Khoirun Nisa, Tsai Jen-Che, Alif Syaiful Adam, Suliyanah
In a physics classroom, it is important to foster students' physics understanding and improve their problem-solving skills to achieve SDGs 4. This study aims to promote students' problem-solving in solving the renewable energy crisis through project activities. A quasi-experimental design was conducted with 60 Indonesian science-major students. Both groups completed pre-, mid-, and post-test assessing four indicators of problem-solving indicators. Results indicate that students in the AI-PBL class outperformed the control class in problem identification, implementation, and evaluation. In contrast, the control class achieved slightly higher scores in planning, suggesting that structured guidance remains important for organizing project tasks. No significant gender differences were observed, indicating equal benefits for male and female students. These findings highlight the complementary potential of AI tools in project-based learning: AI supports analytical and evaluative processes, while teacher scaffolding ensures effective planning and organization. By fostering problem-solving competence, critical thinking, and engagement with real-world environmental challenges, AI-PBL contributes to Sustainable Development Goal 4 by promoting inclusive and quality education. Future research should explore long-term effects and strategies for balancing autonomy, guidance, and ethical use of AI in educational contexts. © 2026 The Authors, published by EDP Sciences.
Department of Education and Human Potentials Development, National Dong Hwa University, Hualien, 9074301, Taiwan; Graduate Institute of Digital Learning and Education, National Taiwan University of Science and Technology, Taipei, 91944, Taiwan; Department of Physics, Universitas Negeri Surabaya, Surabaya, 60231, Indonesia
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