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
页码：275-284
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
