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研究生:倪雅真
研究生(外文):Ni Ya-Chen
論文名稱:兒童文本句子相似度指標及可讀性公式建置與應用
論文名稱(外文):The establishment and application of children corpus sentence similarity indices and readability formula
指導教授:郭伯臣郭伯臣引用關係廖晨惠廖晨惠引用關係
指導教授(外文):Kuo Bor-ChenLiao Chen-Huei
口試委員:曾建銘
口試委員(外文):Cheng Chien-Ming
口試日期:2014-06-16
學位類別:碩士
校院名稱:國立臺中教育大學
系所名稱:教育測驗統計研究所
學門:教育學門
學類:教育測驗評量學類
論文種類:學術論文
論文出版年:2014
畢業學年度:102
語文別:中文
論文頁數:123
中文關鍵詞:最小編輯距離句子結構相似度可讀性
外文關鍵詞:Minimal Edit Distances(MED)Sentence syntax similarityReadability
相關次數:
  • 被引用被引用:4
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本研究目的為建置句子相似度指標之自動化分析系統,並探討兒童語料庫在指標上所呈現的趨勢,進一步檢視指標分數對文本年級適讀性和中高年級閱讀理解測驗通過率之預測力。最後彙整先前團隊研究發展的所有指標,進行迴歸分析,找到一個最佳預測效果的可讀性公式。研究結果如下:
一、 本研究分別以全文及相鄰句建置詞彙與詞性最小編輯距離指標及句子結構相似度指標。
二、 六項指標以多元迴歸分析預測文本適讀年級的解釋量可達22.9%,再進行逐步迴歸分析,其中全文詞彙與詞性的最小編輯距離及全文結構相似度三個指標的預測年級解釋量即可達22.7%。
三、 全文詞彙最小編輯距離指標可預測四、六年級及全部學生理解測驗直接推論的通過率,其解釋量分別為23%、17.4%、21.5%;全文詞性最小編輯距離指標可預測四、六年級及全部學生閱讀理解測驗詮釋整合的通過率,其解釋量分別為13%、16.8%、15%。
四、 從60個指標中選入48個指標進行多元迴歸分析,預測文本適讀年級解釋量可達80.5%。以逐步迴歸進行分析,最具預測力的指標是詞彙習得年齡,解釋量達74.6%,其中12個指標達顯著效果,其解釋量可達79.8%。
五、 從48指標中排除詞彙習得年齡指標進行多元迴歸分析,47個指標對文本年級的整體解釋量達62.5%。再進行逐步迴歸分析,其中達顯著的指標為20個,其解釋量達61%。最具預測力的指標是MTLD,預測效果為26.4%。

The purpose of this study is to establish an auto-analyzing system of sentence similarity indices, to explore the trends of “Children corpus” through the 6 indices and furthermore to survey the contribution of the six indices on predicting the text-suitable grade level and the pass rate of the intermediate and high graders on the comprehension test. At last, by combining all the indices which had been established, the study eventually found a readability formula which could be the best predictor. The results were summarized as follows:

1. This study established the indices for Local and Global Minimal Edit Distances of words and part-of-speech(lexical categories), and the sentence syntax similarity between all adjacent sentences and across paragraphs.
2. The contribution of 6 indexes that can predict text-related grade level was up to 22.9% by multiple regression analysis. In terms of stepwise regression analysis, the R2 value made by the 3 indicators (Global Minimal Edit Distances for words、Global Minimal Edit Distances for part-of-speech、Global sentence syntax similarity) was up to 22.7%.
3. Global Minimal Edit Distances of words can predict the pass rate of the 4th,6th graders and all students on the comprehension test in terms of “make straightforward inferences”. The R2 value was up to 23%、17.4%、21.5%. Global Minimal Edit Distances for part-of-speech can predict the pass rate of the 4th, 6th graders and all students on the comprehension test in terms of “interpret and integrate information”. The R2 value was up to 13%、16.8%、15%。
4. The study did a multiple regression analysis with the chosen 48 indices out of 60 in order to predict the text-suitable grade level. The R2 value was up to 80.5%. While through a stepwise regression analysis, the index of Age of acquisition was the best predictor for the text-suitable grade and it produced an R2 value of 74.6%. There were 12 indices got the most notable effect. The R2 value made by the 12 indices was up to 79.8%.
5. If the study did a multiple regression analysis excluding the variable of Age of acquisition from the 48 chosen indices. The other 47 indices could predict the text-suitable grade level with the R2 value as 62.5%. While through a stepwise regression analysis, the R2 value made by the most notable 20 indices was up to 61%. The MTLD was the best index and predictor as well. Mere the index itself could produce an R2 value as 26.4%.

摘要 ..I
Abstract II
目錄 IV
表目錄 VI
圖目錄 VIII
第一章 緒 論 1
第一節 研究動機 1
第二節 研究目的 …… 3
第三節 名詞解釋 4
第二章 文獻探討 5
第一節 線上文本分析系統COH-METRIX 5
第二節 中文句子的特性及語義、語法結構 13
第三節 閱讀理解 21
第四節 可讀性 28
第三章 研究方法 51
第一節 研究流程 51
第二節 發展句子相似度指標 53
第三節 線上文本自動化分析系統 57
第四節 研究工具 60
第五節 研究對象與限制 67
第六節 資料處理與分析 69
第四章 研究結果與討論 71
第一節 兒童語料庫文本指標趨勢分析 71
第二節 指標分數預測文本適讀年級 77
第三節 指標分數預測閱讀理解層次通過率之表現. 81
第四節 建置可讀性預測公式. 87
第五章 研究結論與建議 105
第一節 結論 105
第二節 建議 106
參考文獻 109
中文參考文獻 109
英文參考文獻 114

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