%0 Conference Proceedings
%T Emotion-Based Adaptive Learning Systems
%+ TYLERS
%+ LSL Digital
%+ University of Mauritius
%A Taurah, Sai, Prithvisingh
%A Bhoyedhur, Jeshta
%A Sungkur, Roopesh, Kevin
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 2nd International Conference on Machine Learning for Networking (MLN)
%C Paris, France
%Y Selma Boumerdassi
%Y Éric Renault
%Y Paul Mühlethaler
%I Springer International Publishing
%3 Machine Learning for Networking
%V LNCS-12081
%P 273-286
%8 2019-12-03
%D 2019
%R 10.1007/978-3-030-45778-5_18
%K Adaptive learning
%K Personalisation
%K Emotion
%K Neural networks
%K Machine learning
%Z Computer Science [cs]
%Z Computer Science [cs]/Networking and Internet Architecture [cs.NI]Conference papers
%X Right from our primary school to professional academic level, the classical education system modus operandi, forces us to follow a series of predefined steps to climb the stairs of academic levels. Traditionally those predefined steps forces students to go through the beginner level to advanced level and then specialized in a specific level. The main problem was that the teaching styles and content delivery was not tailored to every learning styles and student personalities. The traditional education system is moving towards adaptive learning system where students are not bound only to one predefined set of contents. Therefore the traditional “one size fits all” approach is no longer valid as it were before. Each student has their curriculum based on their unique needs and personality. Adaptive learning may be referred as the process of creating unique learning experience for each and every learner based upon the learner’s personality, interests and performance. This research presents a novel approach of adaptive learning by presenting an emotion-based adaptive learning system where the emotion and psychological traits of the learner is considered to provide learning materials that would be most appropriate at that particular instance of time. It shall demonstrate an intelligent agent based expert system using artificial intelligence and emotion detections capabilities to measure the user learning rate and find an optimum learning scheme for the latter.
%G English
%Z TC 6
%2 https://inria.hal.science/hal-03266463/document
%2 https://inria.hal.science/hal-03266463/file/487577_1_En_18_Chapter.pdf
%L hal-03266463
%U https://inria.hal.science/hal-03266463
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC
%~ IFIP-TC6
%~ IFIP-LNCS-12081
%~ IFIP-MLN