Journal of Educational Evaluation for Health Professions

Review

Opportunities, challenges, and future directions of large language models, including ChatGPT in medical education: a systematic scoping review: Xiaojun Xu, Yixiao Chen, Jing Miao; J Educ Eval Health Prof. 2024;21:6. Published online March 15, 2024; DOI: https://doi.org/10.3352/jeehp.2024.21.6

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Abstract PDF Supplementary Material: Background
ChatGPT is a large language model (LLM) based on artificial intelligence (AI) capable of responding in multiple languages and generating nuanced and highly complex responses. While ChatGPT holds promising applications in medical education, its limitations and potential risks cannot be ignored.
Methods
A scoping review was conducted for English articles discussing ChatGPT in the context of medical education published after 2022. A literature search was performed using PubMed/MEDLINE, Embase, and Web of Science databases, and information was extracted from the relevant studies that were ultimately included.
Results
ChatGPT exhibits various potential applications in medical education, such as providing personalized learning plans and materials, creating clinical practice simulation scenarios, and assisting in writing articles. However, challenges associated with academic integrity, data accuracy, and potential harm to learning were also highlighted in the literature. The paper emphasizes certain recommendations for using ChatGPT, including the establishment of guidelines. Based on the review, 3 key research areas were proposed: cultivating the ability of medical students to use ChatGPT correctly, integrating ChatGPT into teaching activities and processes, and proposing standards for the use of AI by medical students.
Conclusion
ChatGPT has the potential to transform medical education, but careful consideration is required for its full integration. To harness the full potential of ChatGPT in medical education, attention should not only be given to the capabilities of AI but also to its impact on students and teachers.

Research articles

Negative effects on medical students’ scores for clinical performance during the COVID-19 pandemic in Taiwan: a comparative study: Eunice Jia-Shiow Yuan, Shiau-Shian Huang, Chia-An Hsu, Jiing-Feng Lirng, Tzu-Hao Li, Chia-Chang Huang, Ying-Ying Yang, Chung-Pin Li, Chen-Huan Chen; J Educ Eval Health Prof. 2023;20:37. Published online December 26, 2023; DOI: https://doi.org/10.3352/jeehp.2023.20.37

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Abstract PDF Supplementary Material: Purpose
Coronavirus disease 2019 (COVID-19) has heavily impacted medical clinical education in Taiwan. Medical curricula have been altered to minimize exposure and limit transmission. This study investigated the effect of COVID-19 on Taiwanese medical students’ clinical performance using online standardized evaluation systems and explored the factors influencing medical education during the pandemic.
Methods
Medical students were scored from 0 to 100 based on their clinical performance from 1/1/2018 to 6/31/2021. The students were placed into pre-COVID-19 (before 2/1/2020) and midst-COVID-19 (on and after 2/1/2020) groups. Each group was further categorized into COVID-19-affected specialties (pulmonary, infectious, and emergency medicine) and other specialties. Generalized estimating equations (GEEs) were used to compare and examine the effects of relevant variables on student performance.
Results
In total, 16,944 clinical scores were obtained for COVID-19-affected specialties and other specialties. For the COVID-19-affected specialties, the midst-COVID-19 score (88.513.52) was significantly lower than the pre-COVID-19 score (90.143.55) (P<0.0001). For the other specialties, the midst-COVID-19 score (88.323.68) was also significantly lower than the pre-COVID-19 score (90.063.58) (P<0.0001). There were 1,322 students (837 males and 485 females). Male students had significantly lower scores than female students (89.333.68 vs. 89.993.66, P=0.0017). GEE analysis revealed that the COVID-19 pandemic (unstandardized beta coefficient=-1.99, standard error [SE]=0.13, P<0.0001), COVID-19-affected specialties (B=0.26, SE=0.11, P=0.0184), female students (B=1.10, SE=0.20, P<0.0001), and female attending physicians (B=-0.19, SE=0.08, P=0.0145) were independently associated with students’ scores.
Conclusion
COVID-19 negatively impacted medical students' clinical performance, regardless of their specialty. Female students outperformed male students, irrespective of the pandemic.

