AutoTutor: An Intelligent Tutoring System With Mixed-Initiative Dialogue
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Abstract
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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Authors
4Topics & keywords
Topics
Keywords
- TUTOR
- Conversation
- Computer science
- Software deployment
- Human–computer interaction
- Architecture
- Intelligent tutoring system
- Measure (data warehouse)
UN Sustainable Development Goals
- Quality Education
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