跳到主要內容

臺灣博碩士論文加值系統

(100.28.132.102) 您好!臺灣時間:2024/06/21 23:32
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

我願授權國圖
: 
twitterline
研究生:林亭延
研究生(外文):Ting-Yan Lin
論文名稱:基於勝算比探討學生背景與學習型態對就業表現的影響
論文名稱(外文):Exploring the Effect of Student’s Background and Learning Styles on Employment Performance Based on Odds Ratio
指導教授:蔡孟峰蔡孟峰引用關係
指導教授(外文):Meng-Feng Tsai
學位類別:碩士
校院名稱:國立中央大學
系所名稱:資訊工程學系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2023
畢業學年度:111
語文別:中文
論文頁數:51
中文關鍵詞:校務研究學習型態因果勝算比探勘勝算比卡方分析路徑分析
外文關鍵詞:institutional researchlearning stylecausal odds ratio miningodds ratiochi-square testpath analysis
相關次數:
  • 被引用被引用:0
  • 點閱點閱:56
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
本研究旨在探討學生背景與學習型態對就業表現的關係,資料樣本以國立中央大學108年畢業生為研究對象。本研究採用實證資料,資料來源為國立中央大學校務資料倉儲,使用資料欄位包含學生背景資料、UCAN職業興趣診斷與畢業後一年調查問卷。並控制該年度的就業環境和薪資水平這兩項因素所造成的影響。在經資料前處理過後,無資料缺失者共217筆。
研究方法為先利用因果勝算比探勘找出資料之間可能蘊含的準因果規則,再透過敘述性統計說明樣本分佈情形,再藉由卡方分析驗證準因果規則是否存在統計相關性,最後使用路徑分析驗證準因果規則是否可能存在因果關係。本研究發現藉由統計方法可驗證因果勝算比探勘所得出之部份準因果規則可能存在因果關係。
在分析問題中,因果勝算比探勘與統計方法之間存在先天差異,這可能是導致兩者產生不同結果的原因。若將因果勝算比探勘作為探索資料間可能因果關係的第一步,而不是最終結論,並在後續研究中,使用統計驗證或其他方法來進一步探討。這種方法提供了對尚未研究的問題進行探索,或者探索現有問題中是否存在尚未考慮的因素的可能性。
The purpose of this study is to investigate the relationship between student background, learning styles, and employment performance. The data sample consists of graduates of Nat-ional Central University in 2019. This study utilizes empirical data obtained from the univer-sity's administrative data repository, including student’s background information, UCAN vo-cational interest diagnosis, and a post-graduation survey conducted one year after graduation. The study controls the impact of employment environment and salary level of that year. After data preprocessing, a total of 217 records with no missing data were included.
The research methodology involves first using causal odds ratio mining to identify pote-ntial quasi-causal rules within the data. Descriptive statistics are then employed to describe th-e distribute-on of the sample, followed by chi-square analysis for validating the statistical cor-relation of the quasi-causal rules. Finally, path analysis is used to verify whether causal relati-onships may exist among the identified quasi-causal rules. The study found that certain quasi-causal rules obtained through statistical methods can be validated to potentially indicate caus-al relationships.
In analyzing the issue, there are inherent differences between causal odds ratio mining and statistical methods, which may account for the divergent results obtained. If causal odds ratio mining is regarded as the first step in exploring possible relationships and causality bet-ween the data, rather than as final conclusions, and if statistical validation or other methods are subsequently employed for further investigation, this approach offers a means to explore unanswered questions or the possibility of unconsidered factors in existing problems.
摘要 i
Abstract ii
誌謝 iv
目錄 v
圖目錄 vii
表目錄 viii
一、 緒論 1
1-1. 研究背景與動機 1
1-2. 研究目的 1
1-3. 研究範圍 2
1-4. 論文架構 2
二、 文獻探討 4
2-1. Kolb經驗學習理論 4
2-2. 資料倉儲 6
2-3. 資料探勘 6
2-4. 路徑分析 9
三、 研究方法 10
3-1. 系統架構與流程 10
3-2. 資料欄位選擇與資料前處理 10
3-3. 關聯規則與因果勝算比 17
3-4. 統計分析方法 18
3-5. 結果探討 19
四、 分析 20
