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February 16, 2023

Struggle in the bubble – a prospective study on the effect of remote learning and distance education on confidence in practical surgical skills acquired during COVID-19 | BMC Medical Education

Demographics

A total of 232 out of 244 medical students completed both the baseline and follow-up questionnaire-based surveys, resulting in a response rate of 95{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}. Demographic data was comparable between the two cohorts (Table 1).

Table 1 Baseline comparison of the characteristics of participants belonging to the COV-19 and postCOV- 19 cohorts

Improvement in self-confidence for unit 1

First, it was evaluated whether the respective teaching methods in both cohorts resulted in an improvement in the self-confidence of students regarding their surgical skills. While analyzing unit 1 (sterile working), we found that both the COV-19 (Fig. 2A) and postCOV-19 (Fig. 2B) cohorts showed significant improvement in post-course confidence compared to pre-course confidence. This result was observed for all five subcategories of unit 1 (Table 2).

Table 2 Self-assessment of pre- and post-course confidence of unit 1

Improvement in self-confidence for unit 2

While analyzing unit 2 (knot tying and skin suturing), we observed that both the COV-19 (Fig. 2C) and postCOV-19 (Fig. 2D) cohorts exhibited significant improvement in post-course confidence compared to pre-course confidence. This result was similar for all five subcategories of unit 2 (Table 3).

Table 3 Self-assessment of pre- and post-course confidence of unit 2

Improvement in self-confidence for unit 3

Upon analyzing unit 3 (history and physical), we identified that both, the COV-19 (Fig. 2E) and postCOV-19 (Fig. 2F) cohorts, revealed significant improvement in post-course confidence compared to pre-course confidence. This result was observed for all three subcategories of unit 3 (Table 4).

Table 4 Self-assessment of pre- and post-course confidence of unit 3

Having established that both the traditional interactive face-to-face hands-on courses and the newly developed interactive remote learning courses were able to significantly improve the confidence of medical students regarding basic surgical skills, it was necessary to determine the course that resulted in a higher difference between the pre- and post-course confidence and the subgroup of students that would benefit the most from a particular teaching method. Subgroup analysis was performed based on sex (male/female), age group (19–22 years/23–29 years/≥30 years), and prior surgical experience (with and without prior surgical experience) for evaluating the difference between the pre- and post-course self-assessment (Δ self-assessment).

Subgroup analysis

Sex

The cohorts were first stratified based on the sex (male or female) of the participants, and the subgroup that benefited the most from a particular learning method was determined. For unit 1, the mean Δ self-assessment in the COV-19 cohort was significantly higher in male students (1.96) than in female students (1.44) (p = 0.0003). However, in the postCOV-19 cohort, the mean Δ self-assessment was significantly higher in female students (1.57) compared to male students (1.29) (p = 0.0372) (Fig. 3A).

For unit 2, the mean Δ self-assessment in the COV-19 cohort was significantly higher in male students (2.59) compared to female students (2.16) (p < 0.0001), whereas no significant difference between males (1.92) and females (2.01) was observed in the mean Δ self-assessment in the postCOV-19 cohort (p = 0.0813) (Fig. 3A).

Nonetheless, for unit 3, we found that the mean Δ self-assessment was comparable between the female and male groups in both cohorts (Fig. 3A).

Age

The two cohorts were stratified based on age, which resulted in three subgroups: 19–22, 23–29, and ≥ 30 years. For unit 1, we found that the mean Δ self-assessment in the COV-19 cohort was the highest for the participants in the age group of 23–29 years (mean Δ self-assessment = 19–22 years: 1.51; 23–29 years: 1.82; ≥30 years: 1.42). Furthermore, the mean Δ self-assessment was significantly higher in students of ages 23–29 years compared to those in the age group of 19–22 years (p = 0.0234). However, no significant differences in the mean Δ self-assessment were observed between the subgroups 19–22 years and ≥ 30 years (p = 0.8443), as well as the subgroups 23–29 years and ≥ 30 years (p = 0.0761).

By contrast, the mean Δ self-assessment of unit 1 did not vary significantly between different age groups in the postCOV-19 (mean Δ self-assessment = 19–22 years: 1.58; 23–29 years: 1.33; ≥30 years: 1.23) cohort (Fig. 3B).

Considering unit 2, we determined that the youngest (19–22 years) subgroup exhibited the maximum improvement in self-assessment for the COV-19 and post-COV19 cohorts. In the COV-19 cohort, the mean Δ self-assessment was significantly higher in the subgroup with participants aged 19–22 years compared to the subgroup with participants aged 23–29 years (p = 0.0017). However, there was no significant difference between the subgroups with participants aged 19–22 years and ≥ 30 years (p = 0.4096), as well as the subgroups with participants aged 23–29 years and ≥ 30 years (p = 0.5073).

In the postCOV-19 cohort, the mean Δ self-assessment was significantly higher in the subgroup with participants aged 19–22 years compared to the subgroups with participants aged 23–29 years (p = 0.0020) and ≥ 30 years (p = 0.0017). In contrast, there was no significant difference observed between the mean Δ self-assessment of the subgroups with participants aged 23–29 years and ≥ 30 years (p = 0.2499) (Fig. 3B).

Upon analyzing unit 3, the mean Δ self-assessment in the COV-19 cohort was significantly higher in the youngest students (19–22 years) compared to the subgroup with participants aged 23–29 years (p = 0.0061) in COV-19. However, there was no significant difference in the mean Δ self-assessment between the participants aged 19–22 years and ≥ 30 years (p = 0.0934) and 23–29 years and ≥ 30 years (p = 0.9923).

Nonetheless, for unit 3, the mean Δ self-assessment was significantly higher in the subgroup with participants aged ≥30 years compared to subgroups with participants aged 19–22 years (p = 0.0224) and 23–29 years (p = 0.0181) in the postCOV-19 cohort (mean Δ self-assessment = 19–22 years: 1.73; 23–29 years: 1.68; ≥30 years: 2.35). However, no significant difference was noted in the mean Δ self-assessment of subgroups with students aged 19–22 years and 23–29 years (p = 0.9332) in the postCOV-19 cohort (Fig. 3B).

Prior surgical experience

Lastly, the two cohorts were stratified based on prior surgical experience. Students without prior surgical experience showed a significantly higher improvement in their self-assessment of post-course confidence compared to pre-course confidence. This result was found for unit 1 and 2 in the COV-19 (unit 1 = mean Δ self-assessment with surgical experience: 0.58; without surgical experience: 1.74; p < 0.0001; unit 2 = mean Δ self-assessment with surgical experience: 1.65; without surgical experience: 2.14; p < 0.0001) and postCOV-19 cohorts (unit 1 = mean Δ self-assessment with surgical experience: 0.77; without surgical experience: 1.57; p < 0.0001; unit 2 = mean Δ self-assessment with surgical experience: 1.15; without surgical experience: 2.10; p < 0.0001).

However, for unit 3, we observed that the mean Δ self-assessment did not vary significantly between students with and without prior surgical experience in the COV-19 cohort (mean Δ self-assessment with surgical experience: 1.21; without surgical experience: 1.09; p = 0.2242) but was significantly higher for students without surgical experience in the postCOV-19 cohort (mean Δ self-assessment with surgical experience: 1.19; without surgical experience: 1.89; p < 0.0001) (Fig. 3C).

To summarize, the mean Δ self-assessment was the highest in the young (19–22 years) male students without surgical experience in the COV-19 cohort and young (19–22 years) and elderly (≥30 years) female students without surgical experience in the postCOV-19 cohort.

Finally, we compared the mean Δ self-assessment of both cohorts using each unit. Both, the COV-19 (Δ self-assessment: 1.58) and postCOV-19 (Δ self-assessment: 1.46) cohorts showed comparable (p = 0.1485) results for unit 1. For unit 2, the mean Δ self-assessment was significantly (p < 0.0001) higher in the COV-19 cohort (Δ self-assessment: 2.26) compared to the postCOV-19 (Δ self-assessment: 1.98). In contrast, for unit 3, the Δ self-assessment was significantly (p < 0.0001) higher in the postCOV-19 cohort (Δ self-assessment: 1.76) compared to the COV-19 cohort (Δ self-assessment: 1.1) (Fig. 3D).

February 11, 2023

Impact of online learning on sense of belonging among first year clinical health students during COVID-19: student and academic perspectives | BMC Medical Education

Online student cross-sectional survey

Demographic characteristics

A total of 179 out of the possible 663 students (27{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} completion) completed the online survey in June 2020. Median age of students was 19 years (IQR 18–28 years) and there were approximately three times as many females as males (Table 1), reflective of the undergraduate health sciences cohort (70{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} female). Student numbers were also reflective of the broader enrolment numbers in the programs (i.e., occupational therapy is the largest program). Just over half (53{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}; n = 94) of students had no prior experience in undertaking a Bachelor degree, and 76{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} of students had not completed any online courses prior to enrolment.

Table 1 Demographic characteristics

Quantitative results to the sense of belonging questionnaire

In terms of students’ sense of belonging to the university, the majority felt ‘quite’ or ‘extremely’ happy with their choice of university (74{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) and felt ‘quite’ or ‘extremely’ welcomed by the university (68{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}). While most students felt respected by both staff (70{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) and students (60{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) at the university, students reported less connectiveness (23.5{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) to the university. Only 20{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} of students reported they felt they were understood as an individual, and only 13{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} felt they ‘quite’ or ‘extremely’ mattered to others at the university (Table 2).

