| Project/Area Number |
14580338
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Japanese language education
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| Research Institution | Keio University |
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Principal Investigator |
MURATA Minori Keio University, International Center, Professor, 国際センター, 教授 (50225372)
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| Project Period (FY) |
2002 – 2004
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| Project Status |
Completed (Fiscal Year 2004)
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| Budget Amount *help |
¥3,500,000 (Direct Cost: ¥3,500,000)
Fiscal Year 2004: ¥700,000 (Direct Cost: ¥700,000)
Fiscal Year 2003: ¥1,000,000 (Direct Cost: ¥1,000,000)
Fiscal Year 2002: ¥1,800,000 (Direct Cost: ¥1,800,000)
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| Keywords | Function Words and Phrases / Textual genre / Expository prose(Academic papers) / Multivariate Analysis / Teaching Japanese as a foreign Language / 計量文体論 / 文型 / 助詞相当句 / 接続語句 / 書きことば / 多変量解析(判別分析) / 論理構造 / 判別分析 |
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| Research Abstract |
The current study analyses function words and phrases that support the logical structure of one representative form of expository prose, in this case academic papers. The present study aims to shed light on the function words and phrases that are commonly used in academic papers from different fields. This study is expected to contribute to the improvement of teaching methods for Japanese for specific purposes, as it will enable us to provide a set of more objective basic data for the development of teaching materials.
As a step toward achieving this goal, 151 text samples from seven different sources were chosen as data. Those seven sources were : (1)papers from the Journal of the Physical Society of Japan ; (2)papers from Science and Technology ; (3)papers from Japanese Literature ; (4)papers from Economics ; (5)an pedagogical economics textbooks ; (6)modern novels, and (7)editorial articles. I counted the frequency of occurrences (per sentence) of the 62 selected sentence patterns from each sample. I examined the univariate distribution of the above 62 patterns, and then applied the Canonical Discriminant Analysis to the 151 samples.
From these results, it was found that the different texts could be classified into their genres correctly at a high discriminant rate (77%) by means of using 12 function words and phrases. The results also showed (i)the important function words and phrases through which the texts could be discriminated into their genres ; and (ii)the significant sentence structures that are commonly used in expository writings. These results revealed that function words and phrases are an important indicator in distinguishing different textual genre.
Further analysis of data from applied physics, electrical engineering, information processing (100 text samples in total) also showed a similarity with our initial result, and thus supported the result obtained from my initial data.
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