challenges of online learning during covid 19 essay

The Challenges of Online Learning during the COVID-19 Pandemic: An Essay Analysis of Performing Arts Education Students

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Challenges of Online Learning During the COVID-19: What Can We Learn on Twitter?

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• First Online: 17 November 2021
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• Wei Quan   ORCID: orcid.org/0000-0003-2270-7376 8  

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The COVID-19 pandemic is an ongoing global pandemic. With schools shut down abruptly in mid-March 2020, education has changed dramatically. With the phenomenal rise of online learning, teaching is undertaken remotely and on digital platforms, making schools, teachers, parents, and students face a steep learning curve. This unplanned and rapid move to online learning with little preparation results in a poor experience for everyone involved. Thus, this study explores how people perceive that online learning during the COVID-19 pandemic is challenging. We focus on tweets in English scraped from March to April 2020 with keywords related to the COVID-19 pandemic and online learning. We applied the latent Dirichlet allocation to discover the abstract topics that occur in the data collection. We analyzed representative tweets from the qualitative perspective to explore and augment quantitative findings. Our findings reveal that most challenges identified align with previous studies. We also shed light on several critical issues, including mental health, the digital divide, and cyberbullying. Future work includes investigating these critical issues to enhance teaching and learning practices in the post-digital era.

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Quan, W. (2021). Challenges of Online Learning During the COVID-19: What Can We Learn on Twitter?. In: Guarda, T., Portela, F., Santos, M.F. (eds) Advanced Research in Technologies, Information, Innovation and Sustainability. ARTIIS 2021. Communications in Computer and Information Science, vol 1485. Springer, Cham. https://doi.org/10.1007/978-3-030-90241-4_40

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Shifting online during COVID-19: A systematic review of teaching and learning strategies and their outcomes

• Joyce Hwee Ling Koh   ORCID: orcid.org/0000-0001-5626-4927 1 &
• Ben Kei Daniel 1  

International Journal of Educational Technology in Higher Education volume  19 , Article number:  56 ( 2022 ) Cite this article

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This systematic literature review of 36 peer-reviewed empirical articles outlines eight strategies used by higher education lecturers and students to maintain educational continuity during the COVID-19 pandemic since January 2020. The findings show that students’ online access and positive coping strategies could not eradicate their infrastructure and home environment challenges. Lecturers’ learning access equity strategies made learning resources available asynchronously, but having access did not imply that students could effectively self-direct learning. Lecturers designed classroom replication, online practical skills training, online assessment integrity, and student engagement strategies to boost online learning quality, but students who used ineffective online participation strategies had poor engagement. These findings indicate that lecturers and students need to develop more dexterity for adapting and manoeuvring their online strategies across different online teaching and learning modalities. How these online competencies could be developed in higher education are discussed.

Introduction

Higher education institutions have launched new programmes online for three decades, but their integration of online teaching and learning into on-campus programmes remained less cohesive (Kirkwood & Price, 2014 ). Since early 2020, educational institutions have been shifting online in response to the COVID-19 pandemic. Some consider this kind of emergency remote teaching a temporary online shift during a crisis, whereas online learning involves purposive design for online delivery (Hodges et al., 2020 ). Two years into the pandemic, fully online, blended or hybridised modalities are still being used in response to evolving COVID-19 health advisories (Jaschik, 2021 ). Even though standards for the pedagogical, social, administrative, and technical requirements of online learning have already been published before the pandemic (e.g. Bigatel et al., 2012 ; Goodyear et al., 2001 ), the online competencies of lecturers and students remain critical challenges for higher education institutions during the pandemic (Turnbull et al., 2021 ). Emerging systematic literature reviews about higher education online teaching and learning during the pandemic focus on the clinical aspects of health science programmes (see Dedeilia et al., 2020 ; Hao et al., 2022 ; Papa et al., 2022 ). Understanding the strategies used in other programmes and disciplines is critical for outlining higher education lecturers’ and students’ future online competency needs.

This study, therefore, presents a systematic literature review of the teaching and learning strategies that lecturers and students used to shift online in response to the pandemic and their consequent outcomes. The review was conducted through content analysis and thematic analysis of 36 peer-reviewed articles published from January 2020 to December 2021. It discusses how relevant online competencies for lecturers and students can be further developed in higher education.

Methodology

A Systematic and Tripartite Approach (STA) (Daniel & Harland, 2017 ) guided the review process. STA draws from systematic review approaches such as the Cochrane Review Methods, widely used in application-based disciplines such as the health sciences (Chandler & Hopewell, 2013 ). It develops systematic reviews through description (providing a summary of the review), synthesis (logically categorising research reviewed based on related ideas, connections and rationales), and critique (providing evidence to support, discard or offer new ideas about the literature).

