STUDYING THE TOPIC OF RESEARCHING SELECTION METHODS USING SWOT ANALYSIS

Abstract

Abstract. This article focuses on the development and implementation of an effective teaching process for the topic “Researching Sorting Methods” within the course “Data Structures and Algorithms” by utilizing the SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis approach. The study emphasizes the importance of integrating modern pedagogical methods into computer science education to improve students’ understanding of sorting algorithms and their practical applications. Through SWOT analysis, students are encouraged to evaluate various sorting methods, including their advantages, limitations, potential improvements, and challenges encountered in real-world computational tasks. The proposed instructional approach promotes analytical thinking, problem-solving skills, and active participation in the learning process. In addition, it helps learners compare different sorting algorithms based on efficiency, complexity, memory usage, and implementation characteristics. The research demonstrates that the use of SWOT analysis enhances students’ comprehension of algorithmic concepts and supports the development of computational thinking skills. The findings suggest that incorporating SWOT-based activities into the teaching of sorting methods can increase learning effectiveness, strengthen critical evaluation abilities, and contribute to higher educational outcomes in computer science and software engineering programs.