The Coronavirus Disease 2019 (COVID-19) pandemic necessitated a rapid and unprecedented shift from traditional, in-person education to online modalities across the globe (Shah et al., 2020). This transformation posed significant challenges for medical education, which relies heavily on hands-on clinical experiences (Papapanou et al., 2022; Rose, 2020). Although institutions like Shiraz University of Medical Sciences in Iran had established Learning Management Systems (LMS) prior to the pandemic, resistance to e-learning adoption and varying levels of preparedness among faculty and students created substantial obstacles. Studies underscore that e-learning’s success in medical education depends on robust infrastructure, digital literacy, and adaptive pedagogy (Alsoufi et al., 2020; Delam et al., 2022; Hrastinski, 2008; Karimian et al., 2022; Subramanian and Rowland, 2022).

E-learning, defined as the use of electronic technologies to deliver and enhance education, typically combines synchronous and asynchronous methods (Howlett et al., 2009). While synchronous platforms offer real-time interaction, they are often hindered by connectivity issues, inadequate infrastructure, and limited engagement (Uppal et al., 2018). Conversely, asynchronous approaches are praised for their flexibility, enabling students to overcome geographical and time-related constraints (Hrastinski, 2008).

These challenges are not unique to Iran. Across low- and middle-income countries, students frequently encountered technological barriers, such as unreliable internet, insufficient access to devices, and lack of institutional support for digital learning (Ishak et al., 2022). In Kenya, for instance, medical students reported significant difficulties with internet connectivity and limited availability of smart devices, which not only disrupted their ability to attend online classes but also limited their engagement with interactive learning resources (Masika et al., 2015). Similarly, in Libya, students expressed dissatisfaction with the feasibility of implementing e-learning platforms. They cited poor infrastructure, insufficient technical support, and a lack of alignment between e-learning systems and their academic needs as major obstacles, which collectively undermined their learning experiences (Alsoufi et al., 2020). These issues highlight the disparities in readiness and capacity for e-learning implementation across different educational contexts (Moeinikia et al., 2022).

Conversely, countries with stronger digital infrastructures achieved more positive outcomes. For example, in Malaysia, the widespread availability of mobile technologies and robust digital frameworks, such as reliable internet access and institutionally supported e-learning platforms, enabled medical students to adapt more effectively to virtual education (Koh et al., 2014). Many students in Malaysia not only embraced online learning but also found it an effective supplement to traditional classroom education, particularly for accessing multimedia resources and improving time management. These contrasting experiences across countries underscore the importance of investing in technological infrastructure, providing equitable access to devices, and offering comprehensive training for both students and educators to ensure the success of e-learning initiatives (Al-Rikabi and Montazer, 2022).

Despite these contextual differences, one common theme across studies is the pivotal role of teacher-student interaction. Effective engagement can mitigate many challenges of e-learning, yet inadequate feedback and limited interaction during synchronous classes have been persistent issues (Alimi et al., 2021). Furthermore, the abrupt transition to online learning exposed the lack of preparedness among students and educators, underscoring the need for institutional support and digital literacy development (Nor and Mohamad, 2013).

This study aims to examine medical students’ perceptions of e-learning during the pandemic at Shiraz University of Medical Sciences. It explores how technological facilities, technical support, e-content quality, and teacher-student interactions shaped their experiences, while considering demographic factors such as age, gender, and access to resources. By addressing these dimensions, the study contributes to the broader discourse on e-learning in medical education, providing insights into how educational systems can better adapt to similar crises in the future.

Mainly, this study aims:

As shown in Table 1, the demographic information of those 507 students who responded to the online survey indicates that 343 (67.7%) were females. The highest percentage of the respondents, 207 (40.8%), were studying for a continuous bachelor’s degree. The mean age of the participants was 26.8 ± 23.7. Detailed demographic information is provided in Table 1.

We were following two main objectives in this research.

Q1. To identify medical students’ perceptions about learning in electronic environment during the COVID-19 pandemic. Findings indicate that all e-learning components significantly showed an average above the cut-off point (P < 0.01) except for the component of synchronous education (P = 0.14) (Figure 1).

Also, the mean and standard deviation (SD) for the participants’ viewpoints of each item are illustrated in Table 2.

Among the items (Table 2), the item with the lowest score was item 13: planned, regular, and sequential presentation of the lesson (3.01 ± 1.72). Also, see item 22 regarding the communication with the professor in the virtual class (3.37 ± 1.54) and item 12 regarding the platform of quizzes and exams in NAVID-LMS (3.38 ± 1.64).

Q2. To identify students’ perceptions about e-learning components, considering contextual variables including age, gender, degree, residence status, school, field of study, computer skills, and previous experience in e-learning.

