Modeling and Inspecting the Question-Asking Process in Educational Dialogues

May 10, 2012
Lee Becker | University of Colorado Boulder

While many studies have demonstrated that dialogue-based tutoring systems have a positive effect on learning, the significant amount of human effort required to author, design, and tune system behaviors still provides a major barrier towards widespread deployment and adoption of these systems. Machine learning presents a path towards reduced human effort, however the custom-built nature of these systems means that any learned behavior is strictly tied to a single implementation. Ideally these behaviors should be able to extend to a variety of materials and concepts. To enable this kind of generalization will require a meta-level model of the dialogue that abstracts utterances to their action, function, and content.

In this talk, I describe the DISCUSS dialogue move taxonomy, an intermediate representation that allows for lesson-independent modeling of dialogue behavior. To demonstrate the utility of this representation, I explore how DISCUSS-based features assist in the process of ranking and selecting follow-up questions within the context of the My Science Tutor (MyST) intelligent tutoring system. Moreover, I show how DISCUSS enables us to model and identify the factors driving the decisions made by experienced human tutors when teaching.

Speaker Details

Lee Becker is a PhD candidate at the University of Colorado Boulder working on a dual PhD in Computer Science and Cognitive Science. The focus of his research is in intelligent tutoring systems, the investigation of machine-assisted means to educate humans. In his research thus far, Lee has sought to improve conversational interactions with tutoring systems and provide mechanisms to better explore and analyze the factors that contribute to successful learning experiences. Prior to graduate school, Lee spent a year teaching English to middle and high school students in Indonesia, and worked for several years developing software to aid in the design of microprocessors for Hewlett-Packard and Intel. Lee hopes to continue pursuing research that reflects his excitement for software, language, and education. More information about his research interests and prior work is available in his research statement and CV.