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Tinker: a relational agent museum guide

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Abstract

A virtual museum guide agent that uses human relationship-building behaviors to engage museum visitors is described. The computer animated agent, named “Tinker”, uses nonverbal conversational behavior, empathy, social dialogue, reciprocal self-disclosure and other relational behavior to establish social bonds with users, and encourage continued interaction and repeated visits. Tinker describes exhibits in the museum, gives directions, and discusses technical aspects of her own implementation. Tinker also recognizes returning visitors through biometric analysis of their hand shapes and dialogue cues. Results from two experiments using Tinker are described. In the first, 29 returning visitors are randomized to interact with the agent with the biometric identification turned on or off. In the second experiment, 1,607 visitors are randomized to interact with versions of Tinker that have relationship-building behavior turned on or off. Results indicate that the use of relational behavior leads to significantly greater engagement by museum visitors, measured by session length, number of sessions, and self-reported attitude, as well as learning gains, as measured by a knowledge test, compared to the same agent that does not use relational behavior. Implications for museum exhibits and intelligent tutoring systems are discussed.

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References

  1. Tran, L. (2007). Teaching science in museums: The pedagogy and goals of museum educators. Science Education, 91, 278–297.

    Article  Google Scholar 

  2. Hein, G. E. (1998). Learning in the museum. New York: Psychology Press.

    Google Scholar 

  3. Moon, Y. (1998). Intimate self-disclosure exchanges: Using computers to build reciprocal relationships with consumers. Cambridge, MA: Harvard Business School.

    Google Scholar 

  4. Cassell, J., Sullivan, J., Prevost, S., & Churchill, E. (Eds.). (2000). Embodied conversational agents. Cambridge, MA: The MIT Press.

    Google Scholar 

  5. Schulman, D., Sharma, M., & Bickmore, T. (2008). The identification of users by relational agents. In Autonomous agents and multi-agent systems (AAMAS).

  6. Wentzel, K. (1999). Social-motivational processes and interpersonal relationships: Implications for understanding motivation at school. Journal of Educational Psychology, 91(1), 76–97.

    Article  Google Scholar 

  7. Yee, N., Bailenson, J., & Rickertsen, K. (2007). A meta-analysis of the impact of the inclusion and realism of human-like faces on user experiences in interfaces. In Conference on human factors in computing systems (CHI).

  8. Damon, W., & Phelps, E. (1989). Strategic uses of peer learning in children’s education. In T. Berndt & G. Ladd (Eds.), Peer relationships in child development (pp. 135–157). New York: Wiley.

    Google Scholar 

  9. Rohrbeck, C., Ginsburg-Block, A., Marika, D., Fantuzzo, J., & Miller, T. (2003). Peer-assisted learning interventions with elementary school students: A meta-analytic review. Journal of Educational Society, 94(2), 240–257.

    Google Scholar 

  10. Hartup, W. (1996). Cooperation, close relationships, and cognitive development. In W. Bukowski, A. Newcomb, & W. Hartup (Eds.), The company they keep: Friendship in childhood and adolescence (pp. 213–237). Cambridge, MA: Cambridge University Press.

  11. Graesser, A., Wiemer-Hastings, K., Wiemer-Hastings, P., & Kreuz, R. (1999). AutoTutor: A simulation of a human tutor. Journal of Cognitive Systems Research, 1, 35–51.

    Article  Google Scholar 

  12. Graesser, A., Moreno, K., Marineau, J., Adcock, A., Olney, A., & Person, N. (2003). AutoTutor improves deep learning of computer literacy: Is it the dialog or the talking head?. Sydney: Artificial Intelligence in Education.

    Google Scholar 

  13. D’Mello, S., Graesser, A., & Picard, R. (2007). Toward an affect-sensitive AutoTutor. IEEE Intelligent Systems, 22(4), 53–61.

    Article  Google Scholar 

  14. D’Mello, S., Lehman, B., Sullins, J., Daigle, R., Combs, R., Vogt, K., et al. (2010). A time for emoting: When affect-sensitivity is and isn’t effective at promoting deep learning. In V. Aleven, J. Kay, & J. Mostow (Eds.), Intelligent tutoring systems (Vol. 6094, pp. 245–254). Berlin: Springer.

  15. D’Mello, S., Olney, A., Williams, C., & Hays, P. (2012). Gaze tutor: A gaze-reactive intelligent tutoring system. International Journal of Human-Computer Studies, 70(5), 377–398.

    Article  Google Scholar 

  16. Lester, J. C., Voerman, J. L., Towns, S. G., & Callaway, C. B. (1997). Cosmo: A life-like animated pedagogical agent with deictic believability. In International joint conference on artificial intelligence (IJCAI).

