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Knowledge map construction based on association rule mining extending with interaction frequencies and knowledge tracking for rules cleaning

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成果类型:
期刊论文
作者:
Fang, Jing*;Xiao, Xiong;He, Xiuling;Li, Yangyang;Yuan, Huanhuan;...
通讯作者:
Fang, Jing;Xiao, X
作者机构:
[Xiao, Xiong; He, Xiuling; Fang, Jing; Jiao, Xiaomin; Fang, J; Li, Yangyang; Xiao, X] Cent China Normal Univ, Natl Engn Res Ctr Elearning, Wuhan, Peoples R China.
[Yuan, Huanhuan] Shanghai Jiao Tong Univ, Shanghai, Peoples R China.
通讯机构:
[Fang, J; Xiao, X ] C
Cent China Normal Univ, Natl Engn Res Ctr Elearning, Wuhan, Peoples R China.
语种:
英文
关键词:
association rule mining;deep knowledge tracking;fuzzy cluster analysis;Knowledge map
期刊:
Interactive Learning Environments
ISSN:
1049-4820
年:
2023
基金类别:
National Natural Science Foundation of China [62177023]
机构署名:
本校为第一且通讯机构
院系归属:
国家数字化学习工程技术研究中心
摘要:
Knowledge maps are teaching tools that can promote deeply learning and avoid knowledge loss by helping students plan learning paths. Mining potential association rules of concepts from student exercise data was a common method to construct knowledge maps automatically. While manual conditions should be set to filter the association rules future to improve the accuracy of knowledge maps, which made the construction of the knowledge map can not automatic totally. So, the study proposed a knowledge map construction method that combined knowledge t...

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