| Project/Area Number |
16500605
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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 | Takushoku University |
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Principal Investigator |
TAKEYA Makoto Takushoku Univ., Faculty of Engineering, Professor, 工学部, 教授 (90197343)
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| Co-Investigator(Kenkyū-buntansha) |
SASAKI Hitoshi Takushoku Univ., Faculty of Engineering, Associate Prof., 助教授 (80276675)
SUGIBAYASI Toshio Takushoku University, Faculty of Engineering, Professor, 教授 (80171172)
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| Project Period (FY) |
2004 – 2005
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| Project Status |
Completed (Fiscal Year 2005)
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| Budget Amount *help |
¥3,700,000 (Direct Cost: ¥3,700,000)
Fiscal Year 2005: ¥1,400,000 (Direct Cost: ¥1,400,000)
Fiscal Year 2004: ¥2,300,000 (Direct Cost: ¥2,300,000)
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| Keywords | virtual reality / virtual space / learning environment / structural knowledge / teaching material / e-learning / バーチャルリアリティ / 仮想現実感 / バーチャルスクール / プラットフォーム / 3D / アバタ / マルチメディア / マルチメディア教材 |
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| Research Abstract |
In education field it has been pointed out that it is important to present learning environment for virtual space and collaborative learning. These learning systems have been developed and utilized in several fields. It is, however, pointed out that there are a lot of problems in cost, equipments and facilities. This paper presents a distance learning system, called a Virtual School, by using virtual reality technology. Secondly, in order to present a new collaborative learning, this paper presents Logical Flow Testing method, called LFT method. This paper discusses classification of similarity indices between a pair of logical flow graphs. Thirdly, this paper discusses an estimation method of learning strategies of individual students based on Strategic Task Sequencing method, called STS method that had been presented by Takeya. The optimum learning sequence is able to obtained according to some instructional strategy by using the STS method. Contrary to this, this paper discusses an estimation method for instructional strategy of a sequence according to the STS method. This estimation method can be realized by introducing membership functions on two parameters that present characteristics of learning strategies.
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