Exploring Technical Quality Factors That Enhance Mobile Learning Applications Services Using Data Mining Techniques

Abstract

Mobile learning (m-learning) has become an increasingly attractive solution for schools and universities that utilize new technologies in their teaching and learning setting. This study investigates the technical factors affecting the development of m-learning applications services from students’ perspectives. It presents a model consisting of twelve technical factors, including content usefulness, scalability, security, functionality, accessibility, interface design, interactivity, reliability, availability, trust, responsiveness, and personalization. To evaluate the model, a questionnaire was designed and distributed to 151 students in Jerash University, Jordan. The results indicate that all technical factors have positive affects on learner satisfaction and overall m-learning applications services, however the data mining analysis revealed that security and scalability factors exert a major impact on student satisfaction with m-learning applications services. This study gives insight for the future of developing and design m-learning applications.