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 Panta Quezada, Jesus Daniel Gutierrez-Arratia, Javier Alejandro Flores-Cohaila; J Educ Eval Health Prof. 2023;20:30. Published online November 20, 2023; DOI: https://doi.org/10.3352/jeehp.2023.20.30

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Abstract PDF Supplementary Material

Purpose
We aimed to describe the performance and evaluate the educational value of justifications provided by artificial intelligence chatbots, including GPT-3.5, GPT-4, Bard, Claude, and Bing, on the Peruvian National Medical Licensing Examination (P-NLME).
Methods
This was a cross-sectional analytical study. On July 25, 2023, each multiple-choice question (MCQ) from the P-NLME was entered into each chatbot (GPT-3, GPT-4, Bing, Bard, and Claude) 3 times. Then, 4 medical educators categorized the MCQs in terms of medical area, item type, and whether the MCQ required Peru-specific knowledge. They assessed the educational value of the justifications from the 2 top performers (GPT-4 and Bing).
Results
GPT-4 scored 86.7% and Bing scored 82.2%, followed by Bard and Claude, and the historical performance of Peruvian examinees was 55%. Among the factors associated with correct answers, only MCQs that required Peru-specific knowledge had lower odds (odds ratio, 0.23; 95% confidence interval, 0.09–0.61), whereas the remaining factors showed no associations. In assessing the educational value of justifications provided by GPT-4 and Bing, neither showed any significant differences in certainty, usefulness, or potential use in the classroom.
Conclusion
Among chatbots, GPT-4 and Bing were the top performers, with Bing performing better at Peru-specific MCQs. Moreover, the educational value of justifications provided by the GPT-4 and Bing could be deemed appropriate. However, it is essential to start addressing the educational value of these chatbots, rather than merely their performance on examinations.

Citations

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Performance of GPT-4V in Answering the Japanese Otolaryngology Board Certification Examination Questions: Evaluation Study
Masao Noda, Takayoshi Ueno, Ryota Koshu, Yuji Takaso, Mari Dias Shimada, Chizu Saito, Hisashi Sugimoto, Hiroaki Fushiki, Makoto Ito, Akihiro Nomura, Tomokazu Yoshizaki
JMIR Medical Education.2024; 10: e57054. CrossRef
Response to Letter to the Editor re: “Artificial Intelligence Versus Expert Plastic Surgeon: Comparative Study Shows ChatGPT ‘Wins' Rhinoplasty Consultations: Should We Be Worried? [1]” by Durairaj et al.
Kay Durairaj, Omer Baker
Facial Plastic Surgery & Aesthetic Medicine.2024;[Epub] 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
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

Efficacy and limitations of ChatGPT as a biostatistical problem-solving tool in medical education in Serbia: a descriptive study: Aleksandra Ignjatović, Lazar Stevanović; J Educ Eval Health Prof. 2023;20:28. Published online October 16, 2023; DOI: https://doi.org/10.3352/jeehp.2023.20.28

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Abstract PDF Supplementary Material

Purpose
This study aimed to assess the performance of ChatGPT (GPT-3.5 and GPT-4) as a study tool in solving biostatistical problems and to identify any potential drawbacks that might arise from using ChatGPT in medical education, particularly in solving practical biostatistical problems.
Methods
ChatGPT was tested to evaluate its ability to solve biostatistical problems from the Handbook of Medical Statistics by Peacock and Peacock in this descriptive study. Tables from the problems were transformed into textual questions. Ten biostatistical problems were randomly chosen and used as text-based input for conversation with ChatGPT (versions 3.5 and 4).
Results
GPT-3.5 solved 5 practical problems in the first attempt, related to categorical data, cross-sectional study, measuring reliability, probability properties, and the t-test. GPT-3.5 failed to provide correct answers regarding analysis of variance, the chi-square test, and sample size within 3 attempts. GPT-4 also solved a task related to the confidence interval in the first attempt and solved all questions within 3 attempts, with precise guidance and monitoring.
Conclusion
The assessment of both versions of ChatGPT performance in 10 biostatistical problems revealed that GPT-3.5 and 4’s performance was below average, with correct response rates of 5 and 6 out of 10 on the first attempt. GPT-4 succeeded in providing all correct answers within 3 attempts. These findings indicate that students must be aware that this tool, even when providing and calculating different statistical analyses, can be wrong, and they should be aware of ChatGPT’s limitations and be careful when incorporating this model into medical education.

