跳到主要內容

臺灣博碩士論文加值系統

(44.201.92.114) 您好!臺灣時間:2023/03/31 11:23
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

: 
twitterline
研究生:顏郁霏
研究生(外文):YEN,YU-FEI
論文名稱:從學習風格探討磨課師課程自我效能之研究
論文名稱(外文):Exploring the Self-efficacy of MOOCs from Learning Styles
指導教授:林豪鏘林豪鏘引用關係
指導教授(外文):Hao-Chiang Koong Lin
口試委員:徐國鈞張華城
口試日期:2019-01-22
學位類別:碩士
校院名稱:國立臺南大學
系所名稱:數位學習科技學系碩士在職專班
學門:教育學門
學類:教育科技學類
論文種類:學術論文
論文出版年:2019
畢業學年度:107
語文別:中文
論文頁數:43
中文關鍵詞:磨課師課程學習風格自我調節效能
外文關鍵詞:MOOCsLearning StyleSelf-regulation Efficacy
相關次數:
  • 被引用被引用:3
  • 點閱點閱:552
  • 評分評分:
  • 下載下載:180
  • 收藏至我的研究室書目清單書目收藏:2
「數位學習」從一直隨著知識的載具改變而有不同的發展及解釋,早期(1958至80年代後期)的電腦輔助教學(Computer-Aided Instruction,CAI),WWW(World Wide Web)的發明以及多媒體電腦及超媒體的出現所稱之網路學習,因通訊科技及平板電腦與智慧型手機的普及所產生的行動學習,學習方式也因為學習載具的普及高網路使用率而產生巨大的改變。
因此本研究透過問卷了解背包客日語MOOCs課程學習者的學習風格,利用自我效能理論,來探討學習者的學習風格和自我效能的關聯性,了解學習者的學習動機,藉此從低完課率的背後找出隱藏著從數據所看不到的學習需求和價值。
據本研究之研究目的及架構,提出欲驗證之研究假設如下:
假設一:不同背景變項之學習者在自我調節效能上有顯著差異。
假設二:不同背景變項之學習者在學習風格上有顯著差異。
假設三:學習者的自我調節效能、學習風格有顯著相關。
假設四:學習者的自我調節效能與是否完課有顯著差異。
假設五:學習者的學習風格與是否完課有顯著差異。
研究結果顯示,學習者的日文程度與是否完課,在自我調節效能上有顯著差異,學習者的職業在學習風格上有顯著差異,而學習者的自我調節效能與學習風格則無顯著相關,因為背包客日語MOOCs的學習者自我調節效能受學習者的學習經驗影響,但不受限於學習者的學習風格。

E-learning has been developed and explained differently with the device of knowledge. The invention of CAI (from 1958 to 1980) and WWW and the multimedia computer and C show up what is calling E-learning. Mobile learning is due to the Information and Communication Technology (ICT), tablets and smart phones are popularized. The style of learning is in greatly changes due to the popularity of learning device and the utilization rate of Internet.
This study learned the learning style of the MOOCs courses’ learners of backpackers’ Japanese and exploring the related of the self-efficacy and learning style from learners with the theory of self-efficacy. To understand the motivation of learning from learners and find out the needs and values of learning behind the data from low completion rate.
According to the research purpose and structure, the research hypotheses proposed for verification are as follows:
Hypotheses1: learners from different background have significant differences in self-regulation efficacy.
Hypotheses2: learners from different background have significant differences in learning style.
Hypotheses3: learners have significant differences in self-regulation efficacy and learning style.
Hypotheses4: learners have significant differences in self-regulation efficacy and whether to complete the course.
Hypotheses5: learners have significant difference in learning style and whether to complete the course.
Research results showed that the Japanese level and whether to complete course of learners had significant differences in self-regulation efficacy and the occupation of learners had significant differences in learning style. The learners had nonsignificant correlation with self-regulation efficacy and learning style because the self-regulation efficacy of backpacker Japanese MOOCs was influence by learning experience of learners but the learning style was not limited to learners.

謝辭 i
摘要 ii
Abstract iii
目錄 v
圖目錄 vii
第一章 緒論 1
1.1 研究背景與動機 1
1.2 研究目的 3
1.3 研究範圍與限制 4
1.4 研究流程 5
第二章 文獻探討 6
2.1 開放式教育之演進 6
2.2 大規模開放線上課程的發展 6
2.3 學習風格 8
2.4 自我效能 9
第三章 研究方法 10
3.1 研究架構 10
3.2 研究假設 11
3.3 測量變項與定義 12
3.4 資料收集及分析方法 13
3.5 描述性統計分析 14
3.6 項目分析 24
3.7 探索性因素分析 27
3.8 信度分析 29
第四章 研究結果與分析 31
第五章 結論與建議 34
5.1 研究結論 34
5.2 研究限制與後續研究 34
參考文獻 36
附錄:正式問卷 40

