Leveraging Cloud Computing Engineering for Sustainable Education: A Computational Evaluation Framework

As the world confronts complex climate-change challenges, integrating sustainability principles into engineering and computing curricula has become imperative. Traditional learning-system infrastructures, however, often lack the scalability, energy efficiency, and computational capacity required for modern data-driven educational environments. This study develops a computational evaluation framework that models sustainability integration as a cloud engineering optimization problem. Through a structured bibliometric and secondary empirical synthesis of 30 peer-reviewed studies (2013–2025), the research introduces the Cloud Sustainability Impact Pathway (CSIP), a reproducible engineering abstraction that maps cloud computing mechanisms—such as virtualization efficiency, elastic provisioning, and AI-driven orchestration—to measurable sustainability outcomes. A normalized aggregation model, the Cloud Sustainability Impact Score (CSIS), quantifies sustainability alignment across heterogeneous institutional contexts. Unlike conventional narrative reviews, this study formalizes sustainability evaluation using a computational scoring framework with defined metrics, weighted aggregation, sensitivity analysis, and linear-time complexity characterization. Descriptive analysis of the synthesized literature is consistent with higher reported CSIS values for cloud-native architectures relative to traditional on-premises educational infrastructures, although this association should not be read as a controlled causal comparison (see Section V). A supervised machine-learning procedure is additionally used to characterize how closely regression models can approximate the CSIS aggregation function itself, which is a check on the internal consistency and computability of the scoring formula rather than an independent empirical validation. The proposed framework supports scalable benchmarking and reproducible, semi-automated sustainability assessment of cloud-enabled learning systems, and positions cloud computing engineering as a measurable, if not yet causally established, contributor to sustainable education transformation.

@article{Bannor2026,
  title     = {Leveraging Cloud Computing Engineering for Sustainable Education: A Computational Evaluation Framework},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {17},
  number    = {9},
  year      = {2026},
  publisher = {The Science and Information Organization},
  author    = {Emmanuel Ofotsu Kwesi Bannor and S. Sarah Maidin and Vinayakumar Ravi and Nguyen Thi Thu Thuy and Nghiem Thi-Lich and Adade Sedom Percy},
  doi       = {10.14569/IJACSA.2026.0170937},
  url       = {https://doi.org/10.14569/IJACSA.2026.0170937}
}