Citations

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Can Generative AI and ChatGPT Outperform Humans on Cognitive-Demanding Problem-Solving Tasks in Science?
Xiaoming Zhai, Matthew Nyaaba, Wenchao Ma
Science & Education.2024;[Epub] CrossRef

Brief report

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; J Educ Eval Health Prof. 2023;20:17. Published online June 12, 2023; DOI: https://doi.org/10.3352/jeehp.2023.20.17

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Abstract PDF Supplementary Material

Learning about one’s implicit bias is crucial for improving one’s cultural competency and thereby reducing health inequity. To evaluate bias among medical students following a previously developed cultural training program targeting New Zealand Māori, we developed a text-based, self-evaluation tool called the Similarity Rating Test (SRT). The development process of the SRT was resource-intensive, limiting its generalizability and applicability. Here, we explored the potential of ChatGPT, an automated chatbot, to assist in the development process of the SRT by comparing ChatGPT’s and students’ evaluations of the SRT. Despite results showing non-significant equivalence and difference between ChatGPT’s and students’ ratings, ChatGPT’s ratings were more consistent than students’ ratings. The consistency rate was higher for non-stereotypical than for stereotypical statements, regardless of rater type. Further studies are warranted to validate ChatGPT’s potential for assisting in SRT development for implementation in medical education and evaluation of ethnic stereotypes and related topics.

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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

Research articles

Relationships between undergraduate medical students’ attitudes toward communication skills learning and demographics in Zambia: a survey-based descriptive study: Mercy Ijeoma Okwudili Ezeala, John Volk; J Educ Eval Health Prof. 2023;20:16. Published online June 1, 2023; DOI: https://doi.org/10.3352/jeehp.2023.20.16

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1 Crossref

Abstract PDF Supplementary Material

Purpose
This study aimed to detect relationships between undergraduate students’ attitudes toward communication skills learning and demographic variables (such as age, academic year, and gender). Understanding these relationships could provide information for communication skills facilitators and curriculum planners on structuring course delivery and integrating communication skills training into the medical curriculum.
Methods
The descriptive study involved a survey of 369 undergraduate students from 2 medical schools in Zambia who participated in communication skills training stratified by academic year using the Communication Skills Attitude Scale. Data were collected between October and December 2021 and analyzed using IBM SPSS for Windows version 28.0.
Results
One-way analysis of variance revealed a significant difference in attitude between at least 5 academic years. There was a significant difference in attitudes between the 2nd and 5th academic years (t=5.95, P˂0.001). No significant difference in attitudes existed among the academic years on the negative subscale; the 2nd and 3rd (t=3.82, P=0.004), 4th (t=3.61, P=0.011), 5th (t=8.36, P˂0.001), and 6th (t=4.20, P=0.001) academic years showed significant differences on the positive subscale. Age showed no correlation with attitudes. There was a more favorable attitude to learning communication skills among the women participants than among the men participants (P=0.006).
Conclusion
Despite positive general attitudes toward learning communication skills, the difference in attitude between the genders, academic years 2 and 5, and the subsequent classes suggest a re-evaluation of the curriculum and teaching methods to facilitate appropriate course structure according to the academic years and a learning process that addressees gender differences.

