期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2019
卷号：10
期号：8
DOI：10.14569/IJACSA.2019.0100835
出版社：Science and Information Society (SAI)
摘要：The adaptive e-learning system (AE-LS) research has long focused on the learner model and learning activities to personalize the learner’s experience. However, there are many unresolved issues that make it difficult for trainee teachers to obtain appropriate information about the learner's behavior. The evolution of the Learning Analytics (LA) offers new possibilities to solve problems of AE-LS. In this paper, we proposed a Business intelligence framework for AE-LS to monitor and manage the performance of the learner more effectively. The suggested architecture of the ALS proposes a data warehouse model that responds to these problems. It defines specifics measures and dimensions, which helps teachers and educational administrators to evaluate and analyze the learner’s activities. By analyzing these interactions, the adaptive e-learning analytic system (AE-LAS) has the potential to provide a predictive view of upcoming challenges. These predictions are used to evaluate the adaptation of the content presentation and improve the performance of the learning process.
关键词：e-Learning; adaptive e-learning system; learner model; learning analytics; business intelligence; data warehouse; content presentation
