應用約略集合理論與群集分析法鑑定學習障礙之研究

Apply Rough Set Theory and Clustering Analysis into the Application to the Identification of Students with Learning Disabilities

陳昭宏(Jao-Hong Cheng) ； 李智民(Chih-Ming Lee) ； 陳佑全(Yu-Chuan Chen)

《智慧科技與應用統計學報》 7卷2期 (2009/12) Pp. 37-47

https://doi.org/10.29807/JTITAS.200912.0003

摘要

由於學習障礙屬於內隱障礙，且其學生人數已位居我國身心障礙學生人數的第二高位，為了提供符合學習障礙學生在教育上的特殊需求，首先必需要能提供正確而迅速的鑑定程序。因障礙個案本身的個別差異也懸殊各異，學習障礙之鑑定在特殊教育領域一直是一個複雜困難的議題。本研究嘗試透過學習障礙學生的魏氏智力量表的施測結果，以約略集合理論(Rough Set Theory)於先行建立學習障礙學生量表分數、智力商數與因數分析所顯現之鑑定與診斷之基本模式。結合群集分析的K-mean分群法根據資料本身的資訊將資料集分成子群體後，再結合約略集合理論 期望能提升學習障礙學生鑑定與診斷之準確度。本文依據研究結果，透過採用約略集合理論，或許有機會能成為未來學習障礙學生鑑定上不錯的選擇方式。

關鍵字

學習障礙 ； 約略集合理論 ； 群集分析法

並列摘要

Among different categories of students with disabilities in recent years because the incidence of people eugenic concepts in general and minority population trends of the multiple effects, all kinds of physical and psychological barriers with the number of generally decreasing. Since learning disabilities are implicit barriers, obstacles, the case itself is the disparity between the different individual differences in the identification of students with disabilities, has been more difficult, the identification of learning disabilities in the field of special education has been a complex and difficult issues. This study try to apply the Rough Set Theory to help simplify the identification of learning disabled students and diagnose the problem. Combining the Clustering Analysis search of the best ways to carry out the diagnosis of learning disabled students work. Perhaps a chance to become the future identification of learning disabled students on the way good choice.

並列關鍵字

Learning Disabilities ； Rough Set Theory ； Clustering Analysis