Framing the review

The following research questions guided the review:

What strategies did higher education lecturers and students use when they shifted teaching and learning online in response to the pandemic?

What were the outcomes arising from these strategies?

Search strategy

Peer-reviewed articles were identified from databases indexing leading educational journals—Educational Database (ProQuest), Education Research Complete (EBSCOhost), ERIC (ProQuest), Scopus, Web of Science (Core Collection), and ProQuest Central. The following search terms were used to locate articles with empirical evidence of lecturers’ and/or students’ shifting online strategies:

(remote OR virtual OR emergency remote OR online OR digital OR eLearning) AND (teaching strateg* OR learning strateg* OR shifting online) AND (higher education OR tertiary OR university OR college) AND (covid*) AND (success OR challenge OR outcome OR effect OR case OR lesson or evidence OR reflection)

The following were the inclusion and exclusion criteria:

Review period—From January 2020 to December 2021, following the first reported case of COVID-19 (WHO, 2020 ).

Language—Only articles published in the English language were included.

Type of article—In order maintain rigour in the findings, only peer-reviewed journal articles and conference proceedings were included, and non-refereed articles and conference proceedings were excluded. Peer-reviewed articles reporting empirical data from the lecturer and/or student perspectives were included. Editorials and literature reviews were examined to deepen conceptual understanding but excluded from the review.

The article’s focus—Articles with adequate descriptions and evaluation of lecturers’ and students’ online teaching and learning strategies undertaken because of health advisories during the COVID-19 pandemic were included. K-12 studies, higher education studies with data gathered prior to January 2020, studies describing general online learning experiences that did not arise from COVID-19, studies describing the functionalities of online learning technologies, studies about tips and tricks for using online tools during COVID-19, studies about the public health impact of COVID-19, or studies purely describing online learning attitudes or successes and challenges during COVID-19 without corresponding descriptions of teaching and learning strategies and their outcomes were excluded.

A list of 547 articles published between January 2020 and December 2021 were extracted using keyword and manual search with a final list of 36 articles selected for review (see Fig.  1 ). The inclusion and exclusion criteria were applied to the PRISMA process (Moher et al., 2009 ). The articles and a summary of coding are found in Appendix .

Article screening with the PRISMA process

Data analysis

Content analysis (Weber, 1990 ) and thematic analysis (Braun & Clarke, 2006 ) were used to answer the research questions. Pertinent sections of each article outlining lecturers’ and/or students’ shifting online strategies were identified, read and re-read for data familiarisation. The first author used content analysis to generate eight teaching and learning strategies. These were verified through an inter-rater analysis where a random selection of eight articles was recoded by a second-rater (22.22% of total articles) and confirmed with adequate Cohen’s kappas (Teaching strategies: 0.88, Learning strategies: 0.78). Frequency counts were analysed to answer research question 1.

For the second research question, we first categorised the various shifting online outcomes described in each article and coded each outcome as “success”, “challenge”, or “mixed”. Successful outcomes include favourable descriptions of teaching, learning, or assessment experiences, minimal issues with technology/infrastructure, favourable test scores, or reasonable attendance/course completion rates, whereas challenging outcomes suggest otherwise. Mixed outcomes were not a success or challenge, for example, positive and negative experiences during learning, assessment or with learning infrastructure, or mixed learning outcomes such as positive test scores but lower ratings of professional confidence. Frequency distributions were used to compare the overall successes and challenges of shifting online (see Tables 1 and 2 of “ Findings ” section). Following this, the pertinent outcomes associated with each of the eight shifting online strategies were pinpointed through thematic analysis and critical relationships were visualised as theme maps. These were continually reviewed for internal homogeneity and external heterogeneity (Patton, 1990 ). To ensure trustworthiness and reliability (Creswell, 1998 ), there was frequent debriefing between the authors to refine themes and theme maps, followed by critical peer review with another lecturer specialising in higher education educational technology practices. Throughout this process, an audit trail was maintained to document the evolution of themes. These processes completed the description and synthesis aspects of the systematic literature review prior to critique and discussion (Daniel & Harland, 2017 ).

Descriptive characteristics

Descriptive characteristics of the articles are summarised in Table 1 .

