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QA on AutoTutor 2004 paper

QA on AutoTutor 2004 paper. CPI 494, March 31, 2009 Kurt VanLehn. What did AutoTutor look like?. Animated agent + dialogue box; voice; Input from student = typed response; may be a couple of words Technology for voice = MS voice (Alan Black; LTI – Festivox)

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QA on AutoTutor 2004 paper

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  1. QA on AutoTutor 2004 paper CPI 494, March 31, 2009 Kurt VanLehn

  2. What did AutoTutor look like? • Animated agent + dialogue box; voice; • Input from student = typed response; may be a couple of words • Technology for voice = MS voice (Alan Black; LTI – Festivox) • There was version that understood speech, sortof • Gestures = Facial, hand waves inward, • Was version that pointed • Can switch faces; no big diff on gains & motivation • Absent agent may not make a different • Voice first then text

  3. What was AutoTutor’s “script”? • Give overall question; first student turn = usually not complete or correct; • Tutor picks an aspect of the correct, complete answer and tries to get student to say it. • Tutor pump/prompts; • T hints; • T assert • Repeat for each missing aspect • Follow the student vs. own ordering • conceptual prereqs • Also answes the student’s questions

  4. What is AutoTutor trying to teach? • Drive stueent with hints to articulate all the aspects of the ideal answer • Its main questions are deep • Constructivist practice; learn by (self-) questioning • Transfer studies? • Types of knowledge • Facts? Concepts? Procedures? Principles? • Facts are too shallow to benefit from AT vs. drill • Concepts OK • Princpiles, especially how to apply them • Could be procedure, but not perhaps the best;

  5. How is AutoTutor different from human tutoring on the same content? • AutoTutor is based on shallower understanding of the student. Based on pattern match (LSA) between its ideal answer aspects and the student’s response. • Human’s do not use super sophisticated tutoring • Humans often do same remediation cycle • By-stander turing test

  6. Is AutoTutor’s dialogue natural? • By stander test • May be is • Hand out dialogues later • Logic is screwy

  7. In terms of learning gains, was AutoTutor effective? • All conditions similar on shallow questions • AutoTutor beat no-tutor and textbook on deep qustions and cloze questions • Interaction plateaus • Motivation unknow resutls…

  8. What kinds of task domains would AutoTutor be good for?

  9. How did AutoTutor analyze the student’s responses? • LSA • Bag of words (unordered list with duplicates allowed)

  10. In terms of step-based tutoring, what are AutoTutor’s steps?

  11. In terms of step-based tutoring, what feedback and hints exist for steps?

  12. Does AutoTutor have an outer loop over tasks?

  13. What model of the student does AutoTutor have?

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