AI-based Flexible Online Laboratory Learning System

dc.AffiliationOctober University for modern sciences and Arts (MSA)
dc.contributor.authorElmesalawy, M.M
dc.contributor.authorAtia, A
dc.contributor.authorYousef, A.M.F
dc.contributor.authorEl-Haleem, A.M.A
dc.contributor.authorAnany, M.G
dc.contributor.authorElmosilhy, N.A
dc.contributor.authorSalama, A.I
dc.contributor.authorHamdy, A
dc.contributor.authorZoghby, H MK
dc.contributor.authorDin, E.S.E
dc.date.accessioned2021-08-06T16:37:09Z
dc.date.available2021-08-06T16:37:09Z
dc.date.issued5/27/2021
dc.descriptionScopusen_US
dc.description.abstractThe worldwide outbreak due to COVID-19 pandemic has led to a great interest in e-learning. However, the lack of suitable online laboratory management systems has posed a particular challenge for sectors that need laboratory activities such as engineering, science and technology. In this paper, the requirements and design for a flexible AI-based laboratory learning system (LLS) that can support online laboratory experimentations are presented. The elicitation of the LLS design requirements is decided based on a conducted survey for a set of LLS features. The LLS is designed with the flexibility to support various types of online experimentations such as virtual or remote controlled experiments using either desktop or web applications. The virtualization technique is used to manage the laboratory resources and allow multiple users to access the LLS. Moreover, the proposed LLS introduces the use of AI techniques to provide efficient virtual lab assistant and adaptive assessment process. © 2021 IEEE.en_US
dc.description.urihttps://www.scimagojr.com/journalsearch.php?q=21100218370&tip=sid&clean=0
dc.identifier.doihttps://doi.org/10.1109/MIUCC52538.2021.9447601
dc.identifier.otherhttps://doi.org/10.1109/MIUCC52538.2021.9447601
dc.identifier.urihttps://qrgo.page.link/SFnFY
dc.language.isoen_USen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofseriesInternational Mobile, Intelligent, and Ubiquitous Computing Conference;Pages 96 - 102
dc.subjectAIen_US
dc.subjectAuthoring Toolen_US
dc.subjectCOVID-19en_US
dc.subjectE-Learningen_US
dc.subjectLMSen_US
dc.subjectVirtualizationen_US
dc.titleAI-based Flexible Online Laboratory Learning Systemen_US
dc.typeArticleen_US

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