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題名：應用資料探勘技術探討高等教育申請入學條件之研究
書刊名：臺東大學綠色科學學刊
作者：林怡均／許文錦／陳仲儼 引用關係
作者(外文)：Lin, Yi-chun／Hsu, Wen-chin／Chen, Chung-yang
出版日期：2015
卷期：5:2
頁次：頁35-55
主題關鍵詞：高等教育；資料探勘；招生條件；商業智慧；Higher education；Data mining；Admission criteria；Business intelligence
原始連結：連回原系統網址new window
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高等教育發展於專業人才培育中是不可或缺的一環，且需能符合聯合國教育科學文化組織（United Nations Educational Scientific and Culture Organization, UNESCO）所提出的公平（equity）、適切（relevance）、卓越（excellence）政策來培育專業人才，故高等教育機構所自行制定之入學標準，應建立適切的選才標準來公平地審核入學資格，並使得錄取之學生經過各系所適切的課程訓練後能有專業卓越的表現。因此，本研究旨在探討入學標準是否符合系所特色，且欲瞭解學生特質對於系所課程表現的影響，進而瞭解學生潛質是否符合該系所之特色，以達成適性揚才之目標。本研究利用資料探勘中分類（classification）、分群（clustering）、關聯（association rules）及屬性選擇（attribute selection）之技術，發掘影響學業表現之因子，並歸納與建立規則模型，進而依據此模型提供招生及決策人員客觀之建議。
Higher education is critical to professional development, and must follow the policy, according to the United Nations Educational, Scientific and Cultural Organization, of fairness, appropriateness and excellence in the development. In this regard, universities and departments should select students on a fair basis with appropriate selection criteria in order to recruit the right students to become excellent in the specific professional domain. Therefore, this study focuses on the admission criteria to see how it aligns with the department educational feature for recruiting the appropriate students. Specifically, this study uses classification, grouping and attribute selection in data mining to discover potential influential factors of applicants that have positively association with the performance of future study. Further, a model is proposed in this regard to provide objective and insightful suggestion for the consideration of admission.
期刊論文
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2.Vandamme, J. P.、Meskens, N.、Superby, J. F.(2007)。Predicting academic performance by data mining methods。Education Economics，15(4)，405-419。  new window
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7.Bhise, R. B.、Thorat, S. S.、Supekar, A. K.(2013)。Importance of data mining in higher education system。Journal of Humanities and Social Science，6(6)，18-21。  new window
8.Dennis, C.、Marsland, D.、Cockett, T.(2001)。Data mining for shopping centres: customer knowledge-management framework。Journal of Knowledge Management，5(4)，368-374。  new window
9.Garton, B. L.、Dyer, J. E.、King, B. O.(2000)。The use of learning styles and admission criteria in predicting academic performance and retention of college freshmen。Journal of Agricultural Education，41(2)，46-53。  new window
10.Gnanasundari, S.、Narendran, P.(2014)。Analysis of different feature selection methods in intrusion detection system。International Journal of Research in Computer Application and Robotics，2(8)，119-125。  new window
11.Goebel, M.、Gruenwald, L.(1999)。A survey of data mining knowledge discovery software tools。ACM SIGKDD Explorations Newsletter，1(1)，20-33。  new window
12.Guruler, H.、Istanbullu, A.、Karahasan, M.(2010)。A new student performance analyzing system knowledge discovery in higher educational databases。Computer & Education，55(1)，247-254。  new window
13.Höschl, C.、Kožený, J.(1997)。Predicting academic performance of medical student: The first three year。American Journal of Psychiatry，154(6)，87-92。  new window
14.Hsieh, Y.-C.、Hu, B.(2005)。Assessment of admission criteria for predicting hotel management students' academic performance。Journal of Teaching in Travel & Tourism，5(4)，1-14。  new window
15.Kabakchieva, D.(2013)。Predicting student performance by using data mining methods for classification。Cybernetics and Information Technologies，13(1)，61-72。  new window
16.Kuncel, N. R.、Hezlett, S. A.(20070223)。Standardized tests predict graduate students' success。Science，315，1080-1081。  new window
17.Li, P. S.、Li, L.、Zong, L.(2007)。Postgraduate educational aspiration and policy and implications: A case study of university in western China。Journal of Higher Education，29(2)，143-158。  new window
18.Markov, Z.、Russell, I.(2006)。An introduction to the WEKA data mining system。ACM SIGCSE Bulletin，38(3)，367-368。  new window
19.Osmanbegovic, E.、Suljic, M.(2012)。Data mining approach for predicting student performance。Journal of Economics and Business，10(1)，3-12。  new window
20.Pandey, U. K.、Pal, S.(2011)。Data mining: A prediction of performer or underperformer using classification。International Journal of Computer Science and Information Technology，2(2)，686-690。  new window
