臺灣博碩士論文加值系統

近年來，隨著台灣經濟不景氣，薪資倒退,國人為了維持基本生活品質加上對未來的不確定感增加導致生育的情況不減反增。在少子化的情況下除了幼托教育首當其衝,而兒童補教機構深受影響，但根據相關單位資訊統計資料結果顯示，台灣補教業不減反增，而補教業者在僧多粥少的情況下，本研究主要利用資料探勘技術來探討顧客滿意度及新課程開發.暑假課程開發之關聯來發展出新的模式新的市場．本研究以現行連鎖美語補習班家長為研究樣本,共發放1020份問卷,回收811份問卷.本研究透過資料探勘將顧客就讀原因,顧客對於該補習班優缺點看法,顧客滿意因素,成人課程主題偏好,兒童暑假課程主題進行分析,研究結果顯示顧客關係管理的改善與新主題課程的研發具有相關.此研究建議該補習班業者可開發親子共讀課程,該管理者也可藉此進一步了解顧客滿意因素如何影響其課程主題策略選用.

The last two decades have seen growing importance placed on research in shadow education. The field of the shadow education in Taiwan has undergone many fluctuation and shifts over the years. The high cost of living and the necessity for both parents to work has given rise to notion that children are an unwelcome border. Shadow education in Taiwan is having trouble to get students and that is not the only problem of the situation. Shadow education is getting more and more in current market. However, research which has empirically documented the link between data mining and shadow education is scant. Therefore, the aim of this article attempts to explore how parents feel about “E” institute of education and their preference of subject course are related. This research involved a survey; the sample focuses on parents whose children study English at “E” Learning Institutes across Taiwan. A total of 1,860 questionnaires were distributed and 811 effective questionnaires. The quantitative analysis of the questionnaires was conducted through clustering analysis and association rules of data mining. In order to indicate the customer relationship and preferences of parents between related. To conclude, this study may be of importance in explaining development of CRM and new curriculum create, as well as in providing, manager of the institute with a better understanding of how parents feel about the institute relate to their strategy use.

Index
淡江大學研究生論文中文提要 I
Abstract II
List of Tables VI
List of Figures VII
Chapter 1.Introduction 1
Chapter 2.Literature review 4
2.1. Shadow education 4
2.2. Customer relationship management 6
2.2.1 CRM in education 7
2.3. Curriculum 8
2.4. Data Mining 9
2.4.1 Cluster analysis and K-means algorithm 9
2.4.2 Association rules 10
Chapter 3 The case firm 13
3.1. About “E” of the learning institute 13
3.2. Programs of “E” learning institute 13
3.2.1 Immersion 13
3.2.2 Elementary 13
Chapter 4 Methodology 15
4.1. Database 15
4.1.1 Research framework 15
4.1.2 System design 16
4.1.3 Conceptual database 17
4.1.4 Questionnaire design 17
4.2. Cluster analysis 22
4.2.1 Data mining for multi-subject course and customer adumbration 22
4.2.2 Customer similarity and segmentation 23
4.3. Association rules 27
4.3.1 Points for development of CRM analysis 27
4.3.2 New curriculum creation analysis 28
Chapter 5. Data mining and results 29
5.1. Pattern-1 points for development of CRM 29
5.2. Pattern-2 new curriculum creation 32
Chapter 6. Managerial implication 39
6.1. Points for development of CRM 39
6.1.1 The reason for choosing the institute 39
6.1.2 Strengths/weaknesses 39
6.1.3 Satisfaction/point of concern 40
6.2. New curriculum creation 45
6.2.1 Parent-child course subject preference/summer vacation English course subject preference 46
6.2.2 Elective student-course subject preference/elective parent-course subject preference 47
Chapter 7. Conclusion 52
REFERENCE 53
APPENDIX 1 Questionnaire 56



