| Project/Area Number |
21K13052
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| Research Category |
Grant-in-Aid for Early-Career Scientists
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| Allocation Type | Multi-year Fund |
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| Review Section |
Basic Section 02100:Foreign language education-related
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| Research Institution | University of Fukui |
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Principal Investigator |
ロンバルディ イヴァン 福井大学, 学術研究院教育・人文社会系部門(総合グローバル), 講師 (10772981)
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| Project Period (FY) |
2021-04-01 – 2025-03-31
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| Project Status |
Granted (Fiscal Year 2023)
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| Budget Amount *help |
¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2024: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2023: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2022: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2021: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
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| Keywords | EFL speaking / progress tracking / course design / learning awareness / learner agency / Progress tracking |
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| Outline of Research at the Start |
How and to what extent can progress tracking help language students gauge the improvement of their speaking abilities in short-term language courses? To answer, the research sets up a case study within a high-stakes English course at a Japanese national university. Participants will be asked to record their classroom interactions in English, listen, rate, evaluate their performance, and reflect on what they have achieved in each class meeting. Participants will be prompted to review recursively and compare their current speaking skills with their older ‘English-speaking selves’.
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| Outline of Annual Research Achievements |
The research design benefitted from an additional year of data collection in FY2023. The researcher deemed it necessary to extend the data collection window to feature at least one semester's worth of data from in-person activities and interviews. This was not possible in FY2021 and FY2022 because of COVID restrictions, thus necessitating the language learning progress and/or the data collection activities to be online. Analysis of the qualitative data from interviews is in progress. It is taking longer than in previous years since meeting the participants in person leads to more elaborate interviews. In general, the research results show a consistent correlation between the implementation of visualization and progress-tracking techniques and participant awareness of their language learning. The correlation was particularly strong in FY 2023, and the reason for this warrants further investigation.
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| Current Status of Research Progress |
Current Status of Research Progress
3: Progress in research has been slightly delayed.
Reason
The research design was updated in the previous years to adapt to the pandemic-induced emergency remote teaching (ERT) situation at the research location. In FY 2023, it was necessary to revert to the original research design, albeit with minor modifications that proved effective during ERT (e.g., a smaller number of progress reviews and an increased number of moments for reflection). Since this fiscal year was the first opportunity to collect data from fully in-person learning activity and research meetings, it was deemed necessary to perform one more data collection cycle. This has, in turn, delayed the creation of guidelines for implementation that will constitute the final product of this research project. However, it is believed that the additional data collection and analysis cycle will be instrumental in writing said guidelines.
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| Strategy for Future Research Activity |
Qualitative data analysis for FY 2023 is in progress, and the results will need to be compared with data from previous years. This will be a priority for the researcher since it contributes directly to research dissemination, which is an ongoing effort.
Since the research is now shaping to include additional cycles of data collection than previously foreseen, it is necessary to amend the original plan to allow for more time to analyze the data, compare the results, and derive a succinct set of guidelines for the implementation of progress tracking into language learning and language teaching. In addition, the research needs to respond to the affordances and the concerns of the widespread adoption of large language model-based AI-chatbots. The availability and affordability of such tools are profoundly changing the landscape of language teaching and language learning. To remain relevant in 2024, the present research needs to acknowledge these tools and inquire about how the research participants use them (or not) for their language learning goals.
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