Artificial Intelligence-Supported Performance-Based Assessment in Oral Radiology Education: A Constructive Alignment Perspective.
Authors
Affiliations (5)
Affiliations (5)
- Department of Oral and Maxillofacial Radiology, Faculty of Dentistry, Lokman Hekim University, Ankara 06510, Turkey.
- Department of Medical Education and Informatics, Başkent University, Ankara 06490, Turkey.
- Department of Medical Education and Informatics, Gazi University, Ankara 06500, Turkey.
- Department of Medical Education and Informatics, Ankara Medipol University, Ankara 06050, Turkey.
- Department of Oral and Maxillofacial Radiology, Faculty of Dentistry, Ankara University, Ankara 06500, Turkey.
Abstract
<b>Background/Objectives:</b> This study aimed to examine the educational implications of an AI-supported performance-based assessment platform in oral radiology education within a constructively aligned framework. <b>Methods:</b> A total of 266 fourth-year dental students evaluated five panoramic radiographs using an AI-supported lesion detection platform with a predefined detection confidence threshold of 40%. Student performance was assessed using a confusion matrix framework, and precision and sensitivity values were calculated. Receiver operating characteristic (ROC) analysis was conducted to explore the relationship between region selection frequency and AI-supported diagnostic performance. Group comparisons were performed using the Mann-Whitney U test. <b>Results:</b> ROC analysis demonstrated a statistically significant but weak inverse association between region selection frequency and AI-supported diagnostic performance (AUC = 0.414, 95% CI: 0.342-0.486, <i>p</i> = 0.018). Students exceeding the cutoff of 8.5 marked regions demonstrated significantly lower performance scores than those at or below the cutoff (<i>p</i> < 0.001). No significant correlation was observed between AI-supported performance scores and traditional summative examination outcomes. <b>Conclusions:</b> AI-supported performance-based assessment demonstrated value in measuring applied diagnostic reasoning distinct from traditional written examinations. Within a constructively aligned framework, such tools may serve as complementary strategies for competency-oriented assessment in dental education.