ChatGPT 3.5, ChatGPT 4.0 ve Hemşirelik Öğrencilerinin Çocuk Acillerde Hemşirelik Yaklaşımı Dersi Sınavındaki Performans Karşılaştırmaları
Öz
Amaç: Bu çalışmanın amacı, ChatGPT modelleri ve öğrenci hemşirelerin çocuk acillerde hemşirelik yaklaşımı dersindeki başarı performanslarını karşılaştırmaktır.
Gereç ve Yöntem: Bu çalışma retrospektif ve karşılaştırmalı bir analiz olarak tasarlanmıştır. Çalışma bir devlet üniversitesinin hemşirelik bölümünde çocuk acillerde hemşirelik yaklaşımı dersinin yarıyıl sonu sınav soruları kullanılarak yapılmıştır. Sınavda yer alan beş seçenekli çoktan seçmeli 40 soru, ChatGPT 3.5 ve ChatGPT 4.0 modellerine yöneltilerek yanıtlanmıştır. Sorulara verilen cevaplar yapay zeka robotlarının verdikleri cevaplarla ve dersi alan öğrenci hemşirelerin verdikleri cevapların ortalamalarıyla karşılaştırılmıştır.
Bulgular: ChatGPT 4.0 sorular %90 oranında doğru yanıt verirken, öğrenciler %82.32 oranında doğru yanıt vermiştir. En düşük doğru yanıt oranı %55 ile ChatGPT 3.5 modelindedir. Bu sınavda en yüksek başarıyı sırasıyla ChatGPT 4.0, öğrenciler ve ChatGPT 3.5 elde etmiştir (p <0.05).
Sonuç: ChatGPT 4.0, çocuk acillerde hemşirelik yaklaşımı konusunda sağladığı doğru önerilerle iyi bir performans sergilemiştir. Yapay zeka temelli sistemler hemşirelik eğitiminde dersin öğretim elemanına ve öğrencilerine yardımcı bir referans aracı olarak kullanılabilir. Bu teknolojilerin hemşirelik eğitiminde nasıl daha etkin kullanılabileceğine yönelik stratejiler geliştirmek ve çalışmalar yapmak önemlidir.
Anahtar Kelimeler
Büyük dil modelleri ChatGPT Çocuk acil hemşireliği Yapay zeka.
Etik Beyan
Bu çalışmanın yürütülmesi için Bursa Uludağ Üniversitesi Sağlık Bilimleri Araştırma ve Yayın Etik Kurulu'ndan onay (24.01.2024 tarih ve 2024-01 sayılı) ve çalışmanın yapıldığı Bursa Uludağ Üniversitesi Sağlık Bilimleri Fakültesi’nden kurum izni alınmıştır.
Destekleyen Kurum
Bu çalışma kapsamında finansal bir destek alınmamıştır.
Kaynakça
- Alkhaqani, A. L. (2023). ChatGPT and academic integrity in nursing and health sciences education. Journal of Medical Research and Reviews, 1(1), 5-8. doi: 10.5455/JMRR.20230624044947
- Asker, Ö. F., Özgür, E. G., Eriç, A., Bekiroğlu, N. (2023). Comparing the performance of medical students, chatgpt-3.5 and chatgpt-4 in biostatistics exam: pros and cons as an education assistant: a cross-sectional research. International Journal of Management Information Systems and Computer Science, 7(2), 85-94. doi: 10.33461/uybisbbd.1329650
- Aydın, A. İ., Özyazıcıoğlu, N. (2023). Assessment of postoperative pain in children with computer assisted facial expression analysis. Journal of Pediatric Nursing, 71, 60–65. doi:10.1016/j.pedn.2023.03.008
- Barata, I. A., Stadnyck, J. M., Akerman, M., OʼNeill, K., Castaneda, J., Subramony, A., … DʼAngelo, J. (2020). Novel approach to emergency departments' pediatric readiness across a health system. Pediatric Emergency Care, 36(6), 274–276. doi:10.1097/PEC.0000000000001385.
- Chow, J. C. L., Sanders, L., Li, K. (2023). Impact of ChatGPT on medical chatbots as a disruptive technology. Frontiers in Artificial Intelligence, 6, 1166014. doi: 10.3389/frai.2023.1166014
- Conlon, C., McDonnell, T., Barrett, M., Cummins, F., Deasy, C., Hensey, C., …Nicholson, E. (2021). The impact of the COVID-19 pandemic on child health and the provision of Care in Paediatric Emergency Departments: a qualitative study of frontline emergency care staff. BMC Health Services Research, 21(1), 279. doi:10.1186/s12913-021-06284-9
- Handa, P., Chhabra, D., Goel, N., Krishnan, S. (2023). Exploring the role of ChatGPT in medical image analysis. Biomedical Signal Processing and Control, 86, 105292. doi: 10.1016/j.bspc.2023.105292
- Hockenberry, M. J., Wilson, D., Rodgers, C. C. (2021). Wong's essentials of pediatric nursing-e-book. Elsevier Health Sciences.