21.Thai-Nighe, N.、Drumond, L.、Krohn-Grimberghe, A.、Schmidt-Thieme, L.(2010)。Recommender system for predicting student performance。Procedia Computer Science，1(2)，2811-2819。  new window
22.Watson, H. J.、Wixom, B. H.(2007)。The current state of business intelligence。Computer Society，40(9)，96-99。  new window
23.Yadav, S. K.、Pal, S.(2012)。Data mining: A prediction for performance improvement of engineering students using classification。World of Computer Science and Information Technology Journal，2(2)，51-56。  new window
24.Yang, B.、Lu, D.-R.(2001)。Predicting academic performance in management education: An empirical investigation of MBA success。Journal of Education for Business，77(1)，15-20。  new window
25.Romero, C.、Ventura, S.(2007)。Educational data mining: a survey from 1995 to 2005。Expert Systems with Applications，33(1)，135-146。  new window
26.Baradwaj, Brijesh Kumar、Pal, Saurabh(2011)。Mining Educational Data to Analyze Students Performance。International Journal of Advanced Computer Science and Applications，2(6)，63-69。  new window
會議論文
1.Bresfelean, V. P.(2007)。Analysis and predictions on students' behavior using decision trees in WEKA environment。The ITI 29th international conference on international technology interface。Zagreb, Croatia：SRCE University Computing Centre。51-56。  new window
2.Kiss, G.(2010)。Using data mining tools in analyzing undergraduate paper results in computer science at Obuda University。2010 of IEEE international conference on intelligent computing and integrated systems。Beijing：IEEE。954-956。  new window
3.Kovačić, Z. J.(2010)。Early prediction of student success: Mining students enrolment data。Proceedings of Informing Science & IT Education Conference (InSITE) 2010。  new window
4.Lobur, M.、Stekh, Y.、Kernytskyy, A.、Sardieh, F. M.(2008)。Some trends in knowledge discovery and data mining。The 2008 International Conference on Perspective Technologies and Methods in MEMS Design。Krasnaya Polyana。  new window
5.Minaei-Bidgoli, B.、Kashy, D. A.、Kortemeyer, G.、Punch, W.(2003)。Predicting student performance: An application of data mining methods with an educational web-based system。The 33rd ASEE/IEEE Frontiers in Education Conference。Boulder, CO.。  new window
6.Wook, M.、Wahab, N.、Awang, N. F.、Yahaya, Y. H.、Isa, M. R. M.、Seong, H. Y.(2009)。Predicting NDUM student's academic performance using data mining techniques。2009 IEEE international conference on computer and electrical engineering。Los Angeles, CA：IEEE。357-361。  new window
7.Zhang, H. Y.(2011)。A short introduction to data mining and its application。The 2011 International Conference on Management and Service Science。Wuhan。  new window
學位論文
1.溫侑柯(2005)。應用資料探勘之關聯法則探討大學入學成績對在學成績的影響--以資管系為例(碩士論文)。南華大學，嘉義縣。  延伸查詢new window
2.楊琇媛(2003)。利用資料倉儲與資料探勘技術於招生策略與學生特質分析之研究(碩士論文)。中原大學，桃園市。  延伸查詢new window
3.顏博文(2003)。應用資料探勘技術分析學生選課特性與學業表現(碩士論文)。中原大學，桃園市。  延伸查詢new window
圖書
1.Delors, J.(1998)。Learning: The treasure within。Paris：UNESCO。  new window
2.Han, J.、Kamber, M.(2001)。Data Mining: Data Mining Concepts and Techniques。San Francisco, CA：Morgan Kaufmann Publishers。  new window
3.袁梅宇(2015)。王者歸來WEKA機器學習與大數據聖經。臺北市：佳魁資訊。  延伸查詢new window
其他
1.大學招生委員會聯合會(2014)。甄選入學，http://www.jbcrc.edu.tw/indexl.htm。  延伸查詢new window
2.Fang, N.，Lu, J.(2009)。Work in progress--A decision tree approach to predicting student performance in a high-enrollment, high-impact, and core engineering course，http://fie-conference.org/fie2009/papers/1106.pdf。  new window
3.Geiser, S.，Santelices, M. V.(2007)。Validity of school grades in predicting student success beyond the freshman year: High-school record vs. standard tests as indications of four-ear college outcomes，http://www.cshe.berkeley.edu/sites/default/files/shared/publications/docs/ROPS.GEISER._SAT_6.13.07.pdf。  new window
4.Holmes, G.，Donkin, A.，Witten, I. H.(1994)。Weka: A machine learning workbench，http://www.cs.waikato.ac.nz/~ihw/papers/94GH-AD-IHW-WEKA.pdf。  new window
5.Ismail, N. H.，Ahmad, F.，Aziz, A. A.(2013)。Implementing WEKA as a data mining to analyze students' academic performances using Naïve Bayes Classifier，https://www.researchgate.net/publication/266082974_Implementing_WEKA_as_a_Data_Mining_Tool_to_Analyze_Students'_Academic_Performances_Using_Naive_Bayes_Classifier。  new window
6.Tovar, E.，Soto, Ó.(2010)。The use of competences assessment to predict i the performance of first year student，http://www.fie-conference.org/fie2010/papers/1498.pdf。  new window
 
 
 
 
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