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Impact of a change from A–F grading to honors/pass/fail grading on academic performance at Yonsei University College of Medicine in Korea: a cross-sectional serial mediation analysis  
Min-Kyeong Kim, Hae Won Kim
J Educ Eval Health Prof. 2024;21:20.   Published online August 16, 2024
DOI: https://doi.org/10.3352/jeehp.2024.21.20
  • 148 View
  • 123 Download
AbstractAbstract PDFSupplementary Material
Purpose
This study aimed to explore how the grading system affected medical students’ academic performance based on their perceptions of the learning environment and intrinsic motivation in the context of changing from norm-referenced A–F grading to criterion-referenced honors/pass/fail grading.
Methods
The study involved 238 second-year medical students from 2014 (n=127, A–F grading) and 2015 (n=111, honors/pass/fail grading) at Yonsei University College of Medicine in Korea. Scores on the Dundee Ready Education Environment Measure, the Academic Motivation Scale, and the Basic Medical Science Examination were used to measure overall learning environment perceptions, intrinsic motivation, and academic performance, respectively. Serial mediation analysis was conducted to examine the pathways between the grading system and academic performance, focusing on the mediating roles of student perceptions and intrinsic motivation.
Results
The honors/pass/fail grading class students reported more positive perceptions of the learning environment, higher intrinsic motivation, and better academic performance than the A–F grading class students. Mediation analysis demonstrated a serial mediation effect between the grading system and academic performance through learning environment perceptions and intrinsic motivation. Student perceptions and intrinsic motivation did not independently mediate the relationship between the grading system and performance.
Conclusion
Reducing the number of grades and eliminating rank-based grading might have created an affirming learning environment that fulfills basic psychological needs and reinforces the intrinsic motivation linked to academic performance. The cumulative effect of these 2 mediators suggests that a comprehensive approach should be used to understand student performance.
Comparison of real data and simulated data analysis of a stopping rule based on the standard error of measurement in computerized adaptive testing for medical examinations in Korea: a psychometric study  
Dong Gi Seo, Jeongwook Choi, Jinha Kim
J Educ Eval Health Prof. 2024;21:18.   Published online July 9, 2024
DOI: https://doi.org/10.3352/jeehp.2024.21.18
  • 445 View
  • 218 Download
AbstractAbstract PDFSupplementary Material
Purpose
This study aimed to compare and evaluate the efficiency and accuracy of computerized adaptive testing (CAT) under 2 stopping rules (standard error of measurement [SEM]=0.3 and 0.25) using both real and simulated data in medical examinations in Korea.
Methods
This study employed post-hoc simulation and real data analysis to explore the optimal stopping rule for CAT in medical examinations. The real data were obtained from the responses of 3rd-year medical students during examinations in 2020 at Hallym University College of Medicine. Simulated data were generated using estimated parameters from a real item bank in R. Outcome variables included the number of examinees’ passing or failing with SEM values of 0.25 and 0.30, the number of items administered, and the correlation. The consistency of real CAT result was evaluated by examining consistency of pass or fail based on a cut score of 0.0. The efficiency of all CAT designs was assessed by comparing the average number of items administered under both stopping rules.
Results
Both SEM 0.25 and SEM 0.30 provided a good balance between accuracy and efficiency in CAT. The real data showed minimal differences in pass/fail outcomes between the 2 SEM conditions, with a high correlation (r=0.99) between ability estimates. The simulation results confirmed these findings, indicating similar average item numbers between real and simulated data.
Conclusion
The findings suggest that both SEM 0.25 and 0.30 are effective termination criteria in the context of the Rasch model, balancing accuracy and efficiency in CAT.
Development of examination objectives for the Korean paramedic and emergency medical technician examination: a survey study  
Tai-hwan Uhm, Heakyung Choi, Seok Hwan Hong, Hyungsub Kim, Minju Kang, Keunyoung Kim, Hyejin Seo, Eunyoung Ki, Hyeryeong Lee, Heejeong Ahn, Uk-jin Choi, Sang Woong Park
J Educ Eval Health Prof. 2024;21:13.   Published online June 12, 2024
DOI: https://doi.org/10.3352/jeehp.2024.21.13
  • 639 View
  • 181 Download
AbstractAbstract PDFSupplementary Material
Purpose
The duties of paramedics and emergency medical technicians (P&EMTs) are continuously changing due to developments in medical systems. This study presents evaluation goals for P&EMTs by analyzing their work, especially the tasks that new P&EMTs (with less than 3 years’ experience) find difficult, to foster the training of P&EMTs who could adapt to emergency situations after graduation.
Methods
A questionnaire was created based on prior job analyses of P&EMTs. The survey questions were reviewed through focus group interviews, from which 253 task elements were derived. A survey was conducted from July 10, 2023 to October 13, 2023 on the frequency, importance, and difficulty of the 6 occupations in which P&EMTs were employed.
Results
The P&EMTs’ most common tasks involved obtaining patients’ medical histories and measuring vital signs, whereas the most important task was cardiopulmonary resuscitation (CPR). The task elements that the P&EMTs found most difficult were newborn delivery and infant CPR. New paramedics reported that treating patients with fractures, poisoning, and childhood fever was difficult, while new EMTs reported that they had difficulty keeping diaries, managing ambulances, and controlling infection.
Conclusion
Communication was the most important item for P&EMTs, whereas CPR was the most important skill. It is important for P&EMTs to have knowledge of all tasks; however, they also need to master frequently performed tasks and those that pose difficulties in the field. By deriving goals for evaluating P&EMTs, changes could be made to their education, thereby making it possible to train more capable P&EMTs.
Revised evaluation objectives of the Korean Dentist Clinical Skill Test: a survey study and focus group interviews  
Jae-Hoon Kim, Young J Kim, Deuk-Sang Ma, Se-Hee Park, Ahran Pae, June-Sung Shim, Il-Hyung Yang, Ui-Won Jung, Byung-Joon Choi, Yang-Hyun Chun
J Educ Eval Health Prof. 2024;21:11.   Published online May 30, 2024
DOI: https://doi.org/10.3352/jeehp.2024.21.11
  • 538 View
  • 196 Download
AbstractAbstract PDFSupplementary Material
Purpose
This study aimed to propose a revision of the evaluation objectives of the Korean Dentist Clinical Skill Test by analyzing the opinions of those involved in the examination after a review of those objectives.
Methods
The clinical skill test objectives were reviewed based on the national-level dental practitioner competencies, dental school educational competencies, and the third dental practitioner job analysis. Current and former examinees were surveyed about their perceptions of the evaluation objectives. The validity of 22 evaluation objectives and overlapping perceptions based on area of specialty were surveyed on a 5-point Likert scale by professors who participated in the clinical skill test and dental school faculty members. Additionally, focus group interviews were conducted with experts on the examination.
