Developing Mathematics Olympiads Through Computational Thinking Approach And Problem Pattern Analysis

Abstract

This community service activity aimed to improve students’ competence in Olimpiade Sains Nasional mathematics at the district/city level through intensive coaching and training programs. The activity involved high school students and was conducted using several stages, including pre-test, material delivery, problem-solving exercises, try-out simulations, and post-test evaluation. The learning materials covered algebra, number theory, combinatorics, geometry, and mathematical problem-solving strategies.

The training implemented Problem Based Learning (PBL), computational thinking, and data-driven learning approaches to strengthen students’ analytical and logical reasoning skills. The results showed a significant improvement in students’ performance. The average pre-test score increased from 59.5 to 82.0 in the post-test. Students also demonstrated improved abilities in identifying problem patterns, applying appropriate solution strategies, and solving Higher Order Thinking Skills (HOTS)-based mathematical problems systematically.

In addition, the program increased students’ motivation and confidence in participating in mathematics olympiad competitions. The integration of computational thinking approaches was also relevant to the field of Data Science because it emphasized analytical, logical, and structured problem-solving skills. Overall, the community service program contributed positively to enhancing students’ mathematical competence and readiness for district/city-level olympiad competitions.