Table 2 Online learning and Sense of Belonging to the University [1]

Table 3 shows how the online learning experiences impacted on students’ perception of the course; 27{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} of students felt ‘quite’ or ‘extremely’ connected to staff while 16{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} of students felt ‘quite’ or ‘extremely’ connected to other students. While 49{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} of students rated 4 and above for the level of respect that they received from other students and their contribution towards the subject, students who had prior higher education felt less respected than students who had no prior higher education (p = 0.03). When asked how the online subject had contributed to understanding, knowledge/skills in their chosen health profession, about half of the students rated the online subject highly (rating 4 and above). Students who had prior higher education indicated higher ratings of understanding and knowledge/skills compared to students without prior higher education (p = 0.07 and p = 0.03 respectively). There was also a significantly higher proportion of students with no prior higher education who identified the online learning experience as either ‘quite’ or ‘extremely’ likely to impact their intention to continue with their current course (p = 0.001).

Table 3 Impact of online profession-specific subject on perception of the course

Qualitative results

Qualitative findings provided insight into experiences of staff and students during the rapid, unplanned transition to online learning. Student questionnaire responses included two open-ended questions expanding on enablers and barriers to sense of belonging. These yielded 145 enablers and 254 barriers to students’ feeling a sense of belonging. Data were subjected to qualitative content analysis by two authors and categories are presented in Additional file 1.

Three focus groups were conducted: two student sessions, each with two students enrolled in Speech Pathology and Paramedicine, and one academic session with five participants. Four full time academics and one casual academic participated from a total population of nine eligible academics. Using the processes described in the methods, focus group analysis was compared with the survey content analysis and the authors identified synergies between them. Findings were then integrated under a global theme, underpinned by organising and basic themes. The following themes reflect triangulation between academic and student focus group data in addition to survey responses.

Global theme—navigating belonging during the COVID-19 crisis: a shared responsibility

“We are in this together…making the best of this”

This theme explores sense of belonging creation during this period as a shared process, where participants perceived they worked together to get through the crisis. Students and academics encountered many challenges as they transitioned to online learning but despite hard times, were able to engage positively. The global theme revealed students and academics were navigating belonging during the COVID-19 crisis, and this journey was a shared responsibility. Both groups were working to achieve positive student engagement that would in turn create a sense of belonging in first-year students. A strong commitment of working hard to make the best out of this was mutually acknowledged.

Students perceived academics had done “a really good job at making sure we belonged…in those first few weeks that we were on campus but even more so probably while we were in Zoom” (Student-Astrid-Focus Group). Academics perceived students were actively engaged in making online learning work and were collegial and collaborative.

The shared experiences about navigating belonging during the COVID-19 crisis, have been captured under four organising themes: dimensions of belonging, individual experiences and challenges, reconceptualising teaching and learning, and relationships are central to belonging. Within each organising theme, basic themes were identified that provide depth to the organising theme (Fig. 1). Additional files 1 and 2 present a summary of the quotes obtained from the open-ended surveys and focus groups respectively, that contribute to the themes in Fig. 1.

Organising theme: dimensions of belonging

This theme outlines that belonging is a multidimensional experience with several facets underpinning participants’ experiences. Students and academics identified several dimensions of belonging in relation to first year students’ experiences, as illustrated by two basic themes that sit under the organising theme: what it means to belong, and layers of belonging.

Basic theme: what it means to belong

This theme explores the idea that belonging at university is underpinned by feeling valued and connected. Academics and students agreed that having a sense of being valued by the university and a desire to have an active connection across all aspects of university life was important for students.

Belonging as a student was gained through a connection with the “vocation” (Student-Claire-Focus Group) or the course and career, and with people who will “be there” (Student-Claire-Focus Group) for them. Furthermore, support of academics was critical to gaining a sense of belonging. It was noted by academics and students, that when students feel they belong at university, they are actively engaged in their learning, and this sense of belonging in turn shapes their overall identity. Students can then “actually sort of relax and become themselves” (Staff-Brooke).

Belonging to their cohort, their course, their future profession, and their university was important for students. One academic noted that the “concept of acceptance” is part of the sense of belonging and goes “both ways” (Staff-Brooke).

Both academics and students agreed that the rapid change to online learning due to COVID-19, meant that developing a sense of belonging was challenged.

Basic theme: layers of belonging

This theme identified layers of belonging reflected in participants’ experiences. Peer, academic and professional layers each contributed to an overall sense of belonging and key examples are provided below.

Peers

Belonging to peers was described as “having that connection to someone that’s going through exactly the same thing as what you’re going through” (Student-Astrid-Focus Group). Students were concerned that when learning moved online that this sense of belonging would be jeopardised by less opportunities for in-person interaction.

Academics

Being connected to academics was perceived by students as directly impacting learning, with one student commenting: “…when they’re not connecting with the teacher, they’re not connecting with the content, they’re not connecting with the feedback. That’s when you develop this sense of feeling like you just don’t belong” (Student-Emily-Focus Group).

Academics perceived it was also important for students to develop a sense of belonging to the university community.

Profession

Belonging to a profession was identified as an important feature of belonging by academics and students. Studying a degree with a clear professional identity facilitated first year students to feel they belonged compared to those undertaking general health science degrees which may have multiple pathways and career options less directly aligned to first year studies.

One academic actively encouraged first year students to belong to their professional association as a way of fostering belonging in first years.

Organising theme—Individual experiences and challenges

This theme outlines that while there are similarities in participants’ experiences, individuals have unique contexts and factors shaping their experiences. Academics and students reflected upon personal impacts of the COVID-19 pandemic on their teaching or learning and how they responded as individuals to the ensuing challenges. Two basic themes emerged: Challenges of transition and recognising different learning preferences.

Basic
theme
—challenges of transition

This theme explored the significant challenges of transitioning to online teaching and learning. For some students, the transition to online learning offered potential benefits of flexibility and reduced travel time. Two of the four students in the focus groups opted for online learning opportunities available in other subjects of study prior to the pandemic to efficiently manage their study and external commitments. Nonetheless, the pandemic brought a raft of personal challenges that diminished these expected benefits. Covid-related changes to family employment, reduced access to childcare support and non-optional home schooling presented new concerns.

Clearly, students missed the opportunity to focus attention on their learning needs when balancing childcare demands and home-schooling during lockdowns.

Unlike a conventional online courses where students choose or plan to be online, the sudden, unexpected, and unplanned move to online study was prefaced by a short period (four weeks) of in-person class time. This initial in-person time was identified as being key to relationship building.

Academics identified positive experiences and challenges during the transition to online learning. The rapid change presented a problem to be solved and individuals could “embrace it and to work effectively…as a team” (Staff-Jane). Quickly strategizing and responding to the demands of online learning required team knowledge, experience, and support. Hence, enhanced team culture was a further positive for academics, being “present for each other” (Staff-Brooke).

Basic
theme
:
recognising different learning preferences

This theme identifies experiences of online learning influenced by personal attributes, individual expectations and learning preferences. Such key factors impacted students’ capacity to maintain focus on academic goals after the rapid change to online learning. Some students reflected that barriers were not solely a feature of online learning environments, reporting that competing priorities, including work commitments and limited contact time with staff as pre-existing challenges to belonging. However, some students directly attributed their limited engagement and reduced motivation to the online learning environment.

Students suggested that active engagement “comes down to personality” (Student-Astrid- Focus Group). If a student was not shy they were comfortable to come forward and participate online. Some students perceived clear links between personal discipline, engagement, commitment, and achievement in online learning environments.

Further, students perceived effective (and ineffective) online group functioning reflected personalities of individual members, with some groups/personalities seen as being able to organise whilst other groups lacked leadership and cohesion.

Students who perceived themselves as active engagers reported being drawn towards other students who demonstrated motivation to interact and learn. Other students perceived their personalities or learning preferences were misaligned with the expectations of belonging in online learning environments and focussed upon tasks rather than connection.

Academics recognised student diversity and a need to reflect and re-evaluate expectations of students in online environments. They accepted that some students may be quietly engaging and learning to belong, but this was harder to observe in online compared to in-person learning environments.

Organising theme—relationships are central to belonging

This theme identified the relationship between all parties as a fundamental aspect of creating a sense of belonging. Two basic themes were influential in shaping perceptions of how relationships and connections contribute to belonging: collaboration with peers is fundamental, and effective and regular communication with staff is necessary.

Basic
theme
—collaboration with peers is fundamental

This theme revealed collaboration with student peers was a key element of creating a sense of belonging. The degree of social interaction with student peers and opportunities to create friendships contributed to feelings of belonging. Accordingly, students found it problematic when peers neglected to turn cameras on during classes, making interaction very difficult. Visualisation of peers and use of cameras in online classes impacted students’ opportunities to get to know each other.

Challenges posed by online learning were further highlighted in the student survey through a focus on non-academic aspects of university and campus life. Typically, university campuses offer interactional opportunities through clubs, sport, and shared spaces to learn and socialise. Campus life, students suggested, may facilitate learning and personal development. Absence of this type of interaction was linked to barriers in developing friendships and consequently a lesser sense of belonging as reflected in Additional file 1.

Basic theme—
communication
with academics is necessary

This theme outlined that communicating with academics was a key component of creating a sense of belonging. With less opportunities for peer support, there was stronger reliance on the academic-student connection, although students reported positive and negative interactions with academics during online learning.

Positive interactions and individualised communication with academics enhanced student sense of satisfaction and belonging. Furthermore, students in the focus groups reported a feeling of trust and a bond created by a shared challenge. Survey responses echoed this sentiment, noting that academics were “non-judgmental and supportive” (Student Survey 18) and created a sense of camaraderie. However, when students perceived impersonal communication from academics, they felt less connected or believed that teaching had become a “transaction” (Student-Astrid- Focus Group). Perceived levels of enthusiasm and engagement from academics influenced student’s perceptions of connection and belonging.

Students identified the online environment as a barrier to communication with academics. While systematic and university level communication was perceived as a useful source of information, students prioritised individualised communication from academic staff as key to belonging.

