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

Authors :
International Association for Development of the Information Society (IADIS)
Holowka, Peter
Source :
International Association for Development of the Information Society. 2020Paper presented at the International Conference on Cognition and Exploratory Learning in Digital Age (CELDA) (17th, 2020).
Publication Year :
2020

Abstract

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.

Details

Language :
English
Database :
ERIC
Journal :
International Association for Development of the Information Society
Publication Type :
Conference
Accession number :
ED626743
Document Type :
Speeches/Meeting Papers<br />Reports - Descriptive