Table 1 shows that articles about shifting online during the pandemic were published steadily between August 2020 and December 2021. About two-thirds of the articles were based on data from the United States of America, Asia, or Australasia, with close to 45% of the articles analysing shifting online strategies used in the disciplines of Natural Sciences and Medical and Health Sciences and around 60% focusing on degree programmes. While there was an exact representation of studies with sample sizes from below 50 to above 150, the majority were descriptive studies, with close to half based on quantitative data gathered through surveys. About half of the articles focused on teaching strategies, while around 40% also examined students' learning strategies. However, only about 20% of the articles had theoretical framing for their teaching strategies. Besides using self-developed theories, the authors also used established theories such as the Community of Inquiry Theory by Garrison et. al. ( 2010 ), the Interaction Framework for Distance Education by Moore ( 1989 ), self-regulated learning by Zimmerman ( 2002 ) and the 5E model of Bybee et. al. ( 2006 ). Different types of shifting online outcomes were reported in the articles. The majority documented the positive and negative experiences associated with synchronous or asynchronous online learning activities, online learning technology and infrastructure, or online assessment. A quarter of the articles reported data on student learning outcomes and attendance/completion rates, while a minority also described teaching workload effects. Table 2 shows other successes and challenges associated with shifting online. Of the articles that examined online learning experiences, over a quarter reported clear successes in terms of positive experiences while about half reported mixed experiences. Majority of the articles examining technology and infrastructure experiences or assessment experiences either reported challenging or mixed experiences. All the articles examining learning outcomes reported apparent successes but only half of those investigating attendance/completion rates found these to be acceptable. Only challenges were reported for teaching workload.

Teaching strategies and outcomes

Lecturers used five teaching strategies to shift online during the pandemic (see Table 3 ).

Online practical skills training

Lecturers had to create online practical skills training . With limited access to clinical, field-based, or laboratory settings, lecturers taught only the conceptual aspects of practical skills through online guest lectures, live skill demonstration sessions, video recordings of field trips, conceptual application exercises, or by substituting skills practice with new theoretical topics (Chan et al., 2020 ; de Luca et al., 2021 ; Dietrich et al., 2020 ; Dodson & Blinn, 2021 ; Garcia-Alberti et al., 2021 ; Gomez et al., 2020 ; Xiao et al., 2020 ). Only in three studies about forest operations, ecology, and nursing was it possible to practice hand skills in alternative locations such as public parks and students’ homes (Dodson & Blinn, 2021 ; Gerhart et al., 2021 ; Palmer et al., 2021 ).

Outcomes : Online practical skills training had different effects on learning experiences, test scores, and attendance/completion rates. Students can attain expected test scores through conceptual learning of practical skills (Garcia-Alberti et al., 2021 ; Gomez et al., 2020 ; Xiao et al., 2020 ). However, not all students had positive learning experiences as some appreciated deeper conceptual learning, but others felt disconnected from peers, anxious about losing hand skills proficiency, and could not maintain class attendance (de Luca et al., 2021 ; Dietrich et al., 2020 ; Gomez et al., 2020 ). Positive learning experiences, reasonable course attendance/completion rates, and higher confidence in content mastery were more achievable when students had opportunities to practice hand skills in alternative locations (Gerhart et al., 2021 ).

Online assessment integrity

Lecturers had to devise strategies to maintain online assessment integrity , primarily through different ways of preventing cheating (see Reedy et al., 2021 ). Pass/Fail grading, reducing examination weightage through a higher emphasis on daily work and class participation, and asking students to make academic integrity declarations were some changes to examination policies (e.g. Ali et al., 2020 ; Dicks et al., 2020 ). Randomising and scrambling questions, administering different versions of examination papers, using proctoring software, open-book examinations, and replacing multiple choice with written questions were other ways of preventing cheating during online examinations (Hall et al., 2021 ; Jaap et al., 2021 ; Reedy et al., 2021 ).

Outcomes : There was concern that shifting to online assessment had detrimental effects on learning outcomes, but several studies reported otherwise (Garcia-Alberti et al., 2021 ; Gomez et al., 2020 ; Hall et al., 2021 ; Jaap et al., 2021 ; Lapitan et al., 2021 ). Nevertheless, there were mixed assessment experiences. When lecturers changed multiple-choice to written critical thinking questions, it made students perceive that examinations have become harder (Garcia-Alberti et al., 2021 ; Khan et al., 2022 ). Some students were anxious about encountering technical problems during online examinations, while others felt less nervous taking examinations at home (Jaap et al., 2021 ). Students also became less confident about the integrity of assessment processes when lecturers failed to set clear rules for open-book examinations (Reedy et al., 2021 ). While Pass/Fail grading alleviated students’ test performance anxiety, some lecturers felt that this lowered academic standards (Dicks et al., 2020 ; Khan et al., 2022 ). More emphasis on daily work alleviated student anxiety as examination weightage was reduced, but students also perceived a corresponding increase in course workload as they had more assignments to complete (e.g. Dietrich et al., 2020 ; Swanson et al., 2021 ).

