| 研究生: |
鄭兆傑 Jhao-Jie Jheng |
|---|---|
| 論文名稱: |
藉由電子書學習系統探討學生線上學習準備度、線上學習行為與學習成果之間的關係-以微積分課程為例 |
| 指導教授: | 蕭嘉璋 |
| 口試委員: | |
| 學位類別: |
碩士 Master |
| 系所名稱: |
理學院 - 數學系 Department of Mathematics |
| 論文出版年: | 2021 |
| 畢業學年度: | 109 |
| 語文別: | 中文 |
| 論文頁數: | 66 |
| 中文關鍵詞: | 線上學習準備度 、線上學習行為 、自主學習 |
| 外文關鍵詞: | Learning readiness, Online learning behavior, Self-directed learning |
| 相關次數: | 點閱:11 下載:0 |
| 分享至: |
| 查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報 |
本研究主要透過電子書學習系統探討學生的「線上學習準備度」、「線上
學習行為」、「學習成果」與「自我評估」之間的相互關係,「線上學習準備度」中包含了電腦/網路的自我效能、自主學習、學習者控制、線上學習的動機、線上交流的自我效能等五個項目。
本研究挑選了中央大學 109 學年度選修微積分課程的部分學生共 429 人作為研究對象,擬制了一份問卷來測量學生的線上學習準備度與自我評估,並於本學期第二次會考時施策。
另外結合 BookRoll線上學習系統的後台數據與問卷的回饋結果,透過統計軟體 SPSS 統整出線上學習準備度、線上學習行為、學習成果與自我評估之間的相互關係。並運用結構方程模型(Structural Equation Modeling, SEM)分析學生的線上學習準備度、線上學習行為與學習成果三者之間的架構與關聯性。
研究結果發現,學生的線上學習準備度對於學生的學習成果,為顯著正相
關;學生的線上學習行為對於學業成績,為顯著正相關。因此我們可以藉由學生的線上學習準備度以及在 BookRoll學習系統上的學習行為來預測學生的學習
成效。
The purpose of the research was to identify the relationship among students’
“online learning readiness”, “online learning behavior”, “learning outcomes” and
“self-assessment” through the e-book learning system. "Online learning readiness" includes five items: computer/internet self-efficacy, self-directed learning, learner
control, motivation for online learning, and online communication self-efficacy.
In this study, the 429 students who took the calculus course in the 109th academic year of Central University were selected as the subjects. A questionnaire was drawn up to measure students' online learning readiness and self-assessment, and the questionnaire was sent during the second examination of this semester.
In addition, combined with the back-end data of the BookRoll online learning
system and the feedback from the questionnaire, the correlation between online learning readiness, online learning behavior, learning outcomes and self-assessment was summarized through the statistical software SPSS. And use structural equation
modeling (SEM) to analyze the structure and correlation between students' online learning readiness, online learning behavior, and learning outcomes.
The results of the study were that students’ online learning readiness is significantly positively correlated with students’ learning outcomes; students’ online learning behaviors are significantly positively correlated with academic performance.
Therefore, we can predict students' learning effectiveness based on their online learning readiness and their learning behavior on the BookRoll learning system.
academic year of Central University were selected as the subjects. A questionnaire was drawn up to measure students' online learning readiness and self-assessment, and
the questionnaire was sent during the second examination of this semester.
In addition, combined with the back-end data of the BookRoll online learning
system and the feedback from the questionnaire, the correlation between online learning readiness, online learning behavior, learning outcomes and self-assessment was summarized through the statistical software SPSS. And use structural equation
modeling (SEM) to analyze the structure and correlation between students' online learning readiness, online learning behavior, and learning outcomes.
The results of the study were that students’ online learning readiness is significantly positively correlated with students’ learning outcomes; students’ online learning behaviors are significantly positively correlated with academic performance.
Therefore, we can predict students' learning effectiveness based on their online learning readiness and their learning behavior on the BookRoll learning system.
1. Shu-ShengLiaw, Hsiu-Mei Huang (2013). Perceived satisfaction, perceived
usefulness and interactive learning environments as predictors to self-regulation
in e-learning environments. Computers & Education, Volume 60, Issue 1, 14-24.
2. Min-Ling Hung, Chien Chou, Chao-Hsiu Chen, Zang-Yuan Own (2010). Learner
readiness for online learning: Scale development and student perceptions.
Computers & Education, Volume 55, Issue 3, 1080-1090.
