The Effect of Integrated Problem-Based Learning with Multiple Representations on Elementary School Students' Computational Thinking Skills in Mathematics - Dea Nur Hafifah; Arita Marini; Yurniwati Yurniwati (LJPI UI Bunga Bangsa Cirebon, 2026)
Computational thinking is an essential skill that students need to develop in the learning process to systematically analyze problems and construct effective solutions. Objective: This study modified the Problem-Based Learning (PBL) method integrated with Multiple Representations (MR) in enhancing elementary students’ computational thinking skills, including decomposition, pattern recognition, abstraction, and algorithmic thinking. Novelty: This study provides empirical evidence on the contribution of an innovative instructional approach in fostering students’ computational thinking skills, thereby supporting the achievement of SDG 4 (Quality Education) through improved learning quality at the elementary level. Method: A quantitative approach was employed using a quasi-experimental design with purposive sampling (N = 62), consisting of 31 students in the experimental group and 31 students in the control group. Data were analyzed through prerequisite tests and hypothesis testing to examine the effectiveness of the PBL-MR method in improving students’ computational thinking skills. Results: The results of the t-test revealed a statistically significant difference between the experimental and control groups (p < 0.001), indicating that the implementation of the PBL-MR method significantly enhanced students’ computational thinking skills. Conclusion: The PBL-MR method is more effective in increasing Computational Thinking skills than the traditional method in the control group. These results indicate that the PBL-MR method is effective in improving students’ computational thinking skills as an effort to support the achievement of SDGs 4, by improving the quality of education through meaningful education for elementary school.