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The purpose of this study is to assess the computational thinking skills of fourth-grade elementary students within the framework of mathematics instruction. Computational thinking is a crucial 21st-century competency that should be cultivated from an early age, particularly in solving mathematical problems. This study adopts a descriptive quantitative method using a written test instrument developed based on four key computational thinking components: decomposition, pattern recognition, abstraction, and algorithmic processes. The participants in this research were fourth-grade students from a selected elementary school. The results indicate that most students demonstrate a moderate level of computational thinking. Among the assessed indicators, decomposition was the most successfully achieved, while algorithmic thinking was the least mastered. These results highlight the importance of integrating contextual and problem-based learning strategies to further enhance students’ computational thinking abilities in mathematics education.

The 21st century is marked by the advancement of science and technology, driving increasingly complex changes in life. In the context of education, a multidisciplinary learning approach has become relevant in enhancing students' complex thinking abilities. This approach allows students to integrate various disciplines in solving existing problems, thereby improving their critical, analytical, and creative thinking skills. This study explores the relationship between multidisciplinary learning and students' complex thinking abilities, the factors influencing its implementation effectiveness, and effective multidisciplinary learning strategies. Based on previous research, multidisciplinary learning has been proven to enhance complex thinking skills by up to 35% compared to conventional learning methods. However, its implementation faces several challenges, including a lack of teacher readiness, limited resources, and a learning culture that still emphasizes rote memorization. Therefore, problem-based learning strategies, cross-disciplinary collaboration, and the use of technology are recommended to improve the effectiveness of this approach.