ANALYSIS OF STUDENTS' MATHEMATICAL REASONING ABILITY ACHIEVEMENTS USING RESOURCE-BASED LEARNING

Abstract

Mathematical reasoning ability is an important competency that underlies problem solving and drawing logical conclusions in mathematics learning. However, many students still face difficulties in developing this ability, especially if the learning process does not support exploration and active involvement. The Resource-Based Learning (RBL) learning model is proposed as an alternative that can overcome this challenge. This study uses a quantitative descriptive approach to analyze the effectiveness of RBL in improving students' mathematical reasoning ability. A total of 115 students were selected through a saturated sampling method. Data were obtained through the Prior Mathematical Knowledge Test (PAM) and the Inductive Reasoning Test, which grouped students into high, medium, and low groups. The results showed that the Transductive Reasoning indicator had the highest achievement in all categories, with students in the high group recording an average score of 95.69%, the medium group 87.70%, and the low group 82%. In contrast, Analogical Reasoning showed the lowest achievement, with an average score of 30.17% (high achievement), 17.62% (medium), and 9% (low). The Generalization Reasoning and Relational Reasoning indicators recorded relatively high achievements, reflecting students' ability to analyze patterns and draw general conclusions from limited data. RBL has been shown to be effective in improving mathematical reasoning skills by encouraging exploration of learning resources, collaboration between students, and critical discussion. These results confirm that the RBL learning model is able to support the development of students' mathematical reasoning skills at various levels of achievement, with special focus needed on improving lower indicators such as Analogical Reasoning.