AI-Enhanced Sustainable Education: From Affective Computing to Intelligent Learning Ecosystems

Dear Colleagues,

As we face global challenges that threaten our way of life, education is more important than ever. UNESCO’s Education for Sustainable Development (ESD) is a key response to these urgent issues. The ESD for 2030 program specifically emphasizes policy guidance, technical support, and innovation networks to achieve the SDGs. However, traditional teaching methods alone cannot meet these growing demands. In the digital age, Artificial Intelligence (AI) has become a critical force that cannot be ignored. This Special Issue proposes that AI-Enhanced Sustainable Education is the essential foundation needed to achieve these global goals. We explore how intelligent systems can turn abstract sustainability concepts into practical, scalable educational practices.

To support UNESCO's call for data-driven policy and equity, we invite research on learning analytics for early intervention and reducing dropout rates. To foster innovation, we seek contributions using Generative AI and immersive environments to enhance content accessibility. Furthermore, to support psychological well-being, we emphasize affective computing and intelligent pedagogical agents for social-emotional learning. Crucially, we address the need for ethical AI and privacy protection to build trustworthy systems. Finally, to ensure long-term resilience, we welcome studies on full-stack architectures and AI-empowered teacher professional development. This Special Issue aims to move from isolated tools to comprehensive Intelligent Learning Ecosystems that actively advance the global sustainability agenda.

This Special Issue encompasses a broad range of cutting-edge research areas, including the following:

• Affective computing and emotion-aware educational technologies for social-emotional learning and psychological well-being;
• AI-driven personalized learning systems and adaptive learning platforms;
• Intelligent pedagogical agents and conversational AI in education;
• Generative AI and large language models (LLMs) for educational innovation;
• Learning analytics for early intervention and reducing dropout rates;
• Full-stack intelligent educational systems and service-oriented architectures;
• Interdisciplinary integration of AI, education, and emerging technologies;
• Gamification, game-based learning, and immersive AI environments;
• Ethical AI, algorithmic fairness, and privacy in sustainable digital ecosystems;
• Empowering teachers with AI for sustainable pedagogical transformation.

Prof. Dr. Hao-Chiang Koong Lin
Dr. Chun-Hsiung Tseng
Dr. Yung-Hao Wong
Guest Editors

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