Prophecy Of E-Erudition Websites Using Naive Bayes Algorithm

  • B. Geetha, V. Vidhyasri, S. Murugesan, M. Kumaran, R. Chandrakala, S. Selvakumaran

Abstract

E-erudition is achieved by the deep integration of modern education and information technology, and plays an important role in promoting educational equity. With the continuous expansion of user groups and application areas, it has become increasingly important to effectively ensure the quality of e- learning. Currently, one of the methods to ensure the quality of e-learning is to use mutually independent e-learning behaviour data to build a learning performance predictor to achieve real- time supervision and feedback during the learning process. However, this method ignores the inherent correlation between e-learning behaviours. Therefore, we propose the behaviour classification based e-learning performance (BCEP) prediction framework, which selects the features of e-learning behaviours, uses feature fusion with behaviour data according to the behaviour classification model to obtain the category feature values of each type of behaviour, and finally builds a learning performance predictor based on machine learning. In addition, because existing e-learning behaviour classification methods do not fully consider the process of learning, we also propose an online behaviour classification model based on the e-learning process called the process-behaviour classification (PBC) model. Experimental results with the Open University Learning Analytics Dataset (OULAD) show that the learning performance predictor based on the BCEP prediction framework has a good prediction effect, and the performance of the PBC model in learning performance prediction is better than traditional classification methods. We construct an e-learning performance predictor from a new perspective and provide a new solution for the quantitative evaluation of e-learning classification methods.

Published
2020-04-24
How to Cite
B. Geetha, V. Vidhyasri, S. Murugesan, M. Kumaran, R. Chandrakala, S. Selvakumaran. (2020). Prophecy Of E-Erudition Websites Using Naive Bayes Algorithm. International Journal of Control and Automation, 13(03), 397-403. Retrieved from http://sersc.org/journals/index.php/IJCA/article/view/38110