A Category-based Framework of a Self-improving Instructional Planner
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概要
- 論文の詳細を見る
To have an instructional plan guide the learning process is significant to various teaching styles and an important task in an ITS. Though various approaches have been used to tackle this task, the compelling need is for an ITS to improve on its own the plans established in a dynamic way. We hypothesize that the use of knowledge derived from student categories can significantly support the improvement of plans on the part of the ITS. This means that category knowledge can become effectors of effective plans. We have conceived a Category-based Self-improving Planning Module (CSPM) for an ITS tutor agent that utilizes the knowledge learned from learner categories to support self-improvement. The learning framework of CSPM employs unsupervised machine learning and knowledge acquisition heuristics for learning from experience. We have experimented on the feasibility of CSPM using recorded teaching scenarios.
- 社団法人 人工知能学会の論文
- 2006-11-01
著者
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NUMAO MASAYUKI
The Institute of Scientific and Industrial Research, Osaka University
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Numao Masayuki
The Institute Of Scientific And Industrial Research Osaka University
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Legaspi Roberto
The Institute Of Scientific And Industrial Research Osaka University
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Sison Raymund
College Of Computer Studies De La Salle University - Manila
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Numao Masayuki
Osaka Univ.
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