Semantic Cohesion and Learning

نویسندگان

  • Arthur Ward
  • Diane J. Litman
چکیده

A previously reported measure of dialog cohesion was extended to measure cohesion by counting semantic similarity (the repetition of meaning) as well as lexical reiteration (the repetition of words) cohesive ties. Adding semantic similarity ties improved the algorithm’s correlation with learning among high pre-testers in one of our corpora of tutoring dialogs, where the lexical reiteration measure alone had correlated only for low pre-testers. Counting cohesive ties which have increasing semantic distance increases the measure’s correlation with learning in that corpus. We also find that both directions of tie, student-to-tutor and tutor-to-student, are equally important in producing these correlations. Finally, we present evidence suggesting that the correlations we find may be with deeper “far transfer” learning.

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تاریخ انتشار 2008