Results
It was necessary to consider including competency assessments for “emergency rescue skills” and “planning and performing prosthetic treatment.” There were no significant differences between current and former examinees in their perceptions of the clinical skill test’s objectives. The professors who participated in the examination and dental school faculty members recognized that most of the objectives were valid. However, some responses stated that “oromaxillofacial cranial nerve examination,” “temporomandibular disorder palpation test,” and “space management for primary and mixed dentition” were unfeasible evaluation objectives and overlapped with dental specialty areas.
Conclusion
When revising the Korean Dentist Clinical Skill Test’s objectives, it is advisable to consider incorporating competency assessments related to “emergency rescue skills” and “planning and performing prosthetic treatment.”
Importance, performance frequency, and predicted future importance of dietitians’ jobs by practicing dietitians in Korea: a survey study
Cheongmin Sohn, Sooyoun Kwon, Won Gyoung Kim, Kyung-Eun Lee, Sun-Young Lee, Seungmin Lee
J Educ Eval Health Prof. 2024;21:1.   Published online January 2, 2024
DOI: https://doi.org/10.3352/jeehp.2024.21.1
  • 1,436 View
  • 253 Download
AbstractAbstract PDFSupplementary Material
Purpose
This study aimed to explore the perceptions held by practicing dietitians of the importance of their tasks performed in current work environments, the frequency at which those tasks are performed, and predictions about the importance of those tasks in future work environments.
Methods
This was a cross-sectional survey study. An online survey was administered to 350 practicing dietitians. They were asked to assess the importance, performance frequency, and predicted changes in the importance of 27 tasks using a 5-point scale. Descriptive statistics were calculated, and the means of the variables were compared across categorized work environments using analysis of variance.
Results
The importance scores of all surveyed tasks were higher than 3.0, except for the marketing management task. Self-development, nutrition education/counseling, menu planning, food safety management, and documentation/data management were all rated higher than 4.0. The highest performance frequency score was related to documentation/data management. The importance scores of all duties, except for professional development, differed significantly by workplace. As for predictions about the future importance of the tasks surveyed, dietitians responded that the importance of all 27 tasks would either remain at current levels or increase in the future.
Conclusion
Twenty-seven tasks were confirmed to represent dietitians’ job functions in various workplaces. These tasks can be used to improve the test specifications of the Korean Dietitian Licensing Examination and the curriculum of dietetic education programs.
Information amount, accuracy, and relevance of generative artificial intelligence platforms’ answers regarding learning objectives of medical arthropodology evaluated in English and Korean queries in December 2023: a descriptive study
Hyunju Lee, Soobin Park
J Educ Eval Health Prof. 2023;20:39.   Published online December 28, 2023
DOI: https://doi.org/10.3352/jeehp.2023.20.39
  • 2,031 View
  • 185 Download
  • 3 Web of Science
  • 3 Crossref
AbstractAbstract PDFSupplementary Material
Purpose
This study assessed the performance of 6 generative artificial intelligence (AI) platforms on the learning objectives of medical arthropodology in a parasitology class in Korea. We examined the AI platforms’ performance by querying in Korean and English to determine their information amount, accuracy, and relevance in prompts in both languages.
Methods
From December 15 to 17, 2023, 6 generative AI platforms—Bard, Bing, Claude, Clova X, GPT-4, and Wrtn—were tested on 7 medical arthropodology learning objectives in English and Korean. Clova X and Wrtn are platforms from Korean companies. Responses were evaluated using specific criteria for the English and Korean queries.
Results
Bard had abundant information but was fourth in accuracy and relevance. GPT-4, with high information content, ranked first in accuracy and relevance. Clova X was 4th in amount but 2nd in accuracy and relevance. Bing provided less information, with moderate accuracy and relevance. Wrtn’s answers were short, with average accuracy and relevance. Claude AI had reasonable information, but lower accuracy and relevance. The responses in English were superior in all aspects. Clova X was notably optimized for Korean, leading in relevance.
Conclusion
In a study of 6 generative AI platforms applied to medical arthropodology, GPT-4 excelled overall, while Clova X, a Korea-based AI product, achieved 100% relevance in Korean queries, the highest among its peers. Utilizing these AI platforms in classrooms improved the authors’ self-efficacy and interest in the subject, offering a positive experience of interacting with generative AI platforms to question and receive information.

Citations

Citations to this article as recorded by  
  • Opportunities, challenges, and future directions of large language models, including ChatGPT in medical education: a systematic scoping review
    Xiaojun Xu, Yixiao Chen, Jing Miao
    Journal of Educational Evaluation for Health Professions.2024; 21: 6.     CrossRef
  • The emergence of generative artificial intelligence platforms in 2023, journal metrics, appreciation to reviewers and volunteers, and obituary
    Sun Huh
    Journal of Educational Evaluation for Health Professions.2024; 21: 9.     CrossRef
  • Comparison of the Performance of ChatGPT, Claude and Bard in Support of Myopia Prevention and Control
    Yan Wang, Lihua Liang, Ran Li, Yihua Wang, Changfu Hao
    Journal of Multidisciplinary Healthcare.2024; Volume 17: 3917.     CrossRef
Effect of a transcultural nursing course on improving the cultural competency of nursing graduate students in Korea: a before-and-after study  
Kyung Eui Bae, Geum Hee Jeong
J Educ Eval Health Prof. 2023;20:35.   Published online December 4, 2023
DOI: https://doi.org/10.3352/jeehp.2023.20.35
  • 1,676 View
  • 184 Download
AbstractAbstract PDFSupplementary Material
Purpose
This study aimed to evaluate the impact of a transcultural nursing course on enhancing the cultural competency of graduate nursing students in Korea. We hypothesized that participants’ cultural competency would significantly improve in areas such as communication, biocultural ecology and family, dietary habits, death rituals, spirituality, equity, and empowerment and intermediation after completing the course. Furthermore, we assessed the participants’ overall satisfaction with the course.
Methods
A before-and-after study was conducted with graduate nursing students at Hallym University, Chuncheon, Korea, from March to June 2023. A transcultural nursing course was developed based on Giger & Haddad’s transcultural nursing model and Purnell’s theoretical model of cultural competence. Data was collected using a cultural competence scale for registered nurses developed by Kim and his colleagues. A total of 18 students participated, and the paired t-test was employed to compare pre-and post-intervention scores.
Results
The study revealed significant improvements in all 7 categories of cultural nursing competence (P<0.01). Specifically, the mean differences in scores (pre–post) ranged from 0.74 to 1.09 across the categories. Additionally, participants expressed high satisfaction with the course, with an average score of 4.72 out of a maximum of 5.0.
