![]() |
|
以作者查詢圖書館館藏 、以作者查詢臺灣博碩士 、以作者查詢全國書目 、勘誤回報 、線上人數:21 、訪客IP:18.119.166.31
姓名 宋宜倫(I-LUN SUNG) 查詢紙本館藏 畢業系所 資訊工程學系 論文名稱 基於模糊理論之課程推薦系統開發與實作:以均一平台為例
(Development and implementation lesson recommender system based on fuzzy logic: a case study of Junyi Academy.)相關論文 檔案 [Endnote RIS 格式]
[Bibtex 格式]
[相關文章]
[文章引用]
[完整記錄]
[館藏目錄]
[檢視]
[下載]
- 本電子論文使用權限為同意立即開放。
- 已達開放權限電子全文僅授權使用者為學術研究之目的,進行個人非營利性質之檢索、閱讀、列印。
- 請遵守中華民國著作權法之相關規定,切勿任意重製、散佈、改作、轉貼、播送,以免觸法。
摘要(中) 隨著開放式教育與學習科技持續演進下,大規模開放線上課程(MOOCs)隨之因應而產生。在台灣MOOCs平台也正在蓬勃發展,均一教育平台是目前台灣免費線上教育平台,提供給學生龐大的影片圖書館、互動式挑戰,還讓家長、老師能夠深入了解學生的學習情況。然而,均一平台雖然提供了豐富的教學短片與互動式練習題,但是卻缺乏良好的課程推薦機制,學生可能學習了超出他能力範圍的課程而遇到學習瓶頸,若此時有個機制在學生學習新章節前先行檢測,了解學生有哪些先備知識不足,並且根據不足的部分推薦課程給學生,將可以降低學生遇到瓶頸的狀況。因此本研究提出一個採用模糊邏輯演算法的課程推薦系統來幫助使用者順利地學習新課程,並且藉由TAM2來探討此系統的使用者行為,實驗結果指出研究模型中的八項假說中有五項是支持的,分別為認知有用性與認知易用性會正向影響使用意圖,工作關聯性、認知易用性與產出品質會正向影響認知有用性。另外成果展示性、主觀規範對認知有用性沒有顯著影響,主觀規範對使用意圖也沒有顯著影響,此三項假說不成立。 摘要(英) Massive open online courses (MOOCs) is rising all over the world recently. In Taiwan, there is a free education platform called “Junyi Academy”. It provides learner massive educational videos and interactive exercises, but lack of lesson recommended that may causes learner stuck at bottleneck when starting a new lesson without enough prior knowledge. In this paper we develop a lesson recommender system based on fuzzy logic to help this problem. We use technology acceptance model 2 to probe user′s technology acceptance. The results showed that perceived usefulness, perceived ease of use have a significant impact on intention to use, and job relevance, perceived ease of use, output quality have a significant impact on perceived usefulness. 關鍵字(中) ★ 大規模開放線上課程
★ 課程推薦系統
★ 模糊理論
★ 科技接受模型2關鍵字(英) ★ MOOCs
★ Fuzzy Logic
★ TAM2
★ lesson recommender system論文目次 摘 要 i
Abstract ii
目 錄 iii
圖目錄 v
表目錄 vi
1. 緒論 1
2. 文獻探討 3
2.1 MOOCs 3
2.2 科技接受模型 5
2.3 模糊邏輯 8
2.3.1 起源 8
2.3.2 模糊集合 9
2.3.3 模糊邏輯演算法 10
3. 課程推薦系統 16
3.1 開發環境建置 16
3.2 系統規劃 16
3.3 系統架構 18
3.4 系統操作介面 19
4. 研究方法 23
4.1 研究模型與假說 23
4.2 科技接受問卷 24
5. 結果與討論 26
5.1 描述性統計 26
5.2 相關分析 27
5.3 迴歸分析 29
6. 結論 34
參考文獻 35
參考文獻 Aiken, L. R. (1983). Number of response categories and statistics on a teacher rating scale. Educational and Psychological Measurement, 43(2), 397-401.
Brown, G., Widing, R. E., & Coulter, R. L. (1991). Customer evaluation of retail salespeople utilizing the SOCO scale: A replication, extension, and application. Journal of the Academy of Marketing Science, 19(4), 347-351.
Belanger, Y., & Thornton, J. (2013). Bioelectricity: A quantitative approach Duke University′s first MOOC.
Chan, S. C., & Lu, M. T. (2004). Understanding internet banking adoption and use behavior: A Hong Kong perspective.
Davis, F. D. (1986). A technology acceptance model for empirically testing new end-user information systems: Theory and results (Doctoral dissertation, Massachusetts Institute of Technology).
Kelman, H. C. (1958). Compliance, identification, and internalization: Three processes of attitude change. Journal of conflict resolution, 51-60.
Lin, C. F. (2005). A study of customer intention and its antecedents on e-commerce of travel industry (Doctoral dissertation, Master Thesis, Department of Business Administration, National Dong Hwa University, Hualien, Taiwan).
L.A. Zadeh, (1965) Fuzzy Sets. Information and Control, 8, 338-358.
Masters, E. R. (1974). The relationship between number of response categories and reliability of likert‐type questionnaires1. Journal of Educational Measurement, 11(1), 49-53.
Means, B., Toyama, Y., Murphy, R., Bakia, M., & Jones, K. (2009). Evaluation of Evidence-Based Practices in Online Learning: A Meta-Analysis and Review of Online Learning Studies. US Department of Education.
Pappano, L. (2012). The Year of the MOOC. The New York Times, 2(12), 2012.
Venkatesh, V., & Davis, F. D. (2000). A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management Science, 46(2), 186-204.
Von Altrock, C. (1997), Fuzzy Logic and Neurofuzzy Applications in Business and Finance, Prentice Hall PTR, Upper Saddle River, NJ.
Warshaw, P. R. (1980). A new model for predicting behavioral intentions: An alternative to Fishbein. Journal of Marketing Research, 153-172.
Yuan, L., Powell, S., & CETIS, J. (2013). MOOCs and open education: Implications for higher education.
指導教授 楊鎮華 審核日期 2015-7-13 推文 plurk
funp
live
udn
HD
myshare
netvibes
friend
youpush
delicious
baidu
網路書籤 Google bookmarks
del.icio.us
hemidemi
myshare