Face-to-Face Interaction with Pedagogical Agents, Twenty Years Later
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Johnson et al. (International Journal of Artificial Intelligence in Education, 11, 47–78, 2000) introduced and surveyed a new paradigm for interactive learning environments: animated pedagogical agents. The article argued for combining animated interface agent technologies with intelligent learning environments, yielding intelligent systems that can interact with learners in natural, human-like ways to achieve better learning outcomes. We outlined a variety of possible uses for pedagogical agents. But we offered only preliminary evidence that they improve learning, leaving that to future research and development. Twenty years have elapsed since work began on animated pedagogical agents. This article re-examines the concepts and predictions in the 2000 article in the context of the current state of the field. Some of the ideas in the paper have become well established and widely adopted, especially in game-based learning environments. Others are only now being realized, thanks to advances in immersive interfaces and robotics that enable rich face-to-face interaction between learners and agents. Research has confirmed that pedagogical agents can be beneficial, but not equally for all learning problems, applications, and learner populations. Although there is a growing body of research findings about pedagogical agents, many questions remain and much work remains to be done.
KeywordsPedagogical agents Game-based learning Virtual tutors Virtual coaches Virtual environments Robotics Teachable agents
The authors wish to acknowledge the contributions of our third co-author, Jeff Rickel, who passed away a few years after the publication of the 2000 article. Jeff’s ideas and research contributions laid much of the groundwork for subsequent work on pedagogical agents. This research was supported in part by the National Science Foundation under Grants DRL-0822200, DRL-1020229, IIS-1138497, IIS-1321056, IIS-1344803, and IIS-1409639. Any opinions, findings, and conclusions expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.
- Arroyo, I., Cooper, D.G., Burleson, W., Woolf, B.P., Muldner, K. & Christopherson, R.M. (2009). Emotion Sensors Go To School. In 14th International Conference on Artificial Intelligence in Education, 17–24.Google Scholar
- Artstein, R., Traum, D., Alexander, O., Leuski, A., Jones, A., Georgila, K., Debevec, P., Swartout, W., Maio, H., & Smith, S. (2014). Time-offset interaction with a Holocaust survivor. In IUI ′14: Proceedings of the 19th International Conference on Intelligent User Interfaces (163–168). New York: ACM Press. doi: 10.1145/2557500.2557540#_blank.
- Baylor, A. L., Ryu, J., & Shen, E. (2003). The effects of pedagogical agent voice and animation on learning, motivation, and perceived persona. Paper presented at the Annual World Conference of Educational Multimedia, Hypermedia, & Telecommunication, Honolulu, Hawaii, 2003.Google Scholar
- Grafsgaard, J., Wiggins, J., Boyer, K., Wiebe, E., & James, L. (2014). Predicting Learning and Affect from Multimodal Data Streams in Task-Oriented Tutorial Dialogue. Proceedings of the Seventh International Conference on Educational Data Mining, London, England, 122–129.Google Scholar
- Johnson, W. L. (2010a). Serious use of a serious game for language learning. International Journal of Artificial Intelligence in Education, 20(2), 175–195.Google Scholar
- Johnson, W. L., & Wang, N. (2010b). The Role of Politeness in Interactive Educational Software. In C.C. Hayes & C.A. Miller (Eds.), Human-Computer Etiquette, 91–113. New York: Taylor and Francis. doi: 10.1201/b10420-8.
- Johnson, W.L. (2015a). Cultural training as behavior change. Proceedings of the 4th International Conference on Cross-Cultural Decision Making. London: CRC Press.Google Scholar
- Johnson, W.L. (2015b). Constructing Virtual Role-Play Simulations. in R Sottilare, A. Graesser, X. Hu, K. Brawner (Eds.), Design Recommendations for Adaptive Intelligent Tutoring Systems: Authoring Tools, 3, 211-226. Orlando: US Army Research Laboratory.Google Scholar
- Johnson, W. L., Rickel, J. W., & Lester, J. C. (2000). Animated pedagogical agents: face-to-face interaction in interactive learning environments. IJAIED, 11, 47–78.Google Scholar
- Johnson, W.L., Friedland, L., Schrider, P., Valente, A., & Sheridan, S. (2011). The Virtual Cultural Awareness Trainer (VCAT): Joint Knowledge Online’s (JKO’s) Solution to the Individual Operational Culture and Language Training Gap. In Proceedings of ITEC 2011. London: Clarion Events.Google Scholar
- Kapoor, A., & Picard, R.W. (2005). Multimodal Affect Recognition in Learning Environments. In Proceedings of the 13th Annual ACM International Conference on Multimedia, 677–682. doi: 10.1145/1101149.1101300.
