博碩士論文 105522052 詳細資訊




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姓名 陳明欣(Ming-Sin Chen)  查詢紙本館藏   畢業系所 資訊工程學系
論文名稱 觀看LINE平台上教學影片行為模式對學生的使用偏好、學習動機及學習成效之影響: 以網路程式課程為例
(Accessing LINE platform instructional video behavior patterns to effect on using preferences, learning motivations, and learning achievements of students: Web programming course as an example.)
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摘要(中) 觀看教學影片是翻轉教室教學中最常見的課前活動,它對於學生的學習成效及學習動機皆常被討論,而LINE做為國人常使用的社群平台,也可被應用在其中,而其使用方式及感受與其他網路學習平台不同,而為了解學生在使用LINE平台對於學習的影響,此研究探究學生在觀看LINE平台上教學影片行為模式對學生的使用偏好、學習動機及學習成效之影響。實驗對象為42位北部大專院校資訊科系學生,實施實驗活動時間為8周,活動主題為網路程式課程,使用LINE平台搭配翻轉教學,在課後觀看教學影片,課堂上詢問問題,此研究開發LINE平台融入影片教學系統,分析系統訊息,探討學生的使用偏好、學習動機及學習成效,分析來源有測驗、問卷已及平台操作紀錄。
結果發現學生會為理解資訊而不斷重複或暫停影片撥放。前測與後測對於學生有顯著差異,學生們的分數大幅提高,然而此實驗學生資質相近,無論先備知識高或低在學習後可得到相同之成果。在行為表現上,全部學生都會看影片一次以上,低先備知識組學生觀看次數以及時間高於高先備知識組學生;低先備知識組學生偏好自我學習,並有固定討論對象,而高先備知識組學生有階段性行為連結,具有自身習慣的紀錄方式,然而學生執行意志未能跟預期學習一樣,在行為上時並沒有預期中來的好,感受是新奇但對於實際使用感受較為負面,未來建議可以使用其他變量,如性別、使用的熱絡度,行為編碼可更細部的定義,由於筆記不易操作,可將LINE 平台作為教學輔助或開發專案。
摘要(英) Watching instructional video is the most common activity in flipped classroom teaching. It is often used for discussing students′ learning effectiveness and learning motivation. LINE is also a common community platform, and flipped classroom teaching can also be applied to it. However, the method and experience on LINE are different to other online learning platforms. In order to understand what poses impact on students′ learning on LINE, this study aims to focus on students′ preferences, learning motivations and learning achievements on instructional video behavior patterns. There are 42 students studying in the information science department at a northern university. The experimental activity lasts for 8 weeks. The theme is the online program course, which is expected to gain the results by conducting the LINE platform with flipped classroom and watching the instructional video after class, and asking questions in the class. Additionally, development on LINE platform integrating into the videos teaching system, as well as using quizzes, questionnaires and platform operation logs are also the methods for this study. At last, analyzing system information helps us get insight into students′ preferences, learning motivation and learning achievements.
For the record, students are repeatedly replaying or pausing the video for understanding learning content. The pre-test and post-test are significantly different for each student. Students’ scores are greatly improved; however, the qualifications of the students are similar to their peers among these 42 students. No matter the students are having high or low prior knowledge, they can get the same achievement after the study. All students watch the videos more than one time. Compared the number of times that the students watch the videos, alone with the total time length, students having low prior knowledge seem to be spending more time than those who has high prior knowledge. The fact shows that students with low prior knowledge prefer self-learning, and tend to make discussions with either their peers or the teacher. As for students with high prior knowledge, since they have their own customary record, this kind of students have a tendency towards having behavior link. However, all students’ executions do not fit the expectations. The feedbacks from this experiment turns out to be negative although some students claim this learning mode novelty. Other variables such as gender and how actively the students are using the learning platform should be included in future research if possible. There are more defining details in the behavior patterns. Noted that as the note-taking function on the LINE platform is not easy to use, suggestions are made that it should be a teaching aid or a development project.
