Discourse Patterns in Why/AutoTutor
Eric Mathews, G. Tanner Jackson, Arthur C. Graesser, Natalie K. Person · 2003
The interfaces of knowledge management systems will benefit from conversational agents, particularly for users who infrequently use such systems. The design of such agents will presumably share some of the dialog management facilities for systems designed for tutoring. For example, Why/AutoTutor is an automated physics tutor that engages students in conversation by simulating the discourse patterns and pedagogical dialog moves of human tutors. This paper describes how the Why/AutoTutor creates original dialog pathways for the learner. The system chains dialog moves, expressions, and discourse markers to simulate the dialog moves of natural human tutors while still controlling the conversational floor and the learning of the student. The agents of some knowledge management facilities of the future will be intelligent conversational agents. Conversational agents direct the flow of mixed-initiative dialog in service of mutual goals. These agents prompt the user when to speak and what to say, provide useful feedback, and answer questions. Conversational agents will be particularly useful for infrequent users of a knowledge management system because they need the most guidance in managing interactions with the system. Animated conversational agents have recently been designed for learning environments and help facilities