Although a random sample of 507 students sought out to participate in this study, the findings and conclusions are limited in their generalizability because they were derived from only one medical university in Iran, and most specifically, the data were collected at an unusual time during the COVID-19 pandemic, when results of any research are significantly overshadowed by the disease. Furthermore, because of the university closure, the data were collected only electronically, so perhaps students who did not have access to the Internet could not fill out the questionnaire despite the likelihood of their having negative views regarding e-learning education.

With these caveats in mind, results have demonstrated that medical students had a positive e-learning experience during the lockdown. This finding parallels another research carried out during the lockdown. Duraku and Hoxha (2020) reported that although students faced challenges in terms of lack of attention in online classes due to various reasons, generally, they had a positive feeling toward e-learning because not only did it draw their attention psychologically away from the pandemic, but also learning-wise, they had more time for lessons and interactions with the professors.

Since the majority of Pakistani students had a negative attitude toward e-learning and were more attracted to face-to-face learning in the future, our findings are in direct conflict with the findings of the study done at the Pakistan College of Medicine and Dentistry. Their main concern was that they believed e-learning had little influence on their learning throughout the pandemic (Abbasi et al., 2020). Medical students’ e-learning experiences in the literature prior to COVID-19 reveal a mixed picture, with a higher proportion of medical studies indicating students’ positive views about e-learning than negative feelings toward it (Jang and Kim, 2014; Singh and Min, 2017). Surprisingly, during the pandemic, the attitudes of medical students in various Middle Eastern nations moved from positive to mediocre or unfavorable (Al-Balas et al., 2020; Gismalla et al., 2021; Ibrahim et al., 2021). This is likely due to the fact that prior to the pandemic, only fully trained lecturers would choose electronically assisted instruction, whereas, during the pandemic, all university lecturers and students were suddenly bombarded with technology upgrades, cultural acceptance, and reduced social and cultural interaction.

However, according to the findings of this study, medical students were dissatisfied with online synchronous classes, possibly because not all students could reliably log into synchronous classes because of geographical limitations, insufficient bandwidth, peer-to-peer traffic, and inadequate video streaming services. In our study, the variable of synchronous education received a lower overall score than the other divisions. There have been several studies that have found that students prefer asynchronous classrooms over live class sessions because, in the latter, professors do not have enough time to answer their inquiries and do not have the necessary abilities to adequately conduct virtual classes (Cole et al., 2014; Rehman and Fatima, 2021). It is possible that this dissatisfaction can be attributed to what Sims (1999) states about the types of interactions that a synchronous session requires in order to be successful: student-teacher interaction, student-learner interaction, learner-content interaction, and learner-interface interaction. Students’ class sizes at this medical university may also be a factor in their discontent with online programs. Studies have shown that online classrooms should not contain more than 30 people despite contradictory results on the link between class size and instructor effectiveness (Lowenthal et al., 2019). It was advised by Sieber (2005) and Lin et al. (2019) that a 12-student class size be used for new instructors to online teaching, regardless of the instructor’s prior online teaching experiences.

For undergraduate courses, Taft et al. (2019) recommend a maximum class size of 20 and between 8 and 15 for graduate courses; a class size that allowed students to engage in a way that didn’t make them feel alone or disjointed but also did not leave them with too few opportunities to do so.

According to the findings of this study, older students were happier with their e-learning experience. However, this conclusion is at odds with the findings of Fleming et al. (2017), who discovered that age did not appear to have any significant impact on either satisfaction with e-learning or future usage intentions. Another research conducted by Dabaj (2009) showed that the younger generation is expected to be more digitally literate and more proficient with e-learning tools and techniques. However, it appears that in our study, age-related experience and wisdom had a more substantial impact on e-learning adoption, particularly during the period of the COVID-19 pandemic, when the majority of students were forced to switch to virtual learning overnight. Similar findings were observed by Christozov et al. (2019), who stated that older students had more confidence in their computer competency and learning skills than younger pupils. They are more driven, have more positive views, and are less worried than before.

According to McSporran and Young (2001), mature female students outperform mature male students when it comes to arranging their studies and conversing online, and as a result, they are more motivated to pursue remote learning. Taking gender into consideration, this finding is partially in conflict with our conclusion because we were unable to detect any statistically significant association between students’ gender and their e-learning experience. This is supported by a study conducted in Malaysia (Nikiforidou et al., 2012).

As a result of our research, we discovered that students’ computer skills played an important role in their e-learning experience. Interestingly, this conclusion is consistent with prior research in this field, which has found that students’ computer skills are a precondition for learning efficiently in a blended learning setting (Isakova et al., 2020; Resien et al., 2020). Müller and Wulf (2020), on the other hand, have a different point of view, believing that it is not the students’ computer skills that should be the primary issue but rather their attitude toward e-learning that should be the primary focus. Students with even the most limited computer skills exhibited a favorable attitude toward online learning, as evidenced by the fact that none of them expressed any issues with technology use in their studies (Muflih et al., 2021). Mohammadyari and Singh (2015), on the other hand, feels that computer skill is not only about knowing how to use a computer but rather is one of many different literacies that individuals require in the twenty-first century in order to grasp and interpret diverse sorts of information.

