ALGORITHMIC THINKING IN MATHEMATICS: A PEDAGOGICAL FRAMEWORK FOR DEEP CONCEPTUAL LEARNING

Abstract

This article explores the role of algorithmic thinking as a pedagogical strategy for fostering deep conceptual understanding in mathematics education at the primary level. In the context of Uzbekistan’s evolving curriculum reforms and increasing emphasis on 21st-century skills, algorithmic thinking offers a structured approach to problem-solving that extends beyond procedural fluency. By promoting stepwise reasoning, pattern recognition, and abstraction, algorithmic thinking helps learners internalize mathematical relationships and logic. The article proposes a pedagogical framework for integrating algorithmic thinking into the teaching of mathematics, supported by cognitive learning theories and international educational models. Through qualitative analysis of classroom practices and teacher interviews in selected primary schools, the study examines how algorithmic thinking contributes to students’ conceptual clarity and long-term retention. The findings suggest that embedding algorithmic reasoning into early mathematical instruction enhances analytical skills, reduces misconceptions, and prepares learners for higher-level mathematical reasoning. The study also addresses challenges in implementation, including teacher preparedness and curriculum alignment, offering practical recommendations for teacher education and instructional design.