RaspyLab: A Low-Cost Remote Laboratory to Learn Programming and Physical Computing Through Python and Raspberry Pi

Title:

RaspyLab: A Low-Cost Remote Laboratory to Learn Programming and Physical Computing Through Python and Raspberry Pi [Download]

Título:

RaspyLab: Un laboratorio remoto de bajo costo para aprender programación y computación física mediante Python y Raspberry Pi [Download]

Authors:

J. Á. Ariza and S. G. Gil

Index Terms:

Programming profession;Robots;Robot sensing systems;Python;Hardware;Remote laboratories;Education;Remote laboratory;problem-based learning (PBL);physical computing;programming;Raspberry Pi;Python

Abstract:

This article describes the development and assessment of RaspyLab which is a low-cost Remote Laboratory (RL) to learn and teach programming with Raspberry Pi and Python language. The RL is composed of 16 stations or nodes that contain hardware components such as display LCD, robotic arm, temperature sensor, among others, and two modes of programming (graphical and text-based) for the students to experiment with their designed algorithms. The concept of the RL was conceived as a pedagogical tool to support the students of Engineering and Computer Science (CS) in an online learning format, given the context of the COVID-19 pandemic. The laboratory has been used by ( ${n} =30$ ) CS students during the second semester of 2020 in the subject of mathematical logic through the methodology of Problem-Based Learning (PBL). To evaluate preliminary the laboratory, it was used a survey with 3 open-ended questions and 12 closed-ended questions on a Likert scale according to the Technology Acceptance Model (TAM). The outcomes show a good reception of the laboratory, an enhancement of the students’ learning regarding the concepts addressed in the course, and an interest of the students for the laboratory to be included in other subjects of the curricula.

DOI:

http://10.1109/RITA.2022.3166877

How to cite:
J. Á. Ariza and S. G. Gil, "RaspyLab: A Low-Cost Remote Laboratory to Learn Programming and Physical Computing Through Python and Raspberry Pi," in IEEE Revista Iberoamericana de Tecnologias del Aprendizaje, vol. 17, no. 2, pp. 140-149, May 2022.