Roger J. Kreuz - US grants

This project is being funded through the Learning and Intelligent Systems (LIS) Initiative. The long-term practical objective of the research is to develop a fully automated computer tutor. The tutor would be able to (a) extract meaning from the contributions that the student types into a keyboard and (b) formulate dialog contributions with pedagogical value and conversational appropriateness. The tutor's discourse moves include: pumping, prompting, hinting, questioning, answering, summarizing, splicing in correct information, providing immediate feedback, and rewording student contributions. The dialog contributions of the tutor would be in different formats and media: printed text, synthesized speech, simulated facial movements, graphic displays, and animation. Such an achievement will require an interdisciplinary integration of theory and empirical research from the fields of cognitive psychology, discourse processing, computational linguistics, artificial intelligence, human-computer interaction, and education. The tutoring topics will be in the domains of computer literacy and introductory medicine. Previous attempts to develop a fully automated tutor have been seriously challenged by some technical and theoretical barriers. These include (a) the problem of interpreting natural language when it is not well-formed semantically and grammatically, (b) the problem of world knowledge being immense, open-ended and incomplete, and (c) the lack of research on human tutorial dialog. Recent advances have dramatically reduced these barriers, so it is time to revisit the mission of developing an automated tutor. According to the recent research on human tutoring, a key feature of effective tutoring lies in generating discourse contributions that assist learners in actively constructing explanations, elaborations, and mental models of the material. The proposed research will advance scientific understanding of how a tutor can manage a smooth, polite dialog that promotes deep learning of the material.

When two humans interact, they often mirror each other's behavior. While discussing a work of art, their eye movements and gestures may become similar or even synchronize. When conversing face to face, they may adjust to facial expressions and gestures of their conversational partner. In addition, they may carefully adapt their sentences to the shared world that each can see. Therefore when two people interact, to some extent they become one "coupled" system. Like a couple dancing, they adjust their behavior in response to their partner. This research will explore how and when two people can be conceived as one dynamic, coupled system. An interdisciplinary team, consisting of two psychologists, a computer scientist, and a philosopher, will develop experiments and computer simulations to find new ways of understanding this "mirroring" and "adapting" that people seem to do while communicating.

Theories of human communication often emphasize strong coupling or, as a default, its absence. This work will supplement such theories by seeking a systematic middle ground based in cognitive mechanisms. How does facilitating memory and attention foster coupling between speakers? Humans can be made to adapt effectively to each other if the conditions are just right, and less often otherwise. The findings from this research could suggest ways of redesigning task environments to facilitate communication between partners. These tasks are common in everyday life, from sharing a computer screen during interaction, navigation, and even educational contexts in which tutors and students discuss visual or other information. The project could help two people couple more strongly, thus helping task partners avoid vagueness and ambiguity, and enhance the efficiency of their communication.