國立臺灣師範大學資訊教育研究所;國立花蓮師範學院數理教育系張國恩林水成潘宏明陳世旺Chang, Kuo-EnLin, Shui-ChengPan, Hung-MingChen, Sei-Wang2014-10-302014-10-301998-03-011027-507xhttp://rportal.lib.ntnu.edu.tw/handle/20.500.12235/34326一張概念圖是由許多命題（propositions）所組成，而每個命題包括兩個概念（concepts）及他們之間的聯結語，因此一張概念圖描述著某一知識內容中概念問的相互連結關係。然而不同的概念與聯結語在一知識主題（knowledge domain）中扮演著不同的角色，其重要性當然會有所不同。因此本文提出一種屬性化概念圖（attributed concept map）的觀念，也就是對概念圖中每一概念及聯結語給予一權值代表其重要性。假設專家或老師已經建構好一張屬性化概念圖，我們稱它為專家概念圖。我們提出一種以模糊集合理論為基礎的評量方式（或稱模糊評量）。將學生建構的概念圖與專家概念圖比對，來評估學生對某一知識主題的了解程度。實驗顯示以屬性化概念圖為主的模糊評量在合理性、穩定性上均有顯著的改進，結果也顯示此方法是可行的。概念圖;屬性化概念圖;模糊評量A concept map consists of a collection of notions interconnected to each other that collectively delineate a significant branch of knowledge. The notions and relationships constituting a map play distinct roles during restating the subject portrayed by the map. The notions and relationships are assigned associated weights by experts to indicate their relative degree of importance in the conceptual context. The resulting map is called the expert concept map. During the evaluation of the prototype mapsstudents were asked to build a map. The maps were compared with the expert concept map using a technique conceptualized in terms of a fuzzy discipline. The maps and techniques were developed and tested against data. The results revealed that approach was feasible.concept mapattributed concept mapfuzzy assessment