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Modeling Complexity, Accuracy, and Fluency of Japanese Learners of English: A Structural Equation Modeling Approach

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Rie Koizumi, Juntendo University; Yo In’nami, Shibaura Institute of Technology

With this study, we aimed to obtain a better understanding of the factor structure of the complexity, accuracy, and fluency (CAF) of English speaking proficiency. For this purpose, 224 Japanese junior and senior high school students with an English level of elementary to lower intermediate took an English speaking test. We transcribed what they said, computed measures to assess CAF, and used structural equation modeling (SEM) to examine whether the model in which the CAF factors are related fit the data. We found that syntactic complexity (SC), accuracy, speed fluency, and repair fluency represent distinct factors and that there are weak, moderate, or strong correlations among these factors. This generally suggests that those who speak fluently by using more words per minute tend to repair their speech more, but they also produce more accurate utterances with more clauses. We suggest pedagogical implications of considering CAF separately in teaching and assessment and benefits of using SEM for analyzing CAF.

本研究では、スピーキング熟達度における複雑さ、正確さ、流暢さ (complexity, accuracy, and fluency: CAF) の因子構造を調べる。中学生・高校生(初級から中級下レベル)の日本人学習者224名に、スピーキングテストを受けてもらった。発話をCAFの指標で数値化し、CAF因子が関連しあうモデルを共分散構造分析を用いて分析した。その結果、統語的複雑さ、正確さ、スピードに関する流暢さ、修正に関する流暢さの4因子の相関モデルがデータに適合し、4因子は関連しあいながらも別個に捉えられることが分かった。因子間の関連は弱いものから強いものがあったが、全体的には、1分間あたりにより多くの語を使って話す学習者は、修正をより多く行うが、より正確な発話と、より多くの節を産出する傾向が見られた。指導や評価の際にCAFを別々に考慮することの重要性や、共分散構造分析でCAFを分析する利点が示された。

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