Integrating Generative AI into Chemistry Education: A ChatGPT-Assisted PJBL-STEM Framework for Improving Scientific Literacy on Reaction Rate

Low scientific literacy among students poses a challenge in 21st-century learning, necessitating the development of relevant and innovative instructional models. This study aims to analyze the effectiveness of a ChatGPT-assisted science, technology, engineering, and mathematics-integrated (STEM-integrated) project-based learning (PjBL) model in improving scientific literacy regarding reaction rate. The study employed a quasi-experimental design of the nonequivalent control group type, with the experimental class implementing ChatGPT-assisted PjBL-STEM and the control class using PjBL-STEM. Data were collected through scientific literacy tests and student response questionnaires, then analyzed using the N-gain test and the independent t-test. The results showed that the implementation of ChatGPT-assisted PjBL-STEM effectively improved students’ scientific literacy, with a higher increase compared to the control class, and yielded student responses in the “very good” category. These findings indicate that the integration of ChatGPT has the potential to serve as an innovative learning alternative to enhance students’ scientific literacy