Table 1. Questionnaire statistics 18
Table 2. Questionnaire data 19
Table 3. Questionnaire results 22
Table 4. K-mean cluster and categories 26
Table 5. Cluster-1 points for development of CRM 30
Table 6. Cluster-2 points for development of CRM 31
Table 7. Cluster-3 points for development of CRM 31
Table 8. Cluster-1 new curriculum creation 36
Table 9. Cluster-2 new curriculum creation 36
Table 10. Cluster-3 new curriculum creation 37
Table 11. Points for development of CRM 45
Table 12. New curriculum creation 51



Figure 1. Research framework 15
Figure 2. System architecture 16
Figure 3. Conceptual database design: E-R model 21
Figure 4. K-means cluster analysis 23
Figure 5. K-mean cluster analysis 25
Figure 6. Cluster-1 points for development of CRM 32
Figure 7. Cluster-2 points for development of CRM 33
Figure 8. Cluster-3 points for development of CRM 34
Figure 9. Cluster-1 new curriculum creation 37
Figure 10. Cluster-2 new curriculum creation 38
Figure 11. Cluster-3 new curriculum creation 38
Figure 12 Points for development of CRM map 44
Figure 13. New curriculum creation map 50

Reference
Agrawal, R., T. Imilienski, and A. Swami, A. 1993. Mining association rules between sets of items in large databases. In Proceedings of the 1993 ACM SIGMOD international conference on management of data, Washington, DC, USA, 207-216.
Agrawal, R., and J. Shafer. 1996. Parallel mining of association rules. IEEE Transactions on Knowledge and Data Engineering 8:962-969.
Berzal, F., J. Cubero, N. Marín, and J. Serrano. 2001. TBAR: An efficient method for association rule mining in relational databases. Data and Knowledge Engineering 37:47-64.
Brady, L. (1995). School-based curriculum development and national curriculum: can they coexist? Curriculum and Teaching, 10(1), 47-53.
Bray, M. (1999). The shadow education system: Private tutoring and its implications for planners. Paris: UNESCO International Institute for Education Planning.
Bray, M. (2003). Adverse effects of private supplementary tutoring: Dimensions, implications and government responses. Paris: UNESCO International Institute for Educational Planning.
Bray, M. (2009). Confronting the shadow education system: What government policies for what private tutoring? Paris: UNESCO International Institute for Educational Planning.
Bray, M., & Kwok, P. (2003). Demand for private supplementary tutoring: Conceptual considerations, and socio-economic patterns in Hong Kong. Economics of Education Review, 22, 611-620.
Bray, M., & Silova, I. (2006). The private tutoring phenomenon: International patterns and perspectives. In I. Silova, V. Būdiene & M. Bray (Eds.), Education in a hidden marketplace: Monitoring of private tutoring (pp. 27-40). New York, NY: Open Society Institute.
Clark, J. L. (1987). Curriculum renewal in school foreign language learning. Oxford: Oxford University Press.
Craig, C. J. (2006). Why is dissemination so difficult? The nature of teacher knowledge and the spread of curriculum reform. American Educational Research Journal, 43(2), 257-293.
Codd, E. F. 1970. A relational model of data for large relational database. Communications of the ACM 13 (2): 377-387.
Dang, H. A. (2007). The determinants and impact of private tutoring classes in Vietnam. Economics of Education Review, 26, 684-699.
Dawson, W. (2010). Private tutoring and mass schooling in East Asia: Reflections of inequality in Japan, South Korea, and Cambodia. Asia Pacific Education Review, 11(1), 14-24.
Elaine D. Seeman Margaret O`Hara, (2006), “Customer relationship management in higher education using systems to improve the student-school relationship”, Campus-Wide Information System, Vol.23 Iss 1 pp.24-34.
Fishman, B. J., Marx, R. W., Best, S., & Tal, R. T. (2003). Linking teacher and student learning to improve professional development in systemic reform. Teaching and Teacher Education, 19, 643-658.
