Construct Knowledge Structure of Linear Algebra

Abstract:

Article Preview

Apply interpretive structural modeling to construct knowledge structure of linear algebra. New fuzzy clustering algorithms improved fuzzy c-means algorithm based on Mahalanobis distance has better performance than fuzzy c-means algorithm. Each cluster of data can easily describe features of knowledge structures individually. The results show that there are six clusters and each cluster has its own cognitive characteristics. The methodology can improve knowledge management in classroom more feasible.

Info:

Periodical:

Advanced Materials Research (Volumes 211-212)

Edited by:

Ran Chen

Pages:

793-797

DOI:

10.4028/www.scientific.net/AMR.211-212.793

Citation:

C. C. Chen et al., "Construct Knowledge Structure of Linear Algebra", Advanced Materials Research, Vols. 211-212, pp. 793-797, 2011

Online since:

February 2011

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Price:

$35.00

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