Academics concurred that effective communication was challenged in online environments, missing non-verbal cues and responsivity that characterises a classroom environment. Although the online learning environment provides an opportunity for academics to connect professionally with students, there were students who left their cameras off, with one academic noting they didn’t push this issue because there are many reasons for students choosing this option.

Organising theme: reconceptualising teaching and learning

This theme reveals how academics and students reconceptualised their expectations and modes of teaching and learning, to manage the crisis. It was not easy for academics or students, and many strategies were employed to make it work, with two basic themes emerging: challenges to online teaching and learning, and strategies to engage and connect.

Basic theme:
challenges
of online teaching and learning: “how do I make this work?”

This theme outlined many challenges faced by both academics and students during a rapid change to online mode. With the rapid change to online learning, academics asked themselves, ‘How do I make this work?’.

Managing workload

Academics reported their workload increased significantly, and they “found it a juggling act” (Staff-Louise) to meet their teaching requirements. Administrative loads consequently increased when reduced in-person contact with students led to more electronic communication. Academics needed to up-skill in online teaching in a short time frame and perceived this responsibility as all encompassing.

The rapid switch to online learning attracted significant academic workload, implementing and adapting content to see how material “might play out in a Zoom environment…[where]…everything takes longer” (Staff-Natalie).

Some students noticed a temptation to disengage from online learning, which meant balancing their workload and study demands became a challenge as they also faced significant workload and stressors in their personal lives due to COVID-19.

Class dynamics

Academics and students spoke about the change to classroom dynamics. The online environment was noted as being one in which it was difficult to read the room to see how students were progressing with their work. Others tried to use humour to enliven a class, only to have the Zoom frame freeze, killing the mood they were trying to create. Hence, staff felt teaching online was less conversational, flexible and responsive compared to face-to-face. Moreover, academics missed hands-on practical elements; a big shift for some programs.

Technological challenges

Academics learnt new skills quickly, but often these skills would be challenged when technology failed. Some academics reported a sense of vulnerability due to technological ineptitude but acknowledged that making mistakes in front of students could humanise the experience. Academics also acknowledged that some students did not have adequate technological resources to meet changes in their learning requirements when classes were placed online.

Basic theme: strategies to engage and connect

This theme reflected the strategies academics and students employed to remain engaged and connected. Academics worked hard to enhance online learning and hoped to connect with students and engage them in activities. Students too were active and appreciated academics’ efforts to facilitate engagement and connection. Underlying many of the strategies adopted by academics was a deep concern for student welfare during this time. Therefore, many academics aimed to ensure students were engaged and connected with each other and with the academic team. Academics built in small group opportunities during online teaching so students could connect, learn, and socialise.

Staff also spoke about informing students they could contact staff for support. One staff member described crossing the divide and actively discouraging a ‘them and us’ dynamic between students and staff.

A variety of teaching tools were identified by staff to build connection and promote engagement. Such tools included interactive quizzes, ice breakers activities, integrating reflective practices into activities and ‘drop in’ sessions. Staff also encouraged students to establish social media groups or other group experiences outside the classroom. Some staff members arrived early to zoom classes and left late to enable students to connect informally.

Students appreciated staff attempts to provide these activities. Students found these initiatives helpful, recognising staff placed effort into knowing students personally and focussing on student wellbeing and achievement. Students cited examples of provision of extra resources, mini-lectures, additional question and answer sessions, and fast response times to student queries. Students also initiated their own engagement strategies, including using group and personal messaging over platforms such as Facebook messenger.

December 30, 2022

Identifying the challenges of online education from the perspective of University of Medical Sciences Students in the COVID-19 pandemic: a Q-methodology-based study | BMC Medical Education

This cross-sectional analyze was executed using the Q methodology during the subsequent six techniques utilizing Barry and Proops method [19].

Phase 1 and 2: defining the concourse

At this phase, a concourse space was fashioned with the identification of the matter or idea of the analyze. The offered sights on the situation elevated for the concourse can be formed from a assessment of texts and authorities in this field [19].

In this review, the matter and notion for the concourse were being the problems of on the web education and learning all through the COVID-19 pandemic. The concourse provided a collection of various supplies associated to the investigation subject that was mentioned among the students. The pupils (P-established) who also experienced contributed before to the enhancement of the initial set of statements. Thirty-one particular learners participated in semi-structured interviews, and we tried using to establish their subjectivity about the investigation matter working with the Q approach [20].

In this analyze, the concourse (sample of people) provided college students of the University of Health care Sciences (paramedical learners) who had enough data about online training for the duration of the COVID-19 pandemic.

Stage 3: screening and assortment of statements (Q-sample)

In the course of the semi-structured interviews with 31 learners, 70 statements ended up extracted about the perceived difficulties of online schooling. The Q goods ended up picked quite diligently so that things did not overlap, and at the exact time, no point of view need to be missing. Thus, the variety process usually takes the most time and hard work of all the measures of the Q methodology. For that reason, exploration group taken out related unrelated, and ambiguous statements from the Q set. Eventually, 50 statements had been selected.

Phase 4: picked P-established

Students who participated in the concourse (interviews) had been chosen as a sample of individuals to take part in sorting in the Q examine (P-established). In the present study, learners have been picked by purposive sampling to include college students who experienced an academic, skilled, experimental marriage or prior information about the subject of study. This range of samples designed the contributors with much more varied mentalities enter the examine. It is advised that in Q experiments, the variety of members to form statements should really be less than the number of statements close to the analyze issue [21]. In the present examine, the range of individuals who rated the troubles of on the web education packages was 31 (Table 1).

Desk 1 The Q-established statements and issue arrays in the analyze of worries on the net instruction among pupils

Phase 5: Q-sort

At this stage, the normal distribution table in the type of a Likert scale from − 5 to + 5 was developed offline. Suggestions on distributing the expressions on the typical distribution table have been delivered. In the first phase, the intent of the examine is the quantity of statements picked by means of the interview. In the second phase, position the statements in 3 columns: “I agree”, “I have no viewpoint,” and “I disagree. In the third phase, the statements (necessary) are distributed in the ordinary Likert distribution diagram (− 5 to 5+), detailing the motive for deciding upon the two ends of the Likert scale from their issue of look at and lastly moving into the demographic facts. So, in Q, the sorting process is subjective [19]. In other text, sorting things in the regular distribution make it possible for each and every participant to existing their internal standpoint via sorting.

Stage 6: examination and interpretation of components

Students’ knowledge obtained from Q sorting were being entered into PQ-Method program model 2.35. The system of analysis and interpretation was executed in three levels: (a) identification of factors, (b) conversion of elements into element arrays (c) interpretation of variables applying element arrays.

A)

Element Identification

The extraction of components in PQ-Method software was performed by the subsequent sequential techniques: (a) principal element examination, (b) identification of latent things, (c) varimax rotation and analysis of loading aspects for unique values earlier mentioned 1.00, d) estimation of the percentage of variance described by the discovered variables and (e) differentiation of interpretable components with at minimum two correlated Q forms [22].

B)

Transform element to element arrays

The correlation among each Q sort and just one discovered element indicates the degree of interaction in between the Q sorts and the recognized factors [19, 23]. The handbook flagging in PQ-Approach program was used for this examine. The correlation coefficients of at the very least .364 had been thought of as the reduce-off issue (the absolute value of the issue load is increased than ((frac2.58sqrtN)). That factor load was 99{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} significant, respectively, and the value of N was equivalent to the quantity of Q statements (N = 50). Sorted for identified elements [24]. Specs specified on a component are employed to create a aspect array for that element. The variable array represents the sorting of that factor (point of watch) applying z-scores. The component array for each individual issue determined the degree to which each individual expression was in the spectrum, so a extra precise interpretation of just about every component (subjectivity) was attained according to the placement of every single expression. (P-worth< 0.05 vs. 0.01) is also determined from the Z score to distinguish expressions [25].

III)

Factor interpretation using factor arrays

Distinct Q expressions were identified, and factors were interpreted textually. The defining expressions for a factor were those that had a rating value of “+ 5”, “+ 4”, “4-,” 5- “in factor arrays that had different scores (P < 0.05) in a given factor Compared to their scores on other factors, the post-P-set interview was conducted at the end of Q sorting to confirm the diagnosis and interpretation of item subgroups among the identified factors.

September 25, 2022

Postgraduate Online Medical Education during the COVID-19

Introduction

Online learning (eLearning) was gradually incorporated into medical education over the past 20 years, which has paralleled the increased use of eLearning across all workforce sectors.¹ A review published in 2006 concluded that eLearning would be “one of the most important developments in the delivery of postgraduate medical education.”¹ The authors of that review article, and many others who shared similar views in the early internet era, could not have known how that prediction would be tested. However, as the world came to be immersed in the SARS-CoV-2 (COVID-19) pandemic in 2020, eLearning surely became important in the delivery of postgraduate medical education.

The COVID-19 pandemic caused a massive change worldwide; affecting all areas of workforce including education. This state of emergency has led to many modifications within the healthcare system, such as cancelling elective surgical procedures, reducing the volume of acute-care surgeries, closing all outpatient clinics, limiting the presence of trainees on service and calling-off departmental educational activities.^2–6 This resulted in significant interruptions of clinical rotations. In addition, traditional in-person academic activities such as face-to-face teaching and simulation labs were halted; examinations, courses and conferences were postponed on an international level.^7,8 Almost overnight, online learning transitioned from its status as a developing option to becoming mandatory if education were to continue.

