A Study of Recruiting Strategies and Student Profiles Using Data Warehouse and Data Mining

碩士 === 中原大學 === 資訊管理研究所 === 91 === When the educational policy changes to multiple enrollment program, each school and department can recruit suitable students. Objective and helpful data will assist administrative person with strategy planning, and then these information will promote student qualit...

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Bibliographic Details
Main Authors: Hsiu-Yuan Yang, 楊琇媛
Other Authors: W. P. Lee
Format: Others
Language:zh-TW
Published: 2003
Online Access:http://ndltd.ncl.edu.tw/handle/z9ezw3
Description
Summary:碩士 === 中原大學 === 資訊管理研究所 === 91 === When the educational policy changes to multiple enrollment program, each school and department can recruit suitable students. Objective and helpful data will assist administrative person with strategy planning, and then these information will promote student quality and raise the competition of school. This search target is Chung Yuan Christian University, and the data resources are scores databases and profile databases from 86 to 90 academic year. The main research objects are following: 1.To apply efficient architecture of data warehouse and design procedure to integrate exotic and distributed student databases through academic research. 2.This study will analyze the relationship between school admission type and academic performance, and the finding of the results is collected to be a great contribution to support the workload of admission application, and recommendation entrollment. Furthermore, these data must help to choose the “right” person via objective information from many applicants. 3.To provide reference documents concerning how to choose marketing target school by analyzing the relationship between education background and academic performance. 4.To make trend analysis in residents, school admission type, and education background by using statistical chart. 5.To mine the If-Then rules of what is the key factor of academic achievement by using Decision Tree Analysis, and find the relationship between semester final scores and profile data including residents, school admission type, and education background. 6.Finally, based on the results, suggestions for educational administration agencies, universities, teachers and future study were proposed.