%0 Conference Proceedings
%T An Automated Tool to Support an Intelligence Learner Management System Using Learning Analytics and Machine Learning
%+ University of East London (UEL)
%+ University of Brighton
%+ Department of Computer and Systems Science [Stockholm]
%+ Mediprospects
%A Islam, Shareeful
%A Mouratidis, Haralambos
%A Mahmud, Hasan
%Z Part 13: Machine Learning
%< avec comité de lecture
%( IFIP Advances in Information and Communication Technology
%B 17th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI)
%C Hersonissos, Crete, Greece
%Y Ilias Maglogiannis
%Y John Macintyre
%Y Lazaros Iliadis
%I Springer International Publishing
%3 Artificial Intelligence Applications and Innovations
%V AICT-627
%P 494-504
%8 2021-06-25
%D 2021
%R 10.1007/978-3-030-79150-6_39
%K Machine learning
%K Learning analytics
%K Predictive analytics
%K Perspective analytics
%Z Computer Science [cs]Conference papers
%X Learner Management Systems (LMSs) are widely deployed across the industry as they provide a cost-saving approach that can support flexible learning opportunities. Despite their benefits, LMSs fail to cater for individual learning behavior and needs and support individualised prediction and progression. Learning Analytics (LAs) support these gaps by correlating existing learner data to provide meaningful predictive and prescriptive analysis. The industry and research community have already recognised the necessity of LAs to support modern learning needs. But a little effort has been directed towards the integration of LA into LMSs. This paper presents a novel automated Intelligence Learner Management System (iLMS) that integrates learner management and learning analytics into a single platform. The presented iLMS considers Machine Learning techniques to support learning analytics including descriptive, predictive and perspective analytics.
%G English
%Z TC 12
%Z WG 12.5
%2 https://inria.hal.science/hal-03287708/document
%2 https://inria.hal.science/hal-03287708/file/509922_1_En_39_Chapter.pdf
%L hal-03287708
%U https://inria.hal.science/hal-03287708
%~ IFIP
%~ IFIP-AICT
%~ IFIP-TC
%~ IFIP-WG
%~ IFIP-TC12
%~ IFIP-AIAI
%~ IFIP-WG12-5
%~ IFIP-AICT-627