The rapid transition from traditional face-to-face to eLearning has transformed the way medical education was delivered and posed many challenges to trainers and trainees involved.^4,9 Synchronous and Asynchronous eLearning modalities have been utilized by several institutions during this period. Numerous platforms were utilized for delivering academic content; the most frequently used were ZOOM and Microsoft-Teams.^10,11 Innovative teaching modalities took place, including the “flipped-classroom” method, where learners were provided with didactic materials and pre-recorded videos prior to the educational session.^11–13 Other strategies were implemented to accommodate for teaching clinical skills and ensuring the continuity of clinical education, achieved through video-recorded surgical procedures as well as providing telehealth patient consultations.¹¹ With regard to evaluation, the most commonly reported assessment method during this period was in the form of multiple-choice questions; other studies reported the conversion of the standard Objective Structured Clinical Examinations (OSCE) to an online version.^11,14

Numerous obstacles and challenges have been reported as a result of this massive transition. Trainers, teachers, and educators were required to rapidly adapt to digital technologies; trainees encountered difficulties with poor bandwidth connectivity; accessibility and time management issues were evident, as well as communication challenges due to the lack of non-verbal language.^11,15

The resulting global experience with online medical education is being shared primarily as information gathered from user surveys. Although quantitative data are essential, detailed qualitative data are as necessary today as they were in the early studies, to allow comprehensive and reliable investigations of this complex intervention comprising “multiple human components (teachers, learners, etc.) interacting in a nonlinear fashion to produce outcomes which are highly context dependent.”¹⁶

Accordingly, we distributed an online survey to postgraduate medical learners and teachers in Riyadh, Saudi Arabia. These data are expected to supplement the expanding total of literature, adding to the reported experiences and possibly contributing to the development of strategies that can resolve specific issues, gaps, and deficiencies in online postgraduate medical education. The aim of this study is to provide qualitative and quantitative assessments of postgraduate online medical education during the COVID-19 pandemic amongst trainers and trainees in Saudi Arabia.

Research Objectives

The research had three main objectives. The first was to describe the experiences, coping, perceptions, satisfaction and preferences for online learning by medical trainers and trainees. The second was to determine how the experiences correlated with perceptions, satisfaction, and preferences. The third and foremost objective was to test the null hypothesis: no difference between trainers and trainees on various aspects of online learning.

Materials and Methods

In this cross-sectional study, a questionnaire was developed through a review of recent publications on online learning during the Covid-19 pandemic in addition to the experiences of the researchers involved. At first, the questionnaires used in previous similar studies were carefully reviewed by the authors. Then, more questions were added based on the experiences of the researchers involved— whom were either active trainers, learning managers or decision makers during the pandemic. The researchers discussed the items of the questionnaire for relevance and finalized only 43 of them.

The questionnaire was pre-tested on a pilot number of potential respondents, with care being taken to exclude them from the main survey. The questionnaire comprised several sections addressing the sociodemographics of participants and measures of experiences, perception, satisfaction, and preferences. Table 1 shows the list of variables used in the research and their corresponding questions. Nominal variables were recorded as multiple-choice questions, while ordinal variables were scored based on a 4-point or 5-point Likert Scale.

Table 1 Variables of the Study

Institutional Review Board (IRB) approval was granted on 1 July 2020 from the local IRB at King Fahad Medical City—under category “Exempt” based on Good Clinical Practice (GCP) Guidelines. The questionnaire included a cover-letter describing the purpose of the study along with a statement of informed consent for research participation—which was developed in accordance with the local IRB guidelines. No participant identifiers were collected as part of our survey and the responses were anonymous. The involved researchers maintained adherence to GCP guidelines throughout the duration of the study.

The questionnaire was distributed by e-mail on August 21, 2020, to 1200 trainers and trainees of academic medical centers within the Riyadh 2nd Health Cluster, which included King Fahad Medical City, Prince Muhammad Ibn Abdulaziz Hospital, Al Yamamah Hospital, King Salman Dialysis Center and three specialized dental centers. The sample size was computed using the Raosoft online formula as 205; based on a total population of trainees and trainers of 1200, alpha error of 0.05, 95{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} confidence level, and a 2:8 distribution based on the estimated trainee-to-trainer ratio. A follow-up was made 1 week after the initial e-mail via a reminder e-mail and/or phone call. Data received were checked and edited for consistency and accuracy. Open-ended items were coded, except for 2 questions (Q18, Q38) which were analyzed qualitatively. The variable “position” was defined as either “trainee” or “trainer.”— “Trainee” was coded to include residents R1-R4, interns, fellows and pre-scholars; “Trainer” was coded to include consultants, assistant consultants, and program directors.

Statistical analysis was carried out using SPSS v.26 to cross-tabulate frequencies of the variables and test for association using the chi square statistic, with significance being set at 0.05 using 2-sided asymptotic p values. Both the Spearman and the Kendall tau correlation coefficients were computed with a critical value of significance of 0.05 and 2-sided p values. The main objective of the analysis was to determine and explain the differences between trainers and trainees. Where indicated, multivariate logistic regression models were used to test for association while controlling for confounding to determine independent associations.

Results

Study Sample Socio-Demographics (S1–5)

A total of 1200 emails were sent out, of which 207 were returned giving a response proportion of 17{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}. Table 2 shows the sample characteristics. There were significant differences between trainees and trainers in age, gender, household size and specialty, but only age showed independent association after running a logistic regression model containing all the socio-demographic variables.

Table 2 Sample Characteristics

Transition from Traditional to Online Learning and Changes in Institutional Policies, Procedures, and Support (Q1, 2, 9–14)

Table 3 shows reported transitions and changes due to the pandemic. A high proportion, 82.1{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}, rated their pre-pandemic computer and internet experience as high or medium and there was no significant difference between trainees and trainers. One-quarter, 25.6{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}, had no online learning experience before the pandemic, with a higher proportion among trainees. There was no significant correlation between their pre-pandemic computer and internet competency with pre-pandemic online learning experience. Age was not correlated with the pre-pandemic computer and internet competency but was significantly negatively correlated with pre-pandemic online learning experience (r_S= −0.257, P < 0.000).

Table 3 Transition from Traditional to Online Learning and Changes in Institutional Policies, Procedures, and Support

There was a positive correlation between the reports of ‘redesigning teaching courses’ and “change of procedures to accommodate online learning” (r_S= 0.360, P < 0.0001). Major or drastic changes were reported in both by 44.9{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} and 39.6{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} of respondents, respectively. The trainees differed from trainers in reporting provision of guidelines before the start of online learning activities (P < 0.024). About 27.3{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} of trainees reported inadequacy, while a higher proportion of trainers, 58.5{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}, reported absence of guidelines. About 70.1{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} of respondents reported a high level of institutional support for online learning with no significant difference between trainees and trainers.

A high proportion of respondents, 80.6{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}, reported coping well or very well with online learning, with no significant differences between trainers and trainees. Coping was negatively correlated with age (r_S= −0.151, P < 0.030), positively correlated with the pre-pandemic computer and internet competency (r_S= 0.202, P < 0.004) but not correlated to pre-pandemic online learning experience (r_S= −0.094, P < 0.177).

The transition from traditional to online learning was associated with stress. About 24.6{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} of trainers reported extreme or major stress compared to 20.7{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} among trainees, and there was overall significant difference in stress between trainers and trainees. Stress was correlated with the pre-pandemic computer and internet competency (r_S=−0.162, P < 0.020), but not with prior experience of online learning or with age; as (r_s= 0.035, P = 0.562) and (r_s= 0.045, P = 0.453), respectively.

Online Learning During the Pandemic: Experiences, Perceptions and Satisfaction (Q3–8, 15–17, 19)

Zoom was the preferred software by 94.2{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} of respondents. All modern equipment were used equally by trainees and trainers; laptops, smartphones and tablets, with desktop computers being the least (9.2{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}). More than half of the respondents, 53.6{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}, reported spending 4 hours or more per day on online learning activities, but there was no significant difference between both groups (P < 0.224). The majority of online learning activities, 92.3{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}, took place at home during quarantine period, with no significant differences between trainees and trainers.

The 2 most popular learning activities were lectures and seminars/webinars accounting for a total 87.9{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} of all activities, but trainees reported more lectures while trainers reported more seminars/webinars. Case presentations/discussions was the most popular form of assessment at 49.3{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}, followed by short oral examinations 15.5{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} and online OSCE 12.6{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}; the rest of the assessment methods were rarely used. It is noteworthy that there were significant differences: trainees reported more case presentations/discussions, 55.8{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}, while trainers reported more short oral examinations 26.4{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} and online OSCE 20.8{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}.

Overall perception of online learning was very positive or positive, totaling 73{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}, with no significant differences between trainees and trainers. Overall perception was correlated with age (r_S= −0.0213, P < 0.002), with stress (r_S= −0.359, P < 0.00), with coping (r_S= 0.672, P < 0.00) and with satisfaction (r_S= −0.835, P < 0.000).

On a Likert scale of 1–5, 71.1{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} of respondents were either satisfied or highly satisfied and 3.9{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} were very unsatisfied, with no differences between trainees and trainers. Satisfaction was correlated with age (rs = −0.136, P < 0.020), Pre-pandemic computer and internet competency (rs = 0.146, P < 0.016), stress (r_S= −0.363, P<0.0001), and coping (r_S= −665, P < 0.0001) but was negatively correlated to overall perception (r_S= ₋₀.835, P < 0.000).

While the response to the item on difficulties of online learning was 39.6{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}, 15.0{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} reported technical problems as the most common problem, with trainers reporting 22.6{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} and trainees reporting 12.3{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}. A question on challenges and opportunities presented by online learning revealed that 39.6{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} agreed that online learning presented challenges and opportunities while 15{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} thought it did not; however, this item had a non-response of 42.5{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}.

Comparison of Online to Traditional Face to Face Learning (Q20–32)

Respondents were asked to compare online to traditional learning on 12 items using a 5 point the Likert scale. These items were highly correlated. In total, the proportion, of “strongly agree” varied between 19.8–47.8{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} among trainees and 8.2–35.3{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} among trainers. Significant differences between trainees and trainers were observed in 6 out of 12 variables. Learners were more satisfied with learner to teacher communication 35{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} vs 30.9{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}; teacher to learner communication 39{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} vs 17{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}; reduction in academic stress 72.1{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} vs 62.3{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}; overall satisfaction 57.1{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} vs 39.7{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}, and academic stimulation 66.9{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} vs 75.5{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}. Trainers agreed that online learning had less stress 62.3{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} vs 72.1{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} and that it gave more time to teachers 75.5{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} vs 66.9{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}.