- Kim, Y., & Baylor, A. (2015). Research-based design of pedagogical agent roles: a review, progress, and recommendations. International Journal of Artificial Intelligence in Education, 25.Google Scholar
- Kim, J., Hill, R. W., Durlach, P. J., Lane, H. C., Forbell, E., Core, M., Marsella, S. C., et al. (2009). Bilat: a game-based environment for practicing negotiation in a cultural context. International Journal of Artificial Intelligence in Education, 19(3), 289–308.Google Scholar
- Laurel, B. (1990). Interface agents: Metaphors with character. In B. Laurel (Ed.), The art of human-computer interface design, 355-365. New York: Addison-Wesley.Google Scholar
- Lester, J.C., Converse, S.A., Kahler, S.E., Barlow, S.T. Stone, B.A., & Bhogal, R.S. (1997a). The persona effect: Affective impact of animated pedagogical agents. In Proceedings of CHI’97, 359–366. doi: 10.1145/258549.258797.
- Lester, J.C., Converse, S.A., Stone, B.A., Kahler, S.E., & Barlow, S.T. (1997b). Animated pedagogical agents and problem-solving effectiveness: A large-scale empirical evaluation. In Proceedings of the Eighth World Conference on Artificial Intelligence in Education (pp. 23–30). Amsterdam: IOS Press.Google Scholar
- McLaren, B. M., Sosnovsky, S., & Aleven, V. (2014). Preface – emerging technologies and landmark systems for learning mathematics and science: dedicated to the memory of Erica Melis – Part 1. International Journal of Artificial Intelligence in Education, 24(3), 211–215. doi: 10.1007/s40593-014-0021-0.CrossRefGoogle Scholar
- McQuiggan, S., Lee, S., & Lester, J. (2007). Early prediction of student frustration. In Proc. of the 2nd Intl. Conf. on Affective Computing and Intelligent Interaction, 698–709. doi: 10.1007/978-3-540-74889-2_61.
- Nagao, K., & Takeuchi, A. (1994). Social interaction: Multimodal conversation with social agents. In Proceedings of the Twelfth National Conference on Artificial Intelligence (AAAI-94) (pp. 22–28). Menlo Park, CA: AAAI Press.Google Scholar
- Nye, B. D., Graesser, A. C., & Hu, X. (2014). AutoTutor and family: a review of 17 years of natural language tutoring. International Journal of Artificial Intelligence in Education, 24(4), 427–469. doi: 10.1007/s40593-014-0029-5.
- Rickel, J., & Johnson, W.L. (1999). Virtual humans for team training in virtual reality. In Proceedings of the Ninth International Conference on Artificial Intelligence in Education. Amsterdam: IOS Press.Google Scholar
- Rowe, J., Shores, L., Mott, B., & Lester, J. (2011). Integrating learning, problem solving, and engagement in narrative-centered learning environments. International Journal of Artificial Intelligence in Education, 21(1), 115–133.Google Scholar
- Sabourin, J., Mott, B., and Lester, J. (2011). Modeling learner affect with theoretically grounded dynamic bayesian networks. Proceedings of the Fourth International Conference on Affective Computing and Intelligent Interaction, Memphis, Tennessee, 286–295. doi: 10.1007/978-3-642-24600-5_32.
- Schank, R. (2010). Learning through storytelling, not documents: knowledge management meets AI. eLearn Magazine, October 2010. Retrieved June 9, 2015 from http://elearnmag.acm.org/featured.cfm?aid=1872819.
- Schroeder, N, Adesope, O., & Gilbert, R. (2013). How effective are pedagogical agents for learning? A meta-analytic review. Journal of Educational Computing Research, 49(1): 1–39. doi: 10.2190/ec.49.1.a.
- Shaw, E., Johnson, W.L., & Ganeshan, R. (1999). Pedagogical agents on the Web. In Proceedings of the Third International Conference on Autonomous Agents, 578-585. New York: ACM Press. doi: 10.1145/301136.301210.
- Swartout, W., Artstein, R., Forbell, E., Foutz, S., Lane, H. C., Lange, B., Morie, J., Noren, D., Rizzo, S., & Traum, D. (2013). Virtual humans for learning. AI Magazine, 34(4), 13–30.Google Scholar
- Woolf, B. P., Arroyo, I., Muldner, K., Burleson, W., Cooper, D. G., Dolan, R., & Christopherson, R. M. (2010). The effect of motivational learning companions on low achieving students and students with disabilities. In Proceedings of the 10th International Conference on Intelligent Tutoring Systems (pp. 327–337). Berlin: Springer. doi: 10.1007/978-3-642-13388-6_37.