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    题名: 科技英文文章難易度分類之研究
    作者: 王湘嵐
    江憲坤
    郭鳳蘭
    关键词: 全民英檢 可讀性 科技英文
    GEPT readability technological English Flesch-Kincaid readability formula KNN
    日期: 2006
    上传时间: 2017-11-28 14:21:59 (UTC+8)
    摘要: 科技產業的發展關係到國家的全球競爭力，提升科技人才的科技英文閱讀能力將有助於其吸取新知和提升創造力。然而，目前並沒有一個嚴謹的科技英文文章難易度辨別之公式來協助學習者過濾和篩選適合其閱讀之科技英文文章。況且，科技英文文章難易度判別和分類之相關研究極為稀少。因此，本研究分析現今Flesch Reading Ease可讀性公式之優缺點，提出一個延伸其公式並加上全民英檢各等級單字和科技專業詞彙作為特徵值之可讀性公式。研究者以全民英檢全真試題初級、中級和中高級之閱讀測驗試題共59篇作為資料來源，採用KNN演算法來做文章分類，以比較Flesch Reading Ease公式和本研究所提出公式之效能。實驗結果顯示，本研究所提出之難易度預測公式遠勝於Flesch-Kincaid公式之效能。
    The development of IT industry is related to a country’s global competition, and enhancing IT talents’ technological English reading ability can thus promote their creativity. Currently, however, there is no reliable formula to judge the readability of technological English to help learners select proper articles to read. Moreover, studies related to readability of technological English articles are extremely rare. Therefore, our study analyzes the advantages and the disadvantages of Flesch-Kincaid readability formula and proposed an extended formula, using GEPT’s vocabulary difficulty levels and technology terminology as the formula’s feature values. The resource of our study comes from 49 GEPT’s beginning, intermediate, and high-intermediate level’s reading comprehension articles. We further classify these articles by KNN algorithm and compare the effectiveness between Flesch-Kincaid formula and our proposed formula. The result indicates that our proposed formula is more effective than the latter in predicting the readability of a technological English article.
    關聯: TANET 2006 台灣網際網路研討會論文集
    軟體創意開發與應用
    数据类型: conference
    显示于类别:[TANET 台灣網際網路研討會] 會議論文

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