A wide diversity of subjective responses was given to the open-ended item asking for what was missed from traditional learning. The most common factors being interaction and associated items, like body language and engagement. Other subjective responses related to classroom dynamics such as good teaching, attention, understanding, explanation and concentration. Others related to the need for human contact such as commitment, passion and activity. The rest of the responses were more objective and measurable such as clinical practice, supervision, time, communication, verbal feedback, and workshops. Some responders said nothing was missing.

Preferences Regarding Online Learning (Q33–38)

The reports on preferred time for online learning activities showed variability with no significant differences between trainees and trainers. The highest was evening hours after work 30.4{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} closely followed by afternoon working hours 29.5{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}, morning working hours 22.2{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}, and night after work 15.0{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}. Weekends were the least popular 2.9{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}. Most respondents, 86{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}, preferred the duration of online learning activities of not more than 2 hours with no significant difference between trainees and trainers. Lectures and case discussions were preferred by 95{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} of both trainees and trainers as the most effective online learning activities. Respondents considered multiple choice questions 54.6{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} and problem-solving questions 28.5{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} as the most effective assessment methods. With regards future preferences, 64.3{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} preferred combining traditional and online methods but a respectable proportion of 25.5{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} preferred continuing eLearning as the sole method of education. A negligible proportion of 9.7{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} wanted discontinuing online learning and returning to traditional methods.

Many respondents did not answer the item about what aspects of online education should continue post pandemic. Lectures and case presentations/discussion were the most mentioned, but these did not come with online learning. Five preferred returning to the traditional methods. One wanted “everything in online learning to continue post-pandemic”.

Discussion

Differences Between Trainers and Trainees

Online medical education is not new; however, the rapid switch to exclusive online learning worldwide required institutions to take a deep dive into what was previously considered a complementary educational tool. Although most publications are related to medical school education, several considerations and issues are common among all educational levels.^11,17 Our research adds to the increasing number of reports documenting issues and perceptions in response to the transition to online learning during the COVID-19 pandemic.

The major null hypothesis of this study states that there was no difference between trainees and trainers on all variables relating to online learning within our study. Knowing the differences is important for tailoring future online activities to suit the abilities and expectations of trainees and trainers alike. Gender differences were not significant in our study; however, a generation gap was obvious from the data. The trainers being older differed in being more married, having larger households and specialties. Besides socio-demographic variables, trainees and trainers had significant differences on 11 variables that can be grouped as transition from traditional to online learning, online assessment activities, and comparison to traditional learning.

Transition to eLearning, Stress, Coping, Perception and Satisfaction

In the transition to online learning, trainees had more years of prior experience with online learning, which reflects the generation gap. The trainees, being younger, are well versed in computer technology and internet use compared to older trainers.

Several variables were correlated with age as the underlying determining factor. Previous experience of online learning by trainees (younger in age) has made their transition to pandemic online learning easier. Younger age explains better coping with online learning through its positive correlation with pre-pandemic computer and internet competency. The younger trainees had lower overall perception, which may be related to having less experience in learning methods and outcomes in general.

A recent literature review summarized barriers and solutions to developing and implementing online learning programs for medical students and postgraduate trainees in global settings; however, they were not complicated by the challenges of a worldwide pandemic.¹⁷ Time and infrastructure issues were 2 barriers during such comparatively relaxed environment in studies reported from 2006 through 2015. A pre-pandemic United States national survey of 214 internal medicine residency program directors reported that synchronous online learning was used by 40{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} and asynchronous learning by 72{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} of programs.¹⁸ The asynchronous programs were considered to be more accommodating of resident schedules and duty hour restrictions. However, even in those non-urgent settings, faculty development was considered to be less than adequate (30{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) or non-existent (56{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) by 86{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} of respondents. In our survey, 74{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} of trainers reported being provided with few (18{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) or no (56{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) guidance prior to implementing online learning. Trainees in our study were more prepared; however, barely one-third (33{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) had received adequate guidelines before embarking on their online learning activities. Conversely, a survey study at the College of Pharmacy (COP) at King Saud bin Abdulaziz University for Health Sciences in Saudi Arabia reported that almost two-thirds of the students believed that the COP was well prepared for the complete transition to online learning during the COVID-19 pandemic.¹⁹ In our study, the trainees were more aware of guidelines before the start of online learning—they must have sought sources other than the trainers. Most likely, they looked for or demanded the guidelines.

As with any transition from the familiar to the new, the introduction of online learning was associated with stress. The trainers experienced more stress with eLearning, which is explained by their shorter experience with online learning before the start of the pandemic. A focus group study of 60 undergraduate medical students’ perceptions of online learning was carried out in Qassim region of Saudi Arabia during April and May 2020. The study reported that, similar to observations in most studies of online learning, technical issues were common barriers.¹⁵ The authors emphasized that providing technology training courses to teachers is essential. Deficiencies in these skills could contribute to stress during the transition period. In our study, almost one-fourth (24{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) of teachers experienced major or excessive stress while transitioning to an online learning setting; while only 4{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} had a negative coping experience once learning activities were underway.

Our results indicated that perception of online learning was positively correlated with coping, which is logical, and was negatively related to stress, which is understandable. Its negative correlation with overall satisfaction is explainable by the clash between the ideal of a high perception and the actual satisfaction from the reality of the experience. Indeed, as online teaching methods are being regarded as an efficient tool for learning, the quality of eLearning was expected to be comparable to traditional methods; and learning outcomes were not expected to be compromised.¹⁹ Most reports of experiences after the transition to online learning in medical education are also related to medical school education.²⁰ For example, a survey study involving pre-clinical students was carried out at the University of California at San Diego during March and April 2020. They reported that, in general, students believed the quality of instruction and their ability to participate were negatively affected by remote learning.²¹ However, the short interval that has transpired since the start of the pandemic did not make-way for examining online learning outcomes achieved by students, with either positive or negative attitude towards it. Furthermore, in November 2020, 30 residents in a Mexican general surgery residency program (PG1-PG5) participated in a study surveying their experience after transitioning to online learning since April 2020.²² Although the academic and organizational level was considered higher than that provided by traditional learning, by 47{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} and 67{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} of participants, most (57{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) were neutral about whether there was a concomitant increase in their academic performance; and whether the changes had been more useful for their training (53{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) compared with their previous training. A systematic review of 29 qualifying articles examined the impact of COVID-19 on all aspects of surgical training, including the transition to online learning.²³ Acknowledging decreased hands-on surgical experience; patient exposure was ubiquitous, which was in some cases accommodated partially by simulations and telemedicine. Although two studies reported 65{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} and 82{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} of trainees had favorable opinions of their online learning; in one study, 65{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} of trainees believed that even their theoretical training had been negatively affected.

Online Learning and Assessment Activities

Trainees differed from trainers in preferences of learning activities. Trainees had a higher proportion of lectures, while trainers had a higher proportion of seminars/webinars. There were notable differences between trainees and trainers regarding assessment activities; trainees mentioned highest participation in case presentations/discussions, while trainers mentioned more short oral examinations and online OSCE. The differences in describing the activities that took place are difficult to explain, since they experienced the same learning activities. There is a possibility that the question item was not understood by one or both groups; they may have indicated their preferences instead of their observations or the preferences biased the observations. We have no data on the distribution of respondents by hospital. It is possible that trainers who responded to the questionnaire were from hospitals that practiced online learning differently from other hospitals to which most trainees belonged.

OSCE assessment was not commonly reported by our study participants. The fact that 15{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} of teachers and 9{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} of students reported it as an assessment method and did not recommend it for the future, suggesting that they may have had a negative experience. Although OSCE has been in use for many years, its effectiveness and role continues to be examined. Some pre-pandemic studies on OSCE assessments for medical students reported higher stress and difficulty levels compared to traditional assessments.²⁴ However, positive experiences of OSCE use in medical school have also been reported. A small survey study in a teaching hospital in Dammam, Saudi Arabia, reported that 63{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} of students and 80{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} of faculty believed that OSCE provided a fair assessment of clinical skills; and approximately two-thirds agreed that it was an enjoyable experience.²⁵ Postgraduate students have also reported positive experiences with OSCE. In 2012, a survey of 66 internal medicine residents’ perceptions of OSCE was examined in Saudi Arabia, after implementation of OSCE as part of the final clerkship exam in 2008.²⁶ On a 5-point Likert scale with 5 indicating strong agreement, the mean score was 4.5 for items asking if the exam was well administered, well structured and if staff guidance was helpful. The mean agreement score for the items asking whether OSCE was stressful was 3.5 and was 2.3 for intimidating. The authors concluded that the overall perception of the residents towards OSCE was favorable and encouraging.

Prior to the COVID-19 pandemic, a small number of postgraduate training programs reported their experiences with virtual OSCEs.²⁷ Subsequently, when the UCL medical school in London canceled face-to-face assessments in response to COVID-19, an online 18-station timed OSCE was convened.²⁷ Assessments were similar to those used in traditional OSCE, including clinical communication skills, written communication, practical skills, examination skills, and professionalism. The authors shared 12 practical tips compiled from their experience and from the literature that can help in the design and delivery of online OSCE. The Harvard School of Dental Medicine developed an online OSCE during the COVID-19 pandemic using the Zoom eLearning platform, because it featured breakout rooms where private mini-sessions could be created by the host.¹⁴ Students signed-in and were allocated to their breakout rooms; then progressed through the rooms when the allotted time had passed. Most students thought the online OSCE was as successful as traditional OSCEs, and all students believed they were able to completely demonstrate their knowledge. Examiners also had positive impressions of the online OSCE and emphasized the importance of calibrations and run-throughs prior to launch. Technical issues were the only difficulties encountered. The authors believed there was value in moving the in-person assessments online in the post-pandemic era.

