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Title:
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TEACHING ROBOTICS DURING COVID-19: MACHINE
LEARNING, SIMULATION, AND AWS DEEPRACER |
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Author(s):
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Peter Holowka |
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ISBN:
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978-989-8704-22-1 |
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Editors:
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Demetrios G. Sampson, Dirk Ifenthaler and Pedro Isaías |
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Year:
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2020 |
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Edition:
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Single |
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Keywords:
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Machine Learning, Artificial Intelligence, AWS DeepRacer, COVID-19, Simulation, Education |
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Type:
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Full |
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First Page:
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227 |
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Last Page:
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234 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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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. |
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