AI for Education Group

Overview

Educational knowledge and intelligent learning environments

The AI for Education Group studies how educational knowledge, retrieval systems, and generative AI can support intelligent and interactive learning. Its research connects educational knowledge graphs and vector databases with multimodal retrieval, graph-augmented generation, and interactive content generation.

The group develops methods for organizing and retrieving educational knowledge, reasoning over structured and multimodal information, and generating interactive actions, scenes, and learning environments.

Research areas

• Educational knowledge graphs. Extracting educational concepts, entities, and relations from course materials and learning resources to construct structured and continuously updated educational knowledge graphs.
• Educational retrieval and vector databases. Developing semantic representations, vector databases, hybrid retrieval, and scalable retrieval systems for educational knowledge and learning resources.
• Multimodal educational retrieval. Retrieving and aligning knowledge across text, images, videos, slides, and other multimodal educational content for knowledge-intensive learning applications.
• Graph-augmented retrieval and generation. Combining knowledge graphs with retrieval-augmented generation to support structured retrieval, multi-hop reasoning, and knowledge-grounded generation over educational content.
• Interactive learning content and environment generation. Generating actions, interactive behaviors, virtual scenes, and learning environments from natural-language and multimodal instructions for interactive and immersive learning applications.