Comparison to Traditional Learning

Trainees differed from trainers on 6 out of 11 items comparing online to traditional learning. Trainees were more apt to agree that online learning was better for teacher-learner communication, reducing academic stress, overall satisfaction and academic stimulation, whereas the trainers disagreed. These disagreements are explainable by the phenomenon of the generation gap considering the experience with computers and the internet, which is higher in the younger trainees. Trainers agreed more than trainees that online learning gave more time to teachers. This is understandable because online learning saves transient time between events such as movement to and within the hospital.

A recent meta-analysis of studies reported from 2000 to 2017, which compared online with offline undergraduate medical education, reported that knowledge and skills were significantly improved with online learning.²⁸ Although not all studies in the review signify that online learning was more effective, none concluded that online learning was less effective than traditional learning. A single-center US study after the COVID-19 pandemic began included 81 emergency medicine and internal medicine residents. They reported that participants preferred in class interactions with peers (85{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) and lecturers (80{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}); with 62{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} reporting decreased engagement with lecturers during online conferences.¹⁰ Residents were significantly more engaged in other tasks during online conferences compared with in-class attendance. In our study, 35{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} of participants disagreed that online learning was academically more stimulating compared with traditional learning settings.

Changes in communication opportunities may contribute to decreased acceptance or effectiveness of online learning. An Egyptian survey (N = 78) and focus group (N = 25) study examined faculty perceptions of medical school responses to the COVID-19 pandemic. They reported that communication issues between faculty and students led to student detachment.²⁹ Almost two-thirds (63{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) of our teachers disagreed that online learning enhanced teacher-learner communication, and 57{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} did not agree that it improved learner-teacher communication. Although our students expressed more positivity, only 39{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} believed learner-teacher communications were improved in the online setting, and 35{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} believed teacher-learner communication was improved.

A survey of 538 clinical years (fourth through sixth year) medical students was performed in all medical schools across Jordan; less than 2 months after a state of emergency was proclaimed in response to the COVID-19 pandemic in 2020.³⁰ Over half of the participants (62{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) reported poor interaction with instructors as a drawback, with only 14{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} reporting better interaction in an online learning setting. More students would prefer a hybrid approach in the future whether they were satisfied (22{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}), neutral (24{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}), or dissatisfied (29{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) with the online learning; and a return to traditional learning was preferred by more students dissatisfied with online learning (15{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) compared with neutral (4{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) and satisfied (1{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) students. The majority of our teachers and students advocated for hybrid (65{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) or online only (26{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) education in the post-pandemic period; accordingly, efforts to maximize the benefits provided by online education are warranted.

A cross-sectional study in India included 55 postgraduate surgery residents who were without previous exposure to online teaching; the study was performed 1 month after transitioning to online didactic training during the COVID-19 lockdown.³¹ The transition included an orientation program for all teachers and residents. Individual items on the quality of online teaching did not indicate perceived superiority of either online or traditional learning; however, the authors considered the overall quality perception of online teaching to be favorable. The participants in our study were almost exclusively involved in theoretical learning and teaching. Transitioning to online education in this capacity does not require the capabilities, infrastructure, and inputs that are required to provide online clinical training. Overall, one-half of our study participants disagreed that online learning was better for teaching skills, with a higher percentage of teachers sharing this view (63{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) compared with students (45{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}). Similarly, a survey study of medical schools was conducted in Libya in mid 2020; stating that over half (55{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) of the participants disagreed or strongly disagreed that online learning can be used for teaching clinical aspects of medical sciences.³²

Recommendations

A review of 14 studies on adaptive processes to the COVID pandemic in undergraduate and residency programs concluded that re-modulating the educational approach provided positive opportunities for personal and professional growth.¹¹ However, the authors acknowledged that these qualitative narrative studies did not systematically analyze the characteristics and results of the changes that were introduced. They also believed that many of the enhancements that were described would require economic inputs that are not achievable in many parts of the world. Another study also suggested that the shift toward online education may have a lasting positive impact.³³

The historical use of online videos for teaching procedural skills to postgraduate medical learners was exemplified when a systematic review was able to identify 20 qualifying articles published between 2009 and 2019.³⁴ In the pre-pandemic period, the use of online videos was considered complementary to the more traditional teaching models. Virtual lectures could allow expert educators to disseminate beneficial knowledge to programs that do not have that level of expertise. Within an institution, cross-disciplinary education may be facilitated. It is considered that on demand virtual asynchronous lessons can be an inexpensive way to improve both access and content quality.³⁵ These authors also believed that cross-institutional virtual collaborations can be part of a low-cost time conservative strategy; providing specialized training that otherwise may not be available in the learners’ institutions.

Several recommendations have emerged as medical training had to be adjusted for the limitations of COVID-19 on a global scale. Telehealth initiatives have been launched and/or expanded in several settings. When permitted by their institutions, residents can benefit from participating in virtual patient visits, reviewing charts and engaging in patient counseling under the supervision of the attending physician.³⁶ Studies for examining the benefit of incorporating telemedicine into resident curricula are warranted. A few programs have responded to the pandemic by creating virtual video-based clinical training.³⁷ A US undergraduate surgical education curriculum developed in response to the pandemic, emphasized the importance of using an interactive live-streaming platform for surgical experience, as well as patient-facing telehealth visits.³⁸ The authors concluded that their virtual surgical education could be expanded for use in the post-pandemic era. Accordingly, institutions could benefit from cooperating on the development of valid strategies to incorporate clinical training into their postgraduate educational programs. Cleveland Clinic in Abu Dhabi constructed a 3-level pandemic response approach for developing and facilitating interventions determined to be necessary to maintain residency training.³⁹ Online didactic education was supplemented by converting rounds to virtual platforms. However, their detailed framework description awaits assessment of its effectiveness and resident perceptions and satisfaction.

It is evident that currently published studies must be examined for their contributions to online learning development and implementation strategies in the future. Surveys such as our study can provide the basis for undertaking additional studies; to identify and adopt creative methods for effective online learning delivery and assessment. Tracking and identifying student skill gaps has become even more essential in a setting with reduced clinical learning opportunities. Innovation opportunities triggered by the pandemic should be taken advantage of; virtual and augmented reality technologies may be particularly important for teaching practical skills such as emergency interventions and surgical techniques.

In summary, our study adds to the baseline provided by numerous other studies of online learning experiences during the first few months of the COVID-19 pandemic. These early publications should be followed with additional studies, where details of program design and modifications in response to these initial observations are shared and realistic assessments of program effectiveness are performed. The availability of adequate qualitative details can contribute to collaborative participation in developing standardized strategies that can overcome the challenges of the pandemic and increase the quality of medical education in the future.

Limitations of the Study

The actual study sample of 207 was adequate according to calculations, but the researchers had been ambitious sending out 1200 questionnaires to capture as much diversity as possible. The relatively low response proportion of 17{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} is explained by the general digital fatigue in the society, because people receive many research questionnaires through the social media. The sampling could have been more representative if it was stratified to account for differences between training hospitals and academic centers. The study could have been enriched by additional qualitative research on some variables to obtain more in-depth understanding of online learning, which is a new phenomenon.

Conclusion

The main finding of the study is the difference between trainees and trainers in their experiences with online learning. This is explained by the generation gap in the acquisition and use of modern technology between the older trainers and the younger trainees. Overall, there was high proportions of coping, perceptions and satisfaction with online learning. The majority of the respondents also preferred continuing online learning combined with traditional methods in the post-pandemic period.

Acknowledgments

Dr. Valerie Zimmerman for her great work in reviewing the manuscript.

Disclosure

The authors report no conflicts of interest in this work.

References

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July 22, 2022

Impact of COVID-19 pandemic on Medical Education in Saudi

Summary of Study

The pandemic of Coronavirus Disease 2019 (COVID-19) has a significant influence on medical education and healthcare institutions. To support the learning objectives during the pandemic, several learning management systems were used. In Saudi Arabia, the majority of colleges adopted the online teaching methods. There is considerable similarity between online and traditional education. While several research have concluded that there are no substantial differences between traditional and e-learning, some have found the opposite. One of the most serious drawbacks of e-learning is the lack of clinical access. In Saudi Arabia, e-learning is not the favored mode of teaching in medical schools. The majority of the students thought of e-learning as an interactive system that allows them to learn.

