Journal of Advances in Medical Education & Professionalism

Review article

Integrating Artificial Intelligence in Medical Education: A Meta-Synthesis of Potentials and Pitfalls of ChatGPT

AHMAD KEYKHA; BEHESHTEH FAZLALI; SARA BEHRAVESH; ZOHREH FARAHMANDPOUR

Volume 13, Issue 3 , July 2025, Pages 155-172

https://doi.org/10.30476/jamp.2024.104617.2071

Abstract

Introduction: ChatGPT serves as a double-edged sword in education, offering either constructive information or potential challenges. Its impact ranges from being a transformative tool ... Read More Introduction: ChatGPT serves as a double-edged sword in education, offering either constructive information or potential challenges. Its impact ranges from being a transformative tool to a disruptive force, making it difficult to evaluate its educational efficacy comprehensively. In light of this complexity, the primary aim of this research was to investigate the opportunities and challenges associated with the integration of ChatGPT into the domain of medical education.Methods: The study utilized the Interaction Equivalency Theorem as its conceptual framework to guide the investigation. To achieve the research objectives, a meta-synthesis of the literature wasconducted to systematically integrate the findings of selected studies. Data collection involved comprehensive searches across specialized academic databases, including Science Direct, Springer, ERIC, Emerald, SAGE, Wiley Online Library, PubMed, and Google Scholar, focusing on publications from 2022 to 2024. 88 articles were meticulously selected based on their relevanceto the research topic. The data were then subjected to thematic analysis, facilitating the extraction of key insights and patterns to address the study objectives.Results: The findings were organized into four primary subthemes highlighting the opportunities presented by ChatGPT in medical education. These sub-themes encompassed benefits for educators, learners, curriculum development, and the learning process. Similarly, the challenges related to the integration of ChatGPT were categorized into four primary sub-themes: addressing the difficulties experienced by educators, learners, curriculum development, and the learning process. Together, these challenges were further delineated into 11 secondary sub-themes,offering a comprehensive analysis of the complexities involved.Conclusion: The findings suggest that improving educational efficiency, assisting with self-development, enhancing communication skills, creating and expanding curriculum, and improving the learning environment are opportunities for utilizing ChatGPT. The study outcomes also reveal that lack of technological knowledge, negative attitudes, reduction in education quality, diminishing students’ capabilities, reducing learning quality, flaws in learning development, difficulties in designing educational content, and bias in learning evaluation are challenges of applying ChatGPT in medical education.

Review article

Intelligent Assessment Systems in Medical Education: A Systematic Review

MAJID ALIZADEH; MARYAM JAFAR SAMERI

Volume 13, Issue 3 , July 2025, Pages 173-190

https://doi.org/10.30476/jamp.2024.104560.2068

Abstract

Introduction: Using Intelligent Assessment Systems (IAS) in medical education has garnered attention as an advanced tool for enhancing educational processes and student evaluation. ... Read More Introduction: Using Intelligent Assessment Systems (IAS) in medical education has garnered attention as an advanced tool for enhancing educational processes and student evaluation. These systems leverage advanced algorithms to rapidly assess the students’ performance and learning progress. This systematic review aimed to examine the role and impact of Intelligent Assessment Systems in improving educational processes, academic evaluation, and learning progress in medical students compared to traditional assessment methods.Methods: This study was conducted using the PRISMA framework for reporting systematic review articles. Databases such as Embase, PubMed, ProQuest, Web of Science, and Scopus up to March 2024 were reviewed using relevant keywords. Eligible articles were selected and evaluated based on predefined inclusion and exclusion criteria.Results: Out of 2741 articles identified, 10 studies were selected for final analysis. This systematic review analyzed 10 studies, demonstrating that interactive assessment systems (IAS) can enhance learning outcomes by up to 40% in certain settings. The findings emphasized the benefits of immediate feedback and reduced instructor workload. The significant role of IAS in enhancing student performance, providing immediate feedback and reducing the workload of instructors was indicated. These systems, through the use of machine learning algorithms and virtual reality simulators, enable more accurate and comprehensive assessment of students’ clinical and cognitive skills. Conclusion: Intelligent Assessment Systems (IAS) significantly improve educational processes and academic evaluation by providing immediate and precise feedback, enhancing student self-efficacy and self-awareness and reducing the training time and costs. The successful implementation of IAS requires careful system design, user training, and continuous technical support. Further studies are recommended to explore the advantages and challenges of these systems and to optimize their implementation in medical education. The long-term impacts of IAS and scalability across educational contexts require further studies. In conclusion, IAS offers transformative potential in medical education globally, provided that challenges are addressed.

