本研究目的在於探討學生於學習管理系統中應用不同類別之功能(教材、考試、作業、討論、即時回饋)與學習成就之關聯性及進一步應用分群的方式來瞭解不同背景之學生使用學習管理系統的群體特性；亦瞭解不同背景之學生在學習管理系統中學習成就的差異，進而探討且提供建議。
  本研究之研究方法為次級資料分析與資料探勘；在研究工具的部分為Rapidminer 中General linear model 的機器學習及SPSS，透過本研究之一般線性模型及分群分析和針對不同學生背景(性別、院別)進行獨立樣本T檢定與單因子獨立變異數分析；研究結果顯示：
壹、使用即時回饋學習管理系統功能與學習成就為正向關聯性，使用考試及作業、教材、討論區之學習管理系統功能與學習成就為負向關聯性。
貳、本研究結果所示使用學習管理系統的使用者最主要多為工學院其次為商學院、全球發展學院、理學院，在使用學習管理系統功能上多為課程之補充教材資源(頁面)，教材，作業，考試，最後為討論區。
參、分群結果顯示群組一及二最主要為工理學院之男性學生；而群組一顯示其工理學院於學習管理系統常用的功能為：「教材、作業、討論、考試」；群組二結果可見工學、商、理學院男性主要使用「頁面」功能；群組三為商管學院之女性學生，群組四為全球發展學院之女性學生；群組三及群組四在分群結果上顯示常用功能皆為：「教材、作業、考試」。
肆、性別在學習成就上有顯著差異，且男性的學習成就低於女性。
伍、院別群組間的學習成就有顯著差異，且各院別學習成就表現之高低，排序由高至低如：「文學院、外國語言學院、教育學院、商管學院、全球發展學院、工學院、國際事務學院」。

The purpose of this research is to explore the relationship between students' application of different types of functions in the learning management system (material, exam, homework, forum, Interactive Response System) and learning achievements and to understand the use of the learning management systems by students with different learning backgrounds by clustering. 
    This research also explores the differences in the learning achievements of students with different learning backgrounds in the learning management system and provides suggestions.
    The research method of this research is secondary analysis and data mining; the research tool is the machine learning of the General linear model in Rapidminer and SPSS. Through the general linear model, cluster analysis of this research, independent sample T test and Analysis of Variance for different student backgrounds (gender, college).; the research results show:
1. The use of Interactive Response System function of learning management system and learning achievements are positively related, and the use of exam function, material function, exam function, homework function and forum function of learning management system are negatively related to learning achievements.
2. The result of this research shows that the users are mostly from the colleges of engineering, followed by the colleges of Business, the colleges of Global Development, and the colleges of Science. 
    The most commonly used learning management system function is the supplementary resources (page function), followed by the material function, homework function, exam function and then the forum function .
3.The clustering result shows that group 1 and 2 are mainly male students from the College of Engineering and Science. 
group 1 show that the commonly used functions in the learning management system of the College of Engineering and the College of Science are: "material function, homework function, forum function, exam function".
    The result of group 2 shows that males from the college of engineering, business, and science mainly use the "page function".
    Group 3 are female students from the College of Business. 
    Group 4 are female students from the College of Global Development. The clustering results of group 3 and group 4 show that the mostly used functions are: "material function, homework function, exam function ".
4. There are significant differences in learning achievement between gender and gender, and the learning achievement of men is lower than that of women.
5. There are significant differences in the learning achievements between colleges, and the ranking of the learning achievement of each college, from high to low, are "the College of Art, Foreign Language, Education, Business, Global Development, Engineering, International Affairs".

謝誌				I	
中文摘要				II
英文摘要				III
表次				VII
圖次				VIII
第一章緒論			1
  第一節研究背景與動機		1
  第二節 研究目的與問題		4
  第三節名詞釋義			6
第二章文獻探討			9
  第一節學習管理系統		9
  第二節使用紀錄			15
  第三節學習成就			18
  第四節學習分析			21
  第五節資料探勘			24
第三章 研究設計			29
  第一節研究架構與研究問題及假設	29
  第二節研究流程			31
  第三節研究對象與抽樣方法	32
  第四節 研究工具及資料處理	33
第四章 研究結果與討論		37
  第一節 一般線性模型分析結果	37
  第二節 K-means分群結果		38
  第三節 獨立樣本T檢定分析結果	40
  第四節 單因子獨立變異數分析	41
第五章 結論與建議		45
  第一節 結論			45
  第二節 建議			49
參考文獻				51
中文部分				51
英文部分				52

表次
表1 北部某私立大學校務資料庫資料表	32

圖次
圖1  學習分析的步驟		21
圖2  CRISP-DM model		27
圖3  研究架構圖			29
圖4  研究流程圖			31
圖5  一般線性模型結果		37
圖6-1  K-means分群結果第一部分	38
圖6-2  K-means分群結果第二部分	38
圖6-3  K-means分群結果第三部分	38
圖7  獨立樣本T檢定分析結果	40
圖8  院別ANOVA描述性統計資料	41
圖9  變異數同質性測試		41
圖10 院別ANOVA			42
圖11-1  Dunnett’s T3 檢定事後多重比較第一部分	43
圖11-2  Dunnett’s T3 檢定事後多重比較第二部分	44

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