Green AI in Education: Leveraging AI for Sustainable Learning and Eco Skills Monitoring
Аннотация
This paper contributes to sustainable learning theory development and policy innovation on green AI, by addressing the intersection of AI technologies, ecological education, and skills monitoring in the context of digital pedagogy, climate-responsive curricula, and educational transformation in developing regions and transitional economies. The research responds to the UNESCO Education for Sustainable Development's call for inclusive transformation by employing the green AI ecosystem as a catalyst for the ideals of environmental literacy, and the symbolic practices of AI tools that are employed to construct discourses of sustainability and learning in this data-informed educational space. In the analysis of an AI-driven educational framework in the Uzbekistan-Kazakhstan corridor, the semantic modeling of student narratives is considered to highlight the keywords and narrative cues used to reproduce ideals of green citizenship and to create affective alignment around a remodeled eco-pedagogical identity. Indicators for measuring eco-competence (e.g., green engagement index, AI-Eco pedagogy fit) are essential for understanding the sentiment variance with respect to identity construction, and other emotional determinants. The structural equation modeling results show that the green AI pathway corresponds to the sustainable skills framework, and sentiment analysis can well predict the eco-literacy patterns. We show that different results indicate if we apply SWOT analysis on a disciplinary level compared to a regional level. In addition, through observing the sentiment trajectories on the digital discourse surface, it can be seen that the evolution of the eco-identity is caused by the affective resonance and the semantic proximity, and the formation of the green skills cluster takes precedence over that of the technical AI fluency.