jozef tvarožek and mária bieliková enhancing learning with off-task social dialogues ec-tel 2010,...
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Jozef Tvarožek and Mária Bieliková
Enhancing Learningwith Off-Task Social Dialogues
EC-TEL 2010, BarcelonaSeptember 30, 2010
Slovak University of Technology in Bratislava
Enhancing Learning with Off-Task Social Dialogues 2
Our Approach to Socially Intelligent Tutor
Enhancing Learning with Off-Task Social Dialogues 3
Learning (1) – Course notes
Enhancing Learning with Off-Task Social Dialogues 4
Learning (2) – Problem solving
Enhancing Learning with Off-Task Social Dialogues 5
Tasks for assessment and practice
Expert’s idea
Task scheme
Task instance
Answer
Answer category
Ability estimateAdaptive selection
Generator
StudentJudge
Estimation
Enhancing Learning with Off-Task Social Dialogues 6
Task scheme specification
A
B
C
A - C
A - B
Solution tree
B - C
Task’s scheme tree
• Parameters, constraints, tree of subtasks and answers• Psychometric IRT parameters, usage indicators
Task scheme:
correct
incorrect
Enhancing Learning with Off-Task Social Dialogues 7
Task instance
Parameters’ specification
Instantiated parameters
Scheme tree Instance tree
Pruned backtracking
Combine
Instance generation
Enhancing Learning with Off-Task Social Dialogues 8
Updating user’s profile
• Off-task dialogues– Qs/As scripted to perform actions• Extracting user’s preferences & behaviors• Extracting event attributes• Recommending events to attend• Negotiating events with others
– Relationship maintenance
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Extracting interests
Tutor: now, look around and solve exercises, ok? see you around!
Student ack / Turn initiative
Tutor: interesting, I for example like to read books, swim, play volleyball and soccer
≥ 40 chars< 40 chars
Extract features (e.g. to draw, watch TV, friends)
Tutor: Hello Kate, how are you? I'm here to make you feel comfortable, so that you learn much... :-)
Tutor: ok, write me about yourself, what you like, and all... I can then prepare exercises that you will like ... ;)
Student greeting
Tuto
r: te
ll m
e m
ore,
pls
.
Enhancing Learning with Off-Task Social Dialogues 10
Sample conversation
Joe:Hello Kate, how are you?I’m here to make you feel comfortable, so that you learn much… :-)
Kate: thnx
Joe:ok, write me about yourself, what you like, and all…I can then prepare some exercises that you will definitely like :P
Kate: like to draw sleep watch TV …
Joe: write a bit more please …
Kate: like to go out go out with my dog
Joe:interesting, I for example like to read books, from sports volleyball, swimming, and also some soccer
Kate: okay
Joe: now, look around this environment and solve some of the exercises, ok?see you around!
Enhancing Learning with Off-Task Social Dialogues 11
Real-life adaptation of tasks
Parameters’ specification
Instantiated parameters
Scheme tree Instance tree
Pruned backtracking
Combine
Instance generation, guided by student’s hobbies
Semantic similarity with student’s
favorite concepts
Enhancing Learning with Off-Task Social Dialogues 12
Evaluation study
• Middle school mathematics• 18 parametric algebra tasks• Tutoring friend– Extract hobbies
• Students did participate in a pilot previously– Familiar with the environment
Enhancing Learning with Off-Task Social Dialogues 13
Is it better than paper&pencil?
• 32 students– Control group = traditional classroom– Experimental group = tutor
– Learning gain: 1.2% vs 10.3%
pre-test post-test gain t-test
mean st.dev mean st.dev mean st.dev t stat p-value
Control group 0.697 0.230 0.709 0.211 0.012 0.258 -0.18 0.428
Exp. group 0.434 0.253 0.538 0.269 0.103 0.172 -2.40 0.015
Enhancing Learning with Off-Task Social Dialogues 14
Are they willing to do it?
• 16 students• Detect student interests in the initial welcome
dialogue: to draw, sleep, watch TV, go out, go out with dog
• Mean word count 11.6 (st.dev 8.7)• Mean feature count 1.56 (st.dev 1.7)• 44% IGNORED the tutor– Others: mfc 2.78 (st.dev 1.39)
Enhancing Learning with Off-Task Social Dialogues 15
Motivating students?
• Those that did engage with the tutor– Less problems attempted, higher success rate.
Control Experimentalmean st.dev Mean st.dev
Number of tasks attempted 7.71 3.86 7.00 1.80
Number of tasks solved correctly 2.85 1.46 4.00 2.45
Questions (response scale: 1=worst, 5=best)
1. How much did you learn in the tutor? 2.29 1.25 3.33 0.71
2. How much did the tutor help you on the post-test?
2.29 1.11 3.33 1.12
3. How much would you like to use the tutor again?
3.14 1.07 4.33 1.12
4. How did you like the tutor? 2.86 1.07 4.22 0.97
Enhancing Learning with Off-Task Social Dialogues 16
Motivating students? (contd.)
• Is the tutoring friend any good?– We don’t know.
– Learning gain: 3.7% vs. 12.3%– We can filter students that are
engaged, and do well.
pre-test post-test gain
mean st.dev mean st.dev mean st.dev
Engaged 0.429 0.245 0.465 0.283 0.037 0.283
Not engaged 0.439 0.273 0.562 0.284 0.123 0.192
Enhancing Learning with Off-Task Social Dialogues 17
Summing up
• Those who engage in the social off-task dialog with the tutor solve problems better :)
• Tutors that are “friends” with students can produce higher learning gains.
• Socially intelligent tutor – tutoring friend:– gets to know you better,– guides you to what you need.
Jozef Tvarožek and Mária Bieliková
Enhancing Learningwith Off-Task Social Dialogues
EC-TEL 2010, BarcelonaSeptember 30, 2010
Slovak University of Technology in Bratislava