4-1. 分析平台 20
4-2. 準因果規則 20
4-3. 樣本特性分析 21
4-4. 學生背景、學習型態對平均每月收入差異分析 25
4-5. 偏最小平方法的結構方程模型 28
五、 結論與未來展望 33
5-1. 研究結果討論 33
5-2. 研究結論 34
5-3. 研究限制 34
5-4. 未來展望 34
六、 參考文獻 36
[1] 網路資料:410教改聯盟-文化部國家文化紀錄庫。
取自https://memory.culture.tw/Home/Detail?Id=312830&IndexCode=Culture_Event
[2] 網路資料:國家發展委員會-大專院校學校數。
取自https://www.ndc.gov.tw/Content_List.aspx?n=CD0C0A5FC08858C9
[3] 網路資料:110年人力運用統計調查結果。
取自https://www.dgbas.gov.tw/News_Content.aspx?n=3602&s=207928
[4] More,A.J., Adapting teaching to the learning styles of native Indian students. ERIC Document Reproduction Service No.ED 366 493, 1993.
[5] Kolb, David., Experiential Learning: Experience As The Source Of Learning And Development., Englewood Cliffs, N.J. :Prentice-Hall, 1996.
[6] Han, J., Kamber, M. & Pei, J., Data Mining Concepts and Techniques., 3rd edition., Morgan Kaufmann Publishers., 2012.
[7] Agrawal, R. and Srikant, R., “Fast Algorithms for Mining Association Rules in Large Databases”, Proceedings of the 20th International Conference on Very Large Data Bases, pp. 487-499, Santiago, Chile, September 1994.
[8] Han, J., Pei, J. & Yin, Y., “Mining Frequent Patterns Without Candidate Generation”, ACM International Conference on Management of Data and Symposium on Principles of Database Systems, pp. 1-12, New York, USA, June 2000.
[9] Messerli, F. H., “Chocolate consumption, cognitive function, and Nobel laureates”. The New England Journal of Medicine, Vol 367(16), pp. 1562-1564, 2010.
[10] J. W. Song and K. C. Chung., “Observational studies: Cohort and case-control studies”, Plastic and Reconstructive Surgery, Vol 126(6), pp. 2234–2242, 2010
[11] Bland, J. M., & Altman, D. G. 2000, “The odds ratio”, British Medical Journal, Vol. 320, pp. 1468, May 2000.
[12] Jiuyong Li, Thuc Duy Le, Lin Liu, Jixue Liu, Zhou Jin, Bingyu Sun, and Saisai Ma., “From Observational Studies to Causal Rule Mining”, ACM Transactions on Intelligent Systems and Technology, Vol 7(2), pp. 1-27, November 2015.
[13] Wright, S., “Correlation and Causation”, Journal of Agricultural Research, Vol 20, pp. 557-585, 1921.
[14] Atkinson, G., Murrell, P. H., & Winters, M. R., “Career Personality Types and Learning Styles. Psychological Reports”, Psychological Reports, Vol 66(1), pp. 160-162, 1990.
[15] Hair, J., Hult, G. T. M., Ringle, C. M., & Sarstedt, A primer on partial least squares structural equation modeling (PLS-SEM)., 2nd edition., SAGE Publications., 2016.
[16] Chin, Wynne & Marcoulides, G., The Partial Least Squares Approach to Structural Equation Modeling., Lawrence Erlbaum Associates Publishers., 1998.
[17] Cohen, J., Statistical power analysis for the behavioral sciences., Lawrence Erlbaum Associates Publishers., 1988.
[18] Baron, R. M., & Kenny, D. A., “The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations”, Journal of Personality and Social Psychology, Vol 51(6), pp. 1173-1182, 1986.
[19] Simpson, E. H., “The Interpretation of Interaction in Contingency Tables”, Journal of the Royal Statistical Society. Series B (Methodological), Vol 13(2), pp. 238-241, 1951.
電子全文 電子全文(網際網路公開日期:20240710)
連結至畢業學校之論文網頁點我開啟連結
註: 此連結為研究生畢業學校所提供,不一定有電子全文可供下載,若連結有誤,請點選上方之〝勘誤回報〞功能,我們會盡快修正,謝謝!
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top