校務研究的雙重角色：人工智慧時代公共價值與績效治理的制度張力

The Dual Roles of Institutional Research in the Age of AI: Institutional Tensions Between Public Value and Performance Governance

高等教育歷經數位轉型與治理改革，校務研究（Institutional Research, IR）已與人工智慧（Artificial Intelligence, AI）結合，正逐步重塑大學決策模式與治理邏輯。本研究從「公共價值」觀點探討AI驅動下校務研究角色之轉變，分析其促進公共利益與強化績效治理間之制度張力。研究發現，校務研究已由傳統決策支援工具轉變為影響治理運作重要機制，AI導入則強化其預測分析和決策參與功能，校務研究若能結合AI，實具提升治理效率、強化問責機制與潛在促進教育公平可能性之作用；惟其嵌入績效導向與數據邏輯，亦可能導致教育價值被簡化為可量化成果，壓縮教育公共性。依「校務研究的雙重角色」觀點，校務研究為公共價值促進者與績效治理工具，建議高等教育應透過制度設計與治理調整，在數據驅動決策與教育公共使命間取得平衡。

Against the backdrop of digital transformation and governance reform in higher education, the integration of Institutional Research (IR) and Artificial Intelligence (AI) is reshaping university decision-making and governance. Drawing on a public value perspective, this paper examines the role transformation of IR in AI-driven higher education and analyzes the institutional tensions between the promotion of public interest and the reinforcement of performance governance. By synthesizing New Public Management (NPM) and data governance theories, this paper argues that IR has evolved from a conventional decision-support tool into an institutional mechanism that actively shapes governance logic. The incorporation of AI further amplifies IR’s capacity for predictive analytics and decision-making involvement. While this integration holds potential for enhancing governance efficiency, strengthening accountability, and advancing educational equity, the embedded performance-oriented and data-driven logic may also reduce educational values to quantifiable outcomes, thereby eroding higher education’s public character. This paper develops the concept of IR’s “dual roles”– simultaneously functioning as a promoter of public value and as an instrument of performance governance. The structural tension between these two roles cannot be resolved by technological advancement alone; its resolution depends on institutional design and governance orientation. Using AI-based student attrition prediction systems as an illustrative case, the paper demonstrates how identical technical capabilities can yield fundamentally different social outcomes depending on the institutional context in which they are embedded. The paper concludes by recommending that higher education institutions establish governance frameworks that embed public value principles– from indicator design to data governance– ensuring that data-driven decision-making and the public mission of education remain in balance.