Readings in knowledge acquisition and learning: automating the construction and improvement of expert systems
Machine learning and knowledge acquisition: integrated approaches
Machine learning and knowledge acquisition: integrated approaches
Building Intelligent Agents: An Apprenticeship Multistrategy Learning Theory, Methodology, Tool and Case Studies
Toward a Unification of Human-Computer Learning and Tutoring
ITS '98 Proceedings of the 4th International Conference on Intelligent Tutoring Systems
Toward a Unification of Human-Computer Learning and Tutoring
ITS '98 Proceedings of the 4th International Conference on Intelligent Tutoring Systems
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Disciple is an apprenticeship, multistrategy learning approach for developing intelligent agents where an expert teaches the agent how to perform domain-specific tasks in a way that resembles how the expert would teach an apprentice. We claim that Disciple can naturally be used to build certain types of educational agents. Indeed, an educator can teach a Disciple agent which in turn can tutor students in the same way it was taught by the educator. This paper presents the Disciple approach and its application to developing an educational agent that generates history test questions. The agent provides intelligent feedback to the student in the form of hints, answer and explanations, and assists in the assessment of student's understanding and use of higher-order thinking skills.