Infusing Raspberry Pi in the Computer Science Curriculum for Enhanced Learning
- Conference
- Location
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Virtual On line
- Publication Date
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June 22, 2020
- Start Date
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June 22, 2020
- End Date
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June 26, 2021
- Conference Session
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Computers in Education Division Technical Session 3: Digital Learning Part I
- Tagged Division
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Computers in Education
- Page Count
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12
- DOI
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10.18260/1-2--34828
- Permanent URL
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https://peer.asee.org/34828
- Download Count
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655
Paper Authors
Fitratullah Khan University of Texas, Rio Grande Valley
Professor Fitratullah Khan has been teaching computer science courses since 1992. His areas of expertise are computer architecture, networking, database systems, computing platforms and languages. As the director of Infrastructure, Telecommunications, and Networking (ITNet), and later as a Chief Technology Officer, at UT Brownsville, he implemented state of the art networking using campus wide fiber ring with redundant links. He established diskless computer labs to provide uniform computing platform across campus, and modernized classrooms to make them congenial to online learning. He was the PI on NSF funded BCEIL (Beowulf-based Curriculum Enrichment Integrated Laboratory) and Co-PI on NSF funded MCALL (Multimedia based Computer Assisted Learning Lab).
Mahmoud K Quweider University of Texas, Rio Grande Valley
M K Quweider is a Professor of Computer & Information Sciences at the U. of Texas at UTRGV. He received his Ph.D. in Engineering Science (Multimedia and Imaging Specialty) and B.S. In Electrical Engineering, M.S. in Applied Mathematics, M.S. in Engineering Science, and M.S. in Biomedical Engineering all from the University of Toledo, Ohio. He also holds a Bachelor of English and a Masters of Business Administration from the University of Texas at Brownsville. After graduation, he was employed at several corporations including Pixera, a digital multimedia processing company in Cupertino, CA, 3COM, a networking and communication company in Schaumberg, IL, and Mercantec, an E-Commerce company in Naperville, IL. He has more than 40 publications in the field, and has served as a reviewer/moderator for several scientific and educational journals and conferences. He joined UTB in the Spring of 2000. His areas of interest include Imaging, Visualization and Animation, Networking and Cyber Security, Web Design, Computer Graphics, and Linguistics.
Ala Qubbaj University of Texas, Rio Grande Valley
Ala Qubbaj, Ph.D.
Dean of the College of Engineering & Computer Science
The University of Texas Rio Grande Valley
Dr. Ala Qubbaj is the Dean for the College of Engineering and Computer Science at the University of Texas Rio Grande Valley (UTRGV) and the Principle Investigator (PI) for the UTRGV’s ADVANCE Institutional Transformation grant funded by the National Science Foundation (NSF); which focuses on increasing the representation and advancement of women in STEM fields. He is also the PI on an NSF INCLUDES (Inclusion across the Nation of Communities of Learners of Underrepresented Discoverers in Engineering and Science) project/Symposium for ADVANCING STEM Latinas in Academic Careers.
Prior to his Dean position, Dr. Qubbaj served as Senior Associate Vice President/Vice Provost for Faculty Affairs & Diversity at UTRGV. He is also a full professor in the department of Mechanical Engineering. Dr. Qubbaj received his Ph.D. from the University of Oklahoma with specialization in combustion and energy system. His research has been sponsored by NSF, the Department of Energy, and the Department of Defense.
Emmett Tomai University of Texas, Rio Grande Valley
Emmett Tomai is an Associate Professor and Chair of the Department of Computer Science at the University of Texas Rio Grande Valley. He received his Ph.D. in Computer Science from Northwestern University in 2009. Before that he received his M.S. in Computer Science (2007), B.S. in Computer Engineering (1997), and B.S. in Electrical Engineering (1997) from Northwestern University. His research interests are in artificial intelligence, machine learning, natural language understanding, and video game development, with emphasis on learning models of decision-making to support commonsense behavior and storytelling. Dr. Tomai also pursues research in computer science education with emphasis on introductory problem-solving, critical thinking, and programming skills.
Liyu Zhang University of Texas, Rio Grande Valley
Liyu Zhang is an Associate Professor in the Department of Computer Science Department of Computer Science at the University of Texas Rio Grande Valley. He received his Ph. D. in Computer Science from the State University of New York at Buffalo in September 2007. Before that he received his M. S. (2000) and B. S. (1997) from Fudan University, Shanghai , China, both in Computer Science. His research interests are in theoretical computer science and its applications, with emphasis on computational complexity, complexity-based cryptography, and design and analysis of algorithms. Dr. Zhang’s research has been sponsored by National Science Foundation and U.S. Department of Education.
Hansheng Lei
Abstract
With the advent of cloud computing, the Internet of Things (IoT), and mobile computing, CS faculty are continuously revamping the curriculum material to address such burgeoning set of technologies in practical and relatable ways. Raspberry Pi (RPi) devices represent an ideal hardware/software framework that embodies all these technologies through its simple architecture, small form factor (that minimizes the volume and footprint of a desktop computer), and ability to integrate various sensors that network together and connect to the Cloud. Therefore, one of the strategies of Computer Science Department, to enhance depth of learning concepts, has been to infuse Raspberry Pi (RPi) in computer science courses. RPi has been incorporated since 2016 in targeted courses, notably, Computer Organization & Assembly Language, Computer Architecture, Database Management Design & Implementation, Unix/Linux Programming, Internet Programming, and Senior Project. An inexpensive credit card sized computer, an RPi lends itself to allow depth of learning of concepts. From implementing firewalls, intrusion detection systems, scripting, client-server based computing, distributed computing, to interfacing with sensors and actuators, a student is guided to polish concepts taught in a class through RPi Project Based Learning (RPBL). Computer science curriculum already provides breadth of learning. The infusion of RPi in key courses provides depth in targeted concepts. There are peripheral desirable consequences as well, including a student learning prevalently used Linux environment even though a targeted course may have nothing directly to do with Linux. Furthermore, RPi provides an opportunity for students to realize that software programs can be interfaced with sensors and actuators to provide immersed experience in programming. From simply interfacing a switch and a Light Emitting Diode (LED) to getting data from sensors, buffering, and uploading to the cloud, a student already would have touched upon multiple disciplines in computer science. This paper provides a blueprint to infusing RPi in the targeted courses, and how each RPi based project provides depth to a targeted concept.
Keywords: Raspberry Pi, Cloud Computing, the Internet of Things (IoT), Mobile Computing
Khan, F., & Quweider, M. K., & Qubbaj, A., & Tomai, E., & Zhang, L., & Lei, H. (2020, June), Infusing Raspberry Pi in the Computer Science Curriculum for Enhanced Learning Paper presented at 2020 ASEE Virtual Annual Conference Content Access, Virtual On line . 10.18260/1-2--34828
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