Andrew M. Olney, Ph.D. - US grants

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.

This project will develop and evaluate the potential of a new human-computer system that bridges the roles of virtual student and virtual teacher to allow humans and computers to take turns teaching and learning from each other. The key insight is that reading comprehension activities (e.g., vocabulary building, summarizing, question generation, concept mapping) closely parallel the knowledge engineering required to create virtual teachers for intelligent tutoring systems (ITSs). The system links these activities so that when students read online, they engage a virtual student in educational tasks that both improve their reading comprehension and simultaneously contribute to the creation of ITSs for future students. An important aspect of the proposed research is to find the optimum balance between student learning (which benefits the individual) and the creation of ITS knowledge representations (which benefits many). Specific research objectives are: (1) to develop a baseline platform (called BrainTrust) such that students can create ITS knowledge representations by teaching a virtual student; (2) to study the relationship between the student's ability, the virtual student's ability, the student's learning outcomes, and the quality of knowledge representations produced. A distinctive characteristic of the proposed research is the study of these questions in ecologically valid conditions, as students engage in authentic study, while also participating in randomized experiments.

The research may lead to the development of systems that improve reading comprehension, which may have broad benefits given the centrality of reading comprehension to all learning. In particular, problems with reading comprehension have been linked to first-year college student dropout that disproportionately affects African-American students. The research will also enhance infrastructure for research and education through the development and dissemination of the BrainTrust platform, a next-generation computing infrastructure to rapidly create and deploy ITSs tailored to specific needs. If this exploratory project demonstrates that the dual outcomes of human learning and high-quality knowledge representations can be achieved, it will open a new area of research that brings teaching these virtual students full circle with learning from their derived intelligent tutoring systems.