Background

Coronavirus disease (COVID-19) was discovered in December 2019 in Wuhan, Hubei Province, China-pneumonia-like symptoms characterize the virus. The disease spread rapidly globally, resulting in an outbreak. The World Health Organization (WHO, 2020) declared it a global pandemic on March 11, 2020.¹

Since March 25, 2020, over 150 countries have temporarily shut down colleges and educational institutions, affecting more than 80{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} of the world’s student population. According to the Saudi Ministry of Education, health authorities have recommended “preventive and precautionary” measures to ensure that students and staff are appropriately protected.²

This has led to a shift in education in most academic faculties, transforming learning from traditional to online. Consequently, colleges provided students with several learning management systems.³ One of the most suggested approaches is scheduled live-online video lectures with interactive discussions using different applications or self-study online recorded lectures.^4,5 Virtual clinical experience was another approach to the suspension of clinical clerkship rotation. This idea supports the concern of the Ministry of Health regarding medical students’ exposure to the virus during training as well as their potential to act as spreaders of the virus in the community.⁶ They were limited patient care and bedside learning opportunities during the pandemic, as doctors and other healthcare workers were required to focus on COVID-19 cases. Hence, students were safe at home, complying with social distance guidelines; they learned about the dynamics of patient interaction by interviewing patients, collaborating with treatment planners, assisting with paperwork, and counselling patients.⁷

Online and traditional education shares several similarities. Students still have to attend class, learn new topics, submit assignments, and participate in group projects. While many studies have found no significant differences between traditional and e-learning, others have reported opposing results.⁸ E-learning offers more program choices, compared with traditional face-to-face learning. It is classified as synchronous or asynchronous. Synchronous e-learning allows live interactions between tutors and students, such as live-video conferences and chats.⁹ Asynchronous e-learning can involve e-mails, recorded videos, etc., where there are time lags between the tutor and their students.⁹

With traditional classroom education, students are confined to taking courses at specific centers on a fixed schedule. Thus, e-learning helps save up to 60{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} of traditional learning time, with the only requirements being an adequate computer, internet connection, and basic computer skills.^10,11

In contrast, online classes involved an absence of in-person, face-to-face classroom, or office interactions. For many students and programs, interpersonal communication is crucial. For example, consulting lecturers in person and discussing matters in groups is an essential motivational activity and learning strategy; however, it is not easy to practice medicine online.^12–16

Additionally, the on-campus atmosphere and the opportunity to meet many people face-to-face is another motivation for students; moreover, it has an essential impact on student performance and understanding lectures. Nevertheless, in e-learning, online classes depend on personal factors, such as: student’s home environment, socioeconomic factors, and parents’ level of education. Unfortunately, conducive surroundings are not always available to many students.

Another essential factor in students’ comprehension; online teaching can easily create a sense of boredom while listening to a monotonous lecture, devoid of interaction and visual stimulation. This reduces students’ motivation to attend future lectures.¹⁷

The perceived benefits of both teaching methods must be thoroughly outlined and assessed to determine which medium generates better student performance. Both approaches are generally beneficial; however, we still need to examine whether one is more superior compared to the other. Hence, this study aimed to measure the effect of online classes on medical students’ comprehension attending campus classes during the COVID-19 pandemic.

Methods

Study Design

We conducted a cross study using an online survey between 2020 and 2021. Data were collected from medical students in their basic and clinical years in the western region of Saudi Arabia using a questionnaire. Questionnaires with incomplete or missing data were excluded from the analysis.

Questionnaire Tool

The survey was adapted from previously validated assessment scales.^3,18 The survey involved 45 multiple-choice and multiple-answer questions, including primary demographic data, such as age, gender, academic year, and the name of the school they attended, without recording any identifying data for confidentiality. Additionally, the survey included general questions about the students’ knowledge of e-learning and the status of the technology tools used during the education process. It also had questions to assess the students’ attitude toward the e-learning system as well as their evaluation and suggestions for improving online teaching. Finally, specific questions were asked to appraise the effect of the COVID-19 pandemic on medical students.

Sampling Strategy

A convenience sampling method was used. All medical students in the Western region of Saudi Arabia were invited to participate in the study. The inclusion criteria were clear in the invitation letter and sent along with the survey link. There was no incentive was provided to the participants to be involved in the study. The survey was conducted online using the Google Forms© and was distributed through social media platforms such as: WhatsApp, and Twitter. A total of 922 respondents were included.

Study Outcomes

The primary outcome was measuring the effect of online classes on medical students’ comprehension of attending campus classes during the COVID-19 pandemic. Secondary outcomes included comparing the level of medical students’ morning excitement for attending lectures before and during COVID-19; further, we also assessed medical students’ attendance rate before and during COVID-19 and the effect of students’ limited clinical exposure on their knowledge. A copy of the questionnaire will be found in Supplementary Section.

Statistical Analysis

Descriptive statistics were used to summarize the data and synthesize a report of the variables. The data description includes proportions and frequencies, for continuous variables. The statistical analyses were carried out using S.P.S.S. (version 27).

Results

Demographics Characteristics

Of the 3700 questionnaires, we collected 922 completed online questionnaires from students of 11 medical schools in the western region of Saudi Arabia. Participants were predominantly women; the sample included 693 (75.2{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) women and 229 (24.8{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) men; their mean age was 22 (28.3{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) years. Umm AL-Qura University had the highest response rate with 232 responses (25.2{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}), followed by King Abdulaziz University with 186 responses (20.2{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) and Taibah University with 112 responses (12.1{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}). Two (0.2{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) of those who completed the survey were not included in the western region of Saudi Arabia. A more significant number of respondents included medical students who had finished their fourth year with a response rate of 325 (35.2{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}), followed by those who completed the fifth year with 310 responses (33.6{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}). Finally, 33 (3.6{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) responses completed by prior-year students or interns were not included in the sample size. For details see Table 1.

Table 1 Demographic Data of the Study Participants

Students’ Experience About e-Learning

Approximately 49.2{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} students started online classes during the first week of lockdown. The majority of institutions preferred Blackboard and Zoom as video-conferencing platforms for e-learning. A total of 624 (67.7{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) students used Blackboard, whereas 612 (66.4{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) used Zoom. Microsoft Teams and Webex Meet were less preferred, as 237 (25.7{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) and 128 (13.9{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) used Microsoft Teams and Webex Meet, respectively. Overall, 727 (78.9{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) students had five or more online classes per week, 30.3{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} of them had live classes (synchronous), 6{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} had recorded classes (asynchronous), and 63.8{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} had both (synchronous and asynchronous) (see Table 2).

Table 2 Students’ Experience About e-Learning

Effect of COVID-19 on the Medical Education Process and Evaluation of e-Learning

A total of 395 (42.8{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) had experienced suspension of their education by the faculty, and 529 (57.4{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) had suspended their clinical training. In addition, 17.4{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} students suspended their education program by themselves due to social status and personal responsibilities. Thus, 410 (44.5{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) students stated that the COVID-19 pandemic did not affect their career plans and future interests, but 331 (35.9{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) reported the opposite. Moreover, owing to the lockdown students had more free time than earlier. Overall, 490 (53.1{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) students spent their time resting and relaxing, 456 (49.5{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) spent time with family, and 386 (41.9{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) spent their time watching television. However, our study showed that many students invested their time wisely, as 619 (67.1{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) students participated in programs related to medical education. Further, approximately 396 (43{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) participated in medical research activities and 401 (43.5{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) in volunteering activities; for details (see Tables 3 and S1).

Table 3 Effect of COVID-19 on the Medical Education Process

Student’s Attitude During COVID-19 Pandemic

Regarding students’ attitudes toward e-learning, 391 (42.4{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) students were worried about losing opportunities to apply for specialty training due to the lockdown. Regarding the students’ perspectives on e-learning, the study shows that a majority of students, that is 451 (48.9{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}), believed that e-learning depends on the comprehensive digital electronic environment displaying educational curriculum through electronic networks. In comparison, 423 (45.9{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) students believed it was an interactive system that provided an opportunity to learn information and telecommunication technology. Moreover, 367 (39.8{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) students believed that e-learning provides digital multimedia content (ie, written text, audio, video, and images). Less than one-third of the students, that is 255 (27.7{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}), believed that e-learning in the medical field is not less expensive than conventional learning. A total of 248 (26.9{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) students considered e-learning as a type of tele-education, and for 207 (22.5{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) instant feedback from the instructor was a benefit of online-learning. E-learning has benefits and drawbacks that affect students’ lives differently. Overall, 603 (65.4{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) students agreed e-learning helps save money and energy, that is typically expended during commuting; moreover, they believed it was a more straightforward learning method.

Furthermore, 365 students (39.6{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) believed that it limits the consequences of social contact and 355 (38.5{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) thought it causes fewer absences than traditional teaching, whereas 296 (32.1{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) students believed that e-learning caused more absences. A total of 232 (25.2{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) students believed that it resulted higher academic achievement, whereas 230 (24.9{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) agreed that results in better student interaction in classes. However, as Table 4 shows, 555 (60.2{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) of students believed the limitation of clinical access was one of the biggest disadvantages of e-learning. Moreover, 466 (50.5{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) students disliked the absence of direct contact with a lecturer in e-learning, whereas 386 (41.9{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) believed that technical requirements were a disadvantage of e-learning. In contrast, 323 (35{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) students did not have a conducive environment in the house during online classes. Approximately one-third (32.8{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) students believed that e-learning courses lower academic achievement; moreover, 160 (17.4{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) felt that online classes were not safe, whereas 280 (30.4{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) students were unable to adapt to e-learning. Regarding student attendance, 727 (78.9{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) students attended five lectures or more per week, and 376 (40.8{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) students were able to participate in more than 80{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} of the classes per week. Moreover, 409 (44.4{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) students attended only 50–80{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} of the classes, whereas 137 (14.9{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) were able to participate in only less than 50{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}. For details see Table 4.

Table 4 Student’s Attitude During COVID-19 Pandemic

Status of Educational Technology Tools During the COVID-19 Pandemic

Table S2 describes the students’ proficiency with using various electronic devices: 108 (11.7{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) reported themselves as proficient, 171 (18.5{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) were perfect, 371 (40.2{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) were good, 228 (24.7{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) had an acceptable level, and 4.8 (44) had an inadequate level. In medical education, the students’ computers varied between tablets (683 [74.1{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}]) and smartphones (457 [49.6{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}]). Further, 543 (58.9{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) students used personal computers. Around, 698 (75.7{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) were dependent on the university’s lectures for their study, 619 (67.1{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) were dependent on self-study and utilized various educational sources, whereas 254 (27.5{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) attended extra courses provided by private education centers.

E-Learning Improvement

Finally, the students could help assess e-learning, as shown in Table S3. Overall, 518 (56.2{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) students did not want to continue using e-learning on its own in the future, whereas 668 (72.5{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) wished to use e-learning in combination with traditional learning.

