DEVELOPING ALGORITHMIC THINKING THROUGH PROBLEM-BASED LEARNING IN MATHEMATICS EDUCATION

Abstract

This article examines the development of algorithmic thinking in students through the application of problem-based learning in mathematics education. Algorithmic thinking is regarded as an essential cognitive skill that enables learners to analyze problems systematically, construct solution strategies, and apply logical reasoning in sequential steps. The study emphasizes that traditional formula-based instruction is often insufficient for developing deep analytical abilities. Therefore, the proposed methodology integrates problem-solving activities with algorithmic modeling to enhance students’ independent thinking and decision-making skills. The article discusses theoretical foundations of algorithmic thinking, describes algorithmic models used in mathematical problem solving, outlines a methodological framework based on structured learning stages, and highlights practical classroom applications. The advantages, challenges, and educational opportunities of this approach are analyzed, and its contribution to modern mathematics education is justified.