Conclusion
The transcultural nursing course effectively enhanced the cultural competency of graduate nursing students. Such courses are imperative to ensure quality care for the increasing multicultural population in Korea.
Technical report
Item difficulty index, discrimination index, and reliability of the 26 health professions licensing examinations in 2022, Korea: a psychometric study
Yoon Hee Kim, Bo Hyun Kim, Joonki Kim, Bokyoung Jung, Sangyoung Bae
J Educ Eval Health Prof. 2023;20:31.   Published online November 22, 2023
DOI: https://doi.org/10.3352/jeehp.2023.20.31
  • 1,136 View
  • 90 Download
AbstractAbstract PDFSupplementary Material
Purpose
This study presents item analysis results of the 26 health personnel licensing examinations managed by the Korea Health Personnel Licensing Examination Institute (KHPLEI) in 2022.
Methods
The item difficulty index, item discrimination index, and reliability were calculated. The item discrimination index was calculated using a discrimination index based on the upper and lower 27% rule and the item-total correlation.
Results
Out of 468,352 total examinees, 418,887 (89.4%) passed. The pass rates ranged from 27.3% for health educators level 1 to 97.1% for oriental medical doctors. Most examinations had a high average difficulty index, albeit to varying degrees, ranging from 61.3% for prosthetists and orthotists to 83.9% for care workers. The average discrimination index based on the upper and lower 27% rule ranged from 0.17 for oriental medical doctors to 0.38 for radiological technologists. The average item-total correlation ranged from 0.20 for oriental medical doctors to 0.38 for radiological technologists. The Cronbach α, as a measure of reliability, ranged from 0.872 for health educators-level 3 to 0.978 for medical technologists. The correlation coefficient between the average difficulty index and average discrimination index was -0.2452 (P=0.1557), that between the average difficulty index and the average item-total correlation was 0.3502 (P=0.0392), and that between the average discrimination index and the average item-total correlation was 0.7944 (P<0.0001).
Conclusion
This technical report presents the item analysis results and reliability of the recent examinations by the KHPLEI, demonstrating an acceptable range of difficulty index and discrimination index values, as well as good reliability.
Research articles
Medical students’ patterns of using ChatGPT as a feedback tool and perceptions of ChatGPT in a Leadership and Communication course in Korea: a cross-sectional study  
Janghee Park
J Educ Eval Health Prof. 2023;20:29.   Published online November 10, 2023
DOI: https://doi.org/10.3352/jeehp.2023.20.29
  • 2,385 View
  • 194 Download
  • 5 Web of Science
  • 6 Crossref
AbstractAbstract PDFSupplementary Material
Purpose
This study aimed to analyze patterns of using ChatGPT before and after group activities and to explore medical students’ perceptions of ChatGPT as a feedback tool in the classroom.
Methods
The study included 99 2nd-year pre-medical students who participated in a “Leadership and Communication” course from March to June 2023. Students engaged in both individual and group activities related to negotiation strategies. ChatGPT was used to provide feedback on their solutions. A survey was administered to assess students’ perceptions of ChatGPT’s feedback, its use in the classroom, and the strengths and challenges of ChatGPT from May 17 to 19, 2023.
Results
The students responded by indicating that ChatGPT’s feedback was helpful, and revised and resubmitted their group answers in various ways after receiving feedback. The majority of respondents expressed agreement with the use of ChatGPT during class. The most common response concerning the appropriate context of using ChatGPT’s feedback was “after the first round of discussion, for revisions.” There was a significant difference in satisfaction with ChatGPT’s feedback, including correctness, usefulness, and ethics, depending on whether or not ChatGPT was used during class, but there was no significant difference according to gender or whether students had previous experience with ChatGPT. The strongest advantages were “providing answers to questions” and “summarizing information,” and the worst disadvantage was “producing information without supporting evidence.”
Conclusion
The students were aware of the advantages and disadvantages of ChatGPT, and they had a positive attitude toward using ChatGPT in the classroom.

Citations

Citations to this article as recorded by  
  • Opportunities, challenges, and future directions of large language models, including ChatGPT in medical education: a systematic scoping review
    Xiaojun Xu, Yixiao Chen, Jing Miao
    Journal of Educational Evaluation for Health Professions.2024; 21: 6.     CrossRef
  • Embracing ChatGPT for Medical Education: Exploring Its Impact on Doctors and Medical Students
    Yijun Wu, Yue Zheng, Baijie Feng, Yuqi Yang, Kai Kang, Ailin Zhao
    JMIR Medical Education.2024; 10: e52483.     CrossRef
  • Integration of ChatGPT Into a Course for Medical Students: Explorative Study on Teaching Scenarios, Students’ Perception, and Applications
    Anita V Thomae, Claudia M Witt, Jürgen Barth
    JMIR Medical Education.2024; 10: e50545.     CrossRef
  • A cross sectional investigation of ChatGPT-like large language models application among medical students in China
    Guixia Pan, Jing Ni
    BMC Medical Education.2024;[Epub]     CrossRef
  • ChatGPT and Clinical Training: Perception, Concerns, and Practice of Pharm-D Students
    Mohammed Zawiah, Fahmi Al-Ashwal, Lobna Gharaibeh, Rana Abu Farha, Karem Alzoubi, Khawla Abu Hammour, Qutaiba A Qasim, Fahd Abrah
    Journal of Multidisciplinary Healthcare.2023; Volume 16: 4099.     CrossRef
  • Information amount, accuracy, and relevance of generative artificial intelligence platforms’ answers regarding learning objectives of medical arthropodology evaluated in English and Korean queries in December 2023: a descriptive study
    Hyunju Lee, Soobin Park
    Journal of Educational Evaluation for Health Professions.2023; 20: 39.     CrossRef
Suggestion for item allocation to 8 nursing activity categories of the Korean Nursing Licensing Examination: a survey-based descriptive study  
Kyunghee Kim, So Young Kang, Younhee Kang, Youngran Kweon, Hyunjung Kim, Youngshin Song, Juyeon Cho, Mi-Young Choi, Hyun Su Lee
J Educ Eval Health Prof. 2023;20:18.   Published online June 12, 2023
DOI: https://doi.org/10.3352/jeehp.2023.20.18
  • 1,934 View
  • 119 Download
AbstractAbstract PDFSupplementary Material
Purpose
This study aims to suggest the number of test items in each of 8 nursing activity categories of the Korean Nursing Licensing Examination, which comprises 134 activity statements including 275 items. The examination will be able to evaluate the minimum ability that nursing graduates must have to perform their duties. Methods: Two opinion surveys involving the members of 7 academic societies were conducted from March 19 to May 14, 2021. The survey results were reviewed by members of 4 expert associations from May 21 to June 4, 2021. The results for revised numbers of items in each category were compared with those reported by Tak and his colleagues and the National Council License Examination for Registered Nurses of the United States. Results: Based on 2 opinion surveys and previous studies, the suggestions for item allocation to 8 nursing activity categories of the Korean Nursing Licensing Examination in this study are as follows: 50 items for management of care and improvement of professionalism, 33 items for safety and infection control, 40 items for management of potential risk, 28 items for basic care, 47 items for physiological integrity and maintenance, 33 items for pharmacological and parenteral therapies, 24 items for psychosocial integrity and maintenance, and 20 items for health promotion and maintenance. Twenty other items related to health and medical laws were not included due to their mandatory status. Conclusion: These suggestions for the number of test items for each activity category will be helpful in developing new items for the Korean Nursing Licensing Examination.