- Huang, H., Zheng, O., Wang, D., Yin, J., Wang, Z., Ding, S., …Shi, B. (2023b). ChatGPT for shaping the future of dentistry: the potential of multi-modal large language model. International Journal of Oral Science, 15(1), 29. doi: 10.1038/s41368-023-00239-y
- Huang, Y., Gomaa, A., Semrau, S., Haderlein, M., Lettmaier, S., Weissmann, T., …Putz, F. (2023a). Benchmarking ChatGPT-4 on a radiation oncology in-training exam and Red Journal Gray Zone cases: potentials and challenges for ai-assisted medical education and decision making in radiation oncology. Frontiers in Oncology, 13, 1265024. doi: 10.3389/fonc.2023.1265024
- Huang, H. (2023). Performance of ChatGPT on registered nurse license exam in Taiwan: A descriptive study. Healthcare, 11(21), 2855. doi: 10.3390/healthcare11212855
- Lewandowski, M., Łukowicz, P., Świetlik, D., Barańska-Rybak, W. (2023). An original study of ChatGPT-3.5 and ChatGPT-4 dermatological knowledge level based on the dermatology specialty certificate examinations. Clinical and Experimental Dermatology, llad255. doi: 10.1093/ced/llad255
- Moore, B., Shah, M. I., Owusu-Ansah, S., Gross, T., Brown, K., Gausche-Hill, M., ...American Academy of Pediatrics Committee on Pediatric Emergency Medicine. (2020). Pediatric readiness in emergency medical services systems. Pediatrics, 145(1). doi: 10.1542/peds.2019-3307
- Ni, Z., Peng, R., Zheng, X., Xie, P. (2024). Embracing the future: Integrating ChatGPT into China’s nursing education system. International Journal of Nursing Sciences, 11(2), 295-299. doi: 10.1016/j.ijnss.2024.03.006
- OpenAI. (2023). ChatGPT. Erişim adresi (01.04.2024): https://openai.com/chatgpt
- Sahyoun, C., Cantais, A., Gervaix, A., Bressan, S., Löllgen, R., Krauss, B., …Pediatric Emergency Medicine Comfort and Analgesia Research in Europe (PemCARE) group of the Research in European Pediatric Emergency Medicine (2021). Pediatric procedural sedation and analgesia in the emergency department: surveying the current European practice. European Journal of Pediatrics, 180(6), 1799–1813. doi: 10.1007/s00431-021-03930-6
- Sanchez-Ramos, L., Lin, L., Romero, R. (2023). Beware of references when using ChatGPT as a source of information to write scientific articles. American Journal of Obstetrics and Gynecology, 229(3), 356–357. doi: 10.1016/j.ajog.2023.04.004
- Su, M. C., Lin, L. E., Lin, L. H., Chen, Y. C. (2024). Assessing question characteristic influences on ChatGPT's performance and response-explanation consistency: Insights from Taiwan's nursing licensing exam. International Journal of Nursing Studies, 153, 104717. Advance online publication. doi: 10.1016/j.ijnurstu.2024.104717
- Taira, K., Itaya, T., Hanada, A. (2023). Performance of the large language model ChatGPT on the national nurse examinations in Japan: Evaluation Study. JMIR Nursing, 6, e47305. doi: 10.2196/47305
- Talan, T., Kalınkara, Y. (2023). The role of artificial intelligence in higher education: ChatGPT assessment for anatomy course. International Journal of Management Information Systems and Computer Science, 7(1), 33-40. https://doi.org/10.33461/uybisbbd.1244777
- von Gerich, H., Moen, H., Block, L. J., Chu, C. H., DeForest, H., Hobensack, M., …Peltonen, L. M. (2022). Artificial Intelligence -based technologies in nursing: A scoping literature review of the evidence. International Journal of Nursing Studies, 127, 104153. doi: 10.1016/j.ijnurstu.2021.104153
- Walker, D. M., Tolentino, V. R. (2020). COVID-19: The impact on pediatric emergency care. Pediatric Emergency Medicine Practice, 17(Suppl 6-1), 1–27.
