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Author:

Liu, Jun (Liu, Jun.) | Sha, Sha (Sha, Sha.) | Zheng, Qinghua (Zheng, Qinghua.) (Scholars:郑庆华) | Chen, Ling (Chen, Ling.)

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Abstract:

Using knowledge maps to compute and rank the difficulty level of knowledge units can guide learners plan their learning activities more effectively. This paper focuses on how to use the topology of a knowledge map to compute and rank the difficulty of knowledge units. We present the hierarchical structure and properties of knowledge maps, propose three hypotheses based on the correlation between the difficulty of knowledge units and learning dependency, and then provide a method for ranking knowledge units with objective and subjective difficulty. The experiment on the "plane geometry" knowledge map shows that our methods can precisely calculate the difficulty of knowledge units. © 2010 IEEE.

Keyword:

Guide learners Hierarchical structures Knowledge map Knowledge units Learning Activity Learning dependencies Objective difficulty Subjective difficulty

Author Community:

  • [ 1 ] [Liu, Jun;Zheng, Qinghua;Chen, Ling]Department of Computer Science and Technology, Xi'an Jiaotong University, Xi'an 710049, China
  • [ 2 ] [Liu, Jun;Sha, Sha;Zheng, Qinghua;Chen, Ling]MOE KLINNS Lab., SKLMS Lab., Xi'an Jiaotong University, Xi'an 710049, China

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Source :

Proceedings - IEEE International Conference on E-Business Engineering, ICEBE 2010

ISSN: 9780769542270

Year: 2010

Publish Date: 2010

Page: 77-82

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 3

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 6

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