探討問題解決模式下的學習行為分析

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姓名

李玉婷(Yu-Ting Li) 查詢紙本館藏

畢業系所

資訊工程學系在職專班

論文名稱

探討問題解決模式下的學習行為分析
(Learning behavior analysis of problem solving)

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摘要(中)

本研究想要透過問題解決模式探討學生在學習上的行為模式，會經由討論板來收集學生討論的資料，記錄學生的討論過程。由於edx的討論板無法擷取討論數據，且有各國不同的學生線上討論，故實驗對象無法明確定義，因此需要有個平台來讓特定的實驗對象(學生)做線上討論，並且記錄學生的討論內容，於是本實驗就開發一個討論板及聊天室並擷取edx的課程到系統中，方便學生點選課程相關的討論板進行討論。
本實驗建立一個學習活動，參與者為資工系大學三年級四十四位學生，實驗時間為一百零三年三月二十四至五月二十一日，共六周的實驗周數，實驗期間，學生可以在Moocs上課並在本實驗所開發的討論板進行討論，最後收集到的文章主題篇數共128篇，而回應文章數共有384篇，其中有9篇是同時有二個編碼，接著將收集到的文章，透過問題解決模式的內容分析及後滯序列分析及分析工具，產生各個行為模式之間的頻率數據，並推導出z-score的值，最後推導成事件轉換圖。
結果會發現P1(提出問題)→P2(提供解決方法)是最有顯著性。也就是幾乎所有「提出問題」的行為，比較容易進入到「提供解決方法、提供意見」的行為；而P2(提供解決方法)→P3(討論其它人的意見)，則可以看出，回應者「提供解決方法」，而下一個回應，很容易進入到「討論回應者所給予的意見及看法」；P2(提供解決方法)→P4(產生結論)也列為顯著性之一，學生會將大家所提供的方法及回應，選擇比較好的回應並產生結論；P3(討論其它人的意見)→P3，當回應者針對其它回應者回答進行回應，下一個回應者又會針前前一個回應者回答內容產生疑惑進而提出自己的想法，代表大家都很熱烈討論。但也發現網路資源眾多學生可以快速找到答案的現象，及學生沒辦法在討論中選擇出比較好的討論結果，造成持續不斷的討論。
透過實驗結果可以推導出本實驗的行為模式是跟舊有模式相符的，以及從中發現老師可以在討論過程中介入討論，引導學生進入更深層的討論，並幫助學生從討論中產生結論，除了鼓勵學生經常使用討論板之外，也要鼓勵學生產生結論。

摘要(英)

This research discusses students’ behavior model through problem-solving model to study students’ on-line learning behavior model. I collected students’ discussing data from forum and record discussing process.
Edx’forum cannot gather discussing data and there are students from different countries discuss on-line. Therefore experiment targets cannot clearly be defined. There should be a platform to let experiment targets(students) discuss on-line and record students’ discussing content. Therefore this research developed a forum and chat room then gathered edx’s lessens into system. Students choice related forum to discuss.
This research starts up a learning activity. Participants are 44 computer science department’ third grade students. Experiment period during 2014/03/24-5/21, total six weeks. During experimental period, students can study at Moocs and discuss at forums that developed by this research. At last, total articles collected are 128.Responses are 384, 9 are two-code simultaneously. After articles collected, get z-score value than produce frequency data between behavior models through problem-solving model’s content analysis and lag-sequential analysis. At last infer it to event transfer chart.
Results reveals that P1(bring up question) →P2(provide solution) is most significant. Almost all of “bring up question” behaviors are easier to become “provide solutions, provide opinion” behaviors. P2(provide solutions) →P3(discuss others’ opinions) can discovered that respondent provides “solutions” and next response is very easy to become “discuss opinions that respondents give”. P2(provide solutions) →P4(conclusions) is also significant. Students will choose better responses and get conclusions from all of methods and responses. P3(discuss others’ opinions) →P3, while respondents answer others’ responses and next respondent also questions and provides opinion means discussions is very hot. But also find out that resources at internet are abundant and students can find out solutions quickly. And students cannot select better results in discussion, though causes constantly discussion process.
Experimental results show that behaviors models are correspondents to old ones. Also discovered that teacher can discuss during discussion process and guide students to deeper discussions. Then help students conclude from discussions. Encourage students use forum often and conclude.

關鍵字(中)

★ 問題解決模式
★ 後滯序列分析
★ 內容分析

關鍵字(英)

★ Problem solving
★ Lag-sequential analysis
★ Quantitative content analysis

論文目次

摘要 i
Abstract iii
目錄 v
圖目錄 vii
表目錄 ix
一、緒論 1
二、文獻探討 4
2-1 問題解決模式(Problem-solving) 4
2-2 同步式學習(Online Synchronous Discussion) 5
三、平台架構與實作 7
3-1 系統設計架構及規劃 7
3-1-2 類別圖 9
3-1-3 DBTool 9
3-1-4 MVC架構 13
3-1-5 Spring 13
3-1-6 Tiles樣板 16
3-1-7 Session Interceptor 18
3-1-8 jsoup 19
3-1-9 Quartz 21
3-1-10 Facebook′s JavaScript SDK 23
3-1-11 樹狀結構Jquery TreeView 25
3-1-12 Log4j 27
3-1-13 Ckeditor 28
3-1-14 JUnit Test Case 30
3-2 使用者所使用功能範圍及流程圖 33
3-2-1 登入架構圖 34
3-2-2 課程清單架構 35
3-2-3 課程清單 35
3-2-4 討論板功能 37
3-2-5 聊天室 40
四、研究方法 43
4-1 研究理論 43
4-1-1問題解決模式 43
4-1-2編碼 43
4-1-3內容分析 44
4-1-4後滯序列分析 44
4-2參與者 44
4-3實驗時間 45
4-3工具 45
4-4實驗流程 45
4-5資料分析 47
五、結果與討論 48
5-1 編碼個數 48
5-2 事件轉換編碼頻率表 49
5-3 z-score 50
5-4 顯著效果的編碼： 51
5-5 事件轉換圖 51
六、結論 53
6-1 P1、P2編碼占最多 53
6-2 學生知識背景不夠 53
6-3知識的增長 53
6-4 跟舊有模型是相符 53
6-5文章篇數少，降低P4結論的產生。 53
6-6網路資源眾多 54
6-7學生都很認真討論，很少提出跟問題本身無關的問題。 54
七、未來展望 55
7-1 鼓勵產生結論 55
7-2 老師的介入 55
7-3鼓勵經常使用 55
參考文獻 56

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指導教授

楊鎮華(Stephen Yang)

審核日期

2015-1-7

推文