An Analysis of Problem Solving Ability using mathematical modeling strategies in Brain-Based Learning

Abstract

Problem-solving ability learning (PSA) is a fundamental problem that needs to be developed in learning mathematics at school. In this research mathematical modeling strategies (MMS) are developed for problem solving. This study aims to investigate how the implementation of MMS for problem-solving in mathematics learning. This study was conducted at SMP Negeri 34 Semarang. This research used sequential explanatory design. The quantitative research design is a quasi experimental design with the nonequivalent posttest-only control group design. Data collection techniques used in this study are documentation, tests, scale, interview, and observation, then processed with a classical completeness test, t-test, and proportion test. The results of this study indicate that (1) PSA on the application of mathematical modelling strategies on Brain-Based Learning (BBL) has achieved classical mastery learning; (2) the PSA of the experimental class by applying mathematical modeling strategies to Brain-Based Learning is better than the control class that uses the Problem Based Learning; and (3) two subjects with high category self-efficacy (SE) have high PSA, two SE subjects are categorized having middle PSA, and two low SE subjects have a low PSA.