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Introduction: Corona virus has disrupted medical education in the world. Most medical schools try to use e-learning to maintain the standard learning of medical students in teaching hospitals. The aim of this study was to identify and explain the factors affecting the clinical education of medical students in distance education in coronary conditions .Method: This qualitative study was performed by content analysis method. Sample research was articles on virtual education, medical education and clinical education in Corona pandemics. 23 articles were selected for the final review. Open coding of articles was performed using MAXQDA10 software. In the next step, the codes were grouped based on conceptual and semantic similarity, and each category was named with the titles that indicated its characteristics. In order to check the validity of the research, the text of the articles was given to two medical education specialists to be coded . Results:The results of data analysis in the process led to the identification of 73 open codes, which finally by categorizing and analyzing the codes, 3 main categories and 7 central categories, including increasing the clinical competence of medical students in corona pandemic (reducing harm to patients using virtual education Improving the quality and quantity of learning using e-learning, increasing students' communication skills in virtual clinical education), Improving the quality of clinical education using the virtual education approach (creating and maintaining standard learning, creating a suitable platform for virtual clinical education), developing clinical education using elearning (reducing time and space constraints in clinical education using cyberspace, creating a simulation environment for clinical education) was formed. Conclusion: Decreasing the quality and quantity of medical education in medical universities over time has a negative effect on the treatment of patients and their health. Due to the corona pandemic and the reduction of medical education in teaching hospitals, e-learning as a new approach in learning can be used to improve the quality of clinical education.
Introduction: Corona virus has disrupted medical education in the world. Most medical schools try to use e-learning to maintain the standard learning of medical students in teaching hospitals. The aim of this study was to identify and explain the factors affecting the clinical education of medical students in distance education in coronary conditions .Method: This qualitative study was performed by content analysis method. Sample research was articles on virtual education, medical education and clinical education in Corona pandemics. 23 articles were selected for the final review. Open coding of articles was performed using MAXQDA10 software. In the next step, the codes were grouped based on conceptual and semantic similarity, and each category was named with the titles that indicated its characteristics. In order to check the validity of the research, the text of the articles was given to two medical education specialists to be coded . Results:The results of data analysis in the process led to the identification of 73 open codes, which finally by categorizing and analyzing the codes, 3 main categories and 7 central categories, including increasing the clinical competence of medical students in corona pandemic (reducing harm to patients using virtual education Improving the quality and quantity of learning using e-learning, increasing students' communication skills in virtual clinical education), Improving the quality of clinical education using the virtual education approach (creating and maintaining standard learning, creating a suitable platform for virtual clinical education), developing clinical education using elearning (reducing time and space constraints in clinical education using cyberspace, creating a simulation environment for clinical education) was formed. Conclusion: Decreasing the quality and quantity of medical education in medical universities over time has a negative effect on the treatment of patients and their health. Due to the corona pandemic and the reduction of medical education in teaching hospitals, e-learning as a new approach in learning can be used to improve the quality of clinical education.
Background: The integration of information technology into educational systems represents a dynamic educational paradigm that delineates modern education for effective engagement in the third millennium. However, prior to its implementation, efforts should be directed towards identifying the factors influencing its acceptance and utilization. Objectives: The present study aimed to investigate the factors influencing the acceptance of e-learning among professors and students of macro medical sciences universities in the third region based on the Davis model in the year 2023. Methods: This study employed a cross-sectional design. The research instrument consisted of a 25-item Davis questionnaire utilizing a 5-point Likert scale, which was distributed to the samples both in person and virtually following validation and reliability confirmation by experts and a pre-test. The study population comprised 308 professors and 400 students from macro medical sciences universities in Macro Region 3. Data analysis utilized descriptive statistics (frequency, percentage, mean, and standard deviation) and inferential statistics (correlation, analysis of variance, and related tests), using SPSS software version 19 and LISREL software for Structural Equation Modeling.Modeling. Results: Data analysis revealed that the structural model of acceptance of electronic learning technology among the students of the University of Medical Sciences in Macro Region 3 is appropriate and applicable in the academic community. The variable of ease of use on attitude towards use demonstrated a coefficient of 0.41 and a T score of 7.16, while the variable of usefulness on decision to use showed a coefficient of 0.46 and a T-score of 6.31. Additionally, usefulness on attitude towards use displayed a coefficient of 0.49 and a T score of 5.92. Moreover, the variable of attitude towards use on decision to use had a coefficient of 0.47 and a T score of 5.65. Finally, the variable of decision to use on use exhibited a coefficient of 0.49 and a T score of 6.42. Conclusions: Conducting preliminary studies to comprehend the current landscape and elucidate the influencing factors in this regard can facilitate the implementation of related programs and pave the way for their efficacy. Moreover, it is advisable for officials and policymakers to employ technology acceptance theories to deploy new systems and technologies, thereby understanding the factors contributing to their acceptance and application, mitigating the risk of failure and resource wastage, and enhancing the quality of education and service delivery.
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