Development of Platform Independent Mobile Learning Tool in Saudi Universities

• Main Authors: Daniyal M. Alghazzawi, Syed Hamid Hasan, Ghadah Aldabbagh, Mohammed Alhaddad, Areej Malibari, Muhammad Zubair Asghar, Hanan Aljuaid
• Format: Article
• Language: English
• Published: MDPI AG 2021-05-01
• Series: Sustainability
• Subjects: mobile learning; m-learning; structured programming; platform independent; cross-platform; ADDIE model
• Online Access: https://www.mdpi.com/2071-1050/13/10/5691

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.