Effective human tutoring has been compared to a delicate balancing act. Students must be allowed to discover and correct problems on their own, but the tutor must intervene before the student becomes frustrated or confused. Natural language dialogue offers the tutor many ways to lead the student through a line of reasoning, and to indirectly notify the student of an error and use a series of hints and followup questions to get the student back on track. These sequences typically unfold across several conversational turns, during which the student can make more errors, initiate topic changes, or give more information than requested. Thus to support tutorial interactions, we require an intelligent information presentation system that can plan ahead, but is able to adapt its plan to the dynamically changing situation. In this paper we discuss how we have adapted the three-layer architecture developed by researchers in robotics to the management of tutorial dialogue.
|Title of host publication||Multimodal Intelligent Information Presentation|
|Editors||Oliviero Stock, Massimo Zancanaro|
|Number of pages||27|
|Publication status||Published - 2005|
|Name||Text, Speech and Language Technology|