Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Assessing the impact of ChatGPT on enhancing learning in preclinical and clinical dental education
0
Zitationen
6
Autoren
2025
Jahr
Abstract
BACKGROUND & OBJECTIVE: Artificial intelligence (AI) is transforming not only education but also healthcare. ChatGPT, offers new opportunities for interactive learning. This study assessed its benefits, challenges, and applications in pre-clinical and clinical dental education. METHODOLOGY: A cross-sectional, questionnaire-based survey was conducted among 300 undergraduate dental students (preclinical and clinical) in Lahore. A validated self-administered questionnaire assessed knowledge, perceptions, and practices. Data were analyzed using SPSS v25.0; chi-square test was applied with significance set at p ≤ 0.05. RESULTS: Awareness of ChatGPT was high (96%). Active use as a learning tool was reported by 86%, with higher use among clinical students (95%) compared to preclinical students (76%) (p<0.001). While 94% expressed interest in integrating ChatGPT into future education, challenges included lack of formal training (49%), difficulties in usage (97%), and skepticism about its relevance to clinical dentistry (46%). Although 89% recognized its role in providing current literature, 72% reported unreliable or inadequate information regarding clinical dentistry. CONCLUSION: ChatGPT is widely adopted as a learning adjunct among dental students, particularly in clinical years. Despite its potential to enhance communication and evidence-based learning, concerns regarding accuracy, reliability, and ethical integration remain. Careful incorporation into curricula is necessary to maximize benefits while addressing limitations.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.316 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.177 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.575 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.776 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.468 Zit.