Correlation Mining and Discovery for Learning Resources

Sharing information and resources on the Internet has become an important activity for education. The use of ubiquitous devices makes possible for learning participants to be engaged in an open and connected social environment, and also allows the learning activities to be performed at any time and...

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Hauptverfasser: Weng, M. M., Kau, B. C., Yen, N. Y.
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description Sharing information and resources on the Internet has become an important activity for education. The use of ubiquitous devices makes possible for learning participants to be engaged in an open and connected social environment, and also allows the learning activities to be performed at any time and any places. In this study, the discovery of correlation among shared resources is concentrated. A hypothetical scenario is considered that the information, such as photos and thoughts, is applicable to be shared with implicit context (i.e. geographical information) by learners through a practical implementation, PadSCORM, on a mobile device. Two major contributions are achieved. First, the correlations among resources are determined through usage experiences mining and geographical information adjustment. It then assists learners in filtering out redundant information by highlighting the significance of resources. Second, an intelligent searching algorithm is proposed to visualize adaptive routes in order to facilitate search process and to enrich the learning activity.
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source IEEE Electronic Library (IEL) Conference Proceedings
subjects Algorithm design and analysis
Context
Correlation
Data mining
Educational institutions
Filtering
Information Filtering
Peravasive Computing
Social Network Analysis
Social network services
Ubiquitous Learning
title Correlation Mining and Discovery for Learning Resources
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