期刊
IEEE TRANSACTIONS ON EDUCATION
卷 48, 期 4, 页码 612-618出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TE.2005.856149
关键词
conversational agents; intelligent tutoring systems; natural language dialogue; STEM learning; tutoring
AutoTtitor 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, AutoTbtor 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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