Investigating the Impact of Learner Proficiency on Their Usage of Vocabulary and Multi-word Expressions: A Longitudinal Multi-modal Corpus
Project/Area Number |
21K00577
|
Research Category |
Grant-in-Aid for Scientific Research (C)
|
Allocation Type | Multi-year Fund |
Section | 一般 |
Review Section |
Basic Section 02080:English linguistics-related
|
Research Institution | Kwansei Gakuin University |
Principal Investigator |
|
Co-Investigator(Kenkyū-buntansha) |
ブルックス ギャビン 名古屋商科大学, 国際学部, 講師 (10610818)
CLENTON JONATHAN 広島大学, 人間社会科学研究科(総), 准教授 (80762434)
Fraser Simon 広島大学, 外国語教育研究センター, 教授 (10403510)
|
Project Period (FY) |
2021-04-01 – 2026-03-31
|
Project Status |
Granted (Fiscal Year 2022)
|
Budget Amount *help |
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2025: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2024: ¥520,000 (Direct Cost: ¥400,000、Indirect Cost: ¥120,000)
Fiscal Year 2023: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2022: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2021: ¥520,000 (Direct Cost: ¥400,000、Indirect Cost: ¥120,000)
|
Keywords | multi-word expressions / vocabulary / corpus / English education |
Outline of Research at the Start |
The current project is a direct response to recent calls by researchers for a large-scale corpus to determine how learners acquire specific language skills, including vocabulary and MWE.
|
Outline of Annual Research Achievements |
This year we continued collecting and transcribing the corpus data. We have been working with some of the 2021 data, but the online data appears to be quite different from the face-to-face data of the next year. We presented at JALT’s pan-sig conference on some preliminary results from the 2021 data and the TESOL conference in the US and have gotten some good feedback and ideas from both of those. The TESOL conference presentation was attended by a corpus linguist from Arizona State university who was able to give us some good ideas on how we might be able to approach the data differently. We are working on a preliminary article about the process of compiling the corpus and are preparing to present on using AI transcription at JALT call.
|
Current Status of Research Progress |
Current Status of Research Progress
2: Research has progressed on the whole more than it was originally planned.
Reason
The project is going fairly well in spite of a few set backs mainly having to do with having teachers collecting data. We have tried to streamline the collection process to make that easier on teachers and to help make it easier for teachers to remember the protocols in the process. Having a dedicated transcriber has been very helpful, but having only one has meant that there is sometimes a bit of a wait on data we’d prefer to have sooner. Because of this we are looking into alternative means of transcription. We are also looking for a new research assistant as the previous one has graduated.
|
Strategy for Future Research Activity |
As mentioned earlier, we’ll be extending the data collection for one more year so we will have 2 years of face-to-face data. This upcoming year we will continue to focus on data collection and our publication opportunities will mainly focus on the process of collecting, transcribing, and getting the data into a format that can be easily worked with. This continues to be one of the biggest challenges in learner corpus linguistics so it a very appropriate field to work with at the moment.
|
Report
(2 results)
Research Products
(8 results)