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Development of Web-based Learning Resource Management System for Educational Knowledge Circulation
PROCEEDINGS

, , , NIME, Japan ; , Chiba Prefecture Boards of Education, Japan ; , , NEC Corporation, Japan

E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, in Phoenix, Arizona, USA ISBN 978-1-880094-50-1 Publisher: Association for the Advancement of Computing in Education (AACE), San Diego, CA

Abstract

A prototype of web-based multimedia database system aiming at educational researchers f and practitioners f knowledge management in terms of usage of educational resources was developed. The system allows users to store and to retrieve educational resources such as learning materials and lesson plans accompanied by educational knowledge such as evaluation, comments, and practice reports, so that users can share the experiences of classroom lessons. The system fs functions include recommendation by collaborative filtering technology and characteristic word extraction by text mining technology as well as multimedia database. The trial service for four Japanese municipal schools revealed that there were not only difficulties peculiar to the system but some general factors that could constrain its use. Main issues include anxiety about privacy protection, and resistance to reuse someone fs work and to be reused own work by someone.

Citation

Kato, H., Hatano, K., Sakamoto, T., Morimoto, H., Komiya, T. & Matsuda, F. (2003). Development of Web-based Learning Resource Management System for Educational Knowledge Circulation. In A. Rossett (Ed.), Proceedings of E-Learn 2003--World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education (pp. 2225-2228). Phoenix, Arizona, USA: Association for the Advancement of Computing in Education (AACE). Retrieved February 17, 2019 from .

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References

  1. Li, H. And Yamanishi, K. (2001). Mining from Open Answers in Questionnaire Data. Proceedings of the 7th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 443-449.

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