Can STEM Learning Supported by Dynamic Mathematics Software (DMS) Enhance Students’ Complex Problem Solving in Climate Change? - Lillian Dhian Nafiatul Azhar; Megita Dwi Pamungkas; Dita Aldila Krisma (Riemann: Research of Mathematics and Mathematics Education, 2026)
The development of students’ Complex Problem Solving (CPS) skills remains constrained by mathematics instruction that is primarily procedural and insufficiently connected to real-world global issues, particularly climate change. To address this limitation, the present study investigates whether STEM learning supported by Dynamic Mathematics Software (DMS) can improve senior high school students’ CPS abilities within climate change contexts. A quasi-experimental, non-equivalent pretest–posttest control group design was implemented with 69 eleventh-grade students. The experimental group participated in STEM learning integrated with DMS, while the control group received direct instruction on the same climate change context. Data were analyzed using descriptive statistics, Wilcoxon signed-rank tests, paired-sample t-tests, N-Gain, and Cohen’s D. Results showed that the experimental group achieved a high N-gain score (0.79), whereas the control group attained a low gain (0.29). The magnitude of this increase is also reflected in the effect size Cohen's d values, 5.893 in the experimental class and 2.438 in the control class. These findings suggest that STEM learning supported by Dynamic Mathematics Software constitutes an effective pedagogical strategy for advancing students’ complex problem-solving skills and strengthening mathematics education