Adequacy of the examination-based licensing system and a training-based licensing system for midwifery license according to changes in childbirth medical infrastructure in Korea: a survey-based descriptive study  
Yun Mi Kim, Sun Hee Lee, Sun Ok Lee, Mi Young An, Bu Youn Kim, Jum Mi Park
J Educ Eval Health Prof. 2023;20:15.   Published online May 22, 2023
DOI: https://doi.org/10.3352/jeehp.2023.20.15
  • 1,380 View
  • 71 Download
AbstractAbstract PDFSupplementary Material
Purpose
The number of Korean midwifery licensing examination applicants has steadily decreased due to the low birth rate and lack of training institutions for midwives. This study aimed to evaluate the adequacy of the examination-based licensing system and the possibility of a training-based licensing system.
Methods
A survey questionnaire was developed and dispatched to 230 professionals from December 28, 2022 to January 13, 2023, through an online form using Google Surveys. Descriptive statistics were used to analyze the results.
Results
Responses from 217 persons (94.3%) were analyzed after excluding incomplete responses. Out of the 217 participants, 198 (91.2%) agreed with maintaining the current examination-based licensing system; 94 (43.3%) agreed with implementing a training-based licensing system to cover the examination costs due to the decreasing number of applicants; 132 (60.8%) agreed with establishing a midwifery education evaluation center for a training-based licensing system; 163 (75.1%) said that the quality of midwifery might be lowered if midwives were produced only by a training-based licensing system, and 197 (90.8%) said that the training of midwives as birth support personnel should be promoted in Korea.
Conclusion
Favorable results were reported for the examination-based licensing system; however, if a training-based licensing system is implemented, it will be necessary to establish a midwifery education evaluation center to manage the quality of midwives. As the annual number of candidates for the Korean midwifery licensing examination has been approximately 10 in recent years, it is necessary to consider more actively granting midwifery licenses through a training-based licensing system.
Factors influencing the learning transfer of nursing students in a non-face-to-face educational environment during the COVID-19 pandemic in Korea: a cross-sectional study using structural equation modeling  
Geun Myun Kim, Yunsoo Kim, Seong Kwang Kim
J Educ Eval Health Prof. 2023;20:14.   Published online April 27, 2023
DOI: https://doi.org/10.3352/jeehp.2023.20.14
  • 1,991 View
  • 162 Download
  • 3 Web of Science
  • 3 Crossref
AbstractAbstract PDFSupplementary Material
Purpose
The aim of this study was to identify factors influencing the learning transfer of nursing students in a non-face-to-face educational environment through structural equation modeling and suggest ways to improve the transfer of learning.
Methods
In this cross-sectional study, data were collected via online surveys from February 9 to March 1, 2022, from 218 nursing students in Korea. Learning transfer, learning immersion, learning satisfaction, learning efficacy, self-directed learning ability and information technology utilization ability were analyzed using IBM SPSS for Windows ver. 22.0 and AMOS ver. 22.0.
Results
The assessment of structural equation modeling showed adequate model fit, with normed χ2=1.74 (P<0.024), goodness-of-fit index=0.97, adjusted goodness-of-fit index=0.93, comparative fit index=0.98, root mean square residual=0.02, Tucker-Lewis index=0.97, normed fit index=0.96, and root mean square error of approximation=0.06. In a hypothetical model analysis, 9 out of 11 pathways of the hypothetical structural model for learning transfer in nursing students were statistically significant. Learning self-efficacy and learning immersion of nursing students directly affected learning transfer, and subjective information technology utilization ability, self-directed learning ability, and learning satisfaction were variables with indirect effects. The explanatory power of immersion, satisfaction, and self-efficacy for learning transfer was 44.4%.
Conclusion
The assessment of structural equation modeling indicated an acceptable fit. It is necessary to improve the transfer of learning through the development of a self-directed program for learning ability improvement, including the use of information technology in nursing students’ learning environment in non-face-to-face conditions.

Citations

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  • Flow in Relation to Academic Achievement in Online-Learning: A Meta-Analysis Study
    Da Xing, Yunjung Lee, Gyun Heo
    Measurement: Interdisciplinary Research and Perspectives.2024; : 1.     CrossRef
  • The Mediating Effect of Perceived Institutional Support on Inclusive Leadership and Academic Loyalty in Higher Education
    Olabode Gbobaniyi, Shalini Srivastava, Abiodun Kolawole Oyetunji, Chiemela Victor Amaechi, Salmia Binti Beddu, Bajpai Ankita
    Sustainability.2023; 15(17): 13195.     CrossRef
  • Transfer of Learning of New Nursing Professionals: Exploring Patterns and the Effect of Previous Work Experience
    Helena Roig-Ester, Paulina Elizabeth Robalino Guerra, Carla Quesada-Pallarès, Andreas Gegenfurtner
    Education Sciences.2023; 14(1): 52.     CrossRef
Evaluation of medical school faculty members’ educational performance in Korea in 2022 through analysis of the promotion regulations: a mixed methods study  
Hye Won Jang, Janghee Park
J Educ Eval Health Prof. 2023;20:7.   Published online February 28, 2023
DOI: https://doi.org/10.3352/jeehp.2023.20.7
  • 2,988 View
  • 133 Download
AbstractAbstract PDFSupplementary Material
Purpose
To ensure faculty members’ active participation in education in response to growing demand, medical schools should clearly describe educational activities in their promotion regulations. This study analyzed the status of how medical education activities are evaluated in promotion regulations in 2022, in Korea.
Methods
Data were collected from promotion regulations retrieved by searching the websites of 22 medical schools/universities in August 2022. To categorize educational activities and evaluation methods, the Association of American Medical Colleges framework for educational activities was utilized. Correlations between medical schools’ characteristics and the evaluation of medical educational activities were analyzed.
