在小組的學習環境中，就像是社會活動一般，彼此成員間都具有影響力。傳統上學生們彼此間的互動是很難紀錄與分析，老師必須要經過許多繁複的方式，才能將互動的情形紀錄下來，再加以分析。當學生人數日益增加的時候，老師也很難掌握每個學生的狀況，更難以利用其中隱含的資訊。
　　本論文針對小組學習時彼此溝通互動的情形進行偵測。以社會理論中密爾森的團體溝通體系理論為基礎，結合圖形理論（Graph theory）及P＊理論等方面的特徵，利用統計方法、貝式推理網路（Bayesian Belief Network）與決策樹（Decision Tree）技術，對於小組學習表現中本論文關心的部分進行分析－包含成績方面、小組學生輟學狀況、小組成員間彼此資源分享情形。其中使用Java applet連接Web-log資料庫，利用資料庫處理資料的機制與性能，發展小組溝通觀察工具，提供老師圖形化的觀察；並且利用決策樹軟體C5.0製作分類器（Classifier），自動幫助老師分類小組學習溝通網路的模式。
　　本論文尋找小組學習溝通網路的模式與結構化描述溝通的細部元素，經過實驗分析找到溝通網路與小組學習表現中成績方面、小組學生輟學狀況、小組成員間彼此資源分享情形之間的關係，發現小組學習溝通網路對這些表現都有影響。也找出團體溝通體系中模式與幾個小組學習表現方面的關係。另外，利用貝式推理網路（Bayesian Belief Network）瞭解小組溝通互動中主要因素之間的關係，和與幾個小組學習表現方面的關係。
　　尋找出來的實驗分析結果，製作成一自動偵測小組學習溝通網路狀況的系統，偵測本論文關心的幾個小組學習表現之異常情形，由自動通知的機制通知老師，幫助老師適時介入小組的學習中引導學生。

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