The field of Artificial Intelligence in Education (AIED) is experiencing a significant shift with the rapid adoption of Generative AI (GAI) technologies. Researchers are exploring the potential of GAI to enhance personalized learning, improve student outcomes, and increase teacher productivity. However, concerns around academic integrity, job security, and institutional pressures to adopt GAI tools are also emerging. The development of institutional policies and guidelines to safeguard security and privacy is becoming a key area of focus. Moreover, the use of large language models (LLMs) and multimodal learning analytics is gaining traction, with applications in areas such as technical interviews, literary criticism, and human-AI collaboration.

Noteworthy papers in this area include: Where is AIED Headed? Key Topics and Emerging Frontiers (2020-2024), which provides a comprehensive analysis of the evolving knowledge structure of the field and identifies emerging frontiers in AIED. Unpacking Generative AI in Education: Computational Modeling of Teacher and Student Perspectives in Social Media Discourse, which presents a modular framework for analyzing online social discourse and highlights the need for clearer institutional policies and support mechanisms for educators and students.