导师
对话
计算机科学
软件部署
人机交互
建筑
智能教学系统
度量(数据仓库)
多媒体
人工智能
数学教育
程序设计语言
心理学
软件工程
视觉艺术
沟通
数据库
艺术
作者
Arthur C. Graesser,Patrick Chipman,Brian C. Haynes,Andrew McGregor Olney
标识
DOI:10.1109/te.2005.856149
摘要
AutoTutor simulates a human tutor by holding a conversation with the learner in natural language. The dialogue is augmented by an animated conversational agent and three-dimensional (3-D) interactive simulations in order to enhance the learner's engagement and the depth of the learning. Grounded in constructivist learning theories and tutoring research, AutoTutor achieves learning gains of approximately 0.8 sigma (nearly one letter grade), depending on the learning measure and comparison condition. The computational architecture of the system uses the .NET framework and has simplified deployment for classroom trials.
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