Citations

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Attitudes toward learning communication skills among Iranian medical students
Naser Yousefzadeh Kandevani, Ali Labaf, Azim Mirzazadeh, Pegah Salimi Pormehr
BMC Medical Education.2024;[Epub] CrossRef

Students’ performance of and perspective on an objective structured practical examination for the assessment of preclinical and practical skills in biomedical laboratory science students in Sweden: a 5-year longitudinal study: Catharina Hultgren, Annica Lindkvist, Sophie Curbo, Maura Heverin; J Educ Eval Health Prof. 2023;20:13. Published online April 6, 2023; DOI: https://doi.org/10.3352/jeehp.2023.20.13

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Abstract PDF Supplementary Material: Purpose
It aims to find students’ performance of and perspectives on an objective structured practical examination (OSPE) for assessment of laboratory and preclinical skills in biomedical laboratory science (BLS). It also aims to investigate the perception, acceptability, and usefulness of OSPE from the students’ and examiners’ point of view.
Methods
This was a longitudinal study to implement an OSPE in BLS. The student group consisted of 198 BLS students enrolled in semester 4, 2015–2019 at Karolinska University Hospital Huddinge, Sweden. Fourteen teachers evaluated the performance by completing a checklist and global rating scales. A student survey questionnaire was administered to the participants to evaluate the student perspective. To assess quality, 4 independent observers were included to monitor the examiners.
Results
Almost 50% of the students passed the initial OSPE. During the repeat OSPE, 73% of the students passed the OSPE. There was a statistically significant difference between the first and the second repeat OSPE (P<0.01) but not between the first and the third attempt (P=0.09). The student survey questionnaire was completed by 99 of the 198 students (50%) and only 63 students responded to the free-text questions (32%). According to these responses, some stations were perceived as more difficult, albeit they considered the assessment to be valid. The observers found the assessment protocols and examiner’s instructions assured the objectivity of the examination.
Conclusion
The introduction of an OSPE in the education of biomedical laboratory scientists was a reliable, and useful examination of practical skills.

Review

Factors associated with medical students’ scores on the National Licensing Exam in Peru: a systematic review: Javier Alejandro Flores-Cohaila; J Educ Eval Health Prof. 2022;19:38. Published online December 29, 2022; DOI: https://doi.org/10.3352/jeehp.2022.19.38

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Abstract PDF Supplementary Material

Purpose
This study aimed to identify factors that have been studied for their associations with National Licensing Examination (ENAM) scores in Peru.
Methods
A search was conducted of literature databases and registers, including EMBASE, SciELO, Web of Science, MEDLINE, Peru’s National Register of Research Work, and Google Scholar. The following key terms were used: “ENAM” and “associated factors.” Studies in English and Spanish were included. The quality of the included studies was evaluated using the Medical Education Research Study Quality Instrument (MERSQI).
Results
In total, 38,500 participants were enrolled in 12 studies. Most (11/12) studies were cross-sectional, except for one case-control study. Three studies were published in peer-reviewed journals. The mean MERSQI was 10.33. A better performance on the ENAM was associated with a higher-grade point average (GPA) (n=8), internship setting in EsSalud (n=4), and regular academic status (n=3). Other factors showed associations in various studies, such as medical school, internship setting, age, gender, socioeconomic status, simulations test, study resources, preparation time, learning styles, study techniques, test-anxiety, and self-regulated learning strategies.
Conclusion
The ENAM is a multifactorial phenomenon; our model gives students a locus of control on what they can do to improve their score (i.e., implement self-regulated learning strategies) and faculty, health policymakers, and managers a framework to improve the ENAM score (i.e., design remediation programs to improve GPA and integrate anxiety-management courses into the curriculum).

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Performance of ChatGPT on the Peruvian National Licensing Medical Examination: Cross-Sectional Study
Javier A Flores-Cohaila, Abigaíl García-Vicente, Sonia F Vizcarra-Jiménez, Janith P De la Cruz-Galán, Jesús D Gutiérrez-Arratia, Blanca Geraldine Quiroga Torres, Alvaro Taype-Rondan
JMIR Medical Education.2023; 9: e48039. CrossRef

Educational/Faculty development material

Common models and approaches for the clinical educator to plan effective feedback encounters: Cesar Orsini, Veena Rodrigues, Jorge Tricio, Margarita Rosel; J Educ Eval Health Prof. 2022;19:35. Published online December 19, 2022; DOI: https://doi.org/10.3352/jeehp.2022.19.35

