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

abstract

• 2016 IEEE. 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.

authors

• Parsaei, Hamid

published proceedings

• IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

author list (cited authors)

• Wang, N., Chen, X., Song, G., Lan, Q., & Parsaei, H. R.

citation count

• 26

complete list of authors

• Wang, Ning||Chen, Xuemin||Song, Gangbing||Lan, Qianlong||Parsaei, Hamid R

publication date

• March 2017

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• IEEE Transactions on Industrial Electronics  Journal

keywords

• Ionic Framework
• Mobile Learning (m-learning)
• Mobile-optimized Application Architecture
• Remote Laboratory
• Unified Framework

Digital Object Identifier (DOI)

• 10.1109/TIE.2016.2620102

start page

• 2382

end page

• 2391

volume

• 64

issue

• 3

URL

• http%3A%2F%2Fdx.doi.org%2F10.1109%2Ftie.2016.2620102