Advances in Internet of Things

Volume 9, Issue 3 (July 2019)

ISSN Print: 2161-6817   ISSN Online: 2161-6825

Google-based Impact Factor: 2.8  Citations  

Cloud Computing at a Cross Road: Quality and Risks in Higher Education

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DOI: 10.4236/ait.2019.93003    1,523 Downloads   4,385 Views  Citations
Author(s)

ABSTRACT

The key determinants of cloud computing provide a convincing argument for HEIs and its stakeholders to adopt the innovation. These benefits reflect the essential quality characteristics of the cloud, such as Broad network Access; Measured Service; On-demand Self-Service; Rapid Elasticity; and Resource Pooling. However, there are also risks associated with the cloud, leading to non-adoption, such as Confidence, Privacy, Security, Surety and Trust. Understanding the impact of these factors can support multiple stakeholders, such as students, lecturers, senior managers and admins in their adoptive decision of CC in their respected institutions. Using the Multiview 3 (MV3) methodology, a research model was proposed to explore the key qualities and risks that determine the adoption or non-adoption of CC by UK HEIs from multiple perspectives. An exploratory qualitative study was conducted on 32 University stakeholders across 2 UK Universities. The findings suggest that security, privacy and trust are the key determinants to non-adoption as participants felt that the cloud cannot fully guarantee the safeguarding of sensitive information. Determinants to cloud adoption include improving relationships between students and teachers via collaborative tools, in addition to proposing cloud apps for mobile devices for accessing virtual learning materials and email securely off-campus. In conclusion, University stakeholders are still at a cross-road when it comes to cloud adoption, but future advances of the cloud may help to steer their decision to adopt this innovative technology given its overwhelming potential.

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Ali, M. (2019) Cloud Computing at a Cross Road: Quality and Risks in Higher Education. Advances in Internet of Things, 9, 33-49. doi: 10.4236/ait.2019.93003.

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