Original Article

Nursing Students’ Perspectives on the Relationship between Virtual Reality Simulation and Clinical Decision-Making, Confidence, and Anxiety: A Cross-Sectional Study

HAZEM ALFANASH; MAHMOUD AL-KALALDEH; KHALDOON ALNAWAFLEH; WESAM ALMAGHARBEH

Volume 13, Issue 3 , July 2025, Pages 191-197

https://doi.org/10.30476/jamp.2025.105619.2115

Abstract

Introduction: This study addresses this gap by assessing the relationship of VR simulation with improving clinical decisionmaking, confidence, and anxiety reduction among nursing students. ... Read More Introduction: This study addresses this gap by assessing the relationship of VR simulation with improving clinical decisionmaking, confidence, and anxiety reduction among nursing students. The aim of this study is the relationship between virtual reality simulation and their clinical decision-making, confidence, and anxiety reduction using a cross-sectional study from the perspectives of nursing students.Methods: This cross-sectional study surveyed 200 nursing students enrolled in clinical courses utilizing virtual reality (VR) simulation for educational purposes. A structured questionnairewas used to assess their clinical decision-making, confidence, and anxiety reduction following the VR simulation course. The survey included scales validated through a panel of experts andquestionnaire validation methodologies, using a 5-point Likert scale. Descriptive statistics were used to summarize the data, and inferential statistical tests, including Pearson’s correlation and independent-sample t-tests, were conducted to examine the associations. Multiple linear regression analysis was performed to assess the predictive value of confidence and anxiety on clinical decision-making while controlling demographic variables.Results: A total of 200 nursing students participated in the study. The mean (SD) clinical decision-making score was 3.16 (1.23) out of 5, while confidence and anxiety reduction scores were 2.64 (1.34) and 2.49 (1.32), respectively. No significant correlation was found between decision-making and confidence (r=-0.079, p=0.264) or anxiety scores (r=0.121, p=0.088), but confidence and anxiety scores showed a weak direct correlation (r=0.180, p=0.011). Multiple linear regression analysis revealed that confidence and anxiety were not significant predictors of decision-making, but gender was a significant predictor, with males scoring higher (β=0.19, p=0.041).Conclusions: While VR directly influences decision-making, it has a limited association with changes in nursing students’ confidence and anxiety levels. These findings suggest that VRsimulation alone may not be sufficient for enhancing confidence and reducing anxiety and should be integrated with other instructional strategies to maximize its effectiveness in nursing education. Future studies should explore complementary training methods to improve clinical preparedness.

