Development of RBL-STEM Materials to Improve Students' Combinatorial Thinking Skills to solve Rainbow Antimagic Coloring Problems and Its Application Scheme on Air Quality Monitoring System with GNN

RBL-STEM is a learning model that combines the Research-Based Learning model and the STEM approach. The RBL model is a student-centered learning model, in RBL students will find a problem that requires a solution. RBL-STEM will require students to solve problems in life with integrated aspects of science, technology, engineering and mathematics. In many research studies, RBL-STEM has been proven to improve students' mathematical thinking skills. This research develops an RBL-STEM learning tool on rainbow antimagic coloring material and its application scheme on air quality monitoring system with graph neural network and sees the effect of the developed tool on students' combinatorial thinking skills. The development of RBL-STEM learning tools to improve students' combinatorial thinking skills in this study meets the criteria of valid, practical and effective. The validity value obtained is 3.87. The observation results of learning implementation amounted to 3.89 with a percentage of 97.33%, and student responses were 97.50% positive so that they met the practical criteria. Based on the results of the posttests, 95% of students were declared complete so that they met the effective criteria. Quantitative analysis in this study was obtained from analyzing pretest and posttest data, where normality test and paired sample t-test were conducted. Based on the normality test, it can be concluded that the pretest and posttest scores are normally distributed, because the significance value is greater than 0.05, namely 0.121 and 0.090. Furthermore, the paired sample t-test test was carried out which showed a sig value. (2-tailed) of 0.000. This result shows that there is a significant increase in the combinatorial thinking ability of students after participating in RBL-STEM learning.