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<Paper uid="W05-0205">
  <Title>Towards Intelligent Search Assistance for Inquiry-Based Learning</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
In Online Inquiry-Based Learning (OIBL)
</SectionTitle>
    <Paragraph position="0"> learners search for information to answer driving questions. While learners conduct sequential related searches, the search engines interpret each query in isolation, and thus are unable to utilize task context.</Paragraph>
    <Paragraph position="1"> Consequently, learners usually get less relevant search results. We are developing a NLP-based search agent to bridge the gap between learners and search engines.</Paragraph>
    <Paragraph position="2"> Our algorithms utilize contextual features to provide user with search term suggestions and results re-ranking. Our pilot study indicates that our method can effectively enhance the quality of OIBL.</Paragraph>
  </Section>
class="xml-element"></Paper>