資料採礦在學生流失偵測上之應用

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Title:	資料採礦在學生流失偵測上之應用
Other Titles:	Application of Data Mining Techniques for Detection of Student Drop out
Authors:	許依宸 Hsu, Yi-chen
Contributors:	資訊管理學系碩士班邱宏彬 Hung-pin Chiu
Keywords:	學生流失;決策樹;資料採礦;類神經網路 neural networks;data mining;student drop out;decision tree
Date:	2009
Issue Date:	2015-03-25 15:25:08 (UTC+8)
Abstract:	依據教育部資料，本國大專校院數量不斷增加，大學日間部學生招生人數亦隨之增加，然而，依據內政部之統計資料，本國出生人口總數卻是不斷減少，因此招生情況是日益嚴峻。本研究以南華大學94-96學年度大學日間部入學學生資料為例，運用資料採礦技術，分析學生歷史學籍資料，找出流失學生之潛在共同因素，建立學生流失預測模型。針對本研究之資料採礦結果，本研究將提出相關之建議，提供學校參考以改善學生流失之情況。　　According to the data from Ministry of Education, the number of college increase constantly. The enrollment of students in the day school also increases. However, the statistics showed from Ministry of Internal Affair that total birth rate of Taiwan is decreasing. Therefore, the enrollment status is getting tougher. This research is based on the day school student enrollment data between 2005~2007 in Nan-hua University. By using the data mining techniques and analyzing the history of student record, this research tried to find the command of potential reason and created a predict model of why students drop out. The analyzing and mining results from this research will provide relevant suggestions to help the university to improve the situation of student drop out.
Appears in Collections:	[Department of Information Management] Disserations and Theses

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