About Education and AI

This collection explores the multifaceted impact of Artificial Intelligence (AI), particularly large language models (LLMs), in the field of education. As AI technologies rapidly evolve, they are reshaping how we teach, learn, assess, and interact within educational environments. This collection aims to bring together research, case studies, theoretical perspectives, and practical implementations that critically examine both the opportunities and challenges posed by AI in educational contexts. Contributions are encouraged from diverse disciplines to foster a comprehensive understanding of how AI can support equity, creativity, personalization, and innovation in learning processes.

Potential Topics:

• AI-driven personalized learning systems and their pedagogical implications
• Ethical and legal considerations of using AI in schools and universities
• The role of large language models in assessment and feedback
• Teacher-AI collaboration in curriculum design
• Bias, equity, and inclusion in AI-based educational tools
• Student perspectives on AI as a learning companion
• Gamification and AI: Enhancing motivation and engagement
• AI in educational policy and governance
• Data privacy and surveillance concerns in AI-enhanced classrooms
• Case studies of AI integration in different educational levels or regions
• Anthropomorphic Educational AI, Student Vulnerability, and Wellbeing
• Ethical, Pedagogical, and Regulatory Challenges of Empathic AI in Education
• Language, Agency, and AI Literacy in Educational Design and Policy

The Collection has been developed through contributions from the following COST Actions: Multi3Generation (CA18231), NexusLinguarum (CA18209), CLILNetLE (CA21114), and UniDive (CA21167). It is also open to submissions from other eligible funding programmes.