Development of Platform Independent Mobile Learning Tool in Saudi Universities

The term “mobile learning” (or “m-learning”) refers to using handheld phones to learn and wireless computing as a learning tool and connectivity technology. This paper presents and explores the latest mobile platform for teaching and studying programming basics. The M-Learning tool was created using a platform-independent approach to target the largest available number of learners while reducing development and maintenance time and effort. Since the code is completely shared across mobile devices (iOS, Android, and Windows Phone), students can use any smartphone to access the app. To make the programme responsive, scalable, and dynamic, and to provide students with personalised guidance, the core application is based on an analysis design development implementation and assessment (ADDIE) model implemented in the Xamarin framework. The application’s key features are depicted in a prototype. An experiment is carried out on BS students at a university to evaluate the efficacy of the generated application. A usefulness questionnaire is administered to an experimental community in order to determine students’ expectations of the developed mobile application’s usability. The findings of the experiment show that the application is considerably more successful than conventional learning in developing students’ online knowledge assessment abilities, with an impact size of 1.96. The findings add to the existing mobile learning literature by defining usability assessment features and offering a basis for designing platform-independent m-learning applications. The current findings are explored in terms of their implications for study and teaching practice.

Analytical Solution of the Effect of Awareness Program by Media on the Spread of an Infectious Disease by Homotopy Perturbation Method

Wireless sensor networks (WSNs) have received wide-ranging considerationdue to their boundless potential in civil and military applications. Maliciousself-replicating codes, known as malware, pose substantial threat to the wireless computing infrastructure. The attacks of the malicious signals in the WSNare epidemic in nature. Biological epidemic models will be helpful to understand the dynamical behavior of the malware attack in WSN. In this paper,A (SEIRS-V) Susceptible - Exposed - Infected - Recovered - Susceptible witha Vaccination compartment, describing the undercurrents of worm propagation with respect to time in wireless sensor network (WSN) is considered. Theanalytical solution of WSN is obtained by Homotopy Perturbation Method.Numerical results are obtained and are graphically interpreted using Maple.The results assures that the dynamics of worm propagation in WSN by theproposed model exhibits rich dynamics.