Operationalizing Mobile Cloud Learning in Conflict-Affected Universities: An Evidence-Based Adoption Model from Sudan

Abstract

Mobile cloud learning has emerged as a promising approach to supporting educational continuity in conflict-affected and resource-constrained higher education environments. However, existing research has primarily focused on readiness assessment and adoption intention while providing limited guidance on how assessment outcomes can be translated into practical implementation strategies. This study addresses this gap by proposing an evidence-based operational adoption model that synthesizes previously validated readiness assessment outcomes and critical success factors into a structured implementation framework. Using a conceptual model development approach, the study translates existing evidence into actionable guidance for institutional decision-making. The main results include the development of a readiness-based classification framework that categorizes institutions into low, medium, and high readiness adoption paths, an operational decision logic linking readiness conditions to appropriate implementation strategies, and a four-phase implementation roadmap consisting of preparation, deployment, evaluation, and continuous improvement. The proposed model emphasizes proportional adoption, low-cost feasibility, and alignment between institutional capacity and implementation scope, making it particularly relevant for fragile and resource-constrained higher education settings. By repositioning readiness assessment as a foundation for operational decision-making rather than a diagnostic endpoint, the study contributes an implementation-oriented perspective to mobile cloud learning adoption research. As a conceptual study, the proposed framework is intended to guide institutional leaders, policymakers, and crisis education planners, while future research should empirically evaluate its effectiveness in real world educational contexts.