| 研究課題/領域番号 |
21K00669
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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 | 叡啓大学 (2022)
広島女学院大学 (2021) |
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研究代表者 |
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| 研究分担者 |
CLENTON JONATHAN 広島大学, 人間社会科学研究科(総), 准教授 (80762434)
ブルックス ギャビン 関西学院大学, 総合政策学部, 講師 (10610818)
Fraser Simon 広島大学, 外国語教育研究センター, 教授 (10403510)
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| 研究期間 (年度) |
2021-04-01 – 2024-03-31
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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 |
4,160千円 (直接経費: 3,200千円、間接経費: 960千円)
2023年度: 1,170千円 (直接経費: 900千円、間接経費: 270千円)
2022年度: 1,950千円 (直接経費: 1,500千円、間接経費: 450千円)
2021年度: 1,040千円 (直接経費: 800千円、間接経費: 240千円)
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| キーワード | productive vocabulary / lexical diversity / multiword units / vocabulary / IELTS / lexical density / pedagogic word-lists / corpus |
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| 研究開始時の研究の概要 |
The aim of the project is to produce a large-scale corpus of student generated texts of academic English, in order to understand the written and spoken vocabulary requirements of different IELTS levels. Participants will number over 1400 L2 post-graduates studying at a large UK university.
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| 研究実績の概要 |
The corpus analysis has led to talks at 2 international conferences, a published paper and a PhD thesis. Our current findings are that Lexical Diversity (LD) measures predict the IELTS bands of hand-marked essays, but the LD of spoken transcripts do not predict IELTS bands. Also, when counting words, it makes a difference if you count words as lemmas, flemmas or word families.
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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
We had intended to collect a little more data by this point, unfortunately due to the QMUL pre-sessional 2022 course still being online (due to Covid19) we could only collect an additional 105 sets of written and spoken data to add to the database. This means that we will need to collect one more batch of data in September 2023 to have a satisfactory sample size with which to fully test our various hypothesis'. Despite not having quite as much data to work with (as initially anticipatated) we completed some analysis and were able to present this at conferences and also publish a paper in a journal.
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| 今後の研究の推進方策 |
We plan to collect more data from Queen Mary University of London pre-sessional students in September 2023. We also expect to present our findings at a large international conference (Vocab@Vic New Zealand December 2023) and then publish more of our findings in high-impact journals.
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