關鍵字(中) ★ LINE
★ 行為模式
★ 使用偏好
★ 學習動機
★ 學習成效
關鍵字(英) ★ LINE
★ behavior patterns
★ preferences
★ learning motivations
★ learning achievements
論文目次 摘  要 i
Abstract ii
致謝 iv
目  錄 v
圖目錄 vii
表目錄 viii
第一章 緒論 1
1.1研究背景 1
1.2目的 2
1.3論文架構 2
第二章 文獻探討 3
2.1翻轉教室 3
2.2社群LINE融入教學影片 4
2.3觀看教學影片行為模式 5
2.4研究問題 6
第三章 系統設計 7
3.1社群LINE融入教學影片 7
3.2社群LINE平台開發 8
3.3社群LINE融入教學影片系統功能 9
3.4社群LINE融入教學影片系統資料庫 10
第四章 研究方法 13
4.1 實驗對象 13
4.2 實驗教材 13
4.3 實驗流程 15
4.4 實驗工具 17
4.5 LINE平台上學習行為紀錄蒐整與編碼 19
4.6學習行為模式分析 21
第五章 研究結果 23
5.1 LINE 平台融入教學影片對學生的先備知識與學習成效分析結果 23
5.2不同先備知識的學生對觀看LINE平台上教學影片行為結果 25
5.2.1不同先備知識對觀看影片撥放次數統計結果 25
5.2.2觀看LINE平台上教學影片行為分析結果 28
5.2.3不同先備知識對觀看影片撥放時間統計結果 31
5.3不同先備知識的學生對系統介面偏好、學習動機及系統使用感受為何 33
5.3.1不同先備知識的學生對系統介面偏好分析結果 33
5.3.2不同先備知識的學生對學習動機分析結果 35
5.3.3不同先備知識的學生對系統使用感受分析結果 36
第六章 結論與建議 38
6.1結論與討論 38
6.2建議 40
參考文獻 42
英文部分 42
中文部分 46
附錄一、研究實驗同意書 47
附錄二、學習成效前測 48
附錄三、學習成效後測 50
附錄四、系統介面偏好問卷 52
附錄五、學習動機問卷 53
附錄六、LINE 平台系統使用感受問卷 55
參考文獻 英文部分
1. All, A., Plovie, B., Castellar, E. P. N., & Van Looy, J. (2017). Pre-test influences on the effectiveness of digital-game based learning: A case study of a fire safety game. Computers & Education, 114, 24-37.
2. Allison, P. D., & Liker, J. K. (1982). Analyzing sequential categorical data on dyadic interaction: A comment on Gottman.
3. Ashby, I., Exter, M., & Varner, D. (2018). Developing cross-cutting competencies for a transdisciplinary world: An extension of Bloom’s Taxonomy. Paper presented at 2018 AECT Summer Research Symposium, Bloomington, Indiana.
4. Bakeman, R., & Gottman, J. M. (1997). Observing interaction: An introduction to sequential analysis. Cambridge university press.
5. Balzotti, J. M., & McCool, L. B. (2016). Using digital learning platforms to extend the flipped classroom. Business and Professional Communication Quarterly, 79(1), 68-80.
6. Bloom, B. S., & Committee of College and University Examiners. (1964). Taxonomy of educational objectives (Vol. 2). New York: Longmans, Green.
7. Briz-Ponce, L., Pereira, A., Carvalho, L., Juanes-Mendez, J. A., & Garcia-Penalvo, F. J. (2017). Learning with mobile technologies–Students’ behavior. Computers in Human Behavior, 72, 612-620.
8. Cheng, G., & Chau, J. (2016). Exploring the relationships between learning styles, online participation, learning achievement and course satisfaction: An empirical study of a blended learning course. British Journal of Educational Technology, 47(2), 257-278.
9. Chiang, Y. C., Chen, C. H., Liao, Y. C., & Liao, C. W. (2016). A Study on Investigating Learning Styles and Skills Learning Motivations for Mechanical Department Students in Vocational High Schools. International Journal of Information and Education Technology, 6(11), 851.
10. Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management science, 35(8), 982-1003.
11. Delen, E., Liew, J., & Willson, V. (2014). Effects of interactivity and instructional scaffolding on learning: Self-regulation in online video-based environments. Computers & Education, 78, 312-320.
12. Giannakos, M. N., Chorianopoulos, K., & Chrisochoides, N. (2015). Making sense of video analytics: Lessons learned from clickstream interactions, attitudes, and learning outcome in a video-assisted course. The International Review of Research in Open and Distributed Learning, 16(1).
13. Heflin, H., Shewmaker, J., & Nguyen, J. (2017). Impact of mobile technology on student attitudes, engagement, and learning. Computers & Education, 107, 91-99.
14. Hsieh, J. S. C., Huang, Y. M., & Wu, W. C. V. (2017). Technological acceptance of LINE in flipped EFL oral training. Computers in Human Behavior, 70, 178-190.
15. Hwang, G. J., Lai, C. L., & Wang, S. Y. (2015). Seamless flipped learning: a mobile technology-enhanced flipped classroom with effective learning strategies. Journal of Computers in Education, 2(4), 449-473.
16. Jonassen, D.H., & Grabowski, B.L. (1993). Handbook of individual differences learning, andinstruction. Part VII. Prior knowledge. Hillsdale: Lawrence Erlbaum Associates.
17. Kukulska-Hulme, A. (2007). Mobile usability in educational context: What have we learnt? International Review of Research in Open and Distance Learning, 8(2), 1-16.
18. Li, L. Y., & Tsai, C. C. (2017). Accessing online learning material: Quantitative behavior patterns and their effects on motivation and learning performance. Computers & Education, 114, 286-297.
19. Loh, K. K., Tan, B. Z. H., & Lim, S. W. H. (2016). Media multitasking predicts video-recorded lecture learning performance through mind wandering tendencies. Computers in Human Behavior, 63, 943-947.
