Work

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

Year: 2025

Type: article

Abstract: 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.

Source: SAGE Open

DOI: 10.1177/21582440251403646

Authors: Jiaxing Wang, Shijie Zhai, Yixuan Wang, Hai-Yan Hua, Yuyan Luo

Institutions: Sichuan University, Chengdu University of Technology, Chongqing University

Language: English

Topic: Environmental Education and Sustainability

Subfield: Management, Monitoring, Policy and Law

Field: Environmental Science

Domain: Physical Sciences

SDGs: Quality education, Climate action

Open Access status: gold

Estimated APC paid: $1,600