Teaching Robotics during COVID-19: Machine Learning, Simulation, and AWS DeepRacer

International Association for the Development of the Information Society. e-mail: secretariat@iadis.org; Web site: http://www.iadisportal.org

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Robotics; COVID-19; Pandemics; Teaching Methods; Secondary School Teachers; Foreign Countries; Computer Science; Electronic Learning; Technology Uses in Education; Virtual Classrooms; Artificial Intelligence; Access to Computers; Disadvantaged

Canada; Turkey

COVID-19 presented a challenge to the traditional methods of teaching programming and robotics in a secondary school environment. When campuses were closed around the world in the spring of 2020, it was not possible for students to access the computer labs nor the robotics equipment that was traditionally used to facilitate the instruction of robotics programming units. This paper presents a design research project in which two secondary institutions in Canada and Turkey collaborated to teach computer science and robotics programming, specifically reinforcement learning, through the use of an online simulation environment. The two student cohorts in the study both were successful in developing reinforcement learning models for autonomous vehicles, despite not having any prior experience in machine learning nor artificial intelligence. The implications of this work are that physical robotics kits and dedicated robotics spaces are not essential to the teaching of programming and robotics. This is especially relevant to marginalized communities that do not have the resources to support robotics instruction, further exacerbating the digital divide.

As Provided

2023

ED626743