- Watari, T., Takagi, S., Sakaguchi, K., Nishizaki, Y., Shimizu, T., Yamamoto, Y., …Tokuda, Y. (2023). Performance comparison of Chatgpt-4 and Japanese medical residents in the general medicine in-training examination: Comparison Study. JMIR Medical Education, 9, e52202. doi: 10.2196/52202
Comparison of CHATGPT 3.5, CHATGPT 4.0 And Nursing Students' Performance in the Nursing Approach in Child Emergencies Course Examinatıon
Öz
Aim: The aim of this study was to compare the success performances of ChatGPT models and student nurses in the course of nursing approach in pediatric emergencies.
Materials and Method: This study was designed as a retrospective and comparative analysis. The study was conducted by using the end-of-semester exam questions of the nursing approach in pediatric emergencies course in the nursing department of a state university. In the exam, 40 multiple-choice questions with five options were directed to ChatGPT 3.5 and ChatGPT 4.0 models. The answers given to the questions were compared with the answers given by the artificial intelligence robots and the averages of the answers given by the student nurses taking the course.
Results: ChatGPT 4.0 gave 90% correct answers to the questions, while the students gave 82.32% correct answers. The lowest correct response rate was 55% for ChatGPT 3.5. In this exam, ChatGPT 4.0, students and ChatGPT 3.5 achieved the highest success respectively (p < 0.05).
Conclusion: ChatGPT 4.0 performed well with the correct suggestions it provided on nursing approach in pediatric emergencies. Artificial intelligence-based systems can be used in nursing education as a reference tool to assist the instructor and students of the course. It is important to develop strategies and conduct studies on how these technologies can be used more effectively in nursing education.
Anahtar Kelimeler
Large language models ChatGPT Pediatric emergency nursing Artificial intelligence
Kaynakça
- Alkhaqani, A. L. (2023). ChatGPT and academic integrity in nursing and health sciences education. Journal of Medical Research and Reviews, 1(1), 5-8. doi: 10.5455/JMRR.20230624044947
- Asker, Ö. F., Özgür, E. G., Eriç, A., Bekiroğlu, N. (2023). Comparing the performance of medical students, chatgpt-3.5 and chatgpt-4 in biostatistics exam: pros and cons as an education assistant: a cross-sectional research. International Journal of Management Information Systems and Computer Science, 7(2), 85-94. doi: 10.33461/uybisbbd.1329650
- Aydın, A. İ., Özyazıcıoğlu, N. (2023). Assessment of postoperative pain in children with computer assisted facial expression analysis. Journal of Pediatric Nursing, 71, 60–65. doi:10.1016/j.pedn.2023.03.008
- Barata, I. A., Stadnyck, J. M., Akerman, M., OʼNeill, K., Castaneda, J., Subramony, A., … DʼAngelo, J. (2020). Novel approach to emergency departments' pediatric readiness across a health system. Pediatric Emergency Care, 36(6), 274–276. doi:10.1097/PEC.0000000000001385.
- Chow, J. C. L., Sanders, L., Li, K. (2023). Impact of ChatGPT on medical chatbots as a disruptive technology. Frontiers in Artificial Intelligence, 6, 1166014. doi: 10.3389/frai.2023.1166014
- Conlon, C., McDonnell, T., Barrett, M., Cummins, F., Deasy, C., Hensey, C., …Nicholson, E. (2021). The impact of the COVID-19 pandemic on child health and the provision of Care in Paediatric Emergency Departments: a qualitative study of frontline emergency care staff. BMC Health Services Research, 21(1), 279. doi:10.1186/s12913-021-06284-9
- Handa, P., Chhabra, D., Goel, N., Krishnan, S. (2023). Exploring the role of ChatGPT in medical image analysis. Biomedical Signal Processing and Control, 86, 105292. doi: 10.1016/j.bspc.2023.105292
- Hockenberry, M. J., Wilson, D., Rodgers, C. C. (2021). Wong's essentials of pediatric nursing-e-book. Elsevier Health Sciences.
