Title :
Real-time learning behavior mining for e-learning
Author :
Kuo, Yen-Hung ; Chen, Juei-Nan ; Jeng, Yu-Lin ; Huang, Yueh-Min
Author_Institution :
Dept. of Eng. Sci., National Cheng Kung Univ., Tainan, Taiwan
Abstract :
Over the last years, we have witnessed an explosive growth of e-learning. More and more learning contents have been published and shared over the Internet. Therefore, how to progress an efficient learning process becomes a critical issue. This paper proposes a sequential mining algorithm to analyze learning behaviors for discovering frequent sequential patterns. By these patterns, we can provide suggestions for learners to select their interest learning contents. Different to other sequential mining algorithms, this study provides an incrementally method to analyze learning sequencing. More specifically, the mining algorithm in this paper can provide real-time analysis, and then report to learners for selecting learning contents more easily.
Keywords :
Internet; computer aided instruction; data mining; Internet; data mining; e-learning; frequent sequential pattern; learning behavior; learning content; real-time analysis; sequential mining; Algorithm design and analysis; Association rules; Data mining; Databases; Electronic learning; Explosives; Internet; Pattern analysis; Time factors; Web mining; data mining; e-learning; frequent pattern; real-time analysis; sequential mining;
Conference_Titel :
Web Intelligence, 2005. Proceedings. The 2005 IEEE/WIC/ACM International Conference on
Print_ISBN :
0-7695-2415-X
DOI :
10.1109/WI.2005.125