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  1. NTU Theses and Dissertations Repository
  2. 管理學院
  3. 管理學院企業管理專班(Global MBA)
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/85789
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dc.contributor.advisor孔令傑(Ling-Chieh Kung)
dc.contributor.authorYi-Rou Wangen
dc.contributor.author汪亦柔zh_TW
dc.date.accessioned2023-03-19T23:24:27Z-
dc.date.copyright2022-07-05
dc.date.issued2021
dc.date.submitted2022-04-18
dc.identifier.citationChamizo-Gonzalez, J., Cano-Montero, E.I., Urquia-Grande, E. and Muñoz-Colomina, C.I. (2015). Educational data mining for improving learning outcomes in teaching accounting within higher education. International Journal of Information and Learning Technology, 32(5), 272-285. Coussement, K. and Van den Poel, D. (2008). Churn prediction in subscription services: An application of support vector machines while comparing two parameter-selection techniques. Expert Systems with Applications, 34(1), 313-327. Coussement, K., Phan, M., De Caigny, A., Benoit, D.F., Raes, A. (2020). Predicting student dropout in subscription-based online learning environments: The beneficial impact of the logit leaf model. Decision Support Systems, 135, 113325 FutureLearn (2021). Learning Subscriptions: the Education Trend of 2020. Retrieved on August 19, 2021, https://www.futurelearn.com/info/blog/learning-subscriptions-2020 Hu, Y.-H., Lo, C.-L. and Shih, S.-P. (2014). Developing early warning systems to predict students’ online learning performance. Computers in Human Behavior, 36, 469-478. LaRose, R. and Whitten, P. (2000). Re-thinking Instructional Immediacy for Web Courses: A Social Cognitive Exploration. Communication Education, 49(4), 320. Lau, Y.-H., Li, J.-B. and Lee, K. (2021). Online Learning and Parent Satisfaction during COVID-19: Child Competence in Independent Learning as a Moderator. Early Education and Development, 32(6), 830-842. Lee, Y., Choi, J. and Kim, T. (2013). Discriminating factors between completers of and dropouts from online learning courses. British Journal of Educational Technology, 44(2), 328-337. Li, C. (2020). The COVID-19 pandemic has changed education forever. This is how. World Economic Forum. Retrieved on August 22, 2021, https://www.weforum.org/agenda/2020/04/coronavirus-education-global-covid19-online-digital-learning/ Liaw, S.-S. and Huang, H.-M (2013). Perceived satisfaction, perceived usefulness and interactive learning environments as predictors to self-regulation in e-learning environments. Computers & Education, 60(1), 14-24. Technavio (2020). Global Online Education Market 2020-2024. Retrieved on August 23, 2021, https://www.technavio.com/report/online-education-market-industry-analysis
dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/85789-
dc.description.abstractnonezh_TW
dc.description.abstractAs subscription-based business models continue to gain traction across the board, users can essentially purchase a subscription service for just about anything other than only newspapers and music streaming services. However, research on subscriptions in the past mostly focus on magazines and traditional utility businesses only. As online learning has become an emerging market around the globe, we conducted this study to identify factors affecting the subscription of online educational products. In this study, we collect real subscription records and the corresponding learning records of both elementary school and junior high school students in Taiwan to analyze what factors may be impacting the length of subscription periods. The record is collected from company P, an online educational products provider, and we take its reading-comprehension product as an example. The results of this study indicate that factors affecting elementary school and junior high school students vary. The length of time spent for completing missions matters for elementary school students, while the average correctness rate and mission completion rate are what subscribers for junior high school students care about. The findings suggest that companies should, in general, make the difficulty level of online learning content “above average” rather than “below average” in order to better retain the subscribers.en
dc.description.provenanceMade available in DSpace on 2023-03-19T23:24:27Z (GMT). No. of bitstreams: 1
U0001-1404202213012800.pdf: 778437 bytes, checksum: 8f844c2c5b368923e7f5c820ff1248e9 (MD5)
Previous issue date: 2021
en
dc.description.tableofcontentsAcknowledgement i Abstract ii Table of Contents iii List of Figures iv List of Tables v 1. Introduction 1 1.1 Background and Motivation 1 1.2 Research Objectives 3 1.3 Research Plan 4 2. Literature Review 5 2.1 Subscription Decisions 5 2.2 Online Learning Performance 6 3. Research Method and Hypotheses 8 3.1 Data Source 8 3.2 Data Description 10 3.3 Hypotheses 11 4. Analysis 14 4.1 Exploratory Data Analysis 14 4.2 Regression Analysis & Interpretation 22 5. Conclusions and Future Directions 26 5.1 Conclusions 26 5.2 Future Directions 27 Bibliography 28
dc.language.isoen
dc.subjectnonezh_TW
dc.subjectregressionen
dc.subjectonline learningen
dc.subjectsubscriptionsen
dc.subjectlearning performanceen
dc.subjectdifficulty levelen
dc.title線上教育產品訂閱期長之影響因子:以閱讀素養產品為例zh_TW
dc.titleFactors Affecting the Length of Subscription Periods of Online Educational Products: Taking A Reading-Comprehension Product as an Exampleen
dc.typeThesis
dc.date.schoolyear110-2
dc.description.degree碩士
dc.contributor.oralexamcommittee郭佳瑋(Chia-Wei Kuo),陳聿宏(Yu-Hung Chen)
dc.subject.keywordnone,zh_TW
dc.subject.keywordonline learning,subscriptions,learning performance,difficulty level,regression,en
dc.relation.page29
dc.identifier.doi10.6342/NTU202200696
dc.rights.note同意授權(全球公開)
dc.date.accepted2022-04-18
dc.contributor.author-college管理學院zh_TW
dc.contributor.author-dept企業管理碩士專班zh_TW
dc.date.embargo-lift2022-07-05-
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