Cohesion and Learning in a Tutorial Spoken Dialog System

Issue 2: Is there an aptitude/treatment interaction?

• Why there might be:
• McNamara & Kintsch
• How we test it:
• Mean pre-test split
• All students
• Above-mean pretest students (“high” pre-testers)
• Below-mean pretest students (“low” pre-testers)

Issue 3: Is interactivity Important?

• Why it might be:
• Chi et al. (01)
• Tutor centered, Student centered, Interactive
• Deep learning through self construction
• Not tutor actions alone
• Litman & Forbes-Riley (05)
• Learning correlated with both:
• student utterances that display reasoning
• tutor questions that require reasoning
• How we test it:
• Interactive corpus – compare tutor to student turns
• Tutor–only corpus
• Student–only corpus

Issue 4: What other processing steps help?

• Tried several on training corpus:
• Removing stop words
• N-turn spans
• Selecting “substantive” turns
• TF-IDF normalization
• Turn-normalized counts
• (Raw tie count / # of turns in dialog)
• Found final options on training corpus:
• One turn spans, turn normalization, no TF-IDF, no substantive turn selection
• All reported results use these options
• Tested options on new corpus

Where did the corpora come from?

• ITSPOKE is a speech-enabled version of
• Why-2 Atlas (VanLehn et al. 02)
• Qualitative physics
• Tutoring Cycle
• Student reads instructional materials
• Takes a pre-test
• Starts Interactive tutoring cycle
• Problem
• Essay
• Tutor evaluates essay, engages in dialog
• Revise essay
• Repeat
• Takes a post-test