校務研究近年於高等教育中備受矚目，尤其重視學生於學習歷程中型態殊異之各類質、量化數據建置，期從數據中將研究結果加值於學生學習成效，回歸以學生為本位之教學理念，共創高等教育領域之教、學雙贏。本文利用資料探勘領域的群集分析技術將學生教學反應回饋分為九群，再對各群分析其特性，以回饋給教師做為教學改進之用。

As the growing of the researches for Institutional Research and the trends of higher education worldwide, learning processes of students become more important than ever. In this paper, we use the cluster analysis to group students into nine clusters and identify their characteristics for teaching improvement.