20. Lopes, A. P., & Soares, F. (2017). “Flipped classroom with a MOOC” an e-learning model into a mathematics course. In INTED2017 Proceedings: International Technology, Education and Development Conference, 11th (pp. 4643-4649). IATED Academy.
21. Lust, G., Vandewaetere, M., Ceulemans, E., Elen, J., & Clarebout, G. (2011). Tool-use in a blended undergraduate course: In Search of user profiles. Computers & Education, 57(3), 2135-2144.
22. Manasijevi?, D., ?ivkovi?, D., Arsi?, S., & Milo?evi?, I. (2016). Exploring students’ purposes of usage and educational usage of Facebook. Computers in Human Behavior, 60, 441-450.
23. McLaughlin, J. E., Roth, M. T., Glatt, D. M., Gharkholonarehe, N., Davidson, C. A., Griffin, L. M., ... & Mumper, R. J. (2014). The flipped classroom: a course redesign to foster learning and engagement in a health professions school. Academic Medicine, 89(2), 236-243.
24. Park, Y. (2011). A pedagogical framework for mobile learning: Categorizing educational applications of mobile technologies into four types. The International Review of Research in Open and Distributed Learning, 12(2), 78-102.
25. Pintrich, P. R. (1991). A manual for the use of the Motivated Strategies for Learning Questionnaire (MSLQ).
26. Sams, A., & Bergmann, J. (2012). Flip your classroom: Reach every student in every class every day. International Society for Technology in Education/ISTE.
27. Sinha, T., Jermann, P., Li, N., & Dillenbourg, P. (2014). Your click decides your fate: Inferring information processing and attrition behavior from mooc video clickstream interactions. arXiv preprint arXiv:1407.7131.
28. Stigler, J., Geller, E., & Givvin, K. (2015). Zaption: A platform to support teaching, and learning about teaching, with video. Journal of E-Learning and Knowledge Society, 11(2).
29. Su Y.S., Huang S.J., & Ding T.-J. (2016). Examining the Effects of MOOCs Learners’ Social Searching Results on Learning Behaviors and Learning Outcomes. Eurasia Journal of Mathematics, Science & Technology Education, 12(9), 2517-2529.
30. Su, Y. S., Ding, T. J., & Lai, C. F. (2017). Analysis of Students Engagement and Learning Performance in a Social Community Supported Computer Programming Course. Eurasia Journal of Mathematics, Science and Technology Education, 13(9), 6189-6201.
31. Thai, N. T. T., De Wever, B., & Valcke, M. (2017). The impact of a flipped classroom design on learning performance in higher education: Looking for the best “blend” of lectures and guiding questions with feedback. Computers & Education, 107, 113-126.
32. Thapa, S. (2017). Social networking service (SNS) enhancing the learning environment of youth: As an effective tool. In Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017 (pp. 798-802). ACM.
33. Veletsianos, G., & Navarrete, C. (2012). Online social networks as formal learning environments: Learner experiences and activities. The International Review of Research in Open and Distributed Learning, 13(1), 144-166.
34. Winters, F. I., Greene, J. A., & Costich, C. M. (2008). Self-regulation of learning within computer-based learning environments: A critical analysis. Educational Psychology Review, 20(4), 429-444.
35. Wong, M. H. O., Xie, X., & Hew, K. F. (2017). Implementing Digital Game Mechanics and Various Video Lecture Formats in a Flipped Research Method Course: What Postgraduate Learners Say?. In New Ecology for Education—Communication X Learning (pp. 143-152). Springer, Singapore.
36. Wortzel, R. (1979). Multivariate analysis. New Jersey: Prentice Hall. Zack, M.(1999),” Developing a Knowledge Strategy.” California Management Review, 41(3), 125-143.
37. Wu, Y.-T., Chang, M., Li, B., Chan, T.-W., Kong, S. C., Lin, H.-C.-K., Chu, H.-C., Jan, M., Lee, M.-H., Dong, Y., Tse, K. H., Wong, T. L., & Li, P. (Eds.). (2016). Conference Proceedings of the 20th Global Chinese Conference on Computers in Education 2016. Hong Kong: The Hong Kong Institute of Education.

中文部分
1. 毛國楠(1997)。成績回饋方式對不同能力水準國中生數學科的學習動機、學習策略、學習態度與學業成就之影響。教育心理學報,(29),117-135。
2. 李靜宜和柯皓仁(2012)。電子資源整合查詢系統使用者接受度與使用行為之研究.。教育資料與圖書館學,49(3),30-62。
3. 資策會FIND,經濟部技術處「資策會FIND(2016)/ 服務系統體系驅動新興事業研發計畫(2/4),資料來源:https://www.iii.org.tw/Press/NewsDtl.aspx?nsp_sqno=1934&fm_sqno=14。
4. 劉政宏、黃博聖、蘇嘉鈴、陳學志、吳有城(2010)。國中小學習動機量表之編製及其信、效度研究。測驗學刊,57(3), 371-402。
指導教授 蘇育生(Yu-Sheng Su) 審核日期 2018-8-17
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