Integrating Machine Learning and Educational Robotics

The Frankie Platform for Teaching Artificial Intelligence in High School

Authors

DOI:

https://doi.org/10.25749/sis.39111

Keywords:

artificial intelligence in education, neural network, educational robotics, technologies in education

Abstract

This study explores an experiment conducted at a tuition-free school in Rio de Janeiro, Brazil, aimed at introducing high school students to Artificial Intelligence (AI) concepts through their mathematical foundations. Eleven students participated in workshops designed to connect mathematics and AI by engaging with a Weightless Neural Network (WNN) algorithm – WiSARD. The scripted activities focused on the mathematical calculations involved in the algorithm's training and classification phases, enhancing students' understanding of machine learning (ML). The results showed that students grasped both the functioning of the WiSARD algorithm and the mathematical principles behind it. Additionally, the activities fostered reflection on ethical concerns related to AI, emphasizing developer responsibility and the importance of protecting personal data.

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Author Biographies

Charles Soares Pimentel, Programa de Pós-Graduação em Informática, Universidade Federal do Rio de Janeiro / Graded-American School of Rio de Janeiro, Brazil

Design and technology educator at Graded – The American School of São Paulo and a D.Sc. candidate at the Federal University of Rio de Janeiro. He is also a research fellow at the Transformative Learning Technologies Lab (TLTL), where he investigates the use of sensors and microcontrollers in schools through IoT applications to support data literacy. His work explores how technology can be a tool for social impact and student empowerment in K–12 education.

Fábio Ferrentini Sampaio, Escola Superior de Tecnologia, Instituto Politécnico de Setúbal, Portugal

Adjunct Professor at Polytechnic University of Setúbal – Portugal. He holds a degree in Computer Science, a Master's degree in Systems and Computer Engineering, and a Ph.D. from the University of London in the area of Science and Computer Science Education. In Brazil, he coordinated several projects in the area of Technologies in Education funded by agencies from the State of Rio de Janeiro and the Federal Government. He has published in specialized journals and books in the areas of Computer Science and Technologies, in partnership with different authors.

References

Aleksander, I., De Gregorio, M., França, F. M. G., Lima, P. M. V., & Morton, H. (2009). A brief introduction to Weightless Neural Systems. In ESANN'2009 proceedings, European Symposium on Artificial Neural Networks - Advances in Computational Intelligence and Learning. 22–24 April, Bruges, Belgium.

Altin, H., & Pedaste, M. (2013). Learning approaches to applying robotics in science education. Journal of Baltic Science Education, 12(3), 365-377. https://dx.doi.org/10.33225/jbse/13.12.365

Bellas, F., & Sousa, A. (2023). Computational intelligence advances in educational robotics. Frontiers in Robotics and AI, 10. https://doi.org/10.3389/frobt.2023.1150409

Bogdan, R. C., & Biklen, S. K. (2006). Qualitative research for education: An introduction to theory and methods. (5th Edition). Allyn and Bacon.

Carneiro, H. C. C., França, F. M. G., & Lima, P. M. V. (2010). WANN-TAGGER: A Weightless Artificial Neural Network Tagger for the Portuguese Language. 2nd International Joint Conference on Computational Intelligence. Lisboa, Portugal.

Castro, E., Cecchi, F., Valente, M., Buselli, E., Salvini, P., & Dario, P. (2018). Can educational robotics introduce young children to robotics and how can we measure it? Journal of Computer Assisted Learning, 34(6), 970-977. https://doi.org/10.1111/jcal.12304

Cohen, L., Manion, L., & Morrison, K. (2018). Research methods in education. (8th Edition). Routledge.

Denzin, N. K., & Lincoln, Y. S. (2011). The Sage handbook of qualitative research. (4th Edition). SAGE Publications.

Eguchi, A. (2022). Understanding Machine Learning Through AI-powered Educational Robotics - Pilot Study with Undergraduate Students. In W. Lepuschitz, M. Merdan, G. Koppensteiner, R. Balogh & D. Obdržálek (Eds.), Robotics in Education. RiE 2022. Lecture Notes in Networks and Systems (vol. 515). Springer. https://doi.org/10.1007/978-3-031-12848-6_5

Eguchi, A. (2023). Revisiting the Pedagogy of Educational Robotics. In R. Balogh, D. Obdržálek & E. Christoforou (Eds.), Robotics in Education. RiE 2023. Lecture Notes in Networks and Systems (vol. 747). Springer. https://doi.org/10.1007/978-3-031-38454-7_8

Fischer, E., & Guzel, G. T. (2022). The case for qualitative research. Journal of Consumer Psychology, 33(1), 259-272. https://doi.org/10.1002/jcpy.1300

Grubišić, V., & Crnokić, B. (2024). A Systematic Review of Robotics’ Transformative Role in Education. In T. Volarić, B. Crnokić & D. Vasić (Eds.), Digital Transformation in Education and Artificial Intelligence Application. Communications in Computer and Information Science (pp. 257-272). Springer.