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3 Crossref

Abstract PDF Supplementary Material

Giving constructive feedback is crucial for learners to bridge the gap between their current performance and the desired standards of competence. Giving effective feedback is a skill that can be learned, practiced, and improved. Therefore, our aim was to explore models in clinical settings and assess their transferability to different clinical feedback encounters. We identified the 6 most common and accepted feedback models, including the Feedback Sandwich, the Pendleton Rules, the One-Minute Preceptor, the SET-GO model, the R2C2 (Rapport/Reaction/Content/Coach), and the ALOBA (Agenda Led Outcome-based Analysis) model. We present a handy resource describing their structure, strengths and weaknesses, requirements for educators and learners, and suitable feedback encounters for use for each model. These feedback models represent practical frameworks for educators to adopt but also to adapt to their preferred style, combining and modifying them if necessary to suit their needs and context.

Citations

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Navigating power dynamics between pharmacy preceptors and learners
Shane Tolleson, Mabel Truong, Natalie Rosario
Exploratory Research in Clinical and Social Pharmacy.2024; 13: 100408. CrossRef
Feedback in Medical Education—Its Importance and How to Do It
Tarik Babar, Omer A. Awan
Academic Radiology.2024;[Epub] CrossRef
Feedback conversations: First things first?
Katharine A. Robb, Marcy E. Rosenbaum, Lauren Peters, Susan Lenoch, Donna Lancianese, Jane L. Miller
Patient Education and Counseling.2023; 115: 107849. CrossRef

Research articles

Possibility of independent use of the yes/no Angoff and Hofstee methods for the standard setting of the Korean Medical Licensing Examination written test: a descriptive study: Do-Hwan Kim, Ye Ji Kang, Hoon-Ki Park; J Educ Eval Health Prof. 2022;19:33. Published online December 12, 2022; DOI: https://doi.org/10.3352/jeehp.2022.19.33

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Abstract PDF Supplementary Material

Purpose
This study aims to apply the yes/no Angoff and Hofstee methods to actual Korean Medical Licensing Examination (KMLE) 2022 written examination data to estimate cut scores for the written KMLE.
Methods
Fourteen panelists gathered to derive the cut score of the 86th KMLE written examination data using the yes/no Angoff method. The panel reviewed the items individually before the meeting and shared their respective understanding of the minimum-competency physician. The standard setting process was conducted in 5 rounds over a total of 800 minutes. In addition, 2 rounds of the Hofstee method were conducted before starting the standard setting process and after the second round of yes/no Angoff.
Results
For yes/no Angoff, as each round progressed, the panel’s opinion gradually converged to a cut score of 198 points, and the final passing rate was 95.1%. The Hofstee cut score was 208 points out of a maximum 320 with a passing rate of 92.1% at the first round. It scored 204 points with a passing rate of 93.3% in the second round.
Conclusion
The difference between the cut scores obtained through yes/no Angoff and Hofstee methods did not exceed 2% points, and they were within the range of cut scores from previous studies. In both methods, the difference between the panelists decreased as rounds were repeated. Overall, our findings suggest the acceptability of cut scores and the possibility of independent use of both methods.

Citations

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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
Presidential address: improving item validity and adopting computer-based testing, clinical skills assessments, artificial intelligence, and virtual reality in health professions licensing examinations in Korea
Hyunjoo Pai
Journal of Educational Evaluation for Health Professions.2023; 20: 8. CrossRef

Equal Z standard-setting method to estimate the minimum number of panelists for a medical school’s objective structured clinical examination in Taiwan: a simulation study: Ying-Ying Yang, Pin-Hsiang Huang, Ling-Yu Yang, Chia-Chang Huang, Chih-Wei Liu, Shiau-Shian Huang, Chen-Huan Chen, Fa-Yauh Lee, Shou-Yen Kao, Boaz Shulruf; J Educ Eval Health Prof. 2022;19:27. Published online October 17, 2022; DOI: https://doi.org/10.3352/jeehp.2022.19.27

