Our Research

Research in LILT addresses issues in artificial intelligence, cognitive science, and human-computer interaction, while applying methodologies from these fields to develop improved educational software. Several research projects are unified by the theme of representational affordances for collaborative learning.

Collaborative Representations is concerned with how different representational systems for online discourse and knowledge representation can promote efficient and effective construction of understanding through asynchronous conversations. This work grew out of the Representational Guidance project, which studied how the representational affordances of tools for building knowledge representations influenced users' collaborative learning processes.

We have a master list of publications online. The most important publications are also listed under the relevant research areas. Finally, LILT directors are involved in organizing several conferences.