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

Abstract:

  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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