1. Allinson,C.W.,&Hayes,J. (1988).The learning styles questionnaire:An alternative to Kolb’s inventory. Journal of Management Studies,25(3),269-281.
2. Allport, G.W. (1961). Pattern and Growth in Personality, New York: Holt, Rinehart & Winston.
3. A Littlejohn, N Hood, C Milligan. (2016). Learning in MOOCs: Motivations and self-regulated learning in MOOCs. The Internet and Higher Education, 29,40-48
4. Breslow, L. B., Pritchard, D. E., DeBoer, J., Stump, G. S., Ho, A. D., & Seaton, D. T. (2013). Studying learning in the worldwide classroom: Research into edX's first MOOC. Research & Practice in Assessment, 8, 13-25.
5. Li Yuan and Stephen Powell. (2013). MOOCs and Open Education: Implications for Higher Education. From http://publications.cetis.ac.uk/2013/667.
6. D Yang, T Sinha, D Adamson, CP Rosé, “Turn on, Tune in, Drop out”: Anticipating student drop outs in Massive Open Online Courses. from Proceedings of the 2013 NIPS Data-driven education workshop 11, 14
7. DeVellis, R.F. ( 1991). Scale Development: Theory and Applications. Newbury Park, CA: Sage Publications, Inc.
8. E Alqurashi. (2016).Self-efficacy in online learning environments: A literature review. Journal of Educational Technology & Society,14(4), 222-240
9. Fang Xu. (2015). Research of the MOOC Study Behavior Influencing Factors. International Conference on Advanced Information and Communication Technology for Education (ICAICTE 2015).
10. GJ Houben. (2016). Retrieval Practice and Study Planning in MOOCs: Exploring Classroom-Based Self-regulated Learning Strategies at Scale. Springer International Publishing,57-71.
11. John Seely Brown and Richard P. Adler. (2008). Open Education, the Long Tail, and Learning 2.0). EDUCAUSE Review, 43(1),16-32.
12. Jordan, K. (2015). Massive open online course completion rates revisited: Assessment, length and attrition. The International Review of Research in Open and Distributed Learning, 16(3). from https://doi.org/10.19173/irrodl.v16i3.2112.
13. MKI Abdul Rahim. (2018). MOOCs Continuance Intention in Malaysia: The Moderating Role of Internet Self-efficacy. International Journal of Supply Chain Management.7(2),132-139.
14. Rivard. ( March 8, 2013). Measuring the MOOC Dropout Rate. From www.insidehighered.com/news/2013/03/08/researchers-explore-who-taking-moocs-and-why-somany-drop-out.
15. R Yilmaz (2016).Knowledge sharing behaviors in e-learning community: Exploring the role of academic self-efficacy and sense of community. Computers in Human Behavior,63,373-382.
16. Sherif Halawaj, Daniel Greene, John Mitchell, ( March 2014). Dropout Prediction in MOOCs using Learner Activity Features. Proceedings of the European MOOC Stakeholder Summit 2014 (EMOOCs2014), At Lausanne, Swiss.
17. Saul McLeod (2017).Kolb - Learning Styles. From http://cei.ust.hk/files/public/simplypsychology_kolb_learning_styles.pdf.
18. Tayeb Brahimi (2015).Learning outside the classroom through MOOCs. Computers in Human Behavior,51(B),604-609.
19. Pintrich, P. & Schunk, D. (1996). The Role of Expectancy and Self-Efficacy Beliefs. Presentation on theme: "The Role of Expectancy & Self-Efficacy Beliefs"— Presentation transcript.
20. Wanli Xing (2016)Corrigendum to “Temporal predication of dropouts in MOOCs: Reaching the low hanging fruit through stacking generalization”. Computers in Human Behavior,58,119-129.
21. 吳美美(民93)。數位學習現況與未來發展。圖書館學與資訊科學(2)92-106。
22. 楊正宏(民97)。 台灣高等教育數位學習現況與發展。數位學習科技期刊 創刊號1-12。
23. 何榮桂(民103)。 大規模網路開放課程(MOOCs)的崛起與發展。台灣教育,686期 。
24. 林季燕(民92)。以自我決定理論預測籃球選手滿足感和退出意圖之研究,國立體育學院教練研究所碩士論文。
25. 黃素梅(民104)。學習動機、知覺價值與課程品質對補習意願影響之研究-以桃園地區日語進修潛在消費者為例。中國科技大學企業管理系碩士論文。
26. 吳鴻松(民97)。科技大學成人學生學習動機與學習滿章度關係之研究-以南部某科技大學為例。國立高雄師範大學成人教育研究所碩士論文。
27. 王弘智(民101)。 自我調節學習,T&D飛訊第183期。
28. 吳宥葶、孫之元、李威儀(民102)。大專院校開放式課程學習者之 自我調節問卷研發與編製。國立臺灣科技大學,人文社會學報,9(3),189-208。
29. 鄒信忠(民104)磨課師(MOOCs)之學習行為研究 -以「防天災保平安」課程為例。國立高雄應用科技大學土木防災科技研究所碩士論文。
30. 洪如萱(民107),情感教育課程之學習成效探討~以MOOCs數位縱習模式分析。國立雲林科技大學技術及職業教育研究所碩士論文。
31. 葉國毅 (民104),MOOC使用者人格特質與其完成率之相關性。國立中央大學企業管理學系碩士論文。

QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top
無相關期刊