Comparing teacher-made and AI-assisted teaching videos for thyroid eye disease: an exploratory study
- 1Department of Ophthalmology, Changzheng Hospital of Naval Medical University, Shanghai, China
- 2Department of General Practice, Changzheng Hospital of Naval Medical University, Shanghai, China
Abstract
Background: Thyroid eye disease (TED), together with its acute and vision-threatening complication, dysthyroid optic neuropathy (DON), requires timely diagnosis and intervention. The limited availability of specialists in orbital diseases poses a significant challenge to ophthalmology residency training. In this context, generative artificial intelligence (AI) has created new opportunities for medical education, though its effectiveness in ophthalmology training remains to be explored.
Objective: This exploratory study aims to evaluate the effectiveness of generative artificial intelligence (AI) in ophthalmology education, focusing on TED domains.
Methods: The 46 residents (28 general residents and 18 ophthalmology residents) were randomly assigned to either an AI-assisted or a teacher-made 5-min teaching video on TED. All participants then completed three tests through online questionnaire experiments, each consisting of 20-item clinical questions about TED. Test 1 served as a baseline assessment of disease knowledge, Test 2 was conducted 5 min after learning to evaluate short-term learning outcomes, along with a questionnaire survey about AI tools, and Test 3 was administered 1 week later to assess long-term learning outcome.
Results: Viewing the AI-assisted video significantly improved test scores from baseline to 5 min (mean difference = 13.04; p = 0.004), but the improvement was not sustained at 1 week (mean difference = 7.61; p = 0.16). Completion time also decreased significantly from baseline to both 5 min (p = 0.009; GMR = 0.57) and 1 week (p < 0.001; GMR = 0.45). No significant differences were observed between the AI-assisted and teacher-made video groups across all assessments (all p > 0.05). Additionally, learning experience was positively correlated with learning outcome (r = 0.60; P < 0.001).
Conclusion: Our findings suggested that the AI-assisted and teacher-made videos for TED education showed no statistically significant difference. However, substantial expert oversight was required, and the AI-assisted workflow did not reduce total production time in this study. Given the limited long-term retention, such AI-assisted videos may be better positioned as supplementary resources combined with human expertise.
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BibTeX
@article{liu2026comparing,
title = {{Comparing teacher-made and AI-assisted teaching videos for thyroid eye disease: an exploratory study}},
author = {Shu Liu and Yue Wang and Yuqing Chen and Yunyun Chang and Ying Wang and Yu Gao and Ruili Wei},
journal = {Frontiers in Cell and Developmental Biology},
year = {2026},
month = oct,
doi = {10.3389/fcell.2026.1963967},
url = {https://doi.org/10.3389/fcell.2026.1963967},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Comparing teacher-made and AI-assisted teaching videos for thyroid eye disease: an exploratory study
AU - Shu Liu
AU - Yue Wang
AU - Yuqing Chen
AU - Yunyun Chang
AU - Ying Wang
AU - Yu Gao
AU - Ruili Wei
PY - 2026
DA - 2026/10/21
JO - Frontiers in Cell and Developmental Biology
DO - 10.3389/fcell.2026.1963967
UR - https://doi.org/10.3389/fcell.2026.1963967
AB - Background: Thyroid eye disease (TED), together with its acute and vision-threatening complication, dysthyroid optic neuropathy (DON), requires timely diagnosis and intervention. The limited availability of specialists in orbital diseases poses a significant challenge to ophthalmology residency training. In this context, generative artificial intelligence (AI) has created new opportunities for medical education, though its effectiveness in ophthalmology training remains to be explored. Objective: This exploratory study aims to evaluate the effectiveness of generative artificial intelligence (AI) in ophthalmology education, focusing on TED domains. Methods: The 46 residents (28 general residents and 18 ophthalmology residents) were randomly assigned to either an AI-assisted or a teacher-made 5-min teaching video on TED. All participants then completed three tests through online questionnaire experiments, each consisting of 20-item clinical questions about TED. Test 1 served as a baseline assessment of disease knowledge, Test 2 was conducted 5 min after learning to evaluate short-term learning outcomes, along with a questionnaire survey about AI tools, and Test 3 was administered 1 week later to assess long-term learning outcome. Results: Viewing the AI-assisted video significantly improved test scores from baseline to 5 min (mean difference = 13.04; p = 0.004), but the improvement was not sustained at 1 week (mean difference = 7.61; p = 0.16). Completion time also decreased significantly from baseline to both 5 min (p = 0.009; GMR = 0.57) and 1 week (p < 0.001; GMR = 0.45). No significant differences were observed between the AI-assisted and teacher-made video groups across all assessments (all p > 0.05). Additionally, learning experience was positively correlated with learning outcome (r = 0.60; P < 0.001). Conclusion: Our findings suggested that the AI-assisted and teacher-made videos for TED education showed no statistically significant difference. However, substantial expert oversight was required, and the AI-assisted workflow did not reduce total production time in this study. Given the limited long-term retention, such AI-assisted videos may be better positioned as supplementary resources combined with human expertise.
SN - 2296-634X
ER -