| Project/Area Number |
23K00767
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Review Section |
Basic Section 02100:Foreign language education-related
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| Research Institution | Tokyo Medical and Dental University |
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Principal Investigator |
デニソン ジェネット 東京医科歯科大学, 教養部, 准教授 (60764793)
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| Co-Investigator(Kenkyū-buntansha) |
Gary Ross 金沢大学, 薬学系, 准教授 (10708142)
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| Project Period (FY) |
2023-04-01 – 2027-03-31
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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 2026: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2025: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2024: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2023: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
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| Keywords | speech recognition / chatbot / ChatGPT / medical English / medical interview / medical communication / speaking practice / online learning / autonomy / verbal engagement |
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| Outline of Research at the Start |
This study will investigate the feasibility of innovative methodologies using speech recognition and chatbot technologies in an autonomous, self-evaluating learning platform for increasing verbal engagement and improving communication skills within medical English education programs.
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| Outline of Annual Research Achievements |
This study is investigating the feasibility of innovative methodologies using speech recognition (SR) and chatbot technologies in an autonomous, self-evaluating learning platform for increasing verbal engagement and improving communication skills within medical English education programs. Our study has proceeded through Stages I and II.
Stage I involved development of content through ChatGPT prompt engineering for an existing SR+ChatGPT speaking program. The first set of content reflected four different tiers of medical English speaking tasks. Task 1 was pronunciation practice of medical terminology based on body system themes. Task 2 was the teaching of interview questions common for doctor-patient medical interview. Task 3 was the practice in mini scenarios of the interview questions learned in task 2. Task 4 was a full simulated interview with a "AI patient" based on constructed medical case.
In Stage II, we tested the first content set on a small cohort of non-Japanese (international) students from medical-related graduate programs at one Japanese university. This first test allowed us to measure the functionality and content appropriateness. The survey results and observations of the interactions with the program suggest that while current SR technology is still struggle to properly recognize some medical terminology, the combined SR+ChatGPT program could provide a good opportunity for self-study speaking practice. With improvements in SR technology and medical-specific LLMs, we will be able to provide accessible medical communication to a variety of English speakers.
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| Current Status of Research Progress |
Current Status of Research Progress
2: Research has progressed on the whole more than it was originally planned.
Reason
As planned, we have completed Stage I (program content development) and Stage II (pilot test on content with non-Japanese cohort).
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| Strategy for Future Research Activity |
We will start Stage III of the study which involves extensive content development for medical communication coursework within a Japanese medical undergraduate program. First, we will begin testing the pilot test content in Japanese medical students based on the following parameters: level-appropriate English, functionality, user friendliness, task instructions, etc. Based on this pilot study with this small cohort of Japanese medical students we will then create additional content and expand the study to a larger cohort of students. Third, we will also look at the ability of ChatGPT to evaluate, provide feedback and track the progress of individual students. The results of Stage III will provide insight on the development of a full course of content for medical English communication programs that utilize the SR+ChatGPT program. As SR and LLM technology advances, we expect better interactions and fewer SR-related technical issues allowing for a more motivating and effective interaction.
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