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future . For speed , we have in -
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: I did n't understand . What
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( VanLehn et al. , 2002 ) . In
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, a student types an essay answering
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. Our experiments suggest that
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can be enhanced to automatically
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Architecture The architecture of
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is shown in Figure 3 . Student
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complete explanations . We are using
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to generate an empirically-based
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ideal essay . Another excerpt with
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is shown in Figure 2 . ` The
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tutor performs the same task as
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. Our subjects are university
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Acknowledgments We would like to thank the
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group and the three anonymous
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qualitative physics problem . In
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, however , the system engages
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tutor performs the same task as
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and Why2-Atlas . Our subjects
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Why2-Atlas team , and Scott Silliman of
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, for system development and
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user-oriented studies . <title>
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: An Intelligent Tutoring Spoken
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student learning . Fi - nally , when
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's evaluation is completed ,
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screenshot shown in Figure 1 .
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first poses conceptual physics
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) . 2 Application Description
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is a speech-enabled version of
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Litman Scott Silliman Abstract
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is a spoken dialogue system that
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ten . After speech recognition ,
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submits what it thinks the student
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through a speaker or headphone .
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is implemented in Python and
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Why2-Atlas server and client .
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monitors the XML being sent between
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qualitative physics problem .
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|
then engages the student in a
|