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jmsthums 2025, 13(1): 88-104 |
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Gooran S, Mirmoghtadaie Z, Khoshgoftar Z, Keshavarz M. Identifying and prioritizing educational needs in e-learning students: a mixed-methods study. jmsthums 2025; 13 (1) :88-104
URL: http://jms.thums.ac.ir/article-1-1356-en.html
URL: http://jms.thums.ac.ir/article-1-1356-en.html
1- Department of E-Learning in Medical Sciences, School Medical Education and Learning Technologies, Shahid Beheshti University of Medical Sciences, Tehran, Iran
2- Department of Medical Education, School Medical Education and Learning Technologies, Shahid Beheshti University of Medical Sciences, Tehran, Iran
3- Department of E-Learning in Medical Sciences, School of Paramedical Sciences, Torbat Heydariyeh University of Medical Sciences, Torbat Heydariyeh, Iran
2- Department of Medical Education, School Medical Education and Learning Technologies, Shahid Beheshti University of Medical Sciences, Tehran, Iran
3- Department of E-Learning in Medical Sciences, School of Paramedical Sciences, Torbat Heydariyeh University of Medical Sciences, Torbat Heydariyeh, Iran
Abstract: (794 Views)
Background & Aim: The evolution of technology is transforming the way medical education is conducted, necessitating the accurate identification of students' learning needs to further enhance the quality of virtual training. A precise comprehension of these necessities can be used to design better educational programs and enable better online learning experiences. The present study aimed to identify the educational needs of e-learning students at Shahid Beheshti University of Medical Sciences and prioritize them.
Methods: This is a mixed-method research that utilized both qualitative and content analysis, as well as a quantitative survey. The qualitative stage was performed in 2020-2022 based on purposive and snowball sampling, and the interviews were held till data saturation. During the quantitative stage, 330 medical sciences students were administered the Diekelmann questionnaire modified to measure the perceived needs and their priority. Data analysis was performed using SPSS software version 26, and the level of significance was set at 5%.
Results: Qualitative interviews resulted in 53 initial concepts, which were distilled to six main categories: infrastructural challenges, monitoring and educational support, instructional content, assessment and evaluation, academic interaction, and challenges and opportunities in virtual learning. Quantitative results showed that "monitoring and support" received the highest priority score (4.91), followed by "assessment" (3.62), "infrastructural challenges" (3.29), "content-related issues" (2.92), and finally "interaction" (1.26).
Conclusion: The results demonstrate the imperative to augment monitoring, support systems, and evaluation of e-learning, especially with regard to potential infrastructural gaps and engagement; universities can better support and ultimately enhance student satisfaction (and e-learning virtual medical education effectiveness) by noting these issues.
Methods: This is a mixed-method research that utilized both qualitative and content analysis, as well as a quantitative survey. The qualitative stage was performed in 2020-2022 based on purposive and snowball sampling, and the interviews were held till data saturation. During the quantitative stage, 330 medical sciences students were administered the Diekelmann questionnaire modified to measure the perceived needs and their priority. Data analysis was performed using SPSS software version 26, and the level of significance was set at 5%.
Results: Qualitative interviews resulted in 53 initial concepts, which were distilled to six main categories: infrastructural challenges, monitoring and educational support, instructional content, assessment and evaluation, academic interaction, and challenges and opportunities in virtual learning. Quantitative results showed that "monitoring and support" received the highest priority score (4.91), followed by "assessment" (3.62), "infrastructural challenges" (3.29), "content-related issues" (2.92), and finally "interaction" (1.26).
Conclusion: The results demonstrate the imperative to augment monitoring, support systems, and evaluation of e-learning, especially with regard to potential infrastructural gaps and engagement; universities can better support and ultimately enhance student satisfaction (and e-learning virtual medical education effectiveness) by noting these issues.
Type of Study: Research |
Subject:
Special
Received: 2024/08/2 | Accepted: 2025/02/5 | Published: 2025/03/21
Received: 2024/08/2 | Accepted: 2025/02/5 | Published: 2025/03/21
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