Implementing a digital twin for a robotic platform to support large-scale coding classes

Conference paper

Heeney, M., Androutsopoulos, K. and Raimondi, F. 2024. Implementing a digital twin for a robotic platform to support large-scale coding classes. Santos, A.L. and Pinto-Albuquerque, M. (ed.) 5th International Computer Programming Education Conference. Lisbon, Portugal 27 - 28 Jun 2024 Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH. https://doi.org/10.4230/oasics.icpec.2024.15
TypeConference paper
TitleImplementing a digital twin for a robotic platform to support large-scale coding classes
AuthorsHeeney, M., Androutsopoulos, K. and Raimondi, F.
Abstract

Constructionist learning involves learners that are actively engaged in the construction of an entity that reflects the learning achievements. When learning to code, such a physical entity can take the shape of a robot, or of a robotic arm, or any other hardware device that is used to manifest the effect of the code that students are writing. Hardware devices have been used in primary and secondary schools, and also in Higher Education. Unfortunately, the use of hardware devices is limited as it does not scale to large cohorts and requires a physical space for face-to-face teaching.
In this paper we introduce a digital twin for a robotic platform to replicate a classroom setting used for teaching first year undergraduate Computer Science students. We describe the architecture of the system and its implementation.

Sustainable Development Goals4 Quality education
Middlesex University ThemeCreativity, Culture & Enterprise
Conference5th International Computer Programming Education Conference
Proceedings TitleOpenAccess Series in Informatics
EditorsSantos, A.L. and Pinto-Albuquerque, M.
ISSN2190-6807
ISBN9783959773478
PublisherSchloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH
Publication dates
Online25 Sep 2024
Print25 Sep 2024
Publication process dates
Accepted2024
Deposited25 Apr 2025
Output statusPublished
Publisher's version
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Open
Copyright Statement

© Michael Heeney, Kelly Androutsopoulos, and Franco Raimondi; licensed under Creative Commons License CC-BY 4.0.

Digital Object Identifier (DOI)https://doi.org/10.4230/oasics.icpec.2024.15
Scopus EID2-s2.0-85205705455
Web address (URL) of conference proceedingshttps://drops.dagstuhl.de/entities/volume/OASIcs-volume-122
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