ChatGPT and Medical Research: A Meta-Synthesis of Opportunities and Challenges

Volume 12, Issue 3 , July 2024, , Pages 135-147

https://doi.org/10.30476/jamp.2024.101068.1910

Abstract

Introduction: The utility of ChatGPT in research is ambiguous, serving as both a boon and bane and presenting challenges and opportunities. Accordingly, this study aimed to delineate ... Read More Introduction: The utility of ChatGPT in research is ambiguous, serving as both a boon and bane and presenting challenges and opportunities. Accordingly, this study aimed to delineate themerits and demerits of ChatGPT within the realm of research.Methods: A meta-synthesis methodology involving a seven-step process was adopted to pursue the research objectives. Data were collected from comprehensive studies across specialized research databases, such as Science Direct, Springer, Eric, Emerald, Sage Journals, Wiley Online Library, PubMed, and Google Scholar, within the time frame spanning from 2022 to 2023. A total of 57 articles were meticulously chosen for analysis through judgmental sampling. Subsequently, key concepts were distilled from these articles and categorized using the thematic analysis approach while considering Karl Llewellyn’s octagonal model from 1963.Results: The outcomes underwent scrutiny employing the thematic analysis strategy devised by Wolcott. The results about the capabilities and constraints of ChatGPT encompass eight dimensions, including formulating the research problem, reviewing relevant literature, selecting an appropriate research design, defining the population and choosing the sample, collecting data, analyzing data, interpreting data, and discussing and drawing conclusions. The credibility of these dimensions was substantiated through adherence to the criteria established by Lincoln and Guba.Conclusion: ChatGPT manifests myriad potentialities and constraints within the research purview based on the results. In light of the expeditious progression of artificial intelligence acrossmultifarious domains, integrating this technological paradigm in research becomes an inexorable imperative, and excluding its use in research is untenable. Thus, policymakers and higher education strategists should devise policies that harness ChatGPT’s potential in research endeavors, engendering many opportunities.

Comparison of the Effects of E-learning Blended with Collaborative Learning and Lecture-Based Teaching Approaches on Academic Self-Efficacy among Undergraduate Nursing Students: A Quasi-Experimental Study

Volume 12, Issue 2 , April 2024, , Pages 102-110

https://doi.org/10.30476/jamp.2024.99100.1828

Abstract

Introduction: Applying new technologies in teaching has led to the phenomenon of blended learning (BL), which is currently flourishing as a specific requirement for higher self-efficacyand ... Read More Introduction: Applying new technologies in teaching has led to the phenomenon of blended learning (BL), which is currently flourishing as a specific requirement for higher self-efficacyand success in increasingly complex healthcare environments. Although various forms of novel education are on the rise worldwide, the effects of electronic learning (EL), combined withcollaborative learning (CL) and lecture-based teaching (LBT) approaches, have not yet been validated on academic self-efficacy among undergraduate nursing students.Methods: Utilizing a pre-/post-test comparison-group design, this quasi-experimental study was conducted on 70 undergraduate nursing students of Urmia University of Medical Sciences, Urmia, Iran, selected by the census sampling technique in 2020. The eligible participants were allocated to intervention groups, viz., the EL+LBT group (n=34) and the EL+CL group (n=36). A learning management system (LMS) was used for both intervention groups along with the LBT approach, and then 10 steps were integrated into the CL approach during 14 sessions, lasting 150 minutes. Afterward, a demographic information form and the College Academic Self-Efficacy Scale (CASES) were administered to collect the data. The data were analyzed using descriptive statistics, Chi-square test, independent-samples t-test, and analysis of covariance (ANCOVA).Results: No significant difference was observed in the CASE scores between the students were taught using the EL+LBT (113.76±16.98) and the EL+CL approaches (107.66±16.70) beforethe interventions (P=0.136). However, the CL+EL approaches resulted in the highest changes in the CASE scores at the pre-(107.66±16.70) and post-test (119.08±25.49) stages (P=0.019). Moreover, the female students attending the CL+EL classrooms experienced significantly positive differences in their CASE scores (127.12±30.34), compared to the males (112.65±19.30) (P=0.011).Conclusion: Blending the EL and CL approaches significantly promoted CASE among the undergraduate nursing students in this study by providing sufficient collaboration, essential educational equipment, and better technical support.

