Work-in-Progress: Developing an IoT-based Engaged Student Learning Environment and Tools for Engineering and Computer Science Programs
- Conference
- Location
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Minneapolis, MN
- Publication Date
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August 23, 2022
- Start Date
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June 26, 2022
- End Date
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June 29, 2022
- Conference Session
- Page Count
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13
- DOI
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10.18260/1-2--41426
- Permanent URL
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https://peer.asee.org/41426
- Download Count
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384
Paper Authors
Mehrube Mehrubeoglu Texas A&M University - Corpus Christi
Dr. Mehrubeoglu received her B.S. degree in Electrical Engineering from The University of Texas at Austin. She earned her M.S. degree in Bioengineering and Ph.D. degree in Electrical Engineering from Texas A&M University. She is currently a Professor and Program Coordinator at the Department of Engineering at Texas A&M University-Corpus Christi. She is interested in multidisciplinary research in imaging applications using a variety of imaging modalities, including thermal imaging, hyperspectral imaging, and other digital imaging technologies that engage targeted sensors, spatial and spectral data processing, pattern recognition and classification. She has engaged in research in data analytics and image segmentation using AI, and more recently, in IoT implementation of sensors and actuators. She also has a special interest in pedagogical methods in teaching and learning.
Lifford McLauchlan Texas A&M University - Kingsville
Dr. Lifford McLauchlan is an Associate Professor and Interim Chair in the Electrical Engineering and Computer Science Department at Texas A&M University - Kingsville, and has also worked for Raytheon, Microvision, AT&T Bell Labs, and as an ONR Distinguished Summer Faculty at SPAWAR San Diego, CA. He has over 55 publications covering areas such as adaptive and intelligent controls, robotics, an ocean wave energy converter, green technology, education, wireless sensor networks and image processing. He is a co-inventor on 3 US patents related to control systems. Dr. McLauchlan is a member of ASEE and was the 2012-2014 Chair of the Ocean and Marine Engineering Division. He is also a member of IEEE (senior member), SPIE, Eta Kappa Nu, ACES and Tau Beta Pi, and has served on the IEEE Corpus Christi Section Board in various capacities such as Chair, Vice Chair, Secretary and Membership Development Officer. Dr. McLauchlan has received the Dean’s Distinguished Service Award twice and the Dean’s Outstanding Teaching Award once for the College of Engineering at Texas A&M University-Kingsville.
G. Beate Zimmer Texas A&M University - Corpus Christi
Beate Zimmer received her PhD in Mathematics from the University of Illinois Urbana Champaign in 1994, initially working in Model Theory and Functional Analysis. Since 2003 she has been an Associate Professor of Mathematics at Texas A&M University - Corpus Christi. She now works in machine learning, image analysis and environmental modeling and teaches a range of course including Calculus, Analysis and Numerical Methods.
David Hicks
David Hicks is an Associate Professor in the Electrical Engineering and Computer Science Department at Texas A&M University-Kingsville. Previously he served as Associate Professor and Department Head at Aalborg University in Esbjerg, Denmark. He has also held positions in research labs in the U.S. as well as Europe, and spent time as a researcher in the software industry.
Abstract
The COVID-19 pandemic forced education institutions everywhere to rapidly pivot to an online format in which students must often work remotely. The rapid transition has been especially challenging for STEM related courses in which students require access to physical devices to complete their work. We describe the initial steps of an NSF funded project focused on creating learning environments and materials designed to support engaged remote student learning. The approach utilizes IoT learning kits that are lent to students to provide hands-on learning experiences and promote remote engaged learning at students’ own chosen environment.
The IoT involves infrastructure in which a wide variety of physical devices interact with one another and share information. When designing, working with or combining these devices, engineering students must consider, among other things, sensors and signals, sensor and system integration, input and output interfaces, system functions, control, network management, system architecture and storage, power consumption and management issues, as well as testing and measurement for validation of proper functionality. Computer science students, on the other hand focus more on cloud infrastructure services for the support and management of IoT devices as well as the security and communications aspects of these systems; computer science students are also involved in, among other things, system architecture and storage, device control, real-time operation, system integration, user interface, and app development to facilitate the proper use of the IoT devices.
This paper describes the initial efforts underway at two Hispanic Serving Institutions in South Texas to develop IoT-based hands-on engaged student learning environments and tools targeting students studying remotely in computer science, electrical engineering and mechanical engineering programs. Three aspects of remote learning are being investigated: 1) Hands-on active problem- and project-based learning (PBL) through the use of IoT kits, 2) Off-campus engaged student learning through hands-on projects using IoT kits, and 3) Scaffolding and Transfer Learning from mathematical concepts to explain the underlying physics theory of the sensors.
Keywords: Internet of Things (IoT), Problem-based-learning, Project-based-learning, PBL, Hands-on learning, engaged student learning, transfer learning
Mehrubeoglu, M., & McLauchlan, L., & Zimmer, G. B., & Hicks, D. (2022, August), Work-in-Progress: Developing an IoT-based Engaged Student Learning Environment and Tools for Engineering and Computer Science Programs Paper presented at 2022 ASEE Annual Conference & Exposition, Minneapolis, MN. 10.18260/1-2--41426
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