Author(s): Mohammed Al-Sarem | Mostafa Bellafkih | Mohammed Ramdani
Journal: International Journal of Computer Science Issues
ISSN 1694-0784
Volume: 8;
Issue: 4;
Start page: 136;
Date: 2011;
Original page
Keywords: Fuzzy Association Rules | Data Mining | Concept Maps | Analysis of Numerical Testing Scores | IJCSI
ABSTRACT
With vigorous development of the Internet, e-learning system has become more and more popular and many adaptive learning systems have been developed. In recent years, researchers have proposed various approaches for developing adaptive learning systems based on concept maps. Nevertheless, most of them deal only with binary grades of each test item, furthermore, the existing methods that based on fuzzy set theory do not take in consideration the conceptual weight of concept in each question that might be cause to construct incorrectly relationships or exaggerate the degree of relationship. To cope with this problem, this study proposes an innovative approach to automatically construct concept maps. Firstly, we use look ahead fuzzy association rule mining algorithm to mind some information about the relationships between questions, then we construct the questions-relationships mapping. After that, we calculate the relevance degree between concepts in each question to obtain the final concept maps.
Journal: International Journal of Computer Science Issues
ISSN 1694-0784
Volume: 8;
Issue: 4;
Start page: 136;
Date: 2011;
Original page
Keywords: Fuzzy Association Rules | Data Mining | Concept Maps | Analysis of Numerical Testing Scores | IJCSI
ABSTRACT
With vigorous development of the Internet, e-learning system has become more and more popular and many adaptive learning systems have been developed. In recent years, researchers have proposed various approaches for developing adaptive learning systems based on concept maps. Nevertheless, most of them deal only with binary grades of each test item, furthermore, the existing methods that based on fuzzy set theory do not take in consideration the conceptual weight of concept in each question that might be cause to construct incorrectly relationships or exaggerate the degree of relationship. To cope with this problem, this study proposes an innovative approach to automatically construct concept maps. Firstly, we use look ahead fuzzy association rule mining algorithm to mind some information about the relationships between questions, then we construct the questions-relationships mapping. After that, we calculate the relevance degree between concepts in each question to obtain the final concept maps.