- Huang, H., Zheng, O., Wang, D., Yin, J., Wang, Z., Ding, S., …Shi, B. (2023b). ChatGPT for shaping the future of dentistry: the potential of multi-modal large language model. International Journal of Oral Science, 15(1), 29. doi: 10.1038/s41368-023-00239-y
- Huang, Y., Gomaa, A., Semrau, S., Haderlein, M., Lettmaier, S., Weissmann, T., …Putz, F. (2023a). Benchmarking ChatGPT-4 on a radiation oncology in-training exam and Red Journal Gray Zone cases: potentials and challenges for ai-assisted medical education and decision making in radiation oncology. Frontiers in Oncology, 13, 1265024. doi: 10.3389/fonc.2023.1265024
- Huang, H. (2023). Performance of ChatGPT on registered nurse license exam in Taiwan: A descriptive study. Healthcare, 11(21), 2855. doi: 10.3390/healthcare11212855
- Lewandowski, M., Łukowicz, P., Świetlik, D., Barańska-Rybak, W. (2023). An original study of ChatGPT-3.5 and ChatGPT-4 dermatological knowledge level based on the dermatology specialty certificate examinations. Clinical and Experimental Dermatology, llad255. doi: 10.1093/ced/llad255
- Moore, B., Shah, M. I., Owusu-Ansah, S., Gross, T., Brown, K., Gausche-Hill, M., ...American Academy of Pediatrics Committee on Pediatric Emergency Medicine. (2020). Pediatric readiness in emergency medical services systems. Pediatrics, 145(1). doi: 10.1542/peds.2019-3307
- Ni, Z., Peng, R., Zheng, X., Xie, P. (2024). Embracing the future: Integrating ChatGPT into China’s nursing education system. International Journal of Nursing Sciences, 11(2), 295-299. doi: 10.1016/j.ijnss.2024.03.006
- OpenAI. (2023). ChatGPT. Erişim adresi (01.04.2024): https://openai.com/chatgpt
- Sahyoun, C., Cantais, A., Gervaix, A., Bressan, S., Löllgen, R., Krauss, B., …Pediatric Emergency Medicine Comfort and Analgesia Research in Europe (PemCARE) group of the Research in European Pediatric Emergency Medicine (2021). Pediatric procedural sedation and analgesia in the emergency department: surveying the current European practice. European Journal of Pediatrics, 180(6), 1799–1813. doi: 10.1007/s00431-021-03930-6
- Sanchez-Ramos, L., Lin, L., Romero, R. (2023). Beware of references when using ChatGPT as a source of information to write scientific articles. American Journal of Obstetrics and Gynecology, 229(3), 356–357. doi: 10.1016/j.ajog.2023.04.004
- Su, M. C., Lin, L. E., Lin, L. H., Chen, Y. C. (2024). Assessing question characteristic influences on ChatGPT's performance and response-explanation consistency: Insights from Taiwan's nursing licensing exam. International Journal of Nursing Studies, 153, 104717. Advance online publication. doi: 10.1016/j.ijnurstu.2024.104717
- Taira, K., Itaya, T., Hanada, A. (2023). Performance of the large language model ChatGPT on the national nurse examinations in Japan: Evaluation Study. JMIR Nursing, 6, e47305. doi: 10.2196/47305
- Talan, T., Kalınkara, Y. (2023). The role of artificial intelligence in higher education: ChatGPT assessment for anatomy course. International Journal of Management Information Systems and Computer Science, 7(1), 33-40. https://doi.org/10.33461/uybisbbd.1244777
- von Gerich, H., Moen, H., Block, L. J., Chu, C. H., DeForest, H., Hobensack, M., …Peltonen, L. M. (2022). Artificial Intelligence -based technologies in nursing: A scoping literature review of the evidence. International Journal of Nursing Studies, 127, 104153. doi: 10.1016/j.ijnurstu.2021.104153
- Walker, D. M., Tolentino, V. R. (2020). COVID-19: The impact on pediatric emergency care. Pediatric Emergency Medicine Practice, 17(Suppl 6-1), 1–27.
- Watari, T., Takagi, S., Sakaguchi, K., Nishizaki, Y., Shimizu, T., Yamamoto, Y., …Tokuda, Y. (2023). Performance comparison of Chatgpt-4 and Japanese medical residents in the general medicine in-training examination: Comparison Study. JMIR Medical Education, 9, e52202. doi: 10.2196/52202
Ayrıntılar
| Birincil Dil | Türkçe |
|---|---|
| Konular | Çocuk Sağlığı ve Hastalıkları Hemşireliği |
| Bölüm | ARAŞTIRMA MAKALELERİ |
| Yazarlar | |
| Erken Görünüm Tarihi | 22 Nisan 2025 |
| Yayımlanma Tarihi | 21 Nisan 2025 |
| Gönderilme Tarihi | 22 Nisan 2024 |
| Kabul Tarihi | 8 Şubat 2025 |
| Yayımlandığı Sayı | Yıl 2025 Cilt: 7 Sayı: 1 |
Kaynak Göster
Bandırma Onyedi Eylül Üniversitesi Sağlık Bilimleri ve Araştırmaları Dergisi Creative Commons Atıf-GayriTicari 4.0 Uluslararası Lisansı ile lisanslanmıştır.