Educational data mining: a review of the state of the art
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Web usage mining for improving students performance in learning management systems
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part III
Multiple instance learning for classifying students in learning management systems
Expert Systems with Applications: An International Journal
Evaluating automatic group formation mechanisms to promote collaborative learning - a case study
International Journal of Learning Technology
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received significant attention in finding customers' behavioral pattern in e-commerce and learners' behavioral pattern in elearning. While hit-counts indicate customers' interest in the product or purchasing behavior, a student's visits to a Learning Management System (LMS) do not necessarily involve transfer of learning. Addressing such complexity in e-learning, this study analyzed students' log of a Learning Management System (LMS) of two subjects at a university in Bangladesh, taught over six weeks duration. Data mining and statistical tools have been used to find relationships between students' LMS access behavior and overall performances. Results show that students having `Low' access obtained poor grade, on campus access was higher than access from home. Background of students is very important for effective usage of web resources. Majority of the student considered LMS to be a quite helpful tool as teaching-learning method. Preparation and cleaning of the web-log files as well as application of data mining algorithms is important for learners' web usage analysis. Keywords-data mining, e-learning.