頁籤選單縮合
題 名 | 以模糊聚類方法分析數學錯誤概念組型例=An Analysis of the Group Style of Math Misconceptions Based on Fuzzy C-meanings |
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作 者 | 陳嘉甄; 陳慶彥; | 書刊名 | 教育研究與發展期刊 |
卷 期 | 5:4 2009.12[民98.12] |
頁 次 | 頁159-186 |
分類號 | 521.33 |
關鍵詞 | 錯誤概念組型; 模糊聚類方法; 學習障礙; 測驗; 數學; Group style of misconceptions; Fuzzy C-means (FCM); Learning disability; Test; Math; |
語 文 | 中文(Chinese) |
中文摘要 | 測驗可以反映學生的學習狀況,認知心理學的興起,使人們開始重視測驗歷程的錯誤反應。目前對於學生解題錯誤類型的探討重點,以錯誤概念的分析為主,皆以個別學生的試題反應為出發點,進行線性推論,少有針對學生整體錯誤反應而進行歸類,而傳統的群集分析方式亦難以處理錯誤概念的組型問題。本研究取國小三上127個樣本接受數學測驗。其中121個為一般樣本,6個為校內鑑定的學習障礙樣本。應用模糊聚類方法(Fuzzy C-means, 或簡寫為FCM)進行錯誤概念的組型探討, 以期獲得一般學生及學習障礙學生的錯誤概念組型及其教學意義。結果顯示,該方法可以得到學生類誤概念組型,亦發現本研究中的學習障礙樣本,其以概念為分析基礎的數學錯誤反應確實出現群聚現象。該結果可提供教師作為補救教學時的初步分類依據,亦可作為日常教學分組參考。 |
英文摘要 | Tests can reflect the students’ learning status. Because of the rising of cognitive psychology, so that researchers are beginning to pay attention to error responses in the course of test. At present, most discussions of problem-solving were focusing on the linear analysis of misconceptions, but very few on the similarity classify of the whole error responses. The traditional clustering method is difficult on finding the group type of misconceptions because of the characteristics of complex data in this research. There are 127 samples in this study which include 121 as general samples and 6 samples with learning disability that were identified by special educational identification group in school. Fuzzy C-means method was used to process the group clustering of misconceptions for obtaining the misconceptions group type and its educational significance.The result revealed that there were 3 clustering groups between all the samples’ misconceptions by using the clustering method FCM (Fuzzy C-meanings). The study also found that the error responses in the math test of most learning disabilities samples were clustered in the same clustering group. The result will provide teachers as a grouping reference in remedial and daily teaching. |
本系統中英文摘要資訊取自各篇刊載內容。