Investigating the Effect of Online Gamification on Electrocardiogram Interpretation and Self-Directed Learning in Nursing Students

Volume 12, Issue 3 , July 2024, , Pages 199-207

https://doi.org/10.30476/jamp.2024.101396.1925

Abstract

Introduction: Knowing and interpreting the Electrocardiogram correctly and taking care based on it is one of the most important ways to save the patient’s life. Therefore, this ... Read More Introduction: Knowing and interpreting the Electrocardiogram correctly and taking care based on it is one of the most important ways to save the patient’s life. Therefore, this study aimed toinvestigate the effect of online gamification on the ability to interpret Electrocardiograms and Self-Directed Learning in nursing students.Methods: The present study was carried out quasi-experimentally on 44 nursing students (22 participants for each group) in the fifth semester in Ilam city in 2023 using a convenience sampling method by four permutations balanced block randomization to control and intervention groups. During four sessions in four weeks, the participants in the intervention group receivedElectrocardiogram interpretation as training on the Storyline platform and playing games in the Socrative software. The control group received the same content in the form of education from the same lecturer. ECG Interpretation Learning Test, Self-Directed Learning, Mini-Mental Status Examination, and demographic questionnaires were filled out before the intervention (pre-test).Then, Electrocardiogram Interpretation Learning Test and Self-Directed Learning questionnaires were completed two weeks after the end of the intervention (post-test), and the data were analyzed in the standard error of 0.05 using Shapiro-Wilk, independent t-test, paired t-test, chi-square, and multiple linear regression tests in SPSS V.16.Results: The mean and standard deviation of the participants’age was 21.35±1.02, and 59% of the samples were male. Before the intervention, no significant difference was observed between the two groups, but after the intervention, the mean and standard deviation of the ECG interpretation scores in the intervention group increased significantly (14.1±2.94) compared to the control group (8.8±1.36) (P=0.007). Also, Self-Directed Learning in the intervention group (168±10.42) compared to the control group (125±4.3) showed a statistically significant difference (P=0.003).Conclusion: Using online gamification as a new educational method in nursing students improves the ability to interpret Electrocardiograms and Self-Directed Learning. It is suggested that this method should be used to teach lessons that are more useful and important at the hospital.

Study of Deep Learning in Medical Education: Opportunities, Achievements and Future Challenges

Volume 12, Issue 3 , July 2024, , Pages 148-162

https://doi.org/10.30476/jamp.2024.99740.1853

Abstract

Introduction: In this era of progress, interest has developed regarding advancing deep learning (DL) in medicine. However, there has been reluctance to use deep learning, particularly ... Read More Introduction: In this era of progress, interest has developed regarding advancing deep learning (DL) in medicine. However, there has been reluctance to use deep learning, particularly among medical educators. The limitations of previous research were examined in this study, along with the extent to which DL can be used in medical education and its potential impact on educational quality. We were interested in discussing DL’s prospects, and determining whether we could benefit from it in medical education.Methods: Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol was used to manage this review procedure. Six databases were searched carefully to obtain relevant studies. Our search identified 981 articles from the database based on our standards. After filtering the duplicated articles, 11 studies were included in the systematic review.Results: The results showed that DL applications attracted researchers’ attention in the medical and education technology owing to their effectiveness to provide the personalized assistanceand feedback. Furthermore, the majority of research concentrated on teaching medical students how to utilize DL applications in the classroom, and all of them tried to improve medical students’proficiency with DL instruments in practical applications. Deep learning components in medical learning environments have two segments—in the educational settings like speech recognitionor Video content analysis for affecting students’ learning, and in the medical settings, applying deep learning from diagnosis to prevention. An integration of them can work better in medicaleducation.Conclusion: Medical education uses DL to improve the students’ education. DL is a powerful instrument which has become more famous in terms of superb outcomes. Besides, using DL in medical education is likely to continue as a hotly debated area of research and a well-known classroom strategy.

Empowering Medical Education: Unveiling the Impact of Reflective Writing and Tailored Assessment on Deep Learning

Volume 12, Issue 3 , July 2024, , Pages 163-171

https://doi.org/10.30476/jamp.2024.101594.1938

Abstract

Introduction: Reflective thinking offers learners insight and encourages deeper understanding by leveraging past experiences. This study explores the impact of reflective writing, a ... Read More