Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Awareness, usage, and perspectives on ChatGPT in dental education among graduate and undergraduate students
0
Zitationen
10
Autoren
2025
Jahr
Abstract
To assess the knowledge, attitudes, and practices (KAP) related to ChatGPT among undergraduate students and graduates in Karachi, Pakistan, and to analyze an association with sociodemographic factors. A cross-sectional study was conducted over three months using a self-administered, structured questionnaire distributed via online platforms (WhatsApp, and emails). The questionnaire included four sections: demographics, knowledge, attitude, and practice related to ChatGPT. A non-probability convenience sampling technique was employed. Data were analyzed using SPSS version 26. Descriptive statistics summarized participant characteristics. Multiple linear regression was used to identify associations between KAP outcomes and sociodemographic variables. A p-value ≤ 0.05 was considered statistically significant. A total of 347 participants responded, of whom 74.6% were female and 76.4% reported awareness of ChatGPT. Age, designation, and years of experience were significantly associated with knowledge (p = 0.012, 0.001, and 0.001, respectively). Attitude was significantly influenced by age and gender (p = 0.03 and 0.04, respectively), while only gender showed a significant association with perception (p = 0.021). Most respondents considered ChatGPT moderately accurate (54.8%) and acknowledged its usefulness in education and research. Ethical concerns and uncertainty about ChatGPT replacing human roles were also noted. The majority of dental students and professionals in Karachi are aware of ChatGPT and hold a cautiously optimistic view of its role in dental education. While attitudes are generally positive, concerns remain regarding ethical implications and clinical applicability. Structured AI training and clear implementation guidelines are needed to support its effective integration in dental practice.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.422 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.300 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.734 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.781 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.519 Zit.