Adaptive learning with real time recommendation system

ABSTRACT 

Artificial Intelligence is revolutionizing the education sector and making enormous research opportunities day by day. Adaptive learning with personalization has the potential to change the education to the next level. Several learning platforms developed so far deliver the study materials and just save the learner's recorded data for suggesting the next relevant course. But there is not enough attention given to the learning content provided for individual learners. In order to provide personalized learning content, it is necessary to evaluate the current knowledge state of the learner, in that particular subject. On this basis, a framework of real time personalized adaptive learning has been constructed.  

In this Adaptive Learning Management System, every learner/user will be evaluated with a set of questions on the subject, which a user wants to learn. The user has to attend the questionnaire about that particular chosen subject. These questions will be prepared by the subject matter experts, in such a deep way that only if the user has already known the subject, he/she will be able to answer. Based on the given answers, the user will be categorized as beginner, medium or expert level of knowledge in that subject. The beginner categorized user will be recommended with the relevant study material where the advanced, expert level of materials will be avoided to show in the user's learning panel.  

Besides providing the recommended course material, this Adaptive Learning Management System keeps track of the learner. It saves each and every material the user has studied. This information will be stored in his/her personalized database. This collection of relevant and reliable data helps in evaluating the individual learner. Personalized Page Rank algorithm helps to.