The general goal of our work is to investigate computational models of dialog that can support effective interaction between people and computer systems. We are particularly interested in the use of dialog for training and education. To support effective communication, dialog systems must facilitate users’ understanding by incrementally presenting only the most relevant information, by evaluating users’ understanding, and by adapting the interaction to address communication problems as they arise. Our model provides a specification and representation of the linguistic, intentional, and social information that influence how people understand and respond in an ongoing dialog and an architecture for combining this information. We represent knowledge uni/ormly in a single, declarative, logical language where the interpretation and performance of communicative acts in dialog occurs as a result of reasoning.