由於網際網路之盛行，許多教師在網路上建立學習系統，使得學生可以在任何地點與時間上課。網際網路的另一個優點是學生在網路上的學習資料隨著時間變化完整地被記錄下來，因此可以用過去學生的學習歷程(Portfolio)與時序上的考量來作為觀察與預測學生成就的依據。然而這個工作要處理到許多的網站上站記錄，要觀察到他們與學習成就之間的關係是相當費時費力的。而老師的教學策略隨時影響著學生的學習行為改變，了解教學策略與學習歷程影響關係，可以幫助老師觀察學生及教學策略擬定的參考，而老師要從網站紀錄得知這些資訊也是相當費時和困難的。
在這篇論文中，我們著力於建構具時間性的學習者模式中的兩個模組，（1）利用Dual model架構，將學生在網路學習環境中具時間性的學習行為歷程及學習成果等學習變數以Decision Tree的形式表示而成的學習成就預測模型 (2) 由老師平常所執行的教學策略和學生在網站上的學習行為歷程，以序列探勘（Sequential Pattern Mining）方法分析教學策略與學生學習行為改變的影響。
本論文所建構的具時間性的學習者模式可以做到（1）幫助老師從學生的學習行為歷程中即時預測學生的學習狀況，若發現學習成果可能不佳的學生，老師可即早給予輔助。（2）幫助老師觀察其教學策略對於學生學習行為的影響，包含觀察和比較不同程度學生對於教學策略的學習行為改變狀況以及個別學生對於教學策略的學習行為改變狀況，以做為老師輔助學生依據及教學策略擬定的參考。

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