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

被引:123
作者
Johnson W.L. [1 ]
Lester J.C. [2 ]
机构
[1] Alelo Inc., Los Angeles, CA
[2] North Carolina State University, Raleigh, NC
基金
美国国家科学基金会;
关键词
Game-based learning; Pedagogical agents; Robotics; Teachable agents; Virtual coaches; Virtual environments; Virtual tutors;
D O I
10.1007/s40593-015-0065-9
中图分类号
学科分类号
摘要
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. © 2015 International Artificial Intelligence in Education Society.
引用
收藏
页码:25 / 36
页数:11
相关论文
共 38 条
[21]  
Lester J.C., Converse S.A., Stone B.A., Kahler S.E., Barlow S.T., Animated pedagogical agents and problem-solving effectiveness: A large-scale empirical evaluation, Proceedings of the Eighth World Conference on Artificial Intelligence in Education, pp. 23-30, (1997)
[22]  
Lester J.C., Stone B.A., Stelling G.D., Lifelike pedagogical agents for mixed-initiative problem solving in constructivist learning environments, User Modeling and User-Adapted Interaction, 9, pp. 1-44, (1999)
[23]  
Mayer R.E., DaPra C.S., An embodiment effect in computer-based learning with an animated pedagogical agent, Journal of Experimental Psychology: Applied, 18, pp. 239-252, (2012)
[24]  
McLaren B.M., Sosnovsky S., Aleven V., 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, pp. 211-215, (2014)
[25]  
McQuiggan S., Lee S., Lester J., Early prediction of student frustration, Proc. of the 2nd Intl. Conf. on Affective Computing and Intelligent Interaction, pp. 698-709, (2007)
[26]  
Moreno R., Mayer R.E., Spires H., Lester J., 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, pp. 177-214, (2001)
[27]  
Nagao K., Takeuchi A., Social interaction: Multimodal conversation with social agents, Proceedings of the Twelfth National Conference on Artificial Intelligence (AAAI-94), pp. 22-28, (1994)
[28]  
Nye B.D., Graesser A.C., Hu X., AutoTutor and family: A review of 17 years of natural language tutoring, International Journal of Artificial Intelligence in Education, 24, 4, pp. 427-469, (2014)
[29]  
Rickel J., Johnson W.L., Virtual humans for team training in virtual reality, Proceedings of the Ninth International Conference on Artificial Intelligence in Education, (1999)
[30]  
Rowe J., Shores L., Mott B., Lester J., Integrating learning, problem solving, and engagement in narrative-centered learning environments, International Journal of Artificial Intelligence in Education, 21, 1, pp. 115-133, (2011)