Face-to-Face Interaction with Pedagogical Agents, Twenty Years Later

详细信息    查看全文

• 作者：W. Lewis Johnson ; James C. Lester
• 关键词：Pedagogical agents ; Game ; based learning ; Virtual tutors ; Virtual coaches ; Virtual environments ; Robotics ; Teachable agents
• 刊名：International Journal of Artificial Intelligence in Education
• 出版年：2016
• 出版时间：March 2016
• 年：2016
• 卷：26
• 期：1
• 页码：25-36
• 全文大小：559 KB
• 参考文献：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.
  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.
  Biswas, G., Leelawong, K., Schwartz, D., & Vye, N. (2005). Learning by teaching: a new agent paradigm for educational software. Applied Artificial Intelligence, 19(3–4), 363–392. doi:10.​1080/​0883951059091020​0 .CrossRef
  Chi, M., Bassok, M., Lewis, M., Reimann, P., & Glaser, R. (1989). Self‐explanations: how students study and use examples in learning to solve problems. Cognitive Science, 13(2), 145–182. doi:10.​1207/​s15516709cog1302​_​1 .CrossRef
  D’Mello, S. K., & Graesser, A. C. (2010). Multimodal semi-automated affect detection from conversational cues, gross body language, and facial features. User Modeling and User-Adapted Interaction, 20(2), 147–187. doi:10.​1007/​s11257-010-9074-4 .CrossRef
  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.
  Hayes-Roth, B., & Doyle, P. (1998). Animate characters. Autonomous Agents and Multi-Agent Systems, 1(2), 195–230.CrossRef
  Johnson, W. L. (2010a). Serious use of a serious game for language learning. International Journal of Artificial Intelligence in Education, 20(2), 175–195.
  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.
  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.
  Johnson, W. L., Rickel, J. W., Stiles, R., & Munro, A. (1998). Integrating pedagogical agents into virtual environments. Presence: Teleoperators and Virtual Environments, 7(6), 523–546. doi:10.​1162/​105474698565929 .CrossRef
  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.
  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.
  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.
  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.
  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.
  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.
  Lester, J. C., Stone, B. A., & Stelling, G. D. (1999). Lifelike pedagogical agents for mixed-initiative problem solving in constructivist learning environments. User Modeling and User-Adapted Interaction, 9, 1–44. doi:10.​1007/​978-94-017-1118-0_​5 .CrossRef
  Mayer, R. E., & DaPra, C. S. (2012). An embodiment effect in computer-based learning with an animated pedagogical agent. Journal of Experimental Psychology: Applied, 18, 239–252. doi:10.​1037/​a0028616 .
  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 .CrossRef
  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 .
  Moreno, R., Mayer, R. E., Spires, H., & Lester, J. (2001). The case for social agency in computer-based teaching: do students learn more deeply when they interact with animated pedagogical agents? Cognition and Instruction, 19, 177–214. doi:10.​1207/​s1532690xci1902_​02 .CrossRef
  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.
  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.
  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.
  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.
  Veletsianos, G. (2010). Contextually relevant pedagogical agents: visual appearance, stereotypes, and first impressions and their impact on learning. Computers & Education, 55(2), 576–585. doi:10.​1016/​j.​compedu.​2010.​02.​019 .CrossRef
  Wang, N., Johnson, W. L., Mayer, R. E., Rizzo, P., Shaw, E., & Collins, H. (2008). The politeness effect: pedagogical agents and learning outcomes. International Journal of Human Computer Studies, 66, 96–112. doi:10.​1016/​j.​ijhcs.​2007.​09.​003 .CrossRef
  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 .
  
• 作者单位：W. Lewis Johnson (1)
  James C. Lester (2)
  
  1. Alelo Inc., Los Angeles, CA, USA
  2. North Carolina State University, Raleigh, NC, USA
  
• 刊物类别：Artificial Intelligence (incl. Robotics); Educational Technology; User Interfaces and Human Computer
• 刊物主题：Artificial Intelligence (incl. Robotics); Educational Technology; User Interfaces and Human Computer Interaction; Computers and Education;
• 出版者：Springer New York
• ISSN：1560-4306

文摘

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.