Review of cloud computing models in education and the unmet needs - Rezqallah Malkawi, Aminah; Abu Bakar, Muhamad Shahbani; Dahalin, Zulkhairi (IAES International Journal of Artificial Intelligence (IJ-AI), 2024)
This article thoroughly examines recently proposed cloud computing (CC) models used within the higher educational institutions (HEI) field, scrutinizing their objectives, structures, and incorporated requirements. Each model's unique architecture and functionality are analyzed to understand their potential educational contributions. Beyond technical considerations, the study explores nuanced requirements essential for successful integration in educational settings. The review exposes diverse aims pursued by the models, such as enhanced scalability, collaborative learning, and resource management, emphasizing their capacity to reshape traditional educational paradigms. However, a notable gap emerges-the absence of cultural and requirement elicitation models within the frameworks. Despite growing cultural diversity and varied educational needs, most models lack components addressing cultural nuances and robust requirement elicitation. In conclusion, the paper identifies a pressing need for a transformative shift in developing CC models for education. The absence of dedicated cultural and requirement elicitation models challenges the holistic effectiveness of these frameworks. Future efforts should prioritize integrating culturally sensitive components and comprehensive requirement elicitation strategies to create adaptive, universally applicable, and inclusive CC educational environments. Addressing these gaps will pave the way for a nuanced and responsive integration of CC technologies in diverse educational settings.