| Project/Area Number |
16300263
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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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 | TOKYO INSTITUTE OF TECHNOLOGY |
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Principal Investigator |
NAKAYAMA Minoru TOKYO INSTITUTE OF TECHNOLOGY, TEH CENTER FOR RESEACH AND DEVELOPMENT OF EDUCATIONAL TECHNOLOGY, Assoc. Professor, 教育工学開発センター, 助教授 (40221460)
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| Co-Investigator(Kenkyū-buntansha) |
AKAHORI Kanji TOKYO INSTITUTE OF TECHNOLOGY TEH CENTER FOR RESEACH AND DEVELOPMENT OF EDUCATIONAL TECHNOLOGY, Professor, 教育工学開発センター, 教授 (80143626)
NISHIHARA Akinori TOKYO INSTITUTE OF TECHNOLOGY TEH CENTER FOR RESEACH AND DEVELOPMENT OF EDUCATIONAL TECHNOLOGY, Professor, 教育工学開発センター, 教授 (90114884)
NISHIKATA Atsuhiro TOKYO INSTITUTE OF TECHNOLOGY TEH CENTER FOR RESEACH AND DEVELOPMENT OF EDUCATIONAL TECHNOLOGY, Assoc. Professor, 教育工学開発センター, 助教授 (60260535)
YAMAMOTO Hiroh SHINSHU UNIVERSITY, SCHOOL OF GENERAL EDUCATION, Professor, 全学教育機構, 教授 (70345768)
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| Project Period (FY) |
2004 – 2006
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| Project Status |
Completed (Fiscal Year 2006)
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| Budget Amount *help |
¥8,800,000 (Direct Cost: ¥8,800,000)
Fiscal Year 2006: ¥1,500,000 (Direct Cost: ¥1,500,000)
Fiscal Year 2005: ¥2,800,000 (Direct Cost: ¥2,800,000)
Fiscal Year 2004: ¥4,500,000 (Direct Cost: ¥4,500,000)
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| Keywords | e-Learning / teaching material development / Self-Organizing Map / learning motivation / personality / learning style / causal analysis / educational evaluation / ストリーミングビデオ / 自己組織化マップ / シーン分割 / 学習者属性 |
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| Research Abstract |
The purpose of this study is to develop a procedure for creating online teaching materials and supporting procedure for learners to improve lecture teaching.
Firstly, we presents a feasibility that scene thumbnail images of lecture video can be summarized using Self-Organizing Map (SOM). To extract a feature of scene thumbnail images from a lecture video, the discrete cosine transformation (DCT) was conducted for 15 segments of a image, then 3 major components from each segment were extracted. The system was applied to an ordinal lecture.
Secondly, to examine the impact of student characteristics on learning performance, 46 freshmen and 67 graduate students from a japanese university completed surveys on three constructs, which were motivation, personality, thinking styles, and participated in two blended learning courses which consisted of offace-to-face lectures with corresponding online modules and tests for 14 weeks. Learning performance as the number of days attended(NDA), the number of completed modules (NCM) and online test scores (OTS) were recorded. The relationship amongst characteristics, learning practice and learning performance are revealed using statistical analysis. Also, the same survey was conducted in a US university, common data were collected.
Thirdly, a prediction procedure for failure of online learners was developed to operate online course. The procedure was based that access log data of the online course for failed learners showed different tendency with ones of finished learners. This procedure can be applied to other class data.
These results show possibility of improving university teaching with information technology and consideration of learner's characteristics.
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