  17. Lester, J., Stone, B., & Stelling, G. (1999). Lifelike pedagogical agents for mixed-initiative problem solving in constructivist learning environments. User Modeling and User-Adapted Interaction, 9(1–2), 1–44.

    Article  Google Scholar 

  18. Baylor, A., & Ryu, J. (2003). The effects of image and animation in enhancing pedagogical agent persona. Journal of Educational Computing Research, 28(4), 373–394.

    Article  Google Scholar 

  19. Baylor, A., & Kim, S. (2008). The effects of agent nonverbal communication on procedural and attitudinal learning outcomes. In H. Prendinger, J. Lester, & M. Ishizuka (Eds.), Intelligent virtual agents (IVA).

  20. Krämer, N. C., & Bente, G. (2010). Personalizing e-Learning. The social effects of pedagogical agents. Educational Psychology Review, 22(1), 71–87.

    Article  Google Scholar 

  21. Kopp, S., Gesellensetter, L., Krämer, N., & Wachsmuth, I. (2005). A conversational agent as museum guide–design and evaluation of a real-world application. In Intelligent virtual agents (IVA) (pp. 329–343). Berlin: Springer.

  22. Shiomi, M., Kanda, T., Ishiguro, H., & Hagita, N. (2006). Interactive humanoid robots for a science museum. Human-robot interaction (HRI).

  23. Swartout, W., Traum, D., Artstein, R., Noren, D., Debevec, P., Bronnenkant, K., et al. (2010). Ada and Grace: Toward realistic and engaging virtual museum guides. In Intelligent virtual agents (IVA).

  24. Kuno, Y., Sadazuka, K., Kawashima, M., Yamazaki, K., Yamazaki, A., & Kuzuoka, H. (2007). Museum guide robot based on sociological nteraction analysis. In Conference on human factors in computing systems (CHI).

  25. Gockley, R., Bruce, A., Forlizzi, J., Michalowski, M., Mundell, A., Rosenthal, S., et al. (2005). Designing robots for long-term social interaction. In IEEE/RSJ international conference on intelligent robots and systems.

  26. Traum, D., Aggarwal, P., Artstein, R., Foutz, S., Gerten, J., Katsamanis, A., et al. (2012). Ada and Grace: Direct interaction with museum visitors. Intelligent virtual agents (IVA).

  27. Burgard, W., Cremers, A., Fox, D., Hahnel, D., Lakemeyer, G., Schulz, D., et al. (1997). The interactive museum tour-guide robot. In Artificial intelligence/innovative applications of artificial intelligence (AAAI ’98/IAAI ’98) (pp. 11–18). American Association for Artificial Intelligence.

  28. Burgard, W., Cremers, A., Fox, D., Hähnel, D., Lakemeyer, G., Schulz, D., et al. (1999). Experiences with an interactive museum tourguide robot. Artificial Intelligence, 114(1–2), 3–55.

    Article  MATH  Google Scholar 

  29. Thrun, S., Bennewitz, M., Burgard, W., Cremers, A., Dellaert, F., & Fox, D., et al. (1999). MINERVA: A second-generation museum tour-guide robot. In IEEE International Conference on Robotics and Automation.

  30. Clodic, A., Fleury, S., Alami, R., Chatila, R., Bailly, G., & Brèthes, L. (2006). Rackham: An interactive robot-guide. In IEEE international symposium on human and robot interactive communication (ROMAN).

  31. Karreman, D., van Dijk, E., & Evers, V. (2012). Using the visitor experiences for mapping the possibilities of implementing a robotic guide in outdoor sites. In IEEE international symposium on robot and human interactive communication (ROMAN).

  32. Bickmore, T., & Picard, R. (2005). Establishing and maintaining long-term human–computer relationships. ACM Transactions on Computer Human Interaction, 12(2), 293–327.

    Article  Google Scholar 

  33. Jain, A., Ross, A., & Prabhakar, S. (2004). An introduction to biometric recognition. IEEE Transactions on Circuits and Systems for Video Technology, 14(1), 4–20.

    Article  Google Scholar 

  34. Kukula, E., & Elliott, S. (2006). Implementation of hand geometry: An analysis of user perspectives and system performance. IEEE Aerospace and Electronic Systems Magazine, 21(3), 3–9.

    Article  Google Scholar 

  35. Jain, A., Ross, A., & Pankanti, S. (1999). A prototype hand geometry-based verification system. In International conference on audio- and video-based biometric person authentication (AVBPA).

  36. Duta, N. (2009). A survey of biometric technology based on hand shape. Pattern Recognition, 42(11), 2797–2806.

    Article  Google Scholar 

  37. Cassell, J., Vilhjálmsson, H., & Bickmore, T. (2001). BEAT: The behavior expression animation toolkit (pp. 477–486). Los Angeles: SIGGRAPH.

