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<Paper uid="J88-3005">
  <Title>REASONING ON A HIGHLIGHTED USER MODEL TO RESPOND TO MISCONCEPTIONS</Title>
  <Section position="2" start_page="0" end_page="0" type="intro">
    <SectionTitle>
1 INTRODUCTION
</SectionTitle>
    <Paragraph position="0"> When people interact with a database or expert system, it is reasonable to expect that they might reveal a misconception about an object modeled by the system.</Paragraph>
    <Paragraph position="1"> Since a human conversational partner would correct such a misconception if it was important to the current goals of the conversation, our database and expert systems should also be equipped with this ability.</Paragraph>
    <Paragraph position="2"> In order to investigate how the process of correcting misconceptions might be automated, a study of transcripts of both humans .interacting with what they thought were expert systems (Malhotra 1975, Malhotra and Sheridan 1976, Schuster 1982), and humans interacting with other humans to achieve some goal (Pollack, Hirschberg, and Webber 1982) was undertaken. The transcripts, which varied greatly in their domains of discourse, were analyzed to determine if there was any regularity in the content and rhetorical force of responses given to misconceptions. The intention of this analysis was not to mimic the actual behavior found in the transcripts, but to use them as a source of intuitions about the context and textual shape of responses as well as the process of generating them.</Paragraph>
    <Paragraph position="3"> The study revealed that a response to a misconception important to the current discourse goals of the participants can be viewed as consisting of three parts: 1. a denial of the incorrect information; 2. a statement of the correct information; and 3. justification for the denial and correction given. For a particular type of misconception (i.e., one involving a particular kind of knowledge), variations in responses could be found in the form of the justification given. The justification often seemed to refute support that might have led to the misconception. While the kind of support someone might have for a misconception seems unrestricted, the form of the justification was limited for misconceptions Copyright 1988 by the Association for Computational Linguistics. Permission to copy without fee all or part of this material is granted provided that the copies are not made for direct commercial advantage and the CL reference and this copyright notice are included on the first page. To copy otherwise, or to republish, requires a fee and/or specific permission.</Paragraph>
  </Section>
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