3. Chin-His Lin, Yining Zhang, Binbin Zheng (2017). The roles of learning
strategies and motivation in online language learning: A structural equation
modeling analysis. Computers & Education, Volume 113, 75-85.
4. Manuela Paechter, Brigitte Maier, Daniel Macher (2010). Students’ expectations of, and experiences in e-learning: Their relation to learning achievements and
course satisfaction. Computers & Education, Volume 54, Issue 1, 222-229.
5. Jin-Young Kim (2010). A study on learners’ perceptional typology and
relationships among the learner’s types, characteristics, and academic achievement in a blended e-Education environment. Computers & Education,
Volume 59, Issue 2, Pages 304-315.
6. Waiman Cheung, Eldon Y. Li, Lester W. Yee (2003). Multimedia learning system and its effect on self-efficacy in database modeling and design: an exploratory
study. Computers & Education, Volume 41, Issue 3, 249-270.
7. Nixon, Martine, McKeown, & Ranson (2019). Organization for Economic Cooperation and Development, Pages 49-50.
8. Rensis Likert, (1932). A Technique for the Measurement of Attitudes, Archives of Psychology. Pages 1-55.
9. Bentler, P. M. & Bonett, D. G. (1980). Significance tests and goodness-of –fit in
the analysis of covariance structures. Psychological Bulletin. Pages 88, 588-606.
10. Marsh, H. W., & Hocevar, D. (1985). Application of confirmatory factor analysis to the study of self-concept: First- and higher order factor models and their
invariance across groups. Psychological Bulletin. Pages 97, 562-582.
11. Marsh, H. W., Balla, J. R., & McDonald, R. P. (1988). Goodness-of-fit indexes in
confirmatory factor analysis: The effect of sample size. Psychological Bulletin.
Pages 103, 391-410.
12. Akpinar, Y., & Hartley, J. R. (1996). Designing interactive learning
environments. Journal of Computer-Assisted Learning, 12(1), 33–46.
13. Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: development of a measure and initial test. MIS Quarterly, 19(2), 189–211.
14. Neyman, J. (1923). Sur les applications de la thar des probabilities aux
experiences Agaricales: Essay des principle. Excerpts reprinted (1990) in English
(D. Dabrowska and T. Speed, translators) in Statistical Science 5, 463-472.
15. 柴康偉(2011),探討學習動機、學習策略及學習滿意度對服務教育課程之
影響(The Study of Learning Motivations, Learning Strategies and Learning
Satisfactions of Service Education),遠東學報,第二十八卷第四期。
16. 許錫銘(1998),我國試辦綜合高中學生學習滿意度之研究,國立彰化師範
大學工業教育研究所碩士論文。
17. 梁雲霞(2006),從自主學習理論到學校實務-概念架構與方案發展,當代
教育研究,第十四卷第四期,頁 171-206。
18. 張偉豪、鄭時宜 (2012),與結構方程模型共舞:曙光初現,前程文化。
19. 陳寬裕、王正華 (2011),論文統計分析實務/SPSS 與 AMOS 的運用
/Advanced statistical analysis using SPSS and AMOS,五南。
20. 吳明隆 (2011),SPSS 統計應用學習實務/問卷分析與應用統計,易習。
21. 林心茹譯(2003)。自律學習(譯自:B. J. Zimmerman, S. Bonner, R. Kovach: Developing Self-Regulated Learners.)。台北,遠流出版社。
22. 程炳林、林清山(2001)。中學生自我調整學習量表之建構及其信效度研
究。中國 測驗學會測驗年刊,48(1),頁 1-41。
23. 程炳林(2002)。大學生學習工作動機問題與自我調整學習策略之關係。教
育心理 學報,33(2), 頁 79-102。
24. 梁雲霞(2006)。從自主學習理論到學校實務:概念架構與方案發展,當代教
育研究, 14(4),171-206。
25. 陳品華(2004)。融入式介入方案對技職大學生自我調整學習之影響研究。
教育與心理 研究,27(1),159-180。
26. 劉佩雲(2000)。自我調整學習模式之驗證。教育與心理研究,23,173-
206。
27. 龐維國、薛慶國(2001)。中國古代的自主學習思想探析。心理科學,
24(1),59-62。
28. 陳茂祥(2001)。自我導向學習理論及其在成人教育上的啟示。朝陽學報,
6,65-89。
29. 教育部(2014)。十二年國民基本教育課程綱要總綱。
30. 黃曉梅(2017)。高中生英語自主學習、學習策略與學習成效關係之研究-以
桃園市為例(碩士論文)。