Results
We defined 6 categories, including teaching, development of education products, education administration and service, scholarship in education, student affairs, and others, and 20 activities with 57 sub-activities. The average number of included activities was highest in the development of education products category and lowest in the scholarship in education category. The weight adjustment factors of medical educational activities were the characteristics of the target subjects and faculty members, the number of involved faculty members, and the difficulty of activities. Private medical schools tended to have more educational activities in the regulations than public medical schools. The greater the number of faculty members, the greater the number of educational activities in the education administration and service categories.
Conclusion
Medical schools included various medical education activities and their evaluation methods in promotion regulations in Korea. This study provides basic data for improving the rewarding system for efforts of medical faculty members in education.
Identifying the nutrition support nurses’ tasks using importance–performance analysis in Korea: a descriptive study  
Jeong Yun Park
J Educ Eval Health Prof. 2023;20:3.   Published online January 18, 2023
DOI: https://doi.org/10.3352/jeehp.2023.20.3
  • 1,976 View
  • 148 Download
AbstractAbstract PDFSupplementary Material
Purpose
Nutrition support nurse is a member of a nutrition support team and is a health care professional who takes a significant part in all aspects of nutritional care. This study aims to investigate ways to improve the quality of tasks performed by nutrition support nurses through survey questionnaires in Korea.
Methods
An online survey was conducted between October 12 and November 31, 2018. The questionnaire consists of 36 items categorized into 5 subscales: nutrition-focused support care, education and counseling, consultation and coordination, research and quality improvement, and leadership. The importance–performance analysis method was used to confirm the relationship between the importance and performance of nutrition support nurses’ tasks.
Results
A total of 101 nutrition support nurses participated in this survey. The importance (5.56±0.78) and performance (4.50±1.06) of nutrition support nurses’ tasks showed a significant difference (t=11.27, P<0.001). Education, counseling/consultation, and participation in developing their processes and guidelines were identified as low-performance activities compared with their importance.
Conclusion
To intervene nutrition support effectively, nutrition support nurses should have the qualification or competency through the education program based on their practice. Improved awareness of nutrition support nurses participating in research and quality improvement activity for role development is required.
Brief report
Are ChatGPT’s knowledge and interpretation ability comparable to those of medical students in Korea for taking a parasitology examination?: a descriptive study  
Sun Huh
J Educ Eval Health Prof. 2023;20:1.   Published online January 11, 2023
DOI: https://doi.org/10.3352/jeehp.2023.20.1
  • 13,442 View
  • 1,066 Download
  • 157 Web of Science
  • 79 Crossref
AbstractAbstract PDFSupplementary Material
This study aimed to compare the knowledge and interpretation ability of ChatGPT, a language model of artificial general intelligence, with those of medical students in Korea by administering a parasitology examination to both ChatGPT and medical students. The examination consisted of 79 items and was administered to ChatGPT on January 1, 2023. The examination results were analyzed in terms of ChatGPT’s overall performance score, its correct answer rate by the items’ knowledge level, and the acceptability of its explanations of the items. ChatGPT’s performance was lower than that of the medical students, and ChatGPT’s correct answer rate was not related to the items’ knowledge level. However, there was a relationship between acceptable explanations and correct answers. In conclusion, ChatGPT’s knowledge and interpretation ability for this parasitology examination were not yet comparable to those of medical students in Korea.

Citations

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  • Performance of ChatGPT on the India Undergraduate Community Medicine Examination: Cross-Sectional Study
    Aravind P Gandhi, Felista Karen Joesph, Vineeth Rajagopal, P Aparnavi, Sushma Katkuri, Sonal Dayama, Prakasini Satapathy, Mahalaqua Nazli Khatib, Shilpa Gaidhane, Quazi Syed Zahiruddin, Ashish Behera
    JMIR Formative Research.2024; 8: e49964.     CrossRef
  • Large Language Models and Artificial Intelligence: A Primer for Plastic Surgeons on the Demonstrated and Potential Applications, Promises, and Limitations of ChatGPT
    Jad Abi-Rafeh, Hong Hao Xu, Roy Kazan, Ruth Tevlin, Heather Furnas
    Aesthetic Surgery Journal.2024; 44(3): 329.     CrossRef
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    Ana Suárez, Víctor Díaz‐Flores García, Juan Algar, Margarita Gómez Sánchez, María Llorente de Pedro, Yolanda Freire
    International Endodontic Journal.2024; 57(1): 108.     CrossRef
  • Bob or Bot: Exploring ChatGPT's Answers to University Computer Science Assessment
    Mike Richards, Kevin Waugh, Mark Slaymaker, Marian Petre, John Woodthorpe, Daniel Gooch
    ACM Transactions on Computing Education.2024; 24(1): 1.     CrossRef
  • A systematic review of ChatGPT use in K‐12 education
    Peng Zhang, Gemma Tur
    European Journal of Education.2024;[Epub]     CrossRef
  • Evaluating ChatGPT as a self‐learning tool in medical biochemistry: A performance assessment in undergraduate medical university examination
    Krishna Mohan Surapaneni, Anusha Rajajagadeesan, Lakshmi Goudhaman, Shalini Lakshmanan, Saranya Sundaramoorthi, Dineshkumar Ravi, Kalaiselvi Rajendiran, Porchelvan Swaminathan
    Biochemistry and Molecular Biology Education.2024; 52(2): 237.     CrossRef
  • Examining the use of ChatGPT in public universities in Hong Kong: a case study of restricted access areas
    Michelle W. T. Cheng, Iris H. Y. YIM
    Discover Education.2024;[Epub]     CrossRef
