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Persuasion and Reflective Learning:
Closing the Feedback Loop


Lars Müller, Verónica Rivera-Pelayo and Stephan Heuer
FZI Research Center for Information Technology Karlsruhe



Persuasive 2012, 7th June 2012


© MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu
Agenda



▪ Introduction & Motivation

▪ Persuade or support reflection?

▪ Closing the feedback loop

▪ Summary



© MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu   1
Introduction


Desired behavioral changes at work are often very
complex
                            “I want to treat my patients better.”




                                          “I need to reduce my stress.”




            “I would like to improve my
            communication and teaching skills.”

© MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu        2
MIRROR Reflective Learning at Work



▪ Learn by observing others and from experiences
▪ Support learning-on-the-job and experience sharing
▪ Learning by reflection on observed practices and collected
    data
▪ Focus on acquisition of
    tacit knowledge




© MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu   3
Motivation

                   Encouraging
                    reflection                                       Persuading



                                       Induce change in
                                           behavior


 Support by using information technology
 Both use feedback loops


       Can both fields of research learn from each other?


© MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu            4
Reflective Learning
 refers to “those intellectual and affective activities in which individuals engage to
 explore their experiences in order to lead to new understandings and
 appreciations“ (Boud et. al)




D. Boud, R. Keogh, and D. Walker. Reflection: Turning Experience into Learning, chapter Promoting Reflection in Learning: a
Model., pages 18-40. Routledge Falmer, New York, 1985.



  © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu                                         6
Persuasive Technology


Use of capturing approaches to provide persuasive feedback

 Capture behavior and rate it
 Provide reinforcement



Limited number of domains

 Clear Goals
 Specific Behavior                                            http://jawbone.com/up

 Behavior that can be measured
                                                                             http://dub.washington.edu/projects/ubifit




© MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu                            7
Persuade or Support Reflection




© MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu   8
Persuade or Support Reflection




© MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu   9
Example: Jawbone UP




© MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu   10
Reflection: A matter of guidance?


Influencing behavior using captured data
▪ Guidance reduces responsibility and effort for the user
▪ Reduces control
 Ethical implications


                           Computer
                           Supported
                           Reflective
                            Learning


                                     Amount of Guidance


 Awareness/                Reflection                            Persuasion    Coercion
 Mindfulness
© MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu            11
Complex goals
Growing number of data sources

 Harder to interpret
 Difficult to link to a goal
                                                    C                B
Unknown target behavior

 User decides
 Cognitive Dissonance Theory
                                                                     A
 Cognitive effort

Three possibly conflicting representations of behavior

 A) What really happened in a situation
 B) What the person believes had happened
 C) What tools have captured about that event

© MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu       12
Requirements for capturing behavior

                    Reflective Learning:                    Persuasive Technology:
                   Capturing experiences                   Capture specific behavior

                     General capturing                       Select best capturing
                        approach                                   approach

                    Select relevant data                             Rate behavior


                      Trigger reflection                   Provide Reinforcement


                                         Change in behavior



© MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu                   13
Closing the Feedback Loop
Persuasive Technology already measures behavior

 Ask the user
    Benefit for capturing?
    Is the data reliable?
 Using of-the-shelf sensors
    Accelerometers
    Biosensors
    Smart Meters
 Biosensors

Which data should be captured to support reflection?
 All data?
 Quantiative vs. Experiential



© MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu   14
Unpredictability of relevance


Which data can help predict relevance?


 Affective context by psychophysiological sensors

                                                                          http://www.affectiva.com/q-sensor/
 Social Interaction
    computer mediated communication
    face to face interaction

   Task context
      Augment tools

                                                                     http://hd.media.mit.edu/badges/




© MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu                     15
Conclusion

Results

 Outlined the design space between reflective learning and persuasive
  technology
 Reflection is a promising approach to induce behavioral change
 Three kinds of cues to identify relevant data for reflection

Outlook

 More data and sensors
 Can we persuade to reflect?




© MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu   16
Thank you very much


                                                                Questions?




© MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu     17

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Persuasion and Reflective Learning: Closing the Feedback Loop

  • 1. Persuasion and Reflective Learning: Closing the Feedback Loop Lars Müller, Verónica Rivera-Pelayo and Stephan Heuer FZI Research Center for Information Technology Karlsruhe Persuasive 2012, 7th June 2012 © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu
  • 2. Agenda ▪ Introduction & Motivation ▪ Persuade or support reflection? ▪ Closing the feedback loop ▪ Summary © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu 1
  • 3. Introduction Desired behavioral changes at work are often very complex “I want to treat my patients better.” “I need to reduce my stress.” “I would like to improve my communication and teaching skills.” © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu 2
  • 4. MIRROR Reflective Learning at Work ▪ Learn by observing others and from experiences ▪ Support learning-on-the-job and experience sharing ▪ Learning by reflection on observed practices and collected data ▪ Focus on acquisition of tacit knowledge © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu 3
  • 5. Motivation Encouraging reflection Persuading Induce change in behavior  Support by using information technology  Both use feedback loops Can both fields of research learn from each other? © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu 4
  • 6. Reflective Learning refers to “those intellectual and affective activities in which individuals engage to explore their experiences in order to lead to new understandings and appreciations“ (Boud et. al) D. Boud, R. Keogh, and D. Walker. Reflection: Turning Experience into Learning, chapter Promoting Reflection in Learning: a Model., pages 18-40. Routledge Falmer, New York, 1985. © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu 6
  • 7. Persuasive Technology Use of capturing approaches to provide persuasive feedback  Capture behavior and rate it  Provide reinforcement Limited number of domains  Clear Goals  Specific Behavior http://jawbone.com/up  Behavior that can be measured http://dub.washington.edu/projects/ubifit © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu 7
  • 8. Persuade or Support Reflection © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu 8
  • 9. Persuade or Support Reflection © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu 9
  • 10. Example: Jawbone UP © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu 10
  • 11. Reflection: A matter of guidance? Influencing behavior using captured data ▪ Guidance reduces responsibility and effort for the user ▪ Reduces control  Ethical implications Computer Supported Reflective Learning Amount of Guidance Awareness/ Reflection Persuasion Coercion Mindfulness © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu 11
  • 12. Complex goals Growing number of data sources  Harder to interpret  Difficult to link to a goal C B Unknown target behavior  User decides  Cognitive Dissonance Theory A  Cognitive effort Three possibly conflicting representations of behavior  A) What really happened in a situation  B) What the person believes had happened  C) What tools have captured about that event © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu 12
  • 13. Requirements for capturing behavior Reflective Learning: Persuasive Technology: Capturing experiences Capture specific behavior General capturing Select best capturing approach approach Select relevant data Rate behavior Trigger reflection Provide Reinforcement Change in behavior © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu 13
  • 14. Closing the Feedback Loop Persuasive Technology already measures behavior  Ask the user  Benefit for capturing?  Is the data reliable?  Using of-the-shelf sensors  Accelerometers  Biosensors  Smart Meters  Biosensors Which data should be captured to support reflection?  All data?  Quantiative vs. Experiential © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu 14
  • 15. Unpredictability of relevance Which data can help predict relevance?  Affective context by psychophysiological sensors http://www.affectiva.com/q-sensor/  Social Interaction  computer mediated communication  face to face interaction  Task context  Augment tools http://hd.media.mit.edu/badges/ © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu 15
  • 16. Conclusion Results  Outlined the design space between reflective learning and persuasive technology  Reflection is a promising approach to induce behavioral change  Three kinds of cues to identify relevant data for reflection Outlook  More data and sensors  Can we persuade to reflect? © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu 16
  • 17. Thank you very much Questions? © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu 17