| 研究課題/領域番号 |
22K00814
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| 研究種目 |
基盤研究(C)
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| 配分区分 | 基金 |
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| 応募区分 | 一般 |
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| 審査区分 |
小区分02100:外国語教育関連
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| 研究機関 | 広島大学 |
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研究代表者 |
CLENTON JONATHAN 広島大学, 人間社会科学研究科(総), 准教授 (80762434)
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| 研究分担者 |
Fraser Simon 広島大学, 外国語教育研究センター, 教授 (10403510)
内原 卓海 早稲田大学, 理工学術院, 講師(任期付) (10905847)
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| 研究期間 (年度) |
2022-04-01 – 2025-03-31
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| 研究課題ステータス |
交付 (2022年度)
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| 配分額 *注記 |
3,640千円 (直接経費: 2,800千円、間接経費: 840千円)
2024年度: 260千円 (直接経費: 200千円、間接経費: 60千円)
2023年度: 2,210千円 (直接経費: 1,700千円、間接経費: 510千円)
2022年度: 1,170千円 (直接経費: 900千円、間接経費: 270千円)
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| キーワード | fluency / vocabulary / speach / lemma / flemma / speaking / knowledge / bilingual / tasks |
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| 研究開始時の研究の概要 |
The plan is to conduct studies across 5 different proficiencies towards the purpose of the larger-scale proposed project: current data suggests that relationships between the three different IELTS speaking task prompts and productive vocabulary knowledge change according to proficiency levels.
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| 研究実績の概要 |
In the current study, we explore potential relationships between lexical diversity (with different text lengths and analysis units), utterance fluency, and general speaking proficiency. We aim to report on an investigation of approximately 105 participants from a UK university divided into three different IELTS proficiency levels. We explore a corpus of participant undergraduate presentations. We investigate and compare flemma, lemma, and simple count influences on LD measure speaking predictability, using three basic LD measures and three sophisticated measures. Following earlier research (Treffers-Daller 2013), we also examine different text lengths.
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| 現在までの達成度 (区分) |
現在までの達成度 (区分)
2: おおむね順調に進展している
理由
To complete the research project, we are currently employing research assistants to process our data bank.
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| 今後の研究の推進方策 |
By investigating whether results mirror recent findings (Myint Maw et al., 2022) that both flemmatization and lemmatization influence LD scores, we examine potential relationships between LD and our other factors, and the extent to which LD is a predictor of general speaking proficiency when simple, flemma, and lemma counts are applied . We also report on different spoken text length influences. We discuss analysis units and text length influences on LD measure predictions of utterance fluency at different levels of general speaking proficiency.
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