  • Performance of ChatGPT on Ophthalmology-Related Questions Across Various Examination Levels: Observational Study
    Firas Haddad, Joanna S Saade
    JMIR Medical Education.2024; 10: e50842.     CrossRef
  • Assessment of Artificial Intelligence Platforms With Regard to Medical Microbiology Knowledge: An Analysis of ChatGPT and Gemini
    Jai Ranjan, Absar Ahmad, Monalisa Subudhi, Ajay Kumar
    Cureus.2024;[Epub]     CrossRef
  • A comparative vignette study: Evaluating the potential role of a generative AI model in enhancing clinical decision‐making in nursing
    Mor Saban, Ilana Dubovi
    Journal of Advanced Nursing.2024;[Epub]     CrossRef
  • Comparison of the Performance of GPT-3.5 and GPT-4 With That of Medical Students on the Written German Medical Licensing Examination: Observational Study
    Annika Meyer, Janik Riese, Thomas Streichert
    JMIR Medical Education.2024; 10: e50965.     CrossRef
  • From hype to insight: Exploring ChatGPT's early footprint in education via altmetrics and bibliometrics
    Lung‐Hsiang Wong, Hyejin Park, Chee‐Kit Looi
    Journal of Computer Assisted Learning.2024; 40(4): 1428.     CrossRef
  • A scoping review of artificial intelligence in medical education: BEME Guide No. 84
    Morris Gordon, Michelle Daniel, Aderonke Ajiboye, Hussein Uraiby, Nicole Y. Xu, Rangana Bartlett, Janice Hanson, Mary Haas, Maxwell Spadafore, Ciaran Grafton-Clarke, Rayhan Yousef Gasiea, Colin Michie, Janet Corral, Brian Kwan, Diana Dolmans, Satid Thamma
    Medical Teacher.2024; 46(4): 446.     CrossRef
  • Üniversite Öğrencilerinin ChatGPT 3,5 Deneyimleri: Yapay Zekâyla Yazılmış Masal Varyantları
    Bilge GÖK, Fahri TEMİZYÜREK, Özlem BAŞ
    Korkut Ata Türkiyat Araştırmaları Dergisi.2024; (14): 1040.     CrossRef
  • Tracking ChatGPT Research: Insights From the Literature and the Web
    Omar Mubin, Fady Alnajjar, Zouheir Trabelsi, Luqman Ali, Medha Mohan Ambali Parambil, Zhao Zou
    IEEE Access.2024; 12: 30518.     CrossRef
  • Potential applications of ChatGPT in obstetrics and gynecology in Korea: a review article
    YooKyung Lee, So Yun Kim
    Obstetrics & Gynecology Science.2024; 67(2): 153.     CrossRef
  • Application of generative language models to orthopaedic practice
    Jessica Caterson, Olivia Ambler, Nicholas Cereceda-Monteoliva, Matthew Horner, Andrew Jones, Arwel Tomos Poacher
    BMJ Open.2024; 14(3): e076484.     CrossRef
  • Opportunities, challenges, and future directions of large language models, including ChatGPT in medical education: a systematic scoping review
    Xiaojun Xu, Yixiao Chen, Jing Miao
    Journal of Educational Evaluation for Health Professions.2024; 21: 6.     CrossRef
  • The advent of ChatGPT: Job Made Easy or Job Loss to Data Analysts
    Abiola Timothy Owolabi, Oluwaseyi Oluwadamilare Okunlola, Emmanuel Taiwo Adewuyi, Janet Iyabo Idowu, Olasunkanmi James Oladapo
    WSEAS TRANSACTIONS ON COMPUTERS.2024; 23: 24.     CrossRef
  • ChatGPT in dentomaxillofacial radiology education
    Hilal Peker Öztürk, Hakan Avsever, Buğra Şenel, Şükran Ayran, Mustafa Çağrı Peker, Hatice Seda Özgedik, Nurten Baysal
    Journal of Health Sciences and Medicine.2024; 7(2): 224.     CrossRef
  • Performance of ChatGPT on the Korean National Examination for Dental Hygienists
    Soo-Myoung Bae, Hye-Rim Jeon, Gyoung-Nam Kim, Seon-Hui Kwak, Hyo-Jin Lee
    Journal of Dental Hygiene Science.2024; 24(1): 62.     CrossRef
  • Medical knowledge of ChatGPT in public health, infectious diseases, COVID-19 pandemic, and vaccines: multiple choice questions examination based performance
    Sultan Ayoub Meo, Metib Alotaibi, Muhammad Zain Sultan Meo, Muhammad Omair Sultan Meo, Mashhood Hamid
    Frontiers in Public Health.2024;[Epub]     CrossRef
  • Unlock the potential for Saudi Arabian higher education: a systematic review of the benefits of ChatGPT
    Eman Faisal
    Frontiers in Education.2024;[Epub]     CrossRef
  • Does the Information Quality of ChatGPT Meet the Requirements of Orthopedics and Trauma Surgery?
    Adnan Kasapovic, Thaer Ali, Mari Babasiz, Jessica Bojko, Martin Gathen, Robert Kaczmarczyk, Jonas Roos
    Cureus.2024;[Epub]     CrossRef
  • Exploring the Profile of University Assessments Flagged as Containing AI-Generated Material
    Daniel Gooch, Kevin Waugh, Mike Richards, Mark Slaymaker, John Woodthorpe
    ACM Inroads.2024; 15(2): 39.     CrossRef
  • Comparing the Performance of ChatGPT-4 and Medical Students on MCQs at Varied Levels of Bloom’s Taxonomy
    Ambadasu Bharatha, Nkemcho Ojeh, Ahbab Mohammad Fazle Rabbi, Michael Campbell, Kandamaran Krishnamurthy, Rhaheem Layne-Yarde, Alok Kumar, Dale Springer, Kenneth Connell, Md Anwarul Majumder
    Advances in Medical Education and Practice.2024; Volume 15: 393.     CrossRef
  • The emergence of generative artificial intelligence platforms in 2023, journal metrics, appreciation to reviewers and volunteers, and obituary
    Sun Huh
    Journal of Educational Evaluation for Health Professions.2024; 21: 9.     CrossRef
  • ChatGPT, a Friend or a Foe in Medical Education: A Review of Strengths, Challenges, and Opportunities
    Mahdi Zarei, Maryam Zarei, Sina Hamzehzadeh, Sepehr Shakeri Bavil Oliyaei, Mohammad-Salar Hosseini
    Shiraz E-Medical Journal.2024;[Epub]     CrossRef
  • Augmenting intensive care unit nursing practice with generative AI: A formative study of diagnostic synergies using simulation‐based clinical cases
    Chedva Levin, Moriya Suliman, Etti Naimi, Mor Saban
    Journal of Clinical Nursing.2024;[Epub]     CrossRef
  • Artificial intelligence chatbots for the nutrition management of diabetes and the metabolic syndrome
    Farah Naja, Mandy Taktouk, Dana Matbouli, Sharfa Khaleel, Ayah Maher, Berna Uzun, Maryam Alameddine, Lara Nasreddine
    European Journal of Clinical Nutrition.2024;[Epub]     CrossRef
  • Large language models in healthcare: from a systematic review on medical examinations to a comparative analysis on fundamentals of robotic surgery online test
    Andrea Moglia, Konstantinos Georgiou, Pietro Cerveri, Luca Mainardi, Richard M. Satava, Alfred Cuschieri
    Artificial Intelligence Review.2024;[Epub]     CrossRef
  • Is ChatGPT Enhancing Youth’s Learning, Engagement and Satisfaction?
