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Learning companions 1 CPI 494, Kurt VanLehn March 26, 2009.

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Presentation on theme: "Learning companions 1 CPI 494, Kurt VanLehn March 26, 2009."— Presentation transcript:

1 Learning companions 1 CPI 494, Kurt VanLehn March 26, 2009

2 3 major dimensions of LCs (LC = learning companions)
Kim, Y. (2007). Desirable characteristics of learning companions. International Journal of Artificial Intelligence and Education, 17, Interviews suggest 3 factors Competency of the LC Personality of the LC: friendly vs. neutral Interaction control: LC vs. human has the conversational initiative

3 Why now? First try to find out what kind of LC is best
Then test efficacy vs. ITS vs. baseline

4 Preference for strong vs. weak LCs when have a choice
Hietala, P., & Niemirepo, T. (1998). The competence of learning companion agents. International Journal of Artificial Intelligence and Education, 9,

5 Types of LCs Strong LC Weak LC One boy, one girl Never make mistakes
Confident Weak LC Often make mistakes, especially at beginning More hesitant

6 Human student’s interface

7 Experimental method Students can switch LC at any time 13 year old
Learning how to solve equations ONLY 14 SUBJECTS! Split on IQ Also split on introversion vs. extroversion 6 sessions of 30 minutes Pretest & posttest

8 Prefer weak LC at beginning and strong LC at end.

9 Weak prefer weak Strong prefer strong

10 Achievement tests All students learned No conditions, so no comparison

11 Expert vs. Motivator vs. Mentor
Baylor, A. L., & Kim, Y. (2005). Simulating instructional roles through pedagogical agents. International Journal of Artificial Intelligence and Education, 15,

12 Types of LCs Expert – knowledgeable Motivator – supportive
Mentor – both knowledgeable & supportive

13 Implementation Animated facial, head & hand gestures Voice
Expert looked like professor Motivator & mentor looked like college students More animated gestures Voice Expert was monotone, authoritative, formal Motivator was enthusiastic, energetic, colloquial Mentor was in between expert & motivator

14

15 Results: Self-reporting
Facilitating learning Expert best, but only in longer study Credibility Motivator < Mentor < Expert Human-like Expert < Mentor < Motivator Engaging But not in longer study

16 Outcomes Self-efficacy question “How confident are you that you can write a lesson plan?” Expert < Motivator < Mentor Domain interest “what do you think about instructional planning?” NS Designing a new lesson Motivator < Expert < Mentor

17 Is there an ATI? Kim, Y. (2007). Desirable characteristics of learning companions. International Journal of Artificial Intelligence and Education, 17, Do strong students prefer strong LC? Do weak students prefer weak LC? Any differences in learning?

18 Task domain Instructional design: Plan & implement supply & demand lesson

19 Experiment design College students in instructional design class
Two instructional factors Interaction control: LC provides info without being asked LC provides info only when asked LC competency Strong LC presents complete, accurate info with confidence Weak LC presents incomplete but accurate info; more tentative

20 Strong vs. weak LC

21 Results: Strong vs. weak LC
High GPA humans Low GPA humans Designing a new lesson NS Recall of ideas from training Strong LC Weak LC Which LC seems more valuable for learning? Which LC produces higher self-efficacy?

22 Results: LC vs. Human initiation of info presentation
High GPA humans Low GPA humans Designing a new lesson NS Recall of ideas from training Which LC seems more valuable for learning? LC control Human control Which LC produces higher self-efficacy?

23 From your reading of Chou, Chan & Lin (2003)
What do these roles mean?

24 Modes/roles of human & learning companion (LC) learners
Human edits LC’s knowledge (e.g., Betty’s Brain) LC solves & human gives immediate feedback, hints Human solves & LC gives immediate feedback, hints Human & LC solve separately, then compare (competition) On each step, human & LC negotiate who will do it & what will be done (collaboration) Human is reaching mastery & LC challenges them with strongly asserted, but wrong opinions – trip them up Human solves problem while delating simple stuff to the LC is limited assistant Teach with conventional teaching then see if agent has learned it LC provides motivation only Source of answers to questions & other content

25 Competence of LC Strong Weak Assertive vs. May reject human’s advice
Just incomplete vs. Troublemaker: Sometimes gives bad suggestions

26 Personality of the LC Neutral, unemotional Authority on the subject
Enthusiastic & empathetic


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