2
Institute for Research and Studies of the Islamic World
10.21608/ijlms.2023.207480.1005
Abstract
ABSTRACT This study explores critical success factors (CSFs) for cloud-based mobile learning and aims to provide a comprehensive framework for effective implementation. The research includes a literature review, expert review, and Analytic Hierarchy Process (AHP) to collect and analyse data. The literature review covers e-learning, mobile learning, and cloud computing to identify CSFs. Seven major domains containing sub-factors are identified, including Mobile Device Compatibility, Data Security, Learner Engagement, Content Quality, Learning Management, Scalability, and Instructor Support. AHP method is used to select the most common and significant factors from the literature review. An expert review is conducted to ensure the framework's comprehensiveness and applicability. The study's findings provide valuable insights for organizations seeking to implement cloud-based mobile learning, as they can use the CSFs identified to ensure successful competitive performance. The study contributes to the field of cloud-based mobile learning by providing a multi-method approach to identifying a comprehensive framework for CSFs.
Hashim, Y., & A. Mekki, W. (2023). PRIORITIZING CSFS FOR CLOUD-BASED M-LEARNING: AHP AND BLACKBOARD CASE STUDY. International Journal of Learning Management Systems, (), 65-78. doi: 10.21608/ijlms.2023.207480.1005
MLA
Yousif E. Hashim; W. A. Mekki. "PRIORITIZING CSFS FOR CLOUD-BASED M-LEARNING: AHP AND BLACKBOARD CASE STUDY". International Journal of Learning Management Systems, , , 2023, 65-78. doi: 10.21608/ijlms.2023.207480.1005
HARVARD
Hashim, Y., A. Mekki, W. (2023). 'PRIORITIZING CSFS FOR CLOUD-BASED M-LEARNING: AHP AND BLACKBOARD CASE STUDY', International Journal of Learning Management Systems, (), pp. 65-78. doi: 10.21608/ijlms.2023.207480.1005
VANCOUVER
Hashim, Y., A. Mekki, W. PRIORITIZING CSFS FOR CLOUD-BASED M-LEARNING: AHP AND BLACKBOARD CASE STUDY. International Journal of Learning Management Systems, 2023; (): 65-78. doi: 10.21608/ijlms.2023.207480.1005