The Human Element in AI-Driven Environmental Education: Teacher Adaptability and Personalization in Promoting Eco-Friendly Behaviors

The ecological crisis deeply impacts the globe. Despite increasing interest in environmental education (EE), there is limited research on how AI technologies influence students’ adoption of eco-friendly behaviors, highlighting a critical research gap. This research aims to explore how psychological and educational factors including adoption of AI in teaching contribute to eco-friendly behaviors. Utilizing the Model of Goal-Directed Behavior alongside theories of class adaptability, this study introduces the AI-Driven Green Behavior Model (AIGB) to elucidate how these elements interact. The study analyzes data from comments on China’s Mooc online education platform and enhances its findings with insights from interviews. Employing Big Data, Structural Equation Modeling, and grounded theory in its analysis, the research underscores the vital role of adaptability and personalization in environmental education. It further underscores the irreplaceable role of human educators in the adoption of AI in teaching.