Apply Kano Quality Model and Data Mining to Analyzing Relationship among Pre- and Post- Entrance Performance of Students, and Entrance Evaluation Criteria
|關鍵字:||入學審查;Kano二維品質;關聯規則;群集分析;entrance evaluation;Kano model;association rule;cluster analysis|
The aim of this research is to understand relationship among pre-and post- entrance performance of department of civil engineering students, and entrance evaluation criteria. Put forward the feasibility of kano model in entrance evaluation criteria. Apply association rule and cluster analysis to explore: (1) the relationship between student background and college grades, (2) the influencing factors of changing major, (3) prestigious school and place benefits; (4) the relationship among pre-and post- college entrance scores, (5) the relationship among the compulsory subject score of civil engineering. We found the difference of gender and high school categories would affect students’ college grades. Students were less likely to change their major, if their next of kin engaged in civil engineering industry. Then, different academic achievement or different graduated schools would affect college students’ academic performance. We also found association rule among the compulsory subjects. Moreover, Document review is more correct than SAT score, when predicting first-year college grades.
|Appears in Collections:||Thesis|