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研究生:錢聖元
研究生(外文):Sheng-Yuan Chien
論文名稱:智慧型線上短句評估機制
論文名稱(外文):An Intelligent Online Short Text Assessment Mechanism
指導教授:黃振榮黃振榮引用關係
指導教授(外文):Chenn-Jung Huang
學位類別:碩士
校院名稱:國立東華大學
系所名稱:資訊工程學系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2016
畢業學年度:104
論文頁數:27
中文關鍵詞:電腦輔助溝通合作學習支持向量機
外文關鍵詞:computer-mediated communication (CMC)collaborative learningSupport Vector Machines (SVM)
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隨著科技的進步以及個人電腦的普及,人們開始嘗試著將科技融入教學環境中以提升學生的學習成效,而近年來已經有許多國內外的相關文獻證明了數位學習對於學生的學習成效有顯著的提升,因此如何有效的將科技融入教學已經是一個被廣為重視的課題。
到目前為止,關於運用電腦輔助溝通(CMC)作為輔助教學環境的相關文獻中,大部分的研究者都將重點放在資訊的交換以及提交訊息。在這項研究中,將提出一種用來偵測學生們在智慧型合作學習平台的發言,是否跟預先設定之議題有關的方法,其中包括利用支持向量機(SVM)對分類器進行訓練、同儕間的互評、以及老師的介入等等,而實驗結果也顯示出了不錯的效果。此外,由老師的回饋表格也表明了該平台也可以減輕老師的教學負擔,從而使得他們可以投入更多的時間和精力來設計更有效率的教學方法。

With the advance of technology and personal computers dissemination, people started to integrate technology into teaching environment in order to elevate the learning efficiency among students. In recent years, several domestic and international related paper have been proved that e-learning could significantly improve the learning efficiency. Thus, it has been served as an important topic that how to effectively integrate technology into learning system.
So far, according to the papers which related to apply computer-mediated communication (CMC) as teaching assistant tool, most researchers focused on the view of exchanging information and presenting posts. Here in this research, we pointed out a method to detect whether the post of students correlated to the pre-established topic in an intelligent collaborative CMC platform. The method included training classifier by using support vector machines (SVM), peer assessment between students, and teacher’s opportune intervention, etc. Based on the experimental result, it showed pretty good learning effect among students. Furthermore, it revealed that the CMC platform also alleviated the teaching loading of teacher according to the feedback sheets from teachers. With the benefit of this platform, teachers can devote more time and energy to design more effective teaching method.

致謝 I
中文摘要 II
英文摘要 III
目錄 IV
圖目錄 VI
表目錄 VII
第一章 緒論 1
第一節 研究動機 1
第二節 研究目的 2
第三節 研究方法 3
第四節 研究範圍 4
第五節 論文架構 4
第二章 文獻探討 5
第一節 數位學習 5
第二節 合作學習 6
第三節 同儕互評 8
第四節 支持向量機 9
第三章 系統設計與流程 10
第一節 系統架構 10
第二節 各模組介紹 11
一、課程支援模組 11
二、文本分類器模組 12
三、特徵提取模組 13
四、同儕互評模組 15
五、回饋模組 18
第四章 實驗結果與分析 19
第五章 結論 24
參考文獻 25

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