Introducing Raspberry Pi and Its Peripherals to a Mechatronics Course Under COVID-19 Disruption Ratchatin Chancharoen Department of Mechanical Engineering Chulalongkorn University Bangkok, Thailand ratchatin.c@chula.ac.th Kuntinee Maneeratana Department of Mechanical Engineering Chulalongkorn University Bangkok, Thailand kuntinee.m@chula.ac.th registered for the Mechatronics. However, these students were motivated by genuine interest. With the rapid changes in technology, it was inevitable at the learning had to be constantly revised. Since the adoption of the Arduino in 2013, the system on chips SoC, with memory and I/O, and system in package SiP, with an additional circuit, were included. For instance, the ESP8866, ESP32, and BeagleBone were deployed. In academic year 2019, it was decided that the Raspberry Pi would offer a better platform for learning than Arduino in terms of the inclusiveness in OS, memory, circuit, I/O pins, and peripheral devices such as USB ports, cameras, and displays, etc., which were assembled into an ecosystem were both flexible and scalable for the future work industry, particularly in the Internet of Things (IoT) [4]. While the cost for locally customized Raspberry Pi itself was slightly higher than the Arduino, the total cost of the study kits for students was comparable. Also, students had to be prepared on the Linux OS, which most students had no prior experience. On the other hand, the need for programming training was not as crucial as all engineering students learned to program with Python in the first year [5]. Another problem arose half-way through the course; the learning was disrupted by the novel coronavirus outbreak. With the campus closure, the instruction design, that emphasized the hands-on approach, peer collaboration, and team learning, faced a challenge to adapt the learning to the online, off-campus platform. During the process, it was clear that the Raspberry Pi with inbuilt internet features significantly reduced the problems during the adoption. The objective of this paper was to report the experiences and lessons learned on the introduction of the Raspberry Pi ecology in a mechatronics course in terms of the technical contents, technology adoption, instruction, and assessment under the disruption from COVID-19 pandemic. Even though the full impact of the disruption occurred halfway through the semester, all activities were affected and adapted. As it was clear that the pandemic would continue throughout the next academic year at least, these activities would be examined and refined. II. RASPBERRY PI PLATFORM The Raspberry Pi, an affordable credit card-sized microcomputer, was developed in 2012 [6]. The board was designed to promote computer science in UK schools but later gained popularity among hobbyists and researchers worldwide. In 2020, the introduction of the Raspberry Pi 4 triggered the change in the learning design in this mechatronics course. Abstract—A more capable Raspberry Pi ecology replaced the Arduino kits in an elective mechatronics course for mechanical engineering students. The paper proposed an instructional design that allowed mechatronics projects to advanced into cyber-physical systems. The in-class lectures were provided at minimal; students were encouraged to learn from the user community. The experiential learning was provided by exercises using kits with compatible peripheral devices as well as student-initiated projects. Written exams were used to assess the theory while the exercises and projects confirmed the same contents experientially. The proposed instruction design mitigated the impact of the COVID-19 pandemic during the second half of the course. A remotely-operated rig was developed with Raspberry Pi for the hands-on exercises. The projects were completed at home. The written exam was conducted online with a newly developed exam room feature in the Courseville LMS with open-ended questions that were designed to test the basic competency and advanced understanding. The resilience of the proposed instructional design overcame challenges from the pandemic with the newly developed tools on the Raspberry Pi platform; students were able to master knowledge, and skills satisfactorily. Keywords—Raspberry Pi ecology, new normal instructional design, engineering education in Thailand I. INTRODUCTION The 3-credit elective course Mechatronics at Chulalongkorn University (CU), Bangkok, Thailand, had been offered to senior and Master students in mechanical engineering. Usually, 20-30 students, who had no prior experience in the microcontroller and the associated programming, registered for the course each year. From 2013 to 2018, the theory and practical experiences were taught using Arduino kits [1]. The knowledge was delivered via lectures and assessed by written exams. There were walk- through exercises and a semester project in which students designed and built mechatronics systems in small groups. Also, the design thinking was formally taught and included in the project conception [2]. Since then, there had been changes in the undergraduate curriculum due to feedbacks from stakeholders and industry. The design thinking was deemed necessary for all engineering students and was taught in a general education course for all first-year students [3]. A basic competency of mechatronics became necessary for mechanical engineers. With the mentoring from Mechatronics, the compulsory course Introduction to Mechatronics was developed with a similar instructional design. There were changes in students. With the compulsory Introduction to Mechatronics course, fewer undergraduate students registered for the elective Mechatronics course. In the academic year 2019, only 18 undergraduate students December 8–11, 2020, Online IEEE TALE2020 – An International Conference on Engineering, Technology and Education Page 883 2020 IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE) | 978-1-7281-6942-2/20/$31.00 ©2020 IEEE | DOI: 10.1109/TALE48869.2020.9368356 © IEEE 2021. This article is free to access and download, along with rights for full text and data mining, re-use and analysis.