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Abstract PDF Supplementary Material: Purpose
Undertaking a standard-setting exercise is a common method for setting pass/fail cut scores for high-stakes examinations. The recently introduced equal Z standard-setting method (EZ method) has been found to be a valid and effective alternative for the commonly used Angoff and Hofstee methods and their variants. The current study aims to estimate the minimum number of panelists required for obtaining acceptable and reliable cut scores using the EZ method.
Methods
The primary data were extracted from 31 panelists who used the EZ method for setting cut scores for a 12-station of medical school’s final objective structured clinical examination (OSCE) in Taiwan. For this study, a new data set composed of 1,000 random samples of different panel sizes, ranging from 5 to 25 panelists, was established and analyzed. Analysis of variance was performed to measure the differences in the cut scores set by the sampled groups, across all sizes within each station.
Results
On average, a panel of 10 experts or more yielded cut scores with confidence more than or equal to 90% and 15 experts yielded cut scores with confidence more than or equal to 95%. No significant differences in cut scores associated with panel size were identified for panels of 5 or more experts.
Conclusion
The EZ method was found to be valid and feasible. Less than an hour was required for 12 panelists to assess 12 OSCE stations. Calculating the cut scores required only basic statistical skills.

Is it possible to introduce an interview to the Korean Medical Licensing Examination to assess professional attributes?: a survey-based observational study: Seung-Joo Na, HyeRin Roh, Kyung Hee Chun, Kyung Hye Park, Do-Hwan Kim; J Educ Eval Health Prof. 2022;19:10. Published online May 10, 2022; DOI: https://doi.org/10.3352/jeehp.2022.19.10

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Abstract PDF Supplementary Material: Purpose
This study aimsed to gather opinions from medical educators on the possibility of introducing an interview to the Korean Medical Licensing Examination (KMLE) to assess professional attributes. Specifically following topics were dealt with: the appropriate timing and tool to assess unprofessional conduct; ; the possiblity of prevention of unprofessional conduct by introducing an interview to the KMLE; and the possibility of implementation of an interview to the KMLE.
Methods
A cross-sectional study approach based on a survey questionnaire was adopted. We analyzed 104 pieces of news about doctors’ unprofessional conduct to determine the deficient professional attributes. We derived 24 items of unprofessional conduct and developed the questionnaire and surveyed 250 members of the Korean Society of Medical Education 2 times. Descriptive statistics, cross-tabulation analysis, and Fisher’s exact test were applied to the responses. The answers to the open-ended questions were analyzed using conventional content analysis.
Results
In the survey, 49 members (19.6%) responded. Out of 49, 24 (49.5%) responded in the 2nd survey. To assess unprofessional conduct, there was no dominant timing among basic medical education (BME), KMLE, and continuing professional development (CPD). There was no overwhelming assessment tool among written examination, objective structured clinical examination, practice observation, and interview. Response rates of “impossible” (49.0%) and “possible” (42.9%) suggested an interview of the KMLE prevented unprofessional conduct. In terms of implementation, “impossible” (50.0%) was selected more often than “possible” (33.3%).
Conclusion
Professional attributes should be assessed by various tools over the period from BME to CPD. Hence, it may be impossible to introduce an interview to assess professional attributes to the KMLE, and a system is needed such as self-regulation by the professional body rather than licensing examination.

Review

Educational applications of metaverse: possibilities and limitations: Bokyung Kye, Nara Han, Eunji Kim, Yeonjeong Park, Soyoung Jo; J Educ Eval Health Prof. 2021;18:32. Published online December 13, 2021; DOI: https://doi.org/10.3352/jeehp.2021.18.32

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Abstract PDF Supplementary Material

