SYSTEM QUALITY CHARACTERISTICS FOR SELECTING MOBILE LEARNING APPLICATIONS

Yıl 2015, Cilt: 16 Sayı: 4, 18 - 27, 05.10.2015

Mohamed Sarrab Hafedh Al-shıhı Bader Al-mantharı

https://doi.org/10.17718/tojde.83031

Cited By: 9

Öz

The majority of M-learning (Mobile learning) applications available today are developed for the formal learning and education environment. These applications are characterized by the improvement in the interaction between learners and instructors to provide high interaction and flexibility to the learning process. M-learning is gaining increased recognition and adoption by different organizations. With the high number of M-learning applications available today, making the right decision about which, application to choose can be quite challenging. To date there is no complete and well defined set of system characteristics for such M-learning applications. This paper presents system quality characteristics for selecting M-learning applications based on the result of a systematic review conducted in this domain.

Anahtar Kelimeler

Mobile learning; M-learning; Mobile Application; System Quality Characteristics

Kaynakça

• Alzahrani, A. Alalwan, N & Sarrab, M. (2014). Mobile Cloud Computing: Advantage,
• Disadvantage and Open Challenge, 7th Euro American Association on Telematics and Information Systems, (EATIS 2014).
• Blackboard. (2014), http://uki.blackboard.com
• Cavus, N & Ibrahim, D (2008). m-Learning: An experiment in using SMS to support learning new English language words. British Journal of Educational Technology, 40(1), 78 –91.
• Cohen, A. (2002). Japan loves wireless. PC Magazine, 21(18), 136.
• Dong, B. Zheng, Q. Yang, J. Li, H & Qiao, M. (2009). An E-learning Ecosystem Based on
• Cloud Computing Infrastructure, Proceeds in 9th IEEE International Conference on Advanced Learning Technologies, ICALT. Riga, Latvia, 125-127. Farooq, F. Schafer, W. Rosson, M & Caroll, J. (2002). M-Education: Bridging the Gap of
• Mobile and Desktop Computing, Centre for Human-Computer Interaction and Department of Computer Science. Virginia Polytechnic Institute and State University, 1-2. Filho, N & Barbosa, E. (2013). A Requirements Catalog for Mobile Learning Environments.
• SAC’13, Coimbra, Portugal. Geddes, S. (2004). Mobile learning in the 21st century: Benefit for learners,ǁ‖ Knowledge
• Tree E-journal, Edition 6, Brisbane, QLD, Australia: Australian Flexible Learning Framework. HR Learning and Development. (2014) Introducing Skillport Mobile, Posted in Learning and Development News, The University of Alabama.
• Moodle. (2014), https://moodle.org
• Oulasvirta, M. Wahlström, & K. Anders Ericsson. (2011). What does it mean to be good at using a mobile device? An investigation of three levels of experience and skill,”
• International Journal of Human-Computer Studies, 69(3), 155-169. Ostashewski, N & Reid, D. (2010). iPod, iPhone, and now iPad: The evolution of multimedia access in a mobile teaching context. In Proceedings of World Conference on
• Educational Multimedia, Hypermedia and Telecommunications, Chesapeake, VA: AACE, 2862-2864.
• Sarrab, M. (2014). M-learning in education: Omani Undergraduate Students Perspective,
• International Educational Technology Conference (IETC-2014), Chicago , USA.
• Sarrab, M. (2014). Mobile Learning (M-learning) Concepts, Characteristics, Methods,
• Components. Platforms and Frameworks, Nova Science Publishers. Sarrab, M, Alzahrani, A, Alalwan, N & Alfarraj, O. (2014). From T-learning into M-learning in education at the University Level: Undergraduate Students Perspective, International
• Journal of Mobile Learning and Organisation. Sarrab, M. Al-Shihi, H & Rehman, O. (2013). Exploring Major Challenges and Benefits of
• M-learning Adoption, British Journal of Applied Science & Technology, 3(4), 826-839. Sarrab, M & Elgamel, L. (2013). Contextual M-Learning System For Higher Education
• Providers in Oman, World Applied Sciences Journal, 22(10), 1412-1419.
• Sarrab, M. Elgamel, L & Aldabbas, H. (2012). Mobile Learning (M-Learning) and Educational Environments. International Journal of Distributed and Parallel Systems (IJDPS), 3(4), 31-38.
• Sarrab. M & Rehman. O. (2014). Empirical Study of Open Source Software Selection for
• Adoption Based on Software Quality Characteristics. Advances in Engineering Software, Elsevier. 69,1-11. Sarrab, M. & Rehman, O. (2013). Selection Criteria of Open Source Software: First Stage for Adoption, International Journal of Information Processing and Management (IJIPM), 4(4), pp. 51-58.
• Schology. (2014), Mobile Apps Overview, Usage and Workflow, Schoology, Inc. www.schoology.com.