Design of a New Mobile-Optimized Remote Laboratory Application Architecture for M-Learning

As mobile learning (M-Learning) has demonstrated increasing impacts on online education, more and more mobile applications are designed and developed for the M-Learning. In this paper, a new mobile-optimized application architecture using Ionic framework is proposed to integrate the remote laboratory into mobile environment for the M-Learning. With this mobile-optimized application architecture, remote experiment applications can use a common codebase to deploy native-like applications on many different mobile platforms such as iOS, Android, Windows Mobile, and Blackberry. To demonstrate the effectiveness of the proposed new architecture for M-Learning, an innovative remote networked proportional-integral-derivative control experiment has been successfully implemented based on this new application architecture. The performance is validated by the Baidu mobile cloud testing bed.