AI in Education

Program Description

The P1 Program, AI in Education, is a research-driven initiative at the intersection of machine learning, artificial intelligence, and educational technologies. The overarching mission is to strengthen the scientific understanding, methodological rigor, and community formation in this rapidly evolving domain, aiming to consolidate fragmented research efforts into a coherent scholarly and professional community that advances both foundational AI research and its responsible application in education. 

The vision of the program is to establish education as a first-class, empirically grounded domain for machine learning research, where advances in models, evaluation methods, and human-AI interaction are informed by complex educational settings and societal needs.
By convening researchers, research students, practitioners, and administrators in a shared intellectual space, the program promotes mutual learning across methodological, applied, and institutional perspectives through a threefold approach: 

1. Provide a structured forum for deep engagement with peer-reviewed research in machine learning–driven educational technologies, drawing on top-tier re search journals.
2. Foster cross-disciplinary scientific interaction, connecting AI and ML researchers with educational scientists as well as pub lic and private sector professionals, thereby enabling new research questions, collaborations, and funding ideas to emerge.
3. Strengthen capacity building by integrating advanced research discussion into formal and informal academic training environments. 

The program emphasizes critical analysis of ML and AI methodologies, evaluation practices, and real-world deployment challenges, ensuring that scientific rigor and responsible AI principles remain central through out. In doing so, the ambition is to advance high-quality, human-centric AI research with tangible societal relevance, which will be demonstrated through sustained engagement with state-of-the-art research on learning analytics, generative AI, adaptive systems, and data-driven educational methods.