Classroom replication

Lecturers used classroom replication strategies to foster regularity, primarily through substituting classroom sessions with video conferencing under pre-pandemic timetables (Palmer et al., 2021 ; Simon et al., 2020 ; Zhu et al., 2021 ). Lecturers also annotated their presentation materials and decorated their teaching locations with content-related backdrops to emulate the ‘chalk and talk’ of physical classrooms (e.g. Chan et al., 2020 ; Dietrich et al., 2020 ; Xiao et al., 2020 ).

Outcomes : Regular video conferencing classes helped students to maintain course attendance/completion rates (e.g. Ahmed & Opoku, 2021 ; Garcia-Alberti et al., 2021 ; Gerhart et al., 2021 ). Student engagement improved when lecturers annotated on Powerpoint™ or digital whiteboards during video conferencing (Hew et al., 2020 ). However, screen fatigue commonly affected concentration, and lecturers had challenges assessing social cues effectively, especially when students turned off their cameras (Khan et al., 2022 ; Lapitan et al., 2021 ; Marshalsey & Sclater, 2020 ). Lecturers tried to shorten class duration with asynchronous activities, only to find students failing to complete their assigned tasks (Grimmer et al., 2020 ).

Learning access equity

Lecturers implemented learning access equity strategies so that those without stable network connections or conducive home environments could continue studying (Abou-Khalil et al., 2021 ; Ahmed & Opoku, 2021 ; Dodson & Blinn, 2021 ; Garcia-Alberti et al., 2021 ; Grimmer et al., 2020 ; Kapasia et al., 2020 ; Khan et al., 2022 ; Marshalsey & Sclater, 2020 ; Pagoto et al., 2021 ; Swanson et al., 2021 ; Yeung & Yau, 2021 ). They equalised learning access by making lecture recordings available, using chat to communicate during live classes, and providing supplementary asynchronous activities (e.g. Gerhart et al., 2021 ; Grimmer et al., 2020 ). Some lecturers only delivered lessons asynchronously through pre-recorded lectures and online resources (e.g. de Luca et al., 2021 ; Dietrich et al., 2020 ). In developing countries, lecturers created access opportunities by sending learning materials through both learning management systems and WhatsApp™ (Kapasia et al., 2020 ).

Outcomes : Learning access strategies maintained some level of student equity through asynchronous learning but created challenging student learning experiences. There is evidence that students could achieve expected test scores through asynchronous learning (Garcia-Alberti et al., 2021 ) but maintaining learning consistency was a challenge, especially for freshmen (e.g. Grimmer et al., 2020 ; Khan et al., 2022 ). Some students found it hard to understand difficult concepts without in-person lectures but they also did not actively attend the live question-and-answer sessions organised by lecturers (Ali et al., 2020 ; Dietrich et al., 2020 ; Gomez et al., 2020 ). Poorly designed lecture recordings and unclear online learning instructions from lecturers compounded these problems (Gomez et al., 2020 ; Yeung & Yau, 2021 ).

Student engagement

Lecturers used two kinds of student engagement strategies, one of which was through active learning. Hew et. al. ( 2020 ) fostered active learning through 5E activities (Bybee et al., 2006 ) that encouraged students to Engage, Explore, Explain, Elaborate, and Evaluate. Lapitan et. al. ( 2021 ) implemented active learning through their DLPCA process, where students Discover, Learn and Practice outside of class with content resources and Collaborate in class before Assessment. Chan et. al. ( 2020 ) used their Theory of Change to support active learning through shared meaning-making. Other studies emphasised active learning but did not reference theoretical frameworks (e.g. Martinelli & Zaina, 2021 ). Many described how lecturers used interactive tools such as Nearpod™, and Padlet™, online polling, and breakout room discussions to encourage active learning (e.g. Ali et al., 2020 ; Gomez et al., 2020 ).

Another student engagement strategy was through regular communication and support, where lecturers sent emails, announcements, and reminders to keep students in pace with assignments (e.g. Abou-Khalil et al., 2021 ). Support was also provided through virtual office hours, social media contact after class hours and uploading feedback over shared drives (e.g. Khan et al., 2022 ; Xiao et al., 2020 ).