    Google Scholar 

  38. Bickmore, T., Caruso, L., Clough-Gorr, K., & Heeren, T. (2005). It’s just like you talk to a friend—relational agents for older adults. Interacting with Computers, 17(6), 711–735.

    Article  Google Scholar 

  39. Bickmore, T., Pfeifer, L., & Schulman, D. (2011). Relational agents improve engagement and learning in science museum visitors. In Intelligent virtual agents conference (IVA), Reykjavik, Iceland.

  40. Wong, A., & Shi, P. (2002). Peg-free hand geometry recognition using hierarchical geometry and shape matching. IAPR Workshop on Machine Vision Applications.

  41. Vapnik, V. (1998). Statistical learning theory. New York: Wiley.

    MATH  Google Scholar 

  42. Havens, L. (1986). Making contact: Uses of language in psychotherapy. Cambridge, MA: Harvard University Press.

    Google Scholar 

  43. Gelso, C., & Hayes, J. (1998). The psychotherapy relationship: Theory, research and practice. New York: Wiley.

  44. Svennevig, J. (1999). Getting acquainted in conversation. Philadephia: John Benjamins.

    Google Scholar 

  45. Altman, I., & Taylor, D. (1973). Social penetration: The development of interpersonal relationships. New York: Holt, Rinhart & Winston.

    Google Scholar 

  46. Gill, D., Christensen, A., & Fincham, F. (1999). Predicting marital satisfaction from behavior: Do all roads really lead to Rome? Personal Relationships, 6, 369–387.

    Article  Google Scholar 

  47. Cole, T., & Bradac, J. (1996). A lay theory of relational satisfaction with best friends. Journal of Social and Personal Relationships, 13(1), 57–83.

    Article  Google Scholar 

  48. Laver, J. (1981). Linguistic routines and politeness in greeting and parting. In F. Coulmas (Ed.), Conversational routine (pp. 289–304). The Hague: Mouton.

    Google Scholar 

  49. Okun, B. (1997). Effective helping: Interviewing and counseling techniques. Pacific Grove, CA: Brooks/Cole.

    Google Scholar 

  50. Bickmore, T., Pfeifer, L., Schulman, D., Perera, S., Senanayake, C., & Nazmi, I. (2008). Public displays of affect: Deploying relational agents in public spaces. In Conference on human factors in computing systems (CHI), Florence, Italy.

  51. Goffman, I. (1967). On face-work. Interaction ritual: Essays on face-to-face behavior (pp. 5–46). New York: Pantheon.

    Google Scholar 

  52. Baron, R., & Kenny, D. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173–1182.

    Article  Google Scholar 

  53. MacKinnon, D. P., Lockwood, C. M., Hoffman, J. M., West, S. G., & Sheets, V. (2002). A comparison of methods to test mediation and other intervening variable effects. Psychological methods, 7, 83–104.

    Article  Google Scholar 

  54. Andersen, J. (1980). Teacher immediacy as a predictor of teaching effectiveness. Communication Yearbook, 3, 543–559.

    Google Scholar 

  55. Witt, P., Wheeless, L., & Allen, M. (2004). A meta-analytical review of the relationship between teacher immediacy and student learning. Communication Monographs, 71(2), 184–207.

    Article  Google Scholar 

  56. Christophel, D. (1990). The relationships among teacher immediacy behaviors, student motivation, and learning. Communication Education, 39(4), 323–340.

    Article  Google Scholar 

  57. Kelley, D., & Gorham, J. (1988). Effects of immediacy on recall of information. Communication Education, 37(3), 198–207.

    Article  Google Scholar 

  58. Gorham, J. (1988). The relationship between verbal teacher immediacy behaviors and student learning. Communication Education, 37(1), 40–53.

    Article  Google Scholar 

  59. Bickmore, T., Schulman, D., & Yin, L. (2010). Maintaining engagement in long-term interventions with relational agents. International Journal of Applied Artificial Intelligence, 24(6), 648–666.

    Article  Google Scholar 

  60. Kidd, C., & Breazeal, C. (2004). Effect of a robot on user perceptions. In IEEE/RSJ international conference on intelligent robots and systems (IROS 2004), Sendai, Japan.

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Acknowledgments

Thanks to Sepalika Perera, Chaamari Senanayake, and Ishraque Nazmi, who helped develop the original Tinker system, to Dan Noren, Taleen Agulian and the staff at Computer Place at the Boston Museum of Science for their assistance, and to Juan Fernandez for maintaining Tinker over the last three years. This material is based upon work supported by the National Science Foundation under Grant No. CAREER IIS- 0545932. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

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Correspondence to Timothy W. Bickmore.

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Bickmore, T.W., Vardoulakis, L.M.P. & Schulman, D. Tinker: a relational agent museum guide. Auton Agent Multi-Agent Syst 27, 254–276 (2013). https://doi.org/10.1007/s10458-012-9216-7

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