Alternating Environmental Teaching through AI: Potential Benefits and Limitations

Environmental education is essential for developing awareness, critical thinking, and problem-solving skills needed to address pressing global challenges such as climate change, biodiversity loss, and resource depletion. Artificial intelligence (AI) can expand access to environmental learning by providing scalable, personalized educational tools that overcome geographical and logistical barriers. This paper explored the perceptions of science teaching about the potential application of AI in environmental teaching. A purposive sampling method was employed to select 25 science teachers, who were selected through an online screening process and subsequently interviewed individually. Findings indicated that AI enabled personalized learning pathways, allowing students to engage with designed content and tasks suited to their individual levels, which enhanced academic growth and interest. AI-powered simulations allowed students to experiment with environmental changes in immersive, risk-free environments, while teachers used AI to simplify complex concepts and create diverse materials, enhancing instructional strategies like flipped classrooms. Individualistic nature of AI-based learning could reduce collaboration, limiting students’ understanding of environmental science and social dimensions. Overreliance on AI also hindered hands-on fieldwork, essential for practical skills and adaptability, while causing strong trust in AI-generated results, weakening critical evaluation and data collection abilities. These findings highlight the need for an optimized integration of AI with collaborative activities, field experiences, and critical thinking to ensure a comprehensive environmental science education.