This study also demonstrated a statistically significant difference between the overall mean score of those who had access to PCs and laptops and the overall mean score of those who could only use their mobile phones. Thus, not only does the choice of hardware have an impact on students’ e-learning experiences in general, but it also has an impact on all of the sub-divisions of this study, as seen above. This outcome may be justified by the fact that practically all of the multimedia material created during the COVID-19 pandemic was not conceived or produced for mobile users; rather, it was created as a consequence of urgency. Consequently, when producing the material, it is possible that professors did not consider the smaller screen of mobile phone users, nor did they consider the kind and size of the typefaces they were employing. Teachers require teacher development training to improve mobile-enhanced instructional methods (Baran et al., 2023). Frohberg et al. (2009) claim that inadequate preparation on the part of instructors is one of the most significant factors contributing to students’ learning failure while utilizing mobile devices. Although approximately 28% of students in our study had only their mobile phones and no access to any personal computers or laptops, teachers should tailor their teaching programs to meet the needs of the majority of students rather than “simply designing their own program around the use of technology” without considering the accessibility of the required devices (Sung et al., 2016).

Additionally, students who had already encountered blended learning prior to the COVID-19 pandemic had a more pleasant e-learning experience than those who had not. Surprisingly, this difference was statistically significant in all aspects of e-learning, with the exception of asynchronous classes. This is because this medical university just opened the academic Learning Management System (NAVID) for the multimedia content to be uploaded by professors for the students shortly after the pandemic began, and this was a new experience for all of the students studying at SUMS at the time of the outbreak. As a result, it is possible that participants’ unfamiliarity with the system and its many modules was the reason why there was a statistically significant association between all of the e-learning variables except for the navigation system. Shafiei Sarvestani et al. (2019) found that students reported that using a large number of modules in the LMS system increased the complexity of the application. The major elements that decide whether a user would accept or reject a new technology, according to the Technology Acceptance Model (TAM), are one’s views of ease of use and usefulness of the new technology. Our research also demonstrated that the teacher-learner contact factor and the asynchronous learning factor both played a significant role in determining whether or not students found e-learning education to be desirable. When it comes to adult learning education, the possibility for interactivity and the capacity to respond contingently to the learner’s actions have been identified as two of the most significant variables to consider (Tang and Chaw, 2016). According to the findings of a study done by Begum et al. (2020), medical students’ knowledge, interaction, attendance, and participation in a class all improved dramatically after the implementation of an interactive teaching module. In terms of asynchronous e-learning, Amiti (2020) noted that, because of its adaptability, the asynchronous mode of learning has become the most widely used type of e-learning worldwide. However, some studies reported that students favored the ideal blend of the two modes of instruction, asynchronous and synchronous, after better technological advancements and the speed of the Internet (Tang and Chaw, 2016).

While students expressed a degree of satisfaction with all six components of e-learning, asynchronous approaches are generally preferred due to their flexibility, which eliminates geographical restrictions and time constraints. Additionally, multimedia e-content can somewhat replicate the presence of a teacher in the classroom. However, the most crucial factor influencing students’ sentiments and satisfaction with e-learning is the quality of teacher-student interaction, which serves as an important lesson for educators and administrators alike. On the other hand, some students lack access to electronic devices such as laptops or PCs. Therefore, it is advisable to design electronic materials and learning tools that are optimized for mobile phones. School administrators should also develop strategies to assist underprivileged or disadvantaged students. Our findings underscore the importance of providing professional content development resources for teachers to help them build the necessary skills for creating virtual content and delivering remote instruction. This support not only enhances students’ academic abilities but also fosters independent learning at home. A review of medical students’ experiences during the pandemic reveals that their responses and perceptions regarding the new learning environment and the shift from in-person to online formats are influenced by multiple factors. Part of this influence stems from the nature of the electronic learning environment, while contextual factors such as demographic characteristics and access to resources also play significant roles. Although it appears that we have moved beyond the COVID-19 era, the effects of this period remain pervasive. It can be argued that our experiences, particularly in education and learning, can be categorized into three phases: before, during, and after the pandemic. Many aspects have changed, leading to fundamental transformations in higher education. Teachers who once preferred face-to-face instruction and were unfamiliar with online teaching methods have now become adept at using various online tools and techniques due to the pandemic, experiencing their benefits firsthand. Today’s university students primarily belong to the digital generation, spending a substantial portion of their academic and daily lives in the digital realm. Furthermore, this rapidly evolving world presents us with new phenomena every day, contributing to increasing uncertainty in the higher education landscape. The emergence of technologies such as electronic simulations, augmented and virtual reality, mobile-based education, and artificial intelligence is reshaping the foundations of education—particularly in medical sciences, which heavily relies on technology. As a result, the future landscape of universities and higher education will be markedly different from what we see today due to these developments and future occurrences.