本研究在探討如何運用模糊理論為基礎，建構一套適性化學習評量系統。評量系統為兼具線上即時學習診斷與輔助學習的系統平台，學習評量的分析結果乃在輔助學生了解自我的學習狀態，線上輔助學習的工具提供學生自我學習的環境，進而提高學習成效。在一般電腦輔助測驗中，依據測驗成績來評估當前的能力，缺乏考量試題與教材之間的關聯性，診斷結果也較容易缺乏彈性度。在本篇論文中，我提出應用模糊理論之適性化學習診斷系統(Application of Fuzzy Theory for Adaptive Learning Diagnosis System; FADS)。此系統利用計算概念相似的方法解決如何訂定試題與教材之間的關聯性，並依據學習者對於教材的反應與評量試題的作答結果，自動化於線上閱讀教材做適性標記，每位學習者皆有不同的適性標記，並以加深加粗的字體提醒學習者再次閱讀的重點提示。同時系統利用學習者的作答結果與試題及教材間的關聯性，來計算每位學習者當時的學習程度，並透過模糊隸屬函數轉化後，計算章節試題難易度比率做適性選題，且自動化於自我練習區產生適性練習卷，提供每位學習者自我學習的環境。本研究以國小四年級社會科第二單元為例，藉由兩百位學生實際參與系統實驗顯示，採用FADS的學生其提升的學習成效皆高於其他組，表示FADS為較兼具適性化與彈性度的學習診斷平台。

In this paper, I present an application of fuzzy theory for adaptive learning diagnosis system, called FADS. This system uses concept similarity method to compute association between item and teaching materials. According to his/her learning response status , to mark the paragraph on the reading area on-line automatically. Every learner has different adaptive mark on the teaching materials. To remind learner taking care the deep and thick paragraph. The system depends on the learning status and association between item and teaching materials to compute learner’s degree of learning simultaneously. The difficulty ratio of chapter and item are transferred by the fuzzy membership function to pick up suitable items for learner. The system was demonstrated by using a society course. There are two hundred students that participated in the experiment to see if the learning effects of the experimental group higher than the others. FADS is a learning diagnosis system holding adaptation and resilience concurrently.

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