Cohesion and Learning in a Tutorial Spoken Dialog System



Yüklə 317 Kb.
səhifə1/9
tarix15.06.2023
ölçüsü317 Kb.
#130757
  1   2   3   4   5   6   7   8   9
cohesion3

Cohesion and Learning in a Tutorial Spoken Dialog System

  • Art Ward
  • Diane Litman

Outline

  • Tutoring
  • Goals
  • 4 issues in measuring cohesion
  • Results

Natural Language Dialog Tutoring

  • Human tutors are better than classroom instruction (Bloom 84)
  • Intelligent Tutoring Systems (ITSs) hope to replicate this advantage
  • Is Dialog important to learning?
    • Dialog acts: question answering, explanatory reasoning, deep student answers (Graesser et al. 95, Forbes-Riley et al. 05)
  • Difficult to automatically tag dialog input, so:
  • Automatically detectable dialog features
    • Average turn length, etc. (Litman et al. 04)
    • We look at Cohesion
      • Lexical Co-occurrence between turns

Goals and Results

  • Goals
    • Want to find if cohesion is correlated with learning in our tutoring dialogs.
    • Want to find a computationally tractable measure of cohesion
      • So can be used in a real-time tutor
  • Results

4 Issues

  • Why/How identify cohesion in dialogs?
  • Do students of different skill levels respond to cohesion in the same way?
    • (Is there an aptitude/treatment interaction?)
  • Is Interactivity Important?
  • What other processing steps help?

Issue 1: How identify cohesion in dialogs?

  • Why might cohesion be important in tutoring?
    • McNamara & Kintsch (96)
      • Students read high & low coherence text
        • High coherence text was low coherence version altered to:
      • Interaction between pre-test score & response to textual coherence

Yüklə 317 Kb.

Dostları ilə paylaş:
  1   2   3   4   5   6   7   8   9




Verilənlər bazası müəlliflik hüququ ilə müdafiə olunur ©azkurs.org 2024
rəhbərliyinə müraciət

gir | qeydiyyatdan keç
    Ana səhifə


yükləyin