# AI benchmarking in dental education assessment

In this cross-sectional comparative study, 49 second-year dental students completed a 45-item multiple-choice final examination in prosthodontic technology under standardized conditions, the same items were submitted to three AI systems (ChatGPT, Gemini, and DeepSeek), and analysis using ANOVA, Cronbach Alpha, and Tukey HSD showed that DeepSeek achieved perfect scores on high-difficulty questions while ChatGPT showed adaptive improvement across attempts, both significantly outperforming the student cohort, whereas Gemini demonstrated lower and consistent accuracy, with significant differences between models (P=0.036, eta-squared=0.891), leading the authors to argue that unsupervised online summative examinations require critical reevaluation of assessment integrity.

In this cross-sectional comparative study, 49 second-year dental students completed a 45-item multiple-choice final examination in prosthodontic technology under standardized conditions, the same items were submitted to three AI systems (ChatGPT, Gemini, and DeepSeek), and analysis using ANOVA, Cronbach Alpha, and Tukey HSD showed that DeepSeek achieved perfect scores on high-difficulty questions while ChatGPT showed adaptive improvement across attempts, both significantly outperforming the student cohort, whereas Gemini demonstrated lower and consistent accuracy, with significant differences between models (P=0.036, eta-squared=0.891), leading the authors to argue that unsupervised online summative examinations require critical reevaluation of assessment integrity.