Adaptive e-learning AI-powered chatbot based on multimedia indexing

Abstract

—With the rapid evolution of e-learning technology, the multiple sources of information become more and more accessible. However, the availability of a wide range of e-learning offers makes it difficult for learners to find the right content for their training needs. In this context, our paper aims to design an e-learning AI-powered Chatbot allowing interaction with learners and suggesting the e-learning content adapted to their needs. In order to achieve these objectives, we first analysed the e-learning multimedia content to extract the maximum amount of information. Then, using Natural Language Processing (NLP) techniques, we introduced a new approach to extract keywords. After that, we suggest a new approach for multimedia indexing based on extracted keywords. Finally, the Chatbot architecture is realized based on the multimedia indexing and deployed on online messaging platforms. The suggested approach aims to have an efficient way to represent the multimedia content based on keywords. We compare our approach with approaches in literature and we deduce that the use of keywords on our approach result on a better representation and reduce time to construct multimedia indexing. The core of our Chatbot is based on this indexed multimedia content which enables it to look for the information quickly. Then our designed Chatbot reduce response time and meet the learner’s need.