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Background & Objective: Aligning faculty members' learning styles with their teaching approaches is a complicated topic in education. Understanding these inclinations can help enhance pedagogical practices and build a more inclusive learning environment. Thus, this study examined the relationship between learning style preferences and teaching technique choices among Iranian faculty members. Material & Methods: From May to July 2022, a cross-sectional online survey was conducted among faculty members at Iranian medical universities via the Porsline website. Virtual snowball sampling was used to recruit 526 individuals. The VARK questionnaire was translated into Persian and showed excellent reliability, with a Cronbach's alpha of 0.94. The final data collection tools included the translated VARK questionnaire, self-assessment questions about teaching methods, university resources, and digital media center equipment. Analytical methods included descriptive statistics, logistic regression analysis, and chi-square testing for data evaluation. Results: The survey found that clinical teachers preferred reading and writing (54%), whereas fundamental science educators preferred visual-auditory and reading-writing. The effect of gender, field of study, learning style, age, and professional academic factors on the dependent variable, teaching method, was investigated using chi-square tests and logistic regression. The findings revealed that while there was no significant relationship between the variable gender and teaching method, significant associations were found with the variables field of study, learning style, age, and professional academic. Notably, it was observed that the effect size of field of study, age, and professional academic on teaching method is small, while for learning style, it is medium in magnitude. Conclusion: The study uncovers a significant correlation between learning styles and teaching methods, suggesting that their learning backgrounds may shape teachers' teaching methods. [ABSTRACT FROM AUTHOR]

Background: Personalized business courses are an effective way to learn the basics of a business or industry. This study analyzed the effectiveness of the business course offered at Smart University of Medical Sciences. Method: This study evaluated the personalized business course using retrospective data to assess learner satisfaction. The course was delivered entirely online but was flexible in delivery. It was designed according to the ASSURE educational model, which emphasizes content presentation and personalization of the learning experience. The course was attended by 132 participants. In this study, the validity of the data collection instrument was confirmed by ten SMUMS faculty members, after which a preliminary study was conducted with 10 pilot samples, yielding a Cronbach coefficient of 96%. For the translation into Persian, the World Health Organization guide was used as a methodological model. Results: A total of 15 out of 18 participants from the Ministry of Science were satisfied with the course, as were 87 out of 107 participants from the Ministry of Health. Satisfaction with the course was higher among males than females, (84.6% versus 74.3%). The course was rated satisfactory by 81.4% of participants. Conclusion: Satisfaction with the course may lead to similar courses being offered in the future. This personalized business course was a great success. Participants were satisfied with the content they learned and the progress they made. [ABSTRACT FROM AUTHOR]

Background: Educational evaluation is one of the main pillars of educational systems, and course evaluation is a survey that students or course members complete at the end of a class or academic course. This study aims to evaluate the 'Artificial Intelligence Fall School Program' at Smart University of Medical Sciences. Methods: This study was conducted by collecting on various aspects of the course, including the course structure, teaching methods, instructors, scientific evaluations, and pre- and post-course tests. The course evaluation was conducted using an online questionnaire. In the initial phase of the study, the sample size was determined to be 96 participants, as calculated using Cochran's formula. The research data were statistically analyzed at two levels: descriptive and inferential. Descriptive analysis was performed using statistical indicators such as frequency, percentage, and mean. The inferential analysis was conducted using the paired t test. Analyses were performed using SPSS 22. Results: From the viewpoint of the participants, all artificial intelligence (AI) schools in the field of medical sciences were deemed satisfactory. A paired t test was used to analyze and compare the pre-test and post-test scores of participants in the Fall AI schools. The results indicated an increase in the post-test scores of participants, following their involvement in the seven-week AI schools, compared to their pre-test scores. Conclusion: This evaluative study offers crucial insights into the effectiveness of the "Fall AI Schools" training program in fostering AI proficiency among medical professionals. The quantitative findings reveal a statistically significant positive response and learning outcomes among the participants across the seven specialized schools. [ABSTRACT FROM AUTHOR]

Background: Co- word analysis is one of the content analysis methods used in scientometric studies and mapping the scientific structure of various fields. The purpose of the present research is to map the structure of distance education using the co-word analysis. Methods: The research method is content analysis using co- word analysis. The research population are 31607 documents indexed in the field of distance education domain in the Web of Science database from 1985 to 2016. For data analysis, the "UCInet" and "BibExcel" softwares have been used. In this research, the symmetric matrix as well as the cluster analysis and the strategic diagram was used for analyzing the data. Results: The findings showed that the concepts of electronic learning and blended learning had the highest frequency in distance education research. The pairs of "e-learning- blended learning", "e-learningeducation and training", and "higher education-e-learning" with 446, 328, and 302 word co-occurrences respectively, and took the first to third places in the field of distance education studies. Findings on hierarchical clustering led to the formation of 13 clusters in this field. Conclusion: The results of this study showed that based on the coword analysis, the structure of the distance education is composed of thirteen clusters as follows: "The process of designing e-learning environments", "E-literacy", "The role of information and communication technologies in the process of teaching and learning", "Strengthening the process of virtual teaching and learning", "Educational scenario", "educational planning" and "Individual learning style" and "Learning and teaching quality", "Human interaction in the virtual environment", "educational feedback", "Educational system", and "Miscellaneous". Newly emerged fields of distance education include "human interaction in the virtual environment", "educational feedback", and "learning system". [ABSTRACT FROM AUTHOR]