A Review of Adaptive and Intelligent Online Learning Systems

Abstract

Education is a vital part of everyone’s life. With the advancement of the internet, online learning has gained a wide scope. With the availability of a wide variety of courses and course content available online, learners usually struggle while choosing the course that will be most beneficial to them. It’s mainly because of the learners having different learning styles, different level of understanding, and different knowledge domains. Along with this, the learners also suffer from improper monitoring and evaluation. The adaptive learning system adapts itself as per the learning style of the learner and an intelligent tutoring system helps in the monitoring and evaluation of the learner’s performance. An intelligent tutoring system also provides an immediate and customized response to the learner. With the combination of Adaptive learning system and intelligent learning system, the online learning system can be developed with advanced capabilities and can be more beneficial to the learners than traditional online learning system. There are various learning styles in which learners can be categorized. Various learning style models are Felder Silverman model, VAK model, David Kolb learning style model etc. The paper presents a discussion on the research work done in the area, showing the work done on adaptive learning systems and intelligent tutoring systems.