This review aims to define the 4 types of the metaverse and to explain the potential and limitations of its educational applications. The metaverse roadmap categorizes the metaverse into 4 types: augmented reality, lifelogging, mirror world, and virtual reality. An example of the application of augmented reality in medical education would be an augmented reality T-shirt that allows students to examine the inside of the human body as an anatomy lab. Furthermore, a research team in a hospital in Seoul developed a spinal surgery platform that applied augmented reality technology. The potential of the metaverse as a new educational environment is suggested to be as follows: a space for new social communication; a higher degree of freedom to create and share; and the provision of new experiences and high immersion through virtualization. Some of its limitations may be weaker social connections and the possibility of privacy impingement; the commission of various crimes due to the virtual space and anonymity of the metaverse; and maladaptation to the real world for students whose identity has not been established. The metaverse is predicted to change our daily life and economy beyond the realm of games and entertainment. The metaverse has infinite potential as a new social communication space. The following future tasks are suggested for the educational use of the metaverse: first, teachers should carefully analyze how students understand the metaverse; second, teachers should design classes for students to solve problems or perform projects cooperatively and creatively; third, educational metaverse platforms should be developed that prevent misuse of student data.

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Brief report

Newly appointed medical faculty members’ self-evaluation of their educational roles at the Catholic University of Korea College of Medicine in 2020 and 2021: a cross-sectional survey-based study: Sun Kim, A Ra Cho, Chul Woon Chung; J Educ Eval Health Prof. 2021;18:28. Published online November 5, 2021; DOI: https://doi.org/10.3352/jeehp.2021.18.28

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Abstract PDF Supplementary Material

This study aimed to investigate the degree to which newly appointed medical faculty members at the Catholic University of Korea are aware of Harden and Crosby’s 12 educational roles and to identify their preferred educational roles. A 12-item survey questionnaire was distributed to 110 participants, and 100 responses were included in the analysis. The respondents gave the highest score to “clinical or practical teacher” and the lowest score to “curriculum planner” for their current personal competencies. For their preferred personal future competencies, they assigned the highest score to “on the job role model” and the lowest score to “student assessor.” They gave almost equally high values to all 12 roles. However, individual faculty members had different preferences for educational roles. Accordingly, medical schools need to plan and implement customized faculty development programs, and efforts to provide appropriate educational roles according to individual faculty members’ preferences are needed.

Citations

Citations to this article as recorded by

Self-directed learning quotient and common learning types of pre-medical students in Korea by the Multi-Dimensional Learning Strategy Test 2nd edition: a descriptive study
Sun Kim, A Ra Cho, Chul Woon Chung
Journal of Educational Evaluation for Health Professions.2022; 19: 32. CrossRef

Research article

Definition of character for medical education based on expert opinions in Korea: Yera Hur; J Educ Eval Health Prof. 2021;18:26. Published online September 29, 2021; DOI: https://doi.org/10.3352/jeehp.2021.18.26

4,869 View
240 Download
3 Web of Science
3 Crossref

Abstract PDF Supplementary Material

Purpose
This follow-up study focused on 3 overarching questions: what keywords can be extracted from experts’ definitions of character?; what is the operational definition of character for medical students?; and what possible solutions can be suggested to address the issues of character education that were identified in the previous study?
Methods
Sixty-three medical education experts recruited through expert sampling and 19 non-medical education experts recruited through snowball sampling answered a questionnaire that addressed the 3 major questions of the study. The responses were analyzed for descriptive statistics with supplementary keyword extraction tools, including the Cortical and Monkey keyword extractors.
Results
A total of 93 definitional statements were counted, and 138 keyword terms were extracted. The top 5 keyword terms mentioned by the medical education experts were “patient”, “empathy”, “qualities”, “attitude”, and “ability”. These keyword terms were quite different from those mentioned by the non-medical education experts. Based on the extracted keywords, an operational definition of character education by the medical education expert group was presented as follows: the basic qualities and ability to empathize with patients affected by illness based on respect for patients and others. Various methods were proposed to solve the issue of character education, and many of them pointed to curriculum development, such as improvements in teaching and learning methods and evaluation methods, including role modeling.
Conclusion
A clear statement of the concept of character education is the start to resolve issues of character education. Character education improvements will be possible at the institutional level according to the above results.

Citations

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BMC Medical Education.2022;[Epub] CrossRef

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