South Carolina and an MSc in Artificial Intelligence and a BSc in Computer Science from the University of Veracruz, Mexico.
Professor Farrukh Zia earned his Master's and PhD in Computer Engineering from Syracuse University in 1988 and 1996, respectively. Before he joined the CET/EMT department of New York City College of Technology in 2002, he worked for Lucent Technologies in New Jersey as a member of the technical staff. Professor Zia's PhD research work was related to the applications of neural networks and fuzzy logic in controlling robotic systems.
Across the world, COVID-19 has shifted the education model by forcing classroom in-person classes to transition into the distance and online learning mode. Engineering and technology programs having a curriculum with a strong emphasis on hands-on labs are facing challenges. The education community around the world is looking for options to adopt the online approach to deliver hands-on courses via Zoom, Blackboard, or video conferencing services, using simulators and other digital tools. To measure the effectiveness of the new educational model, the assessment must be redesigned. We must examine student mastery of the course learning outcomes as measured by several instruments, including labs and hands-on projects. In this paper, we present the design of a hands-on project lab for embedded systems and its corresponding assessment instruments. The embedded system project lab includes topics such as circuit analysis, analog, and digital electronics, computer programing skills, basic instrumentation, and computers to aid in the characterization and troubleshooting. As part of the requirements in this hands-on project lab, students must connect the electronic components and devices correctly on the breadboard without the instructor’s in-person supervision. Students need to use instrumentation, for example, a multimeter, an oscilloscope, and a function generator in the project lab. The paper also presents a practical approach using the Tinkercad simulator for hands-on labs and teaching students in a virtual classroom. The assessment model includes a rubric and a content validity form with performance indicators to assess ABET Student Outcomes (a) and (b) and the program-specific criteria for Electromechanical Engineering Technology.
Wang, Y., & Mendoza, B., & Zia, F. (2021, November), Online Hands-on Embedded System Project in Virtual Classroom Paper presented at 2021 Fall ASEE Middle Atlantic Section Meeting, Virtually Hosted by the section. 10.18260/1-2--38444
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