Abstract: The specific goal of my research is to develop technology capable of supporting effective participation in conversation to achieve a positive impact on human learning, growth, and wellbeing. The foundation for this work is a deep understanding of the mechanics of what makes conversation work in different settings as well as an understanding of what properties of conversation add to or detract from its positive impact on important outcomes of conversation. This research effort has birthed and substantially contributed to the growth of two thriving inter-related areas of research: namely, Automated Analysis of Collaborative Learning Processes and Dynamic Support for Collaborative Learning, where intelligent conversational agents are used to support collaborative learning in a context sensitive way. It is known for the way it bridges theories of interaction and computational modeling technology. The key idea behind my work is to draw insights from rich theoretical models of interaction from sociolinguistics and discourse analysis, and operationalize them in ways that capture the most important essence for achieving impact.
In this talk I will discuss the role of conversation in collaborative learning. I will compare how conversational processes have been operationalized using constructs from the Learning Sciences as well as Linguistics, with an emphasis on Systemic Functional Linguistics. I will then describe an integrated perspective and discuss work towards automation of three important constructs using machine learning and text mining technology. I will highlight findings from quantitative analyses that point to the importance of these constructs in discussion for learning in threaded discussion, synchronous chat, and face to face discussion.
Dr. Carolyn Rosé is an Associate Professor of Language Technologies and Human-Computer Interaction in the School of Computer Science at Carnegie Mellon University. Her research program is focused on better understanding the social and pragmatic nature of conversation, and using this understanding to build computational systems that can improve the efficacy of conversation between people, and between people and computers. In order to pursue these goals, she invokes approaches from computational discourse analysis and text mining, conversational agents, and computer supported collaborative learning. She serves on the executive committee of the Pittsburgh Science of Learning Center and the co-leader of its Social and Communicative Factors of Learning research thrust. She also serves as the Secretary/Treasurer of the International Society of the Learning Sciences and is a member of its Board of Directors. She serves as Associate Editor of the International Journal of Computer Supported Collaborative Learning and the IEEE Transactions on Learning Technologies.
For more information: This presentation is part of the 2013-2014 Distinguished Lecture Series sponsored by the UNC Charlotte College of Computing and Informatics.