To Evaluate the Efficiency of ChatGPT in Medical Education: An Analysis of MCQ-Based Learning and Assessment

被引:0
作者
Husain, Syed Shirjeel [1 ,2 ]
Ansari, Zaid [1 ,2 ]
Hussain, Azhar [1 ,2 ]
Abbasi, Sahar Zubair [3 ]
Ayoob, Tahera [4 ,5 ]
Mujahid, Rimsha [1 ,2 ]
机构
[1] Liaquat Coll Med & Dent, Dept Internal Med, Karachi, Pakistan
[2] Darul Sehat Hosp, Karachi, Pakistan
[3] Coll Phys & Surg Pakistan, Directorate Med Educ, Karachi, Pakistan
[4] Liaquat Coll Med & Dent, Dept Oral Surg, Karachi, Pakistan
[5] Qamar Dent Hosp, Karachi, Pakistan
来源
ANNALS ABBASI SHAHEED HOSPITAL & KARACHI MEDICAL & DENTAL COLLEGE | 2023年 / 28卷 / 04期
关键词
Artificial intelligence; educational assessment; Medical education;
D O I
暂无
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Objective: This study aimed to evaluate the potential of ChatGPT to help students for their assessments via MCQ at different level of cognition by using different subjects of Internal medicine. Methods: This cross-sectional study was conducted in the Department of Internal Medicine in collaboration with post graduate medical education department from June 2023 to August 2023. An MCQ bank was established from three books of MCQ's on subject of Internal Medicine. Total 1428 MCQ's were followed for scrutiny and 307 MCQ's were selected for the assigned task. The selected MCQ's were manually entered one by one in a fresh Chat GPT session. The response was noted against the replies given in respective MCQ's book and marked as correct, not correct or partially correct. MCQ's were categorized as per chapters in Internal medicine and as per cognition level of MCQ's i.e. C1, C2 and C3. Data was analyzed on SPSS version 21.00. Results: Chat GPT replied with 199 correct replies while 98 were wrong and 10 were partially correct. Chat GPT scored 64% overall in all categories. At level of cognition, it solved C2 MCQ's by 80 % but scored 69% and 54% in C1 and C3 categories respectively. Chat GPT replied with 80% accuracy for C2 level MCQ's while results were low for C3 category at around 54%. C1 also had low percentage of correct answers standing close to 69.8%. Almost all subjects showed healthy responses around the mean except for endocrinology and hematology where responses are below 60% and 40% respectively. Conclusion: This study findings suggest that ChatGPT is a useful tool for students and medical educationist with its current framework but a subtle approach should be inclined towards its role in future.
引用
收藏
页码:194 / 200
页数:7
相关论文
共 22 条
[1]   Artificial Intelligence and technology in COVID Era: A narrative review [J].
Ahuja, Vanita ;
Nair, Lekshmi, V .
JOURNAL OF ANAESTHESIOLOGY CLINICAL PHARMACOLOGY, 2021, 37 (01) :28-34
[2]   Evaluating the effectiveness of 'MCQ development workshop using cognitive model framework: A pre-post study [J].
Ali, Rahila ;
Sultan, Amber Shamim ;
Zahid, Nida .
JOURNAL OF THE PAKISTAN MEDICAL ASSOCIATION, 2021, 71 (01) :119-121
[3]   Role of Chat GPT in Public Health [J].
Biswas, Som S. .
ANNALS OF BIOMEDICAL ENGINEERING, 2023, 51 (05) :868-869
[4]   ChatGPT versus human in generating medical graduate exam multiple choice questions-A multinational prospective study (Hong Kong SAR, Singapore, Ireland, and the United Kingdom) [J].
Cheung, Billy Ho Hung ;
Lau, Gary Kui Kai ;
Wong, Gordon Tin Chun ;
Lee, Elaine Yuen Phin ;
Kulkarni, Dhananjay ;
Seow, Choon Sheong ;
Wong, Ruby ;
Co, Michael Tiong-Hong .
PLOS ONE, 2023, 18 (08)
[5]   The Role of ChatGPT, Generative Language Models, and Artificial Intelligence in Medical Education: A Conversation With ChatGPT and a Call for Papers [J].
Eysenbach, Gunther .
JMIR MEDICAL EDUCATION, 2023, 9
[6]   How Does ChatGPT Perform on the United States Medical Licensing Examination (USMLE)? The Implications of Large Language Models for Medical Education and Knowledge Assessment [J].
Gilson, Aidan ;
Safranek, Conrad W. ;
Huang, Thomas ;
Socrates, Vimig ;
Chi, Ling ;
Taylor, Richard Andrew ;
Chartash, David .
JMIR MEDICAL EDUCATION, 2023, 9
[7]   Medical students create multiple-choice questions for learning in pathology education: a pilot study [J].
Grainger, Rebecca ;
Dai, Wei ;
Osborne, Emma ;
Kenwright, Diane .
BMC MEDICAL EDUCATION, 2018, 18
[8]  
Javaid M, 2023, BenchCouncil Trans Benchmarks Stand Eval., V1
[9]  
Kenwright D, 2017, TAPS, P1
[10]   ChatGPT- Reshaping medical education and clinical management [J].
Khan, Rehan Ahmed ;
Jawaid, Masood ;
Khan, Aymen Rehan ;
Sajjad, Madiha .
PAKISTAN JOURNAL OF MEDICAL SCIENCES, 2023, 39 (02) :605-607