<![CDATA[Purpose – This study develops a conceptual framework for an Artificial-Intelligence-based Educational Decision Support System (AI-EDSS) to support academic and administrative decision-making in Nigerian Colleges of Education. It addresses the limited integration of institutional data readiness, AI-enabled analytics, decision-support usability, technology acceptance, human oversight, and governance within existing educational decision-support approaches, particularly in resource-constrained African higher-education contexts.Method – A structured conceptual-synthesis methodology was employed. Literature was searched between January and March 2026 across Scopus, Web of Science, ERIC, IEEE Xplore, ScienceDirect, and Google Scholar. Forty-two sources passed initial screening, of which 21 were retained for inductive-deductive thematic coding, theory mapping, framework construction, and proposition development.Findings – The synthesis produced a five-layer AI-EDSS comprising an Institutional Data Layer, AI/Analytics Processing Layer, Decision-Support and Recommendation Layer, Human-in-the-Loop Interaction Layer, and a cross-cutting Governance, Ethics, and Feedback Layer. Six theoretical propositions were derived linking data integration, predictive utility, user uptake, facilitating conditions, institutional trust, model feedback, and human decision authority.Limitations – The framework is conceptual and has not been empirically validated, prototyped, externally validated, or tested with institutional data. Its propositions require subsequent empirical operationalisation and validation.Originality – The study integrates DSR, educational data mining, UTAUT, human oversight, and responsible governance within a context-sensitive architecture tailored to Nigerian Colleges of Education.]]>
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