JSEE Annual Conference International Session Proceedings
Online ISSN : 2424-1466
Print ISSN : 2189-8936
ISSN-L : 2189-8936
2025 JSEE Annual Conference
Session ID : W-07
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International Session
W-07 A Design-Based Study of AI-Enhanced Multimodal Support for Content Understanding in an English-Medium History Course: Toward Data-Driven Education for Society 5.0
*Ujwal Kumar*Choi HyoseokHatsuko YOSHIKUBO
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Abstract
This design-based study, a collaborative project with student authors, explores the development of CEFR-level English vocabulary use among international students enrolled in an English-medium instruction (EMI) history module at Shibaura Institute of Technology. Customised lecture slides were generated using Claude 3.5, offering tailored content at both B2 and C2 CEFR levels to accommodate the diversity of learners’ English proficiency. Supplementary audio review materials with AI-generated voice narration were provided to enhance comprehension. Student writings were analysed using holistic tools such as the CEFR-based Vocabulary Level Analyser (CVLA) and the AI-powered CEFR-based Writing Level Analyser (CWLA). Initial findings indicate that the mean CEFR score assessed by CVLA rose from 4.65 (just below B2.2) in Week 1 to 5.32 (within the C1–C2 range) in Week 4, with a statistically significant gain (p ‹ 0.01). Final results, completed in July 2025, are expected to inform the design of inclusive, data-driven educational environments aligned with the Society 5.0 vision.
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© 2025 Japanese Society for Engineering Education
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