The Visual Programming Environment ROBI for Educational Robotics

Authors Gustavo Galvão, Alvaro Costa Neto , Cristiana Araújo , Pedro Rangel Henriques



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Gustavo Galvão
  • Centro ALGORITMI, Departamento de Informática, Universidade do Minho, Braga, Portugal
Alvaro Costa Neto
  • Instituto Federal de Educação, Ciência e Tecnologia de São Paulo, Barretos, Brazil
Cristiana Araújo
  • Centro ALGORITMI, Departamento de Informática, Universidade do Minho, Braga, Portugal
Pedro Rangel Henriques
  • Centro ALGORITMI, Departamento de Informática, Universidade do Minho, Braga, Portugal

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Gustavo Galvão, Alvaro Costa Neto, Cristiana Araújo, and Pedro Rangel Henriques. The Visual Programming Environment ROBI for Educational Robotics. In 11th Symposium on Languages, Applications and Technologies (SLATE 2022). Open Access Series in Informatics (OASIcs), Volume 104, pp. 14:1-14:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
https://doi.org/10.4230/OASIcs.SLATE.2022.14

Abstract

This paper presents the outcomes of a research project focused on the training of Computational Thinking, resorting to a block-based visual programming language created to program an Arduino Uno based robot. To support the design and implementation of the visual programming environment Robi, we start discussing the relevance of Educational Robotics to motivate and engage children in programming activities. Students usually face great difficulties to learn computer programming and it is nowadays accepted that young people shall be trained in Computational Thinking to acquire the skills necessary to easily solve problems within and beyond the realm of Computer Science and Engineering. The resolution of obstacles imposed by the costs and reduced availability of typical Educational Robotics kits, in combination with the benefits of existing block-based programming languages, like simplicity and intuitiveness, motivated the project here reported and analyzed. We aim at showing that Robi, a visual block-based programming language and robot programming environment, provides an easy, accessible and intuitive platform to learn how to solve problems programming a computer and support the training of Computational Thinking.

Subject Classification

ACM Subject Classification
  • Software and its engineering → Compilers
  • Social and professional topics → Computing education
Keywords
  • Programming Languages
  • Visual Languages
  • Computer Programming
  • Educational Robotics

