Data Mining for Cognitive e-Learning Systems: A Survey

With the advance in information technology, the electronic learning (e-learning) has played a key role in teaching and learning which has become more and more important in colleges and schools nowadays. Further, the COVID-19 pandemic has led to the rise in teaching and learning courses through online portals. Various educational institutes have adopted video conferencing platforms such as Microsoft platform, Zoom and Webex Blackboard and Google Classroom, leading to the enhancement of e-learning globally. There are many advantages of e-learning which include no time and space constraints for learners to study courses, saves internal training cost, improves classroom teaching, etc. The design of e-learning objectives focuses on providing opportunities for students to learn through virtual experience the functional value of the material by working directly with the content. There has been recent shift in attention towards data mining based e-learning systems that provide us the virtually educational environment independent of any specific hardware platforms. The aim of this paper is to focus on the current status of data mining approaches e.g. educational recommenders, association rule, clustering, profile based approach, personalization, prediction techniques and decision support system for e-learning systems.