    Christina Sanchita Shah, Smriti Mathur, Sushant Kr. Vishnoi
    Journal of Computer Information Systems.2024; : 1.     CrossRef
  • Comparison of ChatGPT, Gemini, and Le Chat with physician interpretations of medical laboratory questions from an online health forum
    Annika Meyer, Ari Soleman, Janik Riese, Thomas Streichert
    Clinical Chemistry and Laboratory Medicine (CCLM).2024;[Epub]     CrossRef
  • Role of ChatGPT in Dentistry: A Review
    Pratik Surana, Priyanka P. Ostwal, Shruti Vishal Dev, Jayesh Tiwari, Kadire Shiva Charan Yadav, Gajji Renuka
    Research Journal of Pharmacy and Technology.2024; : 3489.     CrossRef
  • Applicability of ChatGPT in Assisting to Solve Higher Order Problems in Pathology
    Ranwir K Sinha, Asitava Deb Roy, Nikhil Kumar, Himel Mondal
    Cureus.2023;[Epub]     CrossRef
  • Issues in the 3rd year of the COVID-19 pandemic, including computer-based testing, study design, ChatGPT, journal metrics, and appreciation to reviewers
    Sun Huh
    Journal of Educational Evaluation for Health Professions.2023; 20: 5.     CrossRef
  • Emergence of the metaverse and ChatGPT in journal publishing after the COVID-19 pandemic
    Sun Huh
    Science Editing.2023; 10(1): 1.     CrossRef
  • Assessing the Capability of ChatGPT in Answering First- and Second-Order Knowledge Questions on Microbiology as per Competency-Based Medical Education Curriculum
    Dipmala Das, Nikhil Kumar, Langamba Angom Longjam, Ranwir Sinha, Asitava Deb Roy, Himel Mondal, Pratima Gupta
    Cureus.2023;[Epub]     CrossRef
  • Evaluating ChatGPT's Ability to Solve Higher-Order Questions on the Competency-Based Medical Education Curriculum in Medical Biochemistry
    Arindam Ghosh, Aritri Bir
    Cureus.2023;[Epub]     CrossRef
  • Overview of Early ChatGPT’s Presence in Medical Literature: Insights From a Hybrid Literature Review by ChatGPT and Human Experts
    Omar Temsah, Samina A Khan, Yazan Chaiah, Abdulrahman Senjab, Khalid Alhasan, Amr Jamal, Fadi Aljamaan, Khalid H Malki, Rabih Halwani, Jaffar A Al-Tawfiq, Mohamad-Hani Temsah, Ayman Al-Eyadhy
    Cureus.2023;[Epub]     CrossRef
  • ChatGPT for Future Medical and Dental Research
    Bader Fatani
    Cureus.2023;[Epub]     CrossRef
  • ChatGPT in Dentistry: A Comprehensive Review
    Hind M Alhaidry, Bader Fatani, Jenan O Alrayes, Aljowhara M Almana, Nawaf K Alfhaed
    Cureus.2023;[Epub]     CrossRef
  • Can we trust AI chatbots’ answers about disease diagnosis and patient care?
    Sun Huh
    Journal of the Korean Medical Association.2023; 66(4): 218.     CrossRef
  • Large Language Models in Medical Education: Opportunities, Challenges, and Future Directions
    Alaa Abd-alrazaq, Rawan AlSaad, Dari Alhuwail, Arfan Ahmed, Padraig Mark Healy, Syed Latifi, Sarah Aziz, Rafat Damseh, Sadam Alabed Alrazak, Javaid Sheikh
    JMIR Medical Education.2023; 9: e48291.     CrossRef
  • Early applications of ChatGPT in medical practice, education and research
    Sam Sedaghat
    Clinical Medicine.2023; 23(3): 278.     CrossRef
  • A Review of Research on Teaching and Learning Transformation under the Influence of ChatGPT Technology
    璇 师
    Advances in Education.2023; 13(05): 2617.     CrossRef
  • Performance of GPT-3.5 and GPT-4 on the Japanese Medical Licensing Examination: Comparison Study
    Soshi Takagi, Takashi Watari, Ayano Erabi, Kota Sakaguchi
    JMIR Medical Education.2023; 9: e48002.     CrossRef
  • ChatGPT’s quiz skills in different otolaryngology subspecialties: an analysis of 2576 single-choice and multiple-choice board certification preparation questions
    Cosima C. Hoch, Barbara Wollenberg, Jan-Christoffer Lüers, Samuel Knoedler, Leonard Knoedler, Konstantin Frank, Sebastian Cotofana, Michael Alfertshofer
    European Archives of Oto-Rhino-Laryngology.2023; 280(9): 4271.     CrossRef
  • Analysing the Applicability of ChatGPT, Bard, and Bing to Generate Reasoning-Based Multiple-Choice Questions in Medical Physiology
    Mayank Agarwal, Priyanka Sharma, Ayan Goswami
    Cureus.2023;[Epub]     CrossRef
  • The Intersection of ChatGPT, Clinical Medicine, and Medical Education
    Rebecca Shin-Yee Wong, Long Chiau Ming, Raja Affendi Raja Ali
    JMIR Medical Education.2023; 9: e47274.     CrossRef
  • The Role of Artificial Intelligence in Higher Education: ChatGPT Assessment for Anatomy Course
    Tarık TALAN, Yusuf KALINKARA
    Uluslararası Yönetim Bilişim Sistemleri ve Bilgisayar Bilimleri Dergisi.2023; 7(1): 33.     CrossRef
  • Comparing ChatGPT’s ability to rate the degree of stereotypes and the consistency of stereotype attribution with those of medical students in New Zealand in developing a similarity rating test: a methodological study
    Chao-Cheng Lin, Zaine Akuhata-Huntington, Che-Wei Hsu
    Journal of Educational Evaluation for Health Professions.2023; 20: 17.     CrossRef
  • Examining Real-World Medication Consultations and Drug-Herb Interactions: ChatGPT Performance Evaluation
    Hsing-Yu Hsu, Kai-Cheng Hsu, Shih-Yen Hou, Ching-Lung Wu, Yow-Wen Hsieh, Yih-Dih Cheng
    JMIR Medical Education.2023; 9: e48433.     CrossRef
  • Assessing the Efficacy of ChatGPT in Solving Questions Based on the Core Concepts in Physiology
    Arijita Banerjee, Aquil Ahmad, Payal Bhalla, Kavita Goyal
    Cureus.2023;[Epub]     CrossRef
  • ChatGPT Performs on the Chinese National Medical Licensing Examination
    Xinyi Wang, Zhenye Gong, Guoxin Wang, Jingdan Jia, Ying Xu, Jialu Zhao, Qingye Fan, Shaun Wu, Weiguo Hu, Xiaoyang Li
    Journal of Medical Systems.2023;[Epub]     CrossRef
  • Artificial intelligence and its impact on job opportunities among university students in North Lima, 2023
    Doris Ruiz-Talavera, Jaime Enrique De la Cruz-Aguero, Nereo García-Palomino, Renzo Calderón-Espinoza, William Joel Marín-Rodriguez
    ICST Transactions on Scalable Information Systems.2023;[Epub]     CrossRef
  • Revolutionizing Dental Care: A Comprehensive Review of Artificial Intelligence Applications Among Various Dental Specialties
    Najd Alzaid, Omar Ghulam, Modhi Albani, Rafa Alharbi, Mayan Othman, Hasan Taher, Saleem Albaradie, Suhael Ahmed
    Cureus.2023;[Epub]     CrossRef
  • Opportunities, Challenges, and Future Directions of Generative Artificial Intelligence in Medical Education: Scoping Review
    Carl Preiksaitis, Christian Rose
    JMIR Medical Education.2023; 9: e48785.     CrossRef
  • Exploring the impact of language models, such as ChatGPT, on student learning and assessment
    Araz Zirar
    Review of Education.2023;[Epub]     CrossRef
  • Evaluating the reliability of ChatGPT as a tool for imaging test referral: a comparative study with a clinical decision support system
    Shani Rosen, Mor Saban
    European Radiology.2023; 34(5): 2826.     CrossRef
  • Redesigning Tertiary Educational Evaluation with AI: A Task-Based Analysis of LIS Students’ Assessment on Written Tests and Utilizing ChatGPT at NSTU
    Shamima Yesmin
    Science & Technology Libraries.2023; : 1.     CrossRef
  • ChatGPT and the AI revolution: a comprehensive investigation of its multidimensional impact and potential
    Mohd Afjal
    Library Hi Tech.2023;[Epub]     CrossRef
  • The Significance of Artificial Intelligence Platforms in Anatomy Education: An Experience With ChatGPT and Google Bard
    Hasan B Ilgaz, Zehra Çelik
    Cureus.2023;[Epub]     CrossRef
  • Is ChatGPT’s Knowledge and Interpretative Ability Comparable to First Professional MBBS (Bachelor of Medicine, Bachelor of Surgery) Students of India in Taking a Medical Biochemistry Examination?
