Busra Nur Gokkurt Yilmaz, Furkan Ozbey, Birkan Eyup Yilmaz
{"title":"人工智能辅助个性化反馈对牙科学生放射诊断表现的影响:一项对照研究。","authors":"Busra Nur Gokkurt Yilmaz, Furkan Ozbey, Birkan Eyup Yilmaz","doi":"10.1186/s12909-025-07875-4","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>This study aimed to evaluate the impact of MeSH based personalized learning guides generated by ChatGPT-4o on the radiographic diagnostic performance of dental students and to compare it with the traditional correct/incorrect feedback method.</p><p><strong>Methods: </strong>This randomized controlled study was conducted among fifth-year dental students at Afyonkarahisar Health Sciences University. A total of 110 students were randomly assigned to either the experimental or control group. The experimental group received personalized study guides targeting their learning gaps, generated by ChatGPT-4o based on Medical Subject Headings (MeSH). The control group received only a standard correct/incorrect feedback analysis. One month after the intervention, a post-test was administered to assess diagnostic accuracy and student satisfaction.</p><p><strong>Results: </strong>The increase in test scores from pre- to post-test was significantly higher in the experimental group (3.6 ± 1.0) compared to the control group (1.3 ± 1.2; p < 0.001). Final test scores were also significantly higher in the experimental group (p < 0.001). Survey responses indicated that the experimental group rated the feedback as more understandable, beneficial, and motivating compared to the control group.</p><p><strong>Conclusions: </strong>ChatGPT-4o based personalized feedback proved to be an effective tool for enhancing diagnostic performance and supporting learning in dental education. The findings suggest that AI-driven individualized educational strategies hold significant potential in the future of dental training.</p>","PeriodicalId":51234,"journal":{"name":"BMC Medical Education","volume":"25 1","pages":"1403"},"PeriodicalIF":3.2000,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Effect of artificial intelligence-assisted personalized feedback on radiographic diagnostic performance of dental students: a controlled study.\",\"authors\":\"Busra Nur Gokkurt Yilmaz, Furkan Ozbey, Birkan Eyup Yilmaz\",\"doi\":\"10.1186/s12909-025-07875-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>This study aimed to evaluate the impact of MeSH based personalized learning guides generated by ChatGPT-4o on the radiographic diagnostic performance of dental students and to compare it with the traditional correct/incorrect feedback method.</p><p><strong>Methods: </strong>This randomized controlled study was conducted among fifth-year dental students at Afyonkarahisar Health Sciences University. A total of 110 students were randomly assigned to either the experimental or control group. The experimental group received personalized study guides targeting their learning gaps, generated by ChatGPT-4o based on Medical Subject Headings (MeSH). The control group received only a standard correct/incorrect feedback analysis. One month after the intervention, a post-test was administered to assess diagnostic accuracy and student satisfaction.</p><p><strong>Results: </strong>The increase in test scores from pre- to post-test was significantly higher in the experimental group (3.6 ± 1.0) compared to the control group (1.3 ± 1.2; p < 0.001). Final test scores were also significantly higher in the experimental group (p < 0.001). Survey responses indicated that the experimental group rated the feedback as more understandable, beneficial, and motivating compared to the control group.</p><p><strong>Conclusions: </strong>ChatGPT-4o based personalized feedback proved to be an effective tool for enhancing diagnostic performance and supporting learning in dental education. The findings suggest that AI-driven individualized educational strategies hold significant potential in the future of dental training.</p>\",\"PeriodicalId\":51234,\"journal\":{\"name\":\"BMC Medical Education\",\"volume\":\"25 1\",\"pages\":\"1403\"},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2025-10-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"BMC Medical Education\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1186/s12909-025-07875-4\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"EDUCATION & EDUCATIONAL RESEARCH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMC Medical Education","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12909-025-07875-4","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"EDUCATION & EDUCATIONAL RESEARCH","Score":null,"Total":0}
Effect of artificial intelligence-assisted personalized feedback on radiographic diagnostic performance of dental students: a controlled study.
Background: This study aimed to evaluate the impact of MeSH based personalized learning guides generated by ChatGPT-4o on the radiographic diagnostic performance of dental students and to compare it with the traditional correct/incorrect feedback method.
Methods: This randomized controlled study was conducted among fifth-year dental students at Afyonkarahisar Health Sciences University. A total of 110 students were randomly assigned to either the experimental or control group. The experimental group received personalized study guides targeting their learning gaps, generated by ChatGPT-4o based on Medical Subject Headings (MeSH). The control group received only a standard correct/incorrect feedback analysis. One month after the intervention, a post-test was administered to assess diagnostic accuracy and student satisfaction.
Results: The increase in test scores from pre- to post-test was significantly higher in the experimental group (3.6 ± 1.0) compared to the control group (1.3 ± 1.2; p < 0.001). Final test scores were also significantly higher in the experimental group (p < 0.001). Survey responses indicated that the experimental group rated the feedback as more understandable, beneficial, and motivating compared to the control group.
Conclusions: ChatGPT-4o based personalized feedback proved to be an effective tool for enhancing diagnostic performance and supporting learning in dental education. The findings suggest that AI-driven individualized educational strategies hold significant potential in the future of dental training.
期刊介绍:
BMC Medical Education is an open access journal publishing original peer-reviewed research articles in relation to the training of healthcare professionals, including undergraduate, postgraduate, and continuing education. The journal has a special focus on curriculum development, evaluations of performance, assessment of training needs and evidence-based medicine.