Abstract
This paper proposes a learning framework for Educational Robotics named sBotics, which includes a complete environment for teaching and programming skills acquisition designed for both teachers and K-12 students. Our framework has been developed using a gamified approach with the system and simulated environment developed in the Unity game engine. The main novelty of this platform is its ease-of-use combined with the flexibility to create a variety of scenarios with endless learning potential, in contrast to our evaluations where no alternatives with such characteristics were found for the K-12 range that we are targeting. Also as a contribution of our proposal, robot programs are treated as games that are affected by a disturbance model, which acts in the robotic system and environment variables. This model is introduced in order to approximate what happens in a real robot programming platform. Besides, it is possible for the user, throughout its use, to code in three levels of abstraction: its overly intuitive native programming language called R-Educ, BlockEduc (R-Educ version of Blockly), and C#. Programs can be compiled and interpreted by virtual robots executing any given command. As for teachers, the framework API offers tools that can be employed in the assembly and customization of the learning setup. The whole platform has been built as a tool dedicated to spreading the worlds of Robotics and Programming among youngsters, as well as making them more affordable to everyone. It has been validated by our experiments and is currently being used during the novel Coronavirus pandemic by the official RoboCupJunior Rescue trials in Brazil, currently with more than a thousand competing teams (about 5 thousands students).
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Data Availability
No data was produced for (or from) this study. Nevertheless, the sBotics is available at https://weduc.natalnet.br/sbotics/ and the W-Educ interface is at https://weduc.docs.apiary.io/.
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Acknowledgements
We would like to thank CAPES under grant 001 and CNPq under grants 311640/2018-4, 154225/2020-7, and 153991/2020-8. Also, thanks to Natalnet Associate Labs (www.natalnet.br) of UFRN for using their web facilities.
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This work is partially supported by CAPES Brazil under grant 001, and by CNPq Brazil under grants 311640/2018-4, 154225/2020-7, and 153991/2020-8.
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All authors have made substantial contributions to the conception or design of the work; the acquisition, analysis, or interpretation of data; the creation of new software used in the work; drafted the work or revised it critically for important intellectual content; and approved the version to be published, as described next. Conceptualization: Lucas Moura do Nascimento, Francinaldo Pereira Almeida, Luiz Marcos Garcia Gonçalves, Sarah Thomaz de Lima Sá; Methodology: Lucas Moura do Nascimento, Francinaldo Pereira Almeida, Erika Akemi Yanaguibashi Albuquerque, Luiz Marcos Garcia Gonçalves, Sarah Thomaz de Lima Sá; Formal analysis and investigation: Lucas Moura do Nascimento, Davi Souto Neri, Thiago do Nascimento Ferreira, Francinaldo Pereira Almeida, Erika Akemi Yanaguibashi Albuquerque, Sarah Thomaz de Lima Sá; Writing - original draft preparation: Lucas Moura do Nascimento, Davi Souto Neri, Thiago do Nascimento Ferreira, Francinaldo Pereira Almeida, Erika Akemi Yanaguibashi Albuquerque; Writing - review and editing: Francinaldo Pereira Almeida, Erika Akemi Yanaguibashi Albuquerque, Luiz Marcos Garcia Gonçalves, Sarah Thomaz de Lima Sá; Funding acquisition: Luiz Marcos Garcia Gonçalves, Sarah Thomaz de Lima Sá; Resources: Luiz Marcos Garcia Gonçalves, Sarah Thomaz de Lima Sá; Supervision: Luiz Marcos Garcia Gonçalves, Sarah Thomaz de Lima Sá. In addition, all authors agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.
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This work is supported by CAPES under grant 001, and by CNPq under grants 311640/2018-4, 154225/2020-7 and 153991/2020-8.
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Nascimento, L.M.d., Neri, D.S., Ferreira, T.d.N. et al. sBotics - Gamified Framework for Educational Robotics. J Intell Robot Syst 102, 17 (2021). https://doi.org/10.1007/s10846-021-01364-8
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DOI: https://doi.org/10.1007/s10846-021-01364-8