Cloud Computing Applications in Education
Summary
Cloud computing has transformed educational practice by offering on-demand access to computing resources, storage and applications without the need for local infrastructure. Institutions can deploy scalable learning management systems, virtual laboratories and collaboration platforms that support synchronous and asynchronous activities. This model reduces capital expenditure, enables rapid provisioning of services and facilitates global reach. Data analytics and machine-learning capabilities in the cloud permit real-time insights into student engagement, performance and retention, thereby supporting personalised learning pathways. During periods of disruption—most notably the COVID-19 pandemic—cloud-based platforms proved essential for continuity of instruction, enabling video conferencing, digital assessment and remote resource access. Furthermore, edge computing and content-delivery networks are increasingly integrated to optimise latency and bandwidth for geographically distributed learners. Together, these advancements underscore a shift from static, campus-bound delivery to dynamic, learner-centred ecosystems underpinned by flexible, cost-effective cloud services.
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Cloud Computing Applications in Education publication trend
The graph below shows the total number of articles in cloud computing applications in education across all publications each year (not limited to Nature Index journals).
Technical terms
Cloud computing: Provision of scalable computing resources and services over the Internet, billed on a pay-per-use basis.
E-learning: Delivery of educational content and instruction through electronic media and digital platforms.
Learning Management System (LMS): Software application for the administration, documentation, tracking and delivery of online courses and training programmes.
Structural Equation Modelling (SEM): A multivariate statistical technique for testing and estimating causal relationships using a combination of statistical data and qualitative causal assumptions.
Bibliometric analysis: Quantitative evaluation of publications to identify patterns, trends and structures in a research field through metrics such as co-citation and keyword co-occurrence.
References
- Evaluation of factors affecting university students' satisfaction with e-learning systems used dur-ing Covid-19 crisis: A field study in Jordanian higher education institutions. International Journal of Data and Network Science (2023).
- Mapping Knowledge Area Analysis in E-Learning Systems Based on Cloud Computing. Electronics (2022).
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