Learner’s Dropout Analytics Using Modern Coherent Rule Optimization Technique

Author(s) : M.Ravichandran , DrG.Kulanthaivel , Dr.T. Chellatamilan

Volume & Issue : VOLUME 1 / 2016 , ISSUE 1

Page(s) : 44-50


The rate of increase of dropout learner in e-learning environment is quite high in recent years. The reason for the dropout is also countless. Hence it is required to formulate the system for analyzing the learners profile in e-learning. Educational Data Mining system is mainly focused for analyzing and improving the efficacy of teaching learning process. In this research, we propose a novel method for identifying the reasons for dropout of online learners from the Moodle platform using modern machine learning and association rule mining techniques .The rules generated for discovering the new pattern of dropouts are optimized using modern coherent rule optimization(MCRO).The results are visualized with dropout pattern comparison. This analysis helps the facilitators for customizing the learning platform and to reduce the number of dropout learners.


e-learning, Dropout learner, Association rule optimization, Educational data mining.


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