大學在經營管理、學術發展及重要策略規劃上的評估、決策及品質保證已大量運用校務研究的的觀念與方法。隨著國際開放資料、巨量資料、物聯網、智慧城市、工業4.0等興起的資料科學風潮及國內外高等教育環境的變遷，開啟了運用巨量資料分析方法於校務研究的趨勢。本文提出在確保學生學習成效的目標下，校務研究可藉由巨量資料的演算法，建立運用資料科學治理校務的思維與精進大學治理的成效。並以學生特質、教師教學、課程特色及職場表現中之複雜因果關係為例，說明巨量資料分析與預測模型（演算法）在校務研究的運用。預測結果能回饋至招生與選才，建立最適的招生媒合機制，協助學校各科系能找到最適合學校辦學理念及特色發展的學生。

The concepts and methodologies of the Institutional Research (IR) have been extensively used in the managements, academic developments as well as the evaluation, decision making and quality assurance of the important strategic planning of universities. Due to the uprising agitation of data science, which including international open data resource, big data, internet of things (IOT), smart city and industry 4.0, as well as the evolving of the higher education environment, the implement of big data analysis in IR has started a stream of movement. In the present study, under the goal of accountable learning outcome assurance, the big data algorithms could be employed in the IR to build up the ideology of using data science in the institutional administration and to enhance the administration performance. In addition, with the complex cause-effect relations among student characteristics, instructor teaching, course uniqueness and vocational manifestation, the use of big data analysis and predictive models (algorithms) in IR are illustrated. The predictions can be feedback to the mechanisms of enrollment and selection of new students, and set up an optimal enrolling and matching system to assist each department to locate students that are the most suitable for the education philosophy and specialty developments of the university.