Jamieson, S. (2004). Likert Scales: How to (Ab)use Them. Medical Education, 38(12), 1217-1218. https://doi.org/10.1111/j.1365-2929.2004.02012.x

Johnson, S. D. (1995). Will our research hold up under scrutiny? Journal of Industrial Teacher Education, 32(3), 3-6.

Kozulin, A. (2002). Sociocultural Theory and the Mediated Learning Experience. School Psychology International, 23(1), 7-35. https://doi.org/10.1177/0143034302023001729

Lima Filho, A. S., Guarisa, G. P., Lusquino Filho, L. A. D., Oliveira, L. F. R., Franca, F. M., & Lima, P. M. V. (2020). Wisardpkg--A library for WiSARD-based models. arXiv: 2005.00887. https://doi.org/10.48550/arXiv.2005.00887

Lofland, J., & Lofland, L. H. (1984). Analyzing social settings. Wadsworth Publishing Company.

Memarian, B., & Doleck, T. (2024). Teaching and learning artificial intelligence: Insights from the literature. Education and Information Technolology, 29, 21523-21546. https://doi.org/10.1007/s10639-024-12679-y

Mubin, O., Stevens, C. J., Shahid, S., Al Mahmud, A., & Dong, J. J. (2013). A review of the applicability of robots in education. Technology for Education and Learning, 1(1), 1-7.

Negrini, L., Giang, C., Bonaiuti, G., Cascalho, J. M., Primo, T. T., & Eteokleous, N. (2023). Editorial: Educational robotics as a tool to foster 21st century skills. Frontiers in Education, 8. https://doi.org/10.3389/feduc.2023.1186029

Ng, D. T. K., Su, J., & Chu, S. K. W. (2024). Fostering Secondary School Students’ AI Literacy through Making AI-Driven Recycling Bins. Education and Information Technology, 29, 9715-9746. https://doi.org/10.1007/s10639-023-12183-9

Nurmaini, S., Mohd, H. S., & Jawawi, D. (2009). Modular Weightless Neural Network Architecture for Intelligent Navigation. International Journal of Advances in Soft Computing and Its Applications, 1(1), 1-18. https://www.i-csrs.org/Volumes/ijasca/vol.1/vol.1.1.1.july.09.pdf

Patton, M. Q. (2001). Qualitative Evaluation and Research Methods. (3rd Edition). Sage Publications.

Phokoye, S.P., Epizitone, A., Nkomo, N., Mthalane, P. P., Moyane, S. P., Khumalo, M. M., Luthuli, M., & Zondi, N. P. (2024). Exploring the Adoption of Robotics in Teaching and Learning in Higher Education Institutions. Informatics, 11(4), 91. https://doi.org/10.3390/informatics11040091

Queiroz, R. L., Sampaio, F. F., Lima, C., & Lima, P. M. V. (2021). AI from Concrete to Abstract: Demystifying Artificial Intelligence to the General Public. AI & Society, 36(3), 877-893. https://doi.org/10.1007/s00146-021-01151-x

Su, J., & Yang, W. (2022). Artificial intelligence in early childhood education: A scoping review. Computers and Education: Artificial Intelligence, 3. https://doi.org/10.1016/j.caeai.2022.100049

UNESCO (2014). Global citizenship education: preparing learners for the challenges of the 21st century. https://unesdoc.unesco.org/ark:/48223/pf0000227729

UNESCO (n.d.). UNESCO and Sustainable Development Goals. https://www.unesco.org/en/sdgs

Versuti, F. M., Amiel, T., & Pontual, T. (2019). Orientações para Relato de Pesquisa Qualitativa envolvendo Tecnologias Educacionais. https://cieb.net.br/wp-content/uploads/2019/11/Protocolo-Qualitativo.pdf

Vygotsky, L. S. (2007). A Formação Social da Mente. (7a Edição). Martins Fontes.

Wang, H., Luo, N., Zhou, T., & Yang, S. (2024). Physical Robots in Education: A Systematic Review Based on the Technological Pedagogical Content Knowledge Framework. Sustainability, 16(12), 4987. https://doi.org/10.3390/su16124987

Yang, J. (2023). Real Time Object Tracking Using OpenCV. In 2023 IEEE 3rd International Conference on Data Science and Computer Application (ICDSCA) (pp. 1472-1475). Dalian, China. https://doi.org/10.1109/ICDSCA59871.2023.10392831

Yim, I. H. Y., & Su, J. (2024). Artificial intelligence (AI) learning tools in K-12 education: A scoping review. Journal of Computers in Education, 12, 93-131. https://doi.org/10.1007/s40692-023-00304-9

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Published

2025-06-30