AI-based Flexible Online Laboratory Learning System for Post-COVID-19 Era: Requirements and Design
Mahmoud M. Elmesalawy, Ayman Atia, Ahmed Mohamed Fahmy Yousef, Ahmed M. Abd El‐Haleem, Mohamed G. Anany, Noha A. Elmosilhy, Abdullah I. Salama, Alaa Hamdy, Helmy M. El Zoghby, Eman Serag El Din
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.