Foondun, A. R. (2002). The issue of private tuition: An analysis or the practice in Mauritius and selected South-East Asian countries. International Review of Education, 48(6), 485-515.
Gallo, A., R. Esposito, R. Meo, and M. Marco Botta. 2007. Incremental extraction of association rules in applicative domains. Applied Artificial Intelligence 21 (4): 297-315.
Gordon, P. (1981). The study of the curriculum. London: Batsford.
Gordon, E. E., Morgan, R. R., O’Malley, C. J., & Ponticell, J. (2007). The tutoring revolution: Applying research for best practices, policy implications, and student achievement. Lanham, MD: Rowman & Littlefield Education.
Izumi Mori.David Baker(2010) “the origin of universal shadow education: what the supplemental education phenomenon tells us about the postmodern institution of education. Asia Pacific Educ. Rev. 11:36-48
Kelly, A. (1999). The curriculum: Theory and practice (4th ed.). London: Paul Chapman.
Knowles, J. G. (1999). Pre-service teachers’ professional development: researching the first years of teaching. Journal of Curriculum Studies, 31(1), 99-105.
Kouris, I. N., Makris, C. H., & Tsakalidis, A. K. (2005). Using information retrieval techniques for supporting data mining. Data & Knowledge Engineering, 52 (3), 353-383.
Kwok, P. (2009). A cultural analysis of cram schools in Hong Kong: Impact on youth values and implications. Journal of Youth Studies, 12(1), 104-114.
Lee, C. J. (2005). Korean education fever and private tutoring. KEDI Journal of Education Policy, 2(1), 99-107.
Roesgaard, M. H. (2006). Japanese education and the cram school business: Functions, challenges and perspectives of the juku. Copenhagen: NIAS Press.
Richardson, V. (1997). Constructivist teaching and teacher education: theory and practice. In V. Richardson (Ed.), Constructivist teacher education: Building new understandings (pp. n/a). London: Falmer.
Saad F. Shawer. (2010) “Classroom-level curriculum development: EFL teachers as curriculum-developers, curriculum-markers and curriculum-transmitters” Teaching and Teacher Education. 26(2010) 173-184.
Shu-Hsien Liao, Yin-Ju Chen, and Hsiao-Wei Yang. (2013) Mining customer knowledge for channel and product segmentation, Taylor & Francis Group Research. 27:635-655.
Shu-Hsien Liao, Chih-Hao Wen, Pei-Yuan Hsian, and Chen-Wei Hsu. (2014).Mining customer knowledge for a recommendation system in convenience stores, International Journal of Data Warehouse and Mining. 10(2), 57-88.
Silova, I, Budiene, V. and Bray. M. (Eds.). (2006). Education in a hidden marketplace: Monitoring private tutoring. Open Society Institute.
Snyder, J., Bolin, F., & Zumwalt, K. (1992). Curriculum implementation. In P. W. Jackson (Ed.), Handbook of research on curriculum (pp. 402-435). New York: Macmillan.
Taba, H. (1962). Curriculum development: Theory and practice. New York: Harcourt.
Tsechansky, M., N. Pliskin, G. Rabinowitz, and N. Porath. 1999. Mining relational patterns from multiple relational tables. Decision Support Systems 27 (1-2): 177-195.
Tseng, L. C. J. (1998). Private supplementary tutoring at the senior secondary level in Taiwan and Hong Kong. Master of Education, The University of Hong Kong,
Hong Kong.
Ture, M., I. Kurt, K. A. Turhan, and K. Ozdamar. 2005. Comparing classification techniques for predicting essential hypertension. Expert Systems with Applications 16 (4): 379-384.
Tyler, R. (1949). Basic principles of curriculum and instruction. Chicago: The University of Chicago Press.
Wang, Y. F., Y. L. Chuang, M. H. Hsu, and H. C. Keh. 2004. A personalized recommender system for the cosmetic business. Expert Systems with Applications 26 (3): 427-434.
Yung, Wai-Ho “Shadow education in Hong Kong: the experience of learners of English”. (Thesis, University of Hong Kong,2011).