Discussion

The COVID-19 pandemic has resulted in a remarkable shift in education and learning methods. Additionally, some medical colleges have adopted open-book examinations, which have shifted toward an entirely new online teaching and examination system. Therefore, studying the effects of e-learning using several parameters on medical students is imperative e-learning. This study aimed to measure the impact of online classes on medical students’ comprehension of attending campus classes during the COVID-19 pandemic. Moreover, we compared the different changes in medical students’ levels of excitement and rate of attendance in e-learning before and after the pandemic.

According to medical students’ responses, our findings revealed that the advantages of e-learning vary among students. Of the students, 423 (45.9{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) thought e-learning to be an interactive system that provides a learning opportunity. In contrast, a minimal number of students agreed that they had interactive classes. Consequently, 232 (25.2{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) believed that it offered high academic achievement. Likewise, in the study conducted by Cicha et al, the majority of participants demonstrated a positive feedback about distance learning.¹⁹ In contrast, when asked about the disadvantages, most students believed that the limitations of clinical access were one of the worst disadvantages of e-learning. Moreover, 466 (50.5{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) students disliked the absence of direct contact with the lecturer during classes. In contrast, 323 (35{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) students did not have a calm home environment during online classes. Finally, 280 (30.4{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) could not adapt to their online environment. Compared to our study, similar advantages and disadvantages were found in many reports in the literature.^17,19–22

Technology knowledge is one of the most important factors for easy transition and success in e-learning.^23–25 In our study, the participants reported the need of technical knowledge was one of the major disadvantages of e-learning.

Based on the previous responses of our survey, we noted that medical students believed that e-learning has far more disadvantages, compared with traditional methods that allow for clinical exposure. These disadvantages are considered critical parameters that facilitate each student’s comprehension and understanding. A total of 302 (32.8{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) students believed that e-learning lowered academic achievement.

The survey results indicate a change in the attendance rates during the pandemic, compared with those recorded before the pandemic. A total of 376 (40.8{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) of students could attend more than 80{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} of classes per week. In contrast, 137 (14.9{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) attended less than 50{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} of the classes. The underlying reasons behind their absenteeism include poor internet connection, inappropriate class timing, and discomfort with virtual teaching.

Several studies have supported the impact of the COVID-19 pandemic on medical education using different perspectives. A study that took place in United Kingdom has identified the effect of the COVID-19 outbreak on final year medical students’ examinations, electives, and assistantship placements and the subsequent impact on preparedness and confidence. Many students felt less prepared to begin work as doctors. This study shows that disruptions to student assistantships significantly impact preparedness, which results in lowered academic achievement.²⁶

Another study investigated medical students’ perceptions regarding the role of online teaching in facilitating medical education during the COVID-19 pandemic. This study suggests that most students prefer face-to-face teaching.²⁷ This study reported that the cancellation of clinical examinations and the conversion of written examinations into open book ones reduces student engagement, which was in line with the findings of our study.

A few limitations of e-learning mentioned in this study was related to technical issues. Moreover, many teachers are inadequately prepared and face many technical difficulties. The quality of the sessions delivered may have been affected by several factors, such as poor internet connection, family distractions, and the timing of the tutorials, as demonstrated by our results.

Students’ mental health is impacted by the COVID-19 pandemic, which may be adversely affected by the lack of interaction with friends and colleagues, leading to an increase in anxiety.¹⁸ As mentioned in the same study, the main advantages of online teaching are the time and money saved from the lack of travel, flexibility, and the ability for students to learn at their own pace.²⁷ This is similar to our results.

Another study conducted in Jordan,³ which assessed students’ class experience, lecturers’ interaction, and e-learning advantages and disadvantages. Their results show that the e-learning experience was not favorable for most medical students due to limitations with regard to technology, and that traditional face-to-face teaching method is preferred for various reasonse-learning. Furthermore, the non-direct contact between lecturers and students is a significant obstacle, as students and lecturers have had on-ground interaction during regular lectures prior to COVID-19. Finally, the lack of clinical access to medical students is one of the most significant disadvantages due to the essentiality of patients’ exposure to medical students in clinical years.³ In contrast, their students’ online attendance rate was lower than ours. Thus, the cause of this difference in attendance rates required further investigation.³

Another study evaluated the comparison between face-to-face learning and e-learning modalities in teaching an environmental science course and additionally evaluated factors of gender and class rank.¹¹

The results of this study did not show significant difference in performance between online and traditional classroom students by modality and gender. Further, as there is no significant difference in student performance between the two mediums, higher education institutions may gradually shift away from traditional instruction and implement web-based teaching to capture a larger worldwide audience.

If administered correctly, this shift to web-based teaching could lead to a higher cost efficiency, and higher university revenue.¹¹

Many hospitals have suspended medical student clerkships during COVID-19 pandemic. Unfortunately, in our study, student clerkships in the hospitals were suspended or postponed in about 50{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} of participants. This is can be a major defect in their medical education journey and needs to be compensated as soon as applicable (12,J).

Our study had some limitations. First, the design of the study is cross-sectional in nature, some missing data could limit the conclusion of the study. The independent variables were not adjusted for real-life accuracy. Furthermore, students have different skills, abilities, preparation, and familiarity with online instructions. Experienced traditional classroom students who take online-based classes and lectures may lack the technical requirements of e-learning. Therefore, they may not be prepared to use e-learning efficiently, thus leading to lowered scores. Second, some medical schools may have been disproportionately represented with more significant numbers of responses from some schools. Finally, some aspects of our survey depended on students’ memory, which may have influenced their reporting.

Implications and Recommendations

Our study is relevant as it explored a crucial educational topic. Simultaneously, the COVID-19 pandemic has accelerated the widespread use of electronic learning in medical education without pre-preparations. This fast acceleration should be investigated to determine its advantages and disadvantages. The results of this study will help make critical decisions for the future of medical education. Moreover, it would help improve electronic education and adapt it to the needs of medical education and medical students by considering all the benefits. According to the student’s responses, as shown in the results, 72.5{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} (668) wished to use e-learning in combination with traditional learning. Face-to-face learning is essential to increase the academic achievement of medical students and has higher clinical exposure. Additionally, online-learning helps save time, money, and energy. Additionally, we recommend that medical students should be prepared for online applications and platforms to improve their knowledge and experience.

Future studies are needed to investigate the same topic in the broader field of medical education, including the basic years. Moreover, further examination is necessary to find alternative models of clinical exposure that would be effective in compensation during situations similar to the COVID-19 pandemic. Finally, additional studies are needed to investigate an appropriate and effective way to use e-learning alongside traditional learning.

Conclusion

This study found that advantages of e-learning vary among students. Most of the students thought e-learning to be an interactive system that provides a learning opportunity. In contrast, many of the students believed that there were many disadvantages regarding online teaching methods. These findings has been seen in many reports in the literature recently and indicates that further studies are needed to identify the potential causes.

Ethical Statement and Institutional Review of Board Statement

The study was approved by the Faculty of Medicine at Umm Al-Qura University, Makkah, Saudi Arabia (NO. HAPO-02-K-012-2021-06-696). This study was performed in accordance with the principles stated in the Declaration of Helsinki.

Informed Consent

Informed consent was obtained from all subjects involved in the study.

Disclosure

The authors declare no conflicts of interest.

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Demographics

Improvement in self-confidence for unit 1

Improvement in self-confidence for unit 2

Improvement in self-confidence for unit 3

Subgroup analysis

Sex

Age

Prior surgical experience

Online student cross-sectional survey

Demographic characteristics

Quantitative results to the sense of belonging questionnaire

Qualitative results

Global theme—navigating belonging during the COVID-19 crisis: a shared responsibility

Organising theme: dimensions of belonging

Basic theme: what it means to belong

Basic theme: layers of belonging

Peers

Academics

Profession

Organising theme—Individual experiences and challenges

Basic theme —challenges of transition

Basic theme : recognising different learning preferences

Organising theme—relationships are central to belonging

Basic theme —collaboration with peers is fundamental

Basic theme— communication with academics is necessary

Organising theme: reconceptualising teaching and learning

Basic theme: challenges of online teaching and learning: “how do I make this work?”

Managing workload

Class dynamics

Technological challenges

Basic theme: strategies to engage and connect

Phase 1 and 2: defining the concourse

Stage 3: screening and assortment of statements (Q-sample)

Phase 4: picked P-established

Phase 5: Q-sort

Stage 6: examination and interpretation of components

Introduction

Research Objectives

Materials and Methods

Results

Study Sample Socio-Demographics (S1–5)

Transition from Traditional to Online Learning and Changes in Institutional Policies, Procedures, and Support (Q1, 2, 9–14)

Online Learning During the Pandemic: Experiences, Perceptions and Satisfaction (Q3–8, 15–17, 19)

Comparison of Online to Traditional Face to Face Learning (Q20–32)

Preferences Regarding Online Learning (Q33–38)

Discussion

Differences Between Trainers and Trainees

Transition to eLearning, Stress, Coping, Perception and Satisfaction

Online Learning and Assessment Activities

Comparison to Traditional Learning

Recommendations

Limitations of the Study

Conclusion

Acknowledgments

Disclosure

References

Summary of Study

Background

Methods

Study Design

Questionnaire Tool

Sampling Strategy

Study Outcomes

Statistical Analysis

Results

Demographics Characteristics

Students’ Experience About e-Learning

Effect of COVID-19 on the Medical Education Process and Evaluation of e-Learning

Student’s Attitude During COVID-19 Pandemic

Status of Educational Technology Tools During the COVID-19 Pandemic

E-Learning Improvement

Discussion

Implications and Recommendations

Conclusion

Ethical Statement and Institutional Review of Board Statement

Informed Consent

Disclosure

References

Basic
theme
—challenges of transition

Basic
theme
:
recognising different learning preferences

Basic
theme
—collaboration with peers is fundamental

Basic theme—
communication
with academics is necessary

Basic theme:
challenges
of online teaching and learning: “how do I make this work?”