Comparative Studies: Cloud-Enabled Adaptive Learning System for Scalable Education in Sub-Saharan

2025-06-30

AI Summary

This study addresses the challenge of achieving scalable, low-cost, and equitable educational access in socioeconomically diverse, infrastructure-constrained regions—particularly sub-Saharan Africa—to bridge the global digital divide and educational inequity. Methodologically, it employs cross-national comparative analysis, deployment of a cloud-native adaptive learning system, and cross-regional educational data modeling to uncover how cloud computing and adaptive learning technologies can be effectively adapted across heterogeneous contexts. Key enablers—including lightweight architectures, offline-capable collaboration tools, and localized content delivery—are identified alongside structural constraints such as bandwidth limitations and teacher digital literacy gaps. The study innovatively proposes a “Progressive Cloud-Based Education Deployment Framework” tailored for resource-constrained settings, offering a replicable, scalable, technology-institution co-design pathway. Findings provide empirical evidence and policy-relevant insights to support digital education transformation in low- and middle-income countries.

Technology Category

• Machine Learning: Learning on the Edge & Model Compression
• Application Domains: Internet of Things, Sensor Networks & Smart Cities
• Data Mining & Knowledge Management: Scalability, Parallel & Distributed Systems

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Cloud, edge and content delivery systems for the Web
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Responsible Web: Sustainability and climate impact of web technologies

Abstract

The integration of cloud computing in education can revolutionise learning in advanced (Australia & South Korea) and middle-income (Ghana & Nigeria) countries, while offering scalable, cost-effective and equitable access to adaptive learning systems. This paper explores how cloud computing and adaptive learning technologies are deployed across different socio-economic and infrastructure contexts. The study identifies enabling factors and systematic challenges, providing insights into how cloud-based education can be tailored to bridge the digital and educational divide globally.

Problem

• Exploring cloud computing's role in scalable education systems
• Comparing adaptive learning deployment in diverse socio-economic contexts
• Identifying challenges and solutions for global educational equity

Innovation

• Cloud computing enables scalable education solutions
• Adaptive learning tailors to diverse socio-economic contexts
• Cost-effective cloud systems bridge global educational divides