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References

  1. Cristiana Araújo, Lázaro Lima, and Pedro Rangel Henriques. An Ontology based approach to teach Computational Thinking. In Célio Gonçalo Marques, Isabel Pereira, and Diana Pérez, editors, 21st International Symposium on Computers in Education (SIIE), pages 1-6. IEEE Xplore, November 2019. URL: https://doi.org/10.1109/SIIE48397.2019.8970131.
  2. Soumela Atmatzidou and Stavros Demetriadis. Advancing students’ computational thinking skills through educational robotics: A study on age and gender relevant differences. Robotics and Autonomous Systems, 75:661-670, 2016. URL: https://doi.org/10.1016/j.robot.2015.10.008.
  3. Nicholas Alexander Bascou and Muhsin Menekse. Robotics in k-12 formal and informal learning environments: A review of literature. In 2016 ASEE Annual Conference & Exposition, New Orleans, Louisiana, June 2016. ASEE Conferences. https://peer.asee.org/26119. URL: https://doi.org/10.18260/p.26119.
  4. Fabiane Barreto Vavassori Benitti. Exploring the educational potential of robotics in schools: A systematic review. Computers & Education, 58(3):978-988, 2012. URL: https://doi.org/10.1016/j.compedu.2011.10.006.
  5. Christina Chalmers. Robotics and computational thinking in primary school. International Journal of Child-Computer Interaction, 17:93-100, 2018. Google Scholar
  6. Guanhua Chen, Ji Shen, Lauren Barth-Cohen, Shiyan Jiang, Xiaoting Huang, and Moataz Eltoukhy. Assessing elementary students’ computational thinking in everyday reasoning and robotics programming. Computers & Education, 109:162-175, 2017. URL: https://doi.org/10.1016/j.compedu.2017.03.001.
  7. Morgane Chevalier, Christian Giang, Alberto Piatti, and Francesco Mondada. Fostering computational thinking through educational robotics: a model for creative computational problem solving. International Journal of STEM Education, 7, August 2020. URL: https://doi.org/10.1186/s40594-020-00238-z.
  8. Tomáš Effenberger and Radek Pelánek. Towards making block-based programming activities adaptive. In Proceedings of the Fifth Annual ACM Conference on Learning at Scale, pages 1-4, 2018. Google Scholar
  9. Francesc Esteve, Jordi Adell, Mª Ángeles Llopis, Gracia Valdeolivas, and Julio Pacheco. The development of computational thinking in student teachers through an intervention with educational robotics. Journal of Information Technology Education: Innovations in Practice, 18:139-152, October 2019. URL: https://doi.org/10.28945/4442.
  10. International Society for Technology in Education (ISTE) & Computer Science Teachers Association (CSTA). Operational definition of computational thinking for K-12 education. http://www.iste.org/docs/ct-documents/computational-thinking-operational-definition-flyer.pdf, 2011. Accessed: 2021-12-16.
  11. P. Freire. Pedagogia da Autonomia: Saberes necessários à prática educativa. Paz e Terra, 2011. Google Scholar
  12. Anaclara Gerosa, Víctor Koleszar, Leonel Gómez-Sena, Gonzalo Tejera, and Alejandra Carboni. Educational robotics and computational thinking development in preschool. In 2019 XIV Latin American Conference on Learning Technologies (LACLO), pages 226-230, 2019. URL: https://doi.org/10.1109/LACLO49268.2019.00046.
  13. Carina Soledad González-González. State of the art in the teaching of computational thinking and programming in childhood education. Education in the Knowledge Society, 20:1-15, 2019. Google Scholar
  14. Shuchi Grover and Satabdi Basu. Measuring student learning in introductory block-based programming: Examining misconceptions of loops, variables, and boolean logic. In Proceedings of the 2017 ACM SIGCSE technical symposium on computer science education, pages 267-272, 2017. Google Scholar
  15. Shuchi Grover, Satabdi Basu, Marie Bienkowski, Michael Eagle, Nicholas Diana, and John Stamper. A framework for using hypothesis-driven approaches to support data-driven learning analytics in measuring computational thinking in block-based programming environments. ACM Transactions on Computing Education (TOCE), 17(3):1-25, 2017. Google Scholar
  16. Ting-Chia Hsu, Shao-Chen Chang, and Yu-Ting Hung. How to learn and how to teach computational thinking: Suggestions based on a review of the literature. Computers & Education, 126:296-310, 2018. Google Scholar
  17. Luiz A Junior, Osvaldo T Neto, Marli F Hernandez, Paulo S Martins, Leonardo L Roger, and Fatima A Guerra. A low-cost and simple arduino-based educational robotics kit. Cyber Journals: Multidisciplinary Journals in Science and Technology, Journal of Selected Areas in Robotics and Control (JSRC), December edition, 3(12):1-7, 2013. Google Scholar
  18. Eija Karna-Lin, Kaisa Pihlainen-Bednarik, Erkki Sutinen, and Marjo Virnes. Can robots teach? preliminary results on educational robotics in special education. In Sixth IEEE International Conference on Advanced Learning Technologies (ICALT'06), pages 319-321. IEEE, 2006. Google Scholar
  19. Leo Louis. working principle of arduino and u sing it. International Journal of Control, Automation, Communication and Systems (IJCACS), 1(2):21-29, 2016. Google Scholar
  20. J. Piaget, M. Piercy, and D.E. Berlyne. The Psychology of Intelligence. Routledge classics. Routledge, 2001. Google Scholar
  21. MERT Arduino & Tech. How to make Arduino Obstacle Avoiding Robot Car | Under $20. https://www.youtube.com/watch?v=4CFO0MiSlM8&ab_channel=MERTArduino%26Tech, 2018. Accessed: 2021-12-16.
  22. Salete Teixeira, Diana Barbosa, Cristiana Araújo, and Pedro Rangel Henriques. Improving Game-Based Learning Experience Through Game Appropriation. In Ricardo Queirós, Filipe Portela, Mário Pinto, and Alberto Simões, editors, First International Computer Programming Education Conference (ICPEC 2020), volume 81 of OpenAccess Series in Informatics (OASIcs), pages 27:1-27:10, Dagstuhl, Germany, 2020. Schloss Dagstuhl-Leibniz-Zentrum für Informatik. URL: https://doi.org/10.4230/OASIcs.ICPEC.2020.27.
  23. L.S. Vygotsky, E. Hanfmann, G. Vakar, and A. Kozulin. Thought and Language. The MIT Press. MIT Press, 2012. Google Scholar
  24. David Weintrop and Uri Wilensky. Comparing block-based and text-based programming in high school computer science classrooms. ACM Transactions on Computing Education (TOCE), 18(1):1-25, 2017. Google Scholar
  25. Jeannette M. Wing. Computational thinking. Commun. ACM, 49(3):33-35, March 2006. URL: https://doi.org/10.1145/1118178.1118215.
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