O pensamento computacional no ensino de matemática: contribuições para os anos finais do ensino básico

Abstract

Computational Thinking (CT) encompasses a set of essential skills for problem-solving across various fields of knowledge, combining logical and mathematical reasoning with strategies for organizing and structuring steps in an intelligent and systematic way. These competencies are fundamental not only for computing professionals but for anyone dealing with complex challenges. As such, strategies to integrate CT into basic education have been widely explored in recent years. Studies indicate that its application, especially in conjunction with subjects like Mathematics from the early school years, can significantly enhance students’ problem-solving abilities and promote the development of mathematical, systematic, and algorithmic thinking. The methodology of Computational Thinking is structured around four main pillars: decomposition, abstraction, pattern recognition, and algorithms. Applying these methodological elements to Mathematics aims not only to improve student performance but also to stimulate more efficient and creative problem-solving approaches. However, despite notable progress, there is still a lack of evidence directly linking CT concepts to the mathematical competencies defined by Brazil’s National Common Curricular Base (BNCC). This study aims to propose didactic strategies to address mathematical problems through a mapping between the Fundamental Mathematical Capabilities and the Core Concepts of Computational Thinking. To this end, a set of math problems was developed that integrates both domains, with the objective of disseminating and validating the proposed strategies. Preliminary investigations suggest that Computational Thinking can be seamlessly integrated into Math teaching, with many of its concepts—especially Data Analysis, Abstraction, Problem Decomposition, and Algorithms and Procedures—showing strong correlations with the fundamental competencies of Mathematics.