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Summary of … 3 rd Workshop on Affective and Attitude User Modeling

Summary of … 3 rd Workshop on Affective and Attitude User Modeling. Assessing and Adapting to User Attitudes and Affect: Why, When and How? Co-Chairs: Cristina Conati, Eva Hudlicka, Christine Lisetti. Objectives.

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Summary of … 3 rd Workshop on Affective and Attitude User Modeling

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  1. Summary of …3rd Workshop on Affective and Attitude User Modeling Assessing and Adapting to User Attitudes and Affect: Why, When and How? Co-Chairs: Cristina Conati, Eva Hudlicka, Christine Lisetti

  2. Objectives • Explore core issues in expanding user models to include information of affect and attitudes: • Detection • Modeling • Adaptation • Validation and Evaluation • ... across a range of applications

  3. Focus Questions • Can we begin to identify a taxonomy of circumstances requiring affective user modeling? • What are existing methods of constructing affective user models? (detection/modeling) • Can we define guidelines for model use? (adaptation) • What are methods and issues in validation and evaluation?

  4. Workshop Organization • 8 long papers in 3 Sessions • 5 posters in Poster Session • Small Group Discussion and Presentation • Panel (Fiorella de Rosis, Anthony Jameson, Roz Picard, Amy Kruse)

  5. Necessary Undesirable Identify a Taxonomy of Circumstances Requiring Affective User Modeling? • Possible Applications • Training and Tutoring • Dialogue Systems • CSCW • Telehealth Chainsaw ?? • Critical Factors • Affect central to task (e.g. psychotherapy) • Affect influences user performance (e.g., learning) • Degree to which adaptation is possible • Placement on spectrum must be empirically tested

  6. Can We Define Guidelines for Model Use: When and How to Adapt? • Factors • Context • User’s goals and traits • Target of the adaptation • User affective state • Consequences of affective states (e.g., attention) • Critical issues • User control • Empirical evaluations of adaptation strategies

  7. What are Existing Methods of Constructing Affective User Models? • Detection • Biometric Sensors – Effectiveness varies along various dimensions • Diagnosticity (GSR good for arousal) • Intrusiveness (depends on application, wireless is good) • Reliability (BVP and Respiration low) • NL and speech (Emotionally tagged grammars) • Modeling • Bayesian and Dynamic Belief Networks • Finite State Machine • Other methods analized in small group discussion

  8. What are Methods and Issues for Validation and Evaluation? EVALUATION, DAMN IT!

  9. What are Methods and Issues for Validation and Evaluation? Evaluate the detection/modeling directly • Challenges • Ephemeral • Idiosyncratic • Not always observable • Possible Solution: Multiple Measures (e.g. observations + self-reports) Evaluate the adaptation built on the model for: • User satisfaction • Task performance

  10. Conclusions • Prototype systems exist which can sense frustration / stress and provide adaptive response (e.g., empathy) • Variety of promising detection/modeling methods exist • Critical Needs/Issues • Corpora of Labelled Data • Gold standards for validating measures • Clear definition of constructs • Privacy • Understand level of modeling resolution required: do not overmodel!

  11. For more…see workshop Web pagewww.cs.ubc.ca/~conati/um03-affect/affectum.html Thanks to workshop and panel partecipants!

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