Abstract
AbstractOnline learning is a well-proven application in all walks of the teaching–learning process that depends on wireless mobile technology and Internet connectivity. It is accomplished through mobile handheld devices and wireless networks. It has proved its importance in this COVID pandemic era for distant learning to facilitate online classes for all university students. The first evolution of remote Internet-based learning was termed electronic learning (e-learning) with wired net-connected desktop computers. Mobile learning or m-learning is accomplished with wireless Internet connectivity-enabled laptops or mobile handheld devices. Now, this technology of the teaching–learning process is widely accepted as the education system of pandemic-affected world and is termed online learning. Online learning is a subset of mobile learning over wireless networks using portable electronic devices. Inhibitors caused due to the existing 4G wireless networks, mobile handheld devices, and the outlook of end users are the main factors selected for this particular study. Inhibitors of online learning over 4G networks were identified through an intensive study conducted by discussions with experts, end users, designers and learners. The methodology adopted for this research work is the fuzzy matrix of cross-impact multiplications applied to classification (MICMAC). The fuzzy-MICMAC method is used to analyse the selected inhibitors of online learning over wireless networks. A digraph with all possible interconnections, correlation study and the comparative analysis of fuzzy logic approach to the binary logic ISM-MICMAC method were implemented. More outlined results were achieved with the fuzzy analysis. The driving power-dependence abilities of these inhibitors were recorded, which will resolve many undue variables in the future implementation of the system.Keywords4G inhibitorsOnline learningISMFuzzyMICMACDriving powerDirectional graph
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