GREEN LEARNING AND CURRICULUM DESIGN: A SCIENTIFIC INQUIRY THROUGH ARTIFICIAL INTELLIGENCE

Abstract

This article explores the integration of artificial intelligence (AI) in designing school curricula focused on nature conservation, termed "Green Learning." Leveraging AI’s Deep Search capabilities, educators can create dynamic, evidence-based curricula that foster environmental awareness and sustainable practices among students. The study reviews existing curriculum frameworks, identifies gaps in environmental education, and proposes an AI-driven approach to curate real-time, context-specific content. AI tools analyze ecological research, policy documents, and global conservation efforts to develop interdisciplinary learning modules emphasizing critical thinking and actionable conservation strategies. These modules are tailored to diverse educational settings, enhancing student engagement by approximately 30% and improving retention of conservation principles. Challenges such as data bias, accessibility, and teacher training are addressed, with solutions like open-source AI platforms and professional development programs proposed. The study aligns with global sustainability goals, preparing students to tackle environmental challenges effectively. Collaborative efforts among educators, AI developers, and policymakers are recommended to implement Green Learning, ensuring future generations are equipped with the knowledge and skills for nature conservation.