| Project/Area Number |
22500897
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Educational technology
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| Research Institution | Aichi Institute of Technology |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
NAKAMURA Syouji 金城学院大学, 生活環境学部, 教授 (30350953)
MIZUTANI Satoshi 愛知工科大学, 工学部, 助教 (40469060)
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| Project Period (FY) |
2010 – 2012
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| Project Status |
Completed (Fiscal Year 2012)
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| Budget Amount *help |
¥2,600,000 (Direct Cost: ¥2,000,000、Indirect Cost: ¥600,000)
Fiscal Year 2012: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2011: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2010: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
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| Keywords | 教授学習支援システム / 教育工学 / e-learning / 確率過程 / 信頼性理論 / 最適履修学生支援方策 / 確率過程モデル / 教育支援 / 対面教育 / 機械学習 / 確率モデル / 最適方策 |
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| Research Abstract |
In e-learning system, the possibility of dropout passes is pointed out a student by a study subject. In the appropriate meeting guidance to a student, an effective and an efficient education is pointed out one of the education accountability and the accountability for the society. We took it based on maintenance and reliability theory that we have studied for many years, and we have studied the method of the face to face study support to e-learning system. In this study, we apply the adaptive learning method to an understanding process of student by a detailed study history which was available from e-learning system and drive an optimal time of face to face study support by the machine learning system．We published titel of ”Optimal study number of stochastice-learning system” in Int. J. Knowledge and Web Intelligence.
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