Current status of mobile learning indicators in Universities of Medical Sciences
Background: The speed of advance in medical education, creativity in technology, limit time for new work has created new vision in medical education. Considering the importance of developing Iran's global position in the scientific and technological in Southwest Asia and the importance of impro...
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| Main Authors: | , , , , |
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| Format: | Book |
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Shahid Beheshti University of Medical Sciences,
2024-02-01T00:00:00Z.
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| Summary: | Background: The speed of advance in medical education, creativity in technology, limit time for new work has created new vision in medical education. Considering the importance of developing Iran's global position in the scientific and technological in Southwest Asia and the importance of improving the quality of learning and education, the present study identifies and examines the current status of mobile learning indicators in medical sciences universities. Methods: This study was applied in terms of purpose, descriptive-correlation in nature and survey method. The statistical population of the study consists of specialists from different medical groups. Based on Morgan's table, the sample size was estimated to be 200 people who were selected by simple random. Mobile learning components were extracted using text analysis and interviews with experts. In order to comply with the principle of validity in the questionnaire, in addition to the opinions of supervisors and advisors, the validity of factor analysis has been used. Cronbach's alpha coefficient was estimated above 0.7, so the reliability of the questionnaire was confirmed. For data analysis, exploratory factor analysis and univariate analysis were used in Spss23 software. Results: Four factors (infrastructure, organizational planning, tools and equipment, human resources) and 16 indicators explain about 79.9% of mobile learning variance. Also, according to the obtained results, there were significant differences between the current and desired conditions based on the values (sig<0.05) in all components. Conclusion: Designers of mobile learning tools should maximize the efficiency of this tool while paying attention to users' preferences. |
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| Item Description: | 10.22037/sdh.v10i1.44161 2423-7337 |