Soh, BenAlmaghrabi, Hamad2026-04-022026https://hdl.handle.net/20.500.14154/78555The integration of Information and Communication Technology (ICT) in educational administration offers transformative opportunities to enhance efficiency and user satisfaction, but also presents significant challenges. Despite the potential of ICT systems to stream- line processes and support data-driven decision-making, their implementation is often hindered by fragmented infrastructures, inconsistent adoption, and limited alignment with user needs. This thesis addresses these challenges through the design and evaluation of the AI-integrated IiCE framework, developed to strengthen ICT adoption and administrative performance in educational institutions. Educational administrative environments are inherently complex, characterised by mul- tidimensional data, dynamic workflows, and overlapping responsibilities that often expose systemic inefficiencies. The proposed IiCE framework leverages predictive analytics and user-centred design principles to generate actionable insights for optimising ICT utilisa- tion. Its key objectives include identifying the determinants of user satisfaction, enhancing decision-making processes, and fostering an organisational culture that supports technolo- gical innovation and acceptance. Employing a mixed-methods research approach, this study investigates current ICT ad- option practices in Saudi educational institutions. Quantitative and qualitative analyses, incorporating stakeholder perceptions and institutional data, were conducted to uncover adoption barriers and performance gaps. Machine learning (ML) models were applied to predict user satisfaction trends, while SHAP (Shapley Additive Explanations) techniques provided interpretability by highlighting the most influential factors affecting adoption. The framework also integrates adaptive training modules, modular deployment strategies, and continuous feedback mechanisms to ensure sustainability and contextual adaptability. Grounded in Saudi Arabia’s Vision 2030 for digital transformation, the evaluation of the IiCE framework demonstrates its ability to enhance administrative workflows, optim- ise resource allocation, and strengthen stakeholder engagement. Expert validation con- firms its effectiveness in mitigating inefficiencies, promoting collaboration, and supporting evidence-based management practices. This research contributes to the fields of educational administration and ICT innova- tion by presenting an adaptable, AI-driven framework that bridges the gap between tech- nological potential and practical implementation. The findings underscore the value of advanced AI techniques in managing ICT complexity, driving user satisfaction, and im- proving institutional efficiency. Future work may extend this framework through real-time analytics, greater model interpretability, and cross-domain applications for broader educational impact143enArtificial IntelligenceBig DataData MiningInformation And Communication TechnologyInformation TechnologyExplainable Artificial IntelligencePreferred Reporting Items For Systematic Reviews And Meta- AnalysesMachine LearningThesis