Abstract:
Due to the tremendous development of the Internet, E-learning platforms have nowadays been
considered the most promising platform that assists students to develop their skills to attain
successful outcomes in intended learning. In this technical world, mobile applications and web
applications play an important role in online learning systems. Nowadays, learning technology is
increasing rapidly with different versions to encourage the learners. Online learning is very useful for
every learner and especially, it is very helpful during this covid 19 outbreak, enabling the learners to
learn their desired courses in Learning Management System (LMS). However, the prediction
performance of the learner is challenging in LMS. A course recommendation system guides the
students to select the appropriate course and the personalized environment will have the potential to
attract the learner to such a system. A recommended system is defined as an intelligent system that
suggests a personalized set of data excerpted from a mass volume of information. This research is
attempted to propose feasible methodologies for learning style-based performance prediction and
course recommendation in the E-Khool learning platform using deep learning algorithms. This research
will open many research works in the field of deep learning algorithms in electronic platforms.