    Abhra Ghosh, Nandita Maini Jindal, Vikram K Gupta, Ekta Bansal, Navjot Kaur Bajwa, Abhishek Sett
    Cureus.2023;[Epub]     CrossRef
  • Ethical consideration of the use of generative artificial intelligence, including ChatGPT in writing a nursing article
    Sun Huh
    Child Health Nursing Research.2023; 29(4): 249.     CrossRef
  • Potential Use of ChatGPT for Patient Information in Periodontology: A Descriptive Pilot Study
    Osman Babayiğit, Zeynep Tastan Eroglu, Dilek Ozkan Sen, Fatma Ucan Yarkac
    Cureus.2023;[Epub]     CrossRef
  • Efficacy and limitations of ChatGPT as a biostatistical problem-solving tool in medical education in Serbia: a descriptive study
    Aleksandra Ignjatović, Lazar Stevanović
    Journal of Educational Evaluation for Health Professions.2023; 20: 28.     CrossRef
  • Assessing the Performance of ChatGPT in Medical Biochemistry Using Clinical Case Vignettes: Observational Study
    Krishna Mohan Surapaneni
    JMIR Medical Education.2023; 9: e47191.     CrossRef
  • Performance of ChatGPT, Bard, Claude, and Bing on the Peruvian National Licensing Medical Examination: a cross-sectional study
    Betzy Clariza Torres-Zegarra, Wagner Rios-Garcia, Alvaro Micael Ñaña-Cordova, Karen Fatima Arteaga-Cisneros, Xiomara Cristina Benavente Chalco, Marina Atena Bustamante Ordoñez, Carlos Jesus Gutierrez Rios, Carlos Alberto Ramos Godoy, Kristell Luisa Teresa
    Journal of Educational Evaluation for Health Professions.2023; 20: 30.     CrossRef
  • ChatGPT’s performance in German OB/GYN exams – paving the way for AI-enhanced medical education and clinical practice
    Maximilian Riedel, Katharina Kaefinger, Antonia Stuehrenberg, Viktoria Ritter, Niklas Amann, Anna Graf, Florian Recker, Evelyn Klein, Marion Kiechle, Fabian Riedel, Bastian Meyer
    Frontiers in Medicine.2023;[Epub]     CrossRef
  • Medical students’ patterns of using ChatGPT as a feedback tool and perceptions of ChatGPT in a Leadership and Communication course in Korea: a cross-sectional study
    Janghee Park
    Journal of Educational Evaluation for Health Professions.2023; 20: 29.     CrossRef
  • FROM TEXT TO DIAGNOSE: CHATGPT’S EFFICACY IN MEDICAL DECISION-MAKING
    Yaroslav Mykhalko, Pavlo Kish, Yelyzaveta Rubtsova, Oleksandr Kutsyn, Valentyna Koval
    Wiadomości Lekarskie.2023; 76(11): 2345.     CrossRef
  • Using ChatGPT for Clinical Practice and Medical Education: Cross-Sectional Survey of Medical Students’ and Physicians’ Perceptions
    Pasin Tangadulrat, Supinya Sono, Boonsin Tangtrakulwanich
    JMIR Medical Education.2023; 9: e50658.     CrossRef
  • Below average ChatGPT performance in medical microbiology exam compared to university students
    Malik Sallam, Khaled Al-Salahat
    Frontiers in Education.2023;[Epub]     CrossRef
  • ChatGPT: "To be or not to be" ... in academic research. The human mind's analytical rigor and capacity to discriminate between AI bots' truths and hallucinations
    Aurelian Anghelescu, Ilinca Ciobanu, Constantin Munteanu, Lucia Ana Maria Anghelescu, Gelu Onose
    Balneo and PRM Research Journal.2023; 14(Vol.14, no): 614.     CrossRef
  • ChatGPT Review: A Sophisticated Chatbot Models in Medical & Health-related Teaching and Learning
    Nur Izah Ab Razak, Muhammad Fawwaz Muhammad Yusoff, Rahmita Wirza O.K. Rahmat
    Malaysian Journal of Medicine and Health Sciences.2023; 19(s12): 98.     CrossRef
  • Application of artificial intelligence chatbots, including ChatGPT, in education, scholarly work, programming, and content generation and its prospects: a narrative review
    Tae Won Kim
    Journal of Educational Evaluation for Health Professions.2023; 20: 38.     CrossRef
  • Trends in research on ChatGPT and adoption-related issues discussed in articles: a narrative review
    Sang-Jun Kim
    Science Editing.2023; 11(1): 3.     CrossRef
  • Information amount, accuracy, and relevance of generative artificial intelligence platforms’ answers regarding learning objectives of medical arthropodology evaluated in English and Korean queries in December 2023: a descriptive study
    Hyunju Lee, Soobin Park
    Journal of Educational Evaluation for Health Professions.2023; 20: 39.     CrossRef

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