AI-based Flexible Online Laboratory Learning System
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AI-based Flexible Online Laboratory Learning System
Elmesalawy, M.M
;
Atia, A
;
Yousef, A.M.F
;
El-Haleem, A.M.A
;
Anany, M.G
;
Elmosilhy, N.A
;
Salama, A.I
;
Hamdy, A
;
Zoghby, H MK
;
Din, E.S.E
Full Text link:
https://qrgo.page.link/SFnFY
Date issued:
5/27/2021
Scientific Journal Rankings:
Click Here
Doi:
https://doi.org/10.1109/MIUCC52538.2021.9447601
Publisher:
Institute of Electrical and Electronics Engineers Inc.
Series Info:
International Mobile, Intelligent, and Ubiquitous Computing Conference;Pages 96 - 102
Type:
Article
Keywords:
AI , Authoring Tool , COVID-19 , E-Learning , LMS , Virtualization
Abstract:
The 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.
Description:
Scopus
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