知識表徵與概念學習之研究--以路徑蒐尋網路分析為評量工具

Abstract

本文旨在測使用路徑蒐尋網路分析為評量工具超於現今傳統測驗使用工具之優勢，假設路徑蒐尋網路分析工具將提供教師更清楚學生學習狀況的訊息。本研究採用11位特殊教育學分班學生為研究樣本，來討論他們在課後的知識表徵和知識結構，研究結果指出本測量工具的二個重要性指數之值低於過去研究者所做的結果，本研究者推論此情形的發生乃可能源於研究樣本人數過少，且研究樣本本身同質性過所致。根據本研究，可得知透過具體圖形知道學習者的抽象知識表徵，將有助於明瞭學生的學習狀況。藉由此研究，鼓勵我們去做更多的調查來瞭解學生學會什麼，以及學生是如何進學習。

This paper examines the advantages of using the pathfinder network analysis assessment tool over the traditional methods now in use. It is assumed that the pathfinder network analysis tool will give clearer learning conditional information of students for teachers. To do this research applied the pathfinder network analysis technique to a special education class of 11 students. What follows is a discussion of their knowledge representation and knowledge structures. The results of this study in three crucial indices（GTD, PRX, PFC）are actually lower than those found by previous researchers. Researcher’s inference is that the sample size may be too small and the samples’ characteristics are similarly. According to the result, it shows that knowing learners’ abstract knowledge representation through concrete graph, it is helpful for instructor to know the learning situation of students. By this study, encouraging us to do more investigation in knowing what the students learning and how the students thinking.