Outcomes : Among the student engagement strategies, success in test scores tends to be associated with the use of active learning (Garcia-Alberti et al., 2021 ; Gomez et al., 2020 ; Hew et al., 2020 ; Lapitan et al., 2021 ; Lau et al., 2020 ; Xiao et al., 2020 ). On the other hand, positive learning experiences were more often reported when lecturers emphasised care and empathy through their communication (e.g. Chan et al., 2020 ; Conklin & Dikkers, 2021 ). Students felt this more strongly when lecturers used humour, conversational and friendly tone, provided assurance, set clear expectations, exercised flexibility, engaged their feedback to improve online lessons, and responded swiftly to their questions (e.g. Chan et al., 2020 ; Swanson et al., 2021 ). These interactions fostered the social presence of Garrison et. al.’s ( 2010 ) Community of Inquiry Theory (Conklin & Dikkers, 2021 ). However, keeping up with multiple communication channels increased teaching workload, especially when support requests arrived through social media after work hours (Garcia-Alberti et al., 2021 ; Khan et al. 2022 ; Marshalsey & Sclater, 2020 ).

Learning strategies and outcomes

Students used three learning strategies during the pandemic (see Table 4 ).

Online access

Students had to maintain online access , as institutional support for data and technology was rarely reported (Ahmed & Opoku, 2021 ; Laher et al., 2021 ). Students did so by switching to more reliable internet service providers, purchasing more data, borrowing computing equipment, or switching off webcams during class (Kapasia et al., 2020 ; Mahmud & German, 2021 ).

Outcomes : Unstable internet connections, noisy home environments, tight study spaces, and disruptions from family duties were challenges often reported in students’ learning environments (e.g. Castelli & Sarvary, 2021 ; Yeung & Yau, 2021 ). The power supply was unstable in developing countries and students also had limited financial resources to purchase data. To keep studying, these students relied on materials shared through WhatsApp™ groups or Google Drive™ and learnt using mobile phones even though their small screen sizes affected students’ learning quality (Kapasia et al., 2020 ).

Online participation

Students had to maintain online participation by redesigning study routines according to when lecturers posted lecture recordings, identifying personal productive hours, changing work locations at home to improve focus and concentration, and devising study strategies to use online resources effectively, such as through note-taking (e.g. Abou-Khalil et al., 2021 ; Mahmud & German, 2021 ; Marshalsey & Sclater, 2020 ). Students also adjusted their online communication style by taking the initiative to contact lecturers through email, discussion forums, or chat for support, and learning new etiquette for video conferencing (Abou-Khalil et al., 2021 ; Dietrich et al., 2020 ; Mahmud & German, 2021 ; Simon et al., 2020 ; Yeung & Yau, 2021 ). Students recognised the need for active online participation (Yeung & Yau, 2021 ) but most tended to switch off webcams and avoided speaking up during class (Ahmed & Opoku, 2021 ; Castelli & Sarvary, 2021 ; Dietrich et al., 2020 ; Khan et al., 2022 ; Lapitan et al., 2021 ; Marshalsey & Sclater, 2020 ; Munoz et al., 2021 ; Rajab & Soheib, 2021 ).

Outcomes : Mahmud and German ( 2021 ) found that students lack the confidence to plan their study strategies, seek help, and manage time. Students also lacked confidence and switched off webcams out of privacy concerns or because they felt self-conscious about their appearances and home environments (Marshalsey & Sclater, 2020 ; Rajab & Soheib, 2021 ). Too many turned off webcams and this became a group norm (Castelli & Sarvary, 2021 ). Classes eventually became dominated by more vocal students, making the quieter ones feel left out (Dietrich et al., 2020 ).

Positive coping

Students’ positive coping strategies included family support, rationalising their situation, focusing on their future, self-motivation, and making virtual social connections with classmates (Ando, 2021 ; Laher et al., 2021 ; Mahmud & German, 2021 ; Reedy et al., 2021 ; Simon et al., 2020 ).

Outcomes : Positive coping strategies helped students to improve learning experiences, maintain attendance/completion rates, and avoid academic integrity violations during online examinations (Ando, 2021 ; Reedy et al., 2021 ; Simon et al., 2020 ). However, these strategies cannot circumvent technology and infrastructure challenges (Mahmud & German, 2021 ), while the realities of economic, family, and health pressures during the pandemic threatened their educational continuity and caused some to manifest negative coping behaviours such as despondency and overeating (Laher et al., 2021 ).

Higher education online competencies

This systematic review outlined eight teaching and learning strategies for shifting online during the pandemic. Online teaching competency frameworks published before the pandemic advocate active