Pudjiadi, Antonius Hocky and Alatas, Fatima Safira and Faizi, Muhammad and Rusdi, Rusdi and Sulistijono, Eko and Nency, Yetty Movieta and Julia, Madarina and Juliaty, Aidah and Hartoyo, Edi and Susanah, Susi and Wilar, Rocky and Nugroho, Hari Wahyu and Indrayady, Indrayady and Lubis, Bugis Mardina and Haris, Syafruddin and Suparyatha I.B.G., Ida Bagus Gede and Amarassaphira D., Daniar and Monica E., Ervin and Ongko L., Lukito (2024) Integration of Artificial Intelligence in Pediatric Education: Perspectives from Pediatric Medical Educators and Residents. Healthcare Informatics Research, 30 (3). 244 - 252. ISSN 2093-369X
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Abstract
Objectives: The use of technology has rapidly increased in the past century. Artificial intelligence (AI) and information technology (IT) are now applied in healthcare and medical education. The purpose of this study was to assess the readiness of Indonesian teaching staff and pediatric residents for AI integration into the curriculum. Methods: An anonymous online survey was distributed among teaching staff and pediatric residents from 15 national universities. The questionnaire consisted of two sections: demographic information and questions regarding the use of IT and AI in child health education. Responses were collected using a 5-point Likert scale: strongly disagree, disagree, neutral, agree, and highly agree. Results: A total of 728 pediatric residents and 196 teaching staff from 15 national universities participated in the survey. Over half of the respondents were familiar with the terms IT and AI. The majority agreed that IT and AI have simplified the process of learning theories and skills. All participants were in favor of sharing data to facilitate the development of AI and expressed readiness to incorporate IT and AI into their teaching tools. Conclusions: The findings of our study indicate that pediatric residents and teaching staff are ready to implement AI in medical education.
| Item Type: | Article |
|---|---|
| Additional Information: | Cited by: 1; All Open Access; Gold Open Access; Green Final Open Access; Green Open Access |
| Uncontrolled Keywords: | adult; article; artificial intelligence; child; curriculum; digital technology; disease management; health care personnel; health education; human; Indonesian; information technology; integration; learning theory; Likert scale; medical education; medical informatics; medical information system; pediatrics; questionnaire; resident; teaching |
| Subjects: | R Medicine > RJ Pediatrics > RJ101 Child Health. Child health services |
| Divisions: | Faculty of Medicine, Public Health and Nursing > Non Surgical Divisions |
| Depositing User: | Ani PURWANDARI |
| Date Deposited: | 05 Aug 2025 01:45 |
| Last Modified: | 05 Aug 2025 01:45 |
| URI: | https://ir.lib.ugm.ac.id/id/eprint/19858 |
