Artificial intelligence analysis of facial movements and satisfaction in online medical lectures: a cross-sectional study
Mari Miya, Yu Akaishi, Tatsuhiko Anzai, Kenji Suzuki, Masanaga Yamawaki · 2026
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Description
A peer-reviewed research article from Europe PMC (2026). BackgroundDetecting learners’ real-time reactions during learning is important. One potential approach is to utilize learners’ nonverbal information. Among nonverbal cues, facial expressions have been shown to influence educational outcomes. Recent technological advances have made quantitative facial expression analysis feasible. In this study, a machine learning tool, a core component of artificial intelligence, was used to quantify subtle facial movements of medical students and examine their relationship with lecture satisfaction.MethodsFifth-year medical students attended synchronous and asynchronous online lectures while being recorded.
Catalog record
| CREATOR | Mari Miya, Yu Akaishi, Tatsuhiko Anzai, Kenji Suzuki, Masanaga Yamawaki |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 38 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |