Improving Students’ Creative Thinking in Macromolecule Lessons Through AI-Based Ethnochemistry Project-Based Learning

Abstract

Creative thinking is recognized as a vital skill in 21st-century education, especially in chemistry, where abstract and complex concepts often present learning challenges. This research investigates the impact of an Artificial Intelligence (AI)-supported ethnochemistry Project-Based Learning (PjBL) model on students’ understanding of macromolecule content. A quasi-experimental method was applied using a pretest-posttest control group design. The study involved 70 twelfth-grade students from SMA N 2 Sleman, selected through purposive sampling. Participants were divided into two groups: the experimental group experienced the AI-integrated ethnochemistry PjBL model, while the control group followed the standard ethnochemistry-based PjBL approach. Data on students' creative thinking were gathered through essay-based assessments administered before and after the intervention. Findings revealed that the experimental group achieved an average N-Gain of 0.44 (moderate level), outperforming the control group’s 0.32. A t-test analysis indicated a statistically significant difference between the two groups (p = 0.005 < 0.05). These results suggest that integrating AI into an ethnochemistry PjBL model has a notable positive effect on enhancing students' creative thinking skills in learning macromolecules.