1 / 18

Our Approach to Socially Intelligent Tutor

Our Approach to Socially Intelligent Tutor. Learning (1) – Course notes. Learning (2) – Problem solving. Tasks for assessment and practice. Expert’s idea. Ability estimate. Task scheme. Adaptive selection. Estimation. Generator. Answer category. Task instance. Judge. Student. Answer.

talor
Download Presentation

Our Approach to Socially Intelligent Tutor

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Our Approach to Socially Intelligent Tutor Enhancing Learning with Off-Task Social Dialogues

  2. Learning (1) – Course notes Enhancing Learning with Off-Task Social Dialogues

  3. Learning (2) – Problem solving Enhancing Learning with Off-Task Social Dialogues

  4. Tasks for assessment and practice Expert’s idea Ability estimate Task scheme Adaptive selection Estimation Generator Answer category Task instance Judge Student Answer Enhancing Learning with Off-Task Social Dialogues

  5. Task scheme specification • Parameters, constraints, tree of subtasks and answers • Psychometric IRT parameters, usage indicators Solution tree Task’s scheme tree correct A - C incorrect A A - B B C B - C Task scheme: Enhancing Learning with Off-Task Social Dialogues

  6. Task instance Instance generation Parameters’ specification Pruned backtracking Instantiated parameters Scheme tree Instance tree Combine Enhancing Learning with Off-Task Social Dialogues

  7. 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 Enhancing Learning with Off-Task Social Dialogues

  8. Extracting interests Tutor: Hello Kate, how are you?I'm here to make you feel comfortable, so that you learn much... :-) Student greeting Tutor: ok, write me about yourself, what you like, and all... I can thenprepare exercises that you will like ... ;) Extract features (e.g. to draw, watch TV, friends) Tutor: tell me more, pls. < 40 chars ≥40 chars Tutor: interesting, I for example like to readbooks,swim, play volleyball and soccer Student ack / Turn initiative Tutor: now, look around and solve exercises,ok?see you around! Enhancing Learning with Off-Task Social Dialogues

  9. Sample conversation Enhancing Learning with Off-Task Social Dialogues

  10. Real-life adaptation of tasks Instance generation, guided by student’s hobbies Parameters’ specification Semantic similarity with student’sfavorite concepts Pruned backtracking Instantiated parameters Scheme tree Instance tree Combine Enhancing Learning with Off-Task Social Dialogues

  11. 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

  12. Is it better than paper&pencil? • 32 students • Control group = traditional classroom • Experimental group = tutor • Learning gain: 1.2% vs 10.3% Enhancing Learning with Off-Task Social Dialogues

  13. 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: mfc2.78 (st.dev 1.39) Enhancing Learning with Off-Task Social Dialogues

  14. Motivating students? • Those that did engage with the tutor • Less problems attempted, higher success rate. Enhancing Learning with Off-Task Social Dialogues

  15. 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 areengaged, and do well.  Enhancing Learning with Off-Task Social Dialogues

  16. 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. Enhancing Learning with Off-Task Social Dialogues

More Related