Tutor Inteligente: Machine Learning Applied to the Mathematics Teaching and Learning Process in Primary Schools

• Paulo Ricardo Mesquita Rosa Santos UVA http://orcid.org/0009-0002-6003-5371
• Vinícius Marques da Silva Ferreira FioCruz https://orcid.org/0000-0003-3664-3510
• Luiz Anastácio Alves FioCruz https://orcid.org/0000-0002-0785-7272
• Alfredo Nazareno Pereira Boente UFRJ https://orcid.org/0000-0002-2718-4917
• João Jorge Sarto Neto UNIG https://orcid.org/0009-0004-1938-7003
• Jean Marcos Rebello Marinho UVA https://orcid.org/0009-0005-8154-9023

DOI: https://doi.org/10.5753/latinoware.2024.245781

Abstract

This article presents the development of Tutor Inteligente, a system based on machine learning, created to personalize the teaching-learning process of mathematics in basic education. The methodology adopted involves machine learning techniques for analyzing and adapting content to students' individual needs. The development of the system follows an incremental approach with agile methodologies (SCRUM), including continuous testing (TDD) and integration with real-time assessment tools. Partial results show that the Intelligent Tutor provides immediate feedback and adaptive support, promoting a more effective and interactive learning experience for students with specific difficulties in mathematics. The conclusion points to the system as a complementary tool to teaching, capable of enriching the educational process and increasing knowledge retention.

Keywords: Machine Learning, Intelligent Tutoring, Adaptive Education, Mathematics in Basic Education, Education 4.0

References

J. R. Anderson, A. T. Corbett, K. R. Koedinger, and R. Pelletier, “Cognitive tutors: Lessons learned,” The journal of the learning sciences, vol. 4, no. 2, pp. 167–207, 1995.

K. R. Koedinger, J. R. Anderson, W. H. Hadley, and M. A. Mark, “Intelligent tutoring goes to school in the big city,” International Journal of Artificial Intelligence in Education, vol. 8, pp. 30–43, 1997.

F. G. Cozman, G. A. Plonski, and H. Neri, Inteligência artificial: avanços e tendências. Instituto de Estudos Avançados, 2021, [livro eletrônico]. [Online]. Available: [link]

C. A. Silva, “O impacto das tecnologias digitais no engajamento dos estudantes,” Revista de Tecnologia Educacional, vol. 29, no. 4, pp. 56–67, 2017.

K. VanLehn, “The relative effectiveness of human tutoring, intelligent tutoring systems, and other tutoring systems,” Educational psychologist, vol. 46, no. 4, pp. 197–221, 2011.

J. A. Valente, “A utilização de ferramentas digitais no ensino da matemática,” Revista de Educação e Matemática, vol. 45, no. 3, pp. 123–135, 2020.

B. P. Woolf, Building intelligent interactive tutors: Student-centered strategies for revolutionizing e-learning. Morgan Kaufmann, 2010.