17th AIAI 2021, 25 - 27 June 2021, Greece

An automated tool to support an intelligence learner management system using Learning Analytics and Machine Learning

Shareeful Islam, Hasan Mahmud, Haralambos Mouratidis


  Learner Management Systems (LMSs) are widely deployed across the industry as they provide a cost-saving approach that can support flexible learning oppor-tunities. Despite their benefits, LMSs fail to cater for individual learning behav-ior and needs and support individualised prediction and progression. Learning Analytics (LAs) support these gaps by correlating existing learner data to pro-vide 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 Learn-ing techniques to support learning analytics including descriptive, predictive and perspective analytics.  

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