Persuasion and Reflective Learning: Closing the Feedback Loop

  • Lars Müller
  • Verónica Rivera-Pelayo
  • Stephan Heuer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7284)


Reflecting about past experiences can lead to new insights and changes in behavior that are similar to the goals of persuasive technology. This paper compares both research directions by examining the underlying feedback loops. Persuasive technology aims at reinforcing clearly defined behaviors to achieve measurable goals and therefore focuses on the optimal form of feedback to the user. Reflective learning aims at establishing goals and insights. Hence, the design of tools is mainly concerned with providing the right data to trigger a reflection process. In summary, both approaches differ mainly in the amount of guidance and this opens up a design space between reflective learning and persuasive computing. Both approaches may learn from each other and can use common capturing technologies. However, tools for reflective learning require additional concepts and cues to account for the unpredictability of relevance of captured data.


Feedback Loop Learning Tool Acceleration Sensor Reflective Learning Computer Mediate Communication 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1. (2012),
  2. 2.
    Boud, D., Keogh, R., Walker, D.: Promoting Reflection in Learning: a Model. In: Reflection: Turning Experience into Learning, pp. 18–40. Routledge Falmer, New York (1985)Google Scholar
  3. 3.
    Consolvo, S., Landay, J.A., McDonald, D.W.: Designing for behavior change in everyday life. Computer 42, 86–89 (2009)CrossRefGoogle Scholar
  4. 4.
    Consolvo, S., McDonald, D., Landay, J.: Theory-driven design strategies for technologies that support behavior change in everyday life. In: CHI 2009, pp. 405–414. ACM (2009)Google Scholar
  5. 5.
    Daudelin, M.W.: Learning from experience through reflection. Organizational Dynamics 24(3), 36–48 (1996)CrossRefGoogle Scholar
  6. 6.
    Dewey, J.: Experience and Education. Macmillan, London & New York (1938)Google Scholar
  7. 7.
    Festinger, L.: A theory of cognitive dissonance. Stanford Univ. Press (1957)Google Scholar
  8. 8.
    Fogg, B.J.: Creating Persuasive Technologies: An Eight-Step Design Process. In: Persuasive 2009. ACM (2009)Google Scholar
  9. 9.
    Fogg, B.: Persuasive technology Using Computers to Change What We Think and Do. Morgan Kaufmann Publishers (2003)Google Scholar
  10. 10.
    Froehlich, J., Chen, M.Y., Consolvo, S., Harrison, B., Landay, J.A.: MyExperience: a system for in situ tracing and capturing of user feedback on mobile phones. In: MobiSys 2007, pp. 57–70. ACM, New York (2007)CrossRefGoogle Scholar
  11. 11.
    Froehlich, J., Dillahunt, T., Klasnja, P., Mankoff, J., Consolvo, S., Harrison, B., Landay, J.A.: Ubigreen: investigating a mobile tool for tracking and supporting green transportation habits. In: CHI 2009, pp. 1043–1052. ACM, New York (2009)CrossRefGoogle Scholar
  12. 12.
    Gasser, R., Brodbeck, D., Degen, M., Luthiger, J., Wyss, R., Reichlin, S.: Persuasiveness of a Mobile Lifestyle Coaching Application Using Social Facilitation. In: IJsselsteijn, W.A., de Kort, Y.A.W., Midden, C., Eggen, B., van den Hoven, E. (eds.) PERSUASIVE 2006. LNCS, vol. 3962, pp. 27–38. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  13. 13.
    Goetz, T.: Harnessing the power of feedback loops (June 2011),
  14. 14.
    Jawbone Up (2012),
  15. 15.
    Kolb, D.A.: Experiential Learning: Experience as the source of learning and development. Prentice Hall, Englewood Cliffs (1984)Google Scholar
  16. 16.
    Li, I., Dey, A.K., Forlizzi, J.: Understanding my data, myself: supporting self-reflection with ubicomp technologies. In: UbiComp 2011, pp. 405–414 (2011)Google Scholar
  17. 17.
    Loftus, E.F.: Planting misinformation in the human mind: A 30-year investigation of the malleability of memory. Learning & Memory 12, 361–366 (2005)CrossRefGoogle Scholar
  18. 18.
    Mamykina, L., Mynatt, E., Davidson, P.: MAHI: investigation of social scaffolding for reflective thinking in diabetes management. In: Proceedings CHI 2008, pp. 477–486 (2008)Google Scholar
  19. 19.
    Mirror - reflective learning at work (2012),
  20. 20.
    Moon, J.A.: Reflection in learning and professional development. Routledge (1999)Google Scholar
  21. 21.
    Mora, S., Rivera-Pelayo, V., Müller, L.: Supporting Mood Awareness in Collaborative Settings. In: CollaborateCom 2011 (2011)Google Scholar
  22. 22.
    Morris, M.E.: Technologies for Heart and Mind: New directions in embedded Assessment. Intel. Technology Journal 11(01) (2007)Google Scholar
  23. 23.
  24. 24.
    Norman, D.A.: Explorations in Cognition. W.H.Freeman & Co Ltd. (1974)Google Scholar
  25. 25.
    Olguin, D., Waber, B.N., Kim, T., Mohan, A., Ara, K., Pentland, A.S.: Sensible organizations: Technology and methodology for automatically measuring organizational behavior. IEEE Transactions on Systems, Man, and Cybernetics-Part B: Cybernetics 39(01) (2009)Google Scholar
  26. 26.
    Patel, S.N., Robertson, T., Kientz, J.A., Reynolds, M.S., Abowd, G.D.: At the Flick of a Switch: Detecting and Classifying Unique Electrical Events on the Residential Power Line (Nominated for the Best Paper Award). In: Krumm, J., Abowd, G.D., Seneviratne, A., Strang, T. (eds.) UbiComp 2007. LNCS, vol. 4717, pp. 271–288. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  27. 27.
    Poh, M., Swenson, N., Picard, R.: A wearable sensor for unobtrusive, long-term assessment of electrodermal activity. IEEE Transactions on Biomedical Engineering 57(5), 1243–1252 (2010)CrossRefGoogle Scholar
  28. 28.
    Rescuetime (2012),
  29. 29.
    Rosenblueth, A., Wiener, N., Bigelow, J.: Behavior, Purpose and Teleology. Philosophy of Science 10(1), 18–24 (1943)CrossRefGoogle Scholar
  30. 30.
    Schön, D.A.: Educating the Reflective Practitioner. Jossey-Bass (1987)Google Scholar
  31. 31.
    Sellen, A.J., Whittaker, S.: Beyond total capture: a constructive critique of lifelogging. Commun. ACM 53, 70–77 (2010)CrossRefGoogle Scholar
  32. 32.
    Skinner, B.F.: About behaviorism. Knopf (1974)Google Scholar
  33. 33.
    The Quantified Self (2012),
  34. 34.
    Wright, D.B., Loftus, E.F.: Eyewitness memory, pp. 18–40. Routledge, New York (2008)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Lars Müller
    • 1
  • Verónica Rivera-Pelayo
    • 1
  • Stephan Heuer
    • 1
  1. 1.FZI Research Center of Information TechnologyKarlsruheGermany

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