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Developing a Dynamic Assessment System to Enhance Medical Students' Learning Outcomes in Medical Image Interpretation
會議論文集

Developing a Dynamic Assessment System to Enhance Medical Students' Learning Outcomes in Medical Image Interpretation

T.-H. Wang, S.-Y. Liu, C.-H. Kao, C.-H. Wu, C.-Y. Lu 和 J.-F. Lirng
Proceedings of the 2025 17th International Conference on Education Technology and Computers, ICETC 2025, 頁碼.348-352
2025
Web of Science ID: WOS:001739950900060

摘要

Dynamic assessment graduated prompt medical image interpretation WAML system E-learning Education computing Image enhancement Learning systems Medical education Medical image processing Multimedia systems Students Assessment system Dynamic assessment Graduated prompt Image interpretation Medical image interpretation Medical students Performance Student learning outcomes Web based Web-based adaptive medical learning system Clinical research
This study, grounded on the Web-based Adaptive Medical Learning (WAML) digital platform, investigates the effectiveness of implementing graduated prompts in the learning process of medical image interpretation among medical students. The research design integrates principles from dynamic assessment and multimedia learning theory, employing three graduated prompts to guide learners from initial observation to clinical integration. Experimental results demonstrate that learners' performance significantly improved through graduated prompts. Notably, learners with initially lower achievement levels, after receiving the complete sequence of prompts, exhibited final performance comparable to that of high-achieving peers. This finding reflects the compensation effect of the WAML system, effectively narrowing the performance gap. The results affirm that graduated prompting enhances learning outcomes and facilitates knowledge integration and clinical application skills. These findings offer valuable implications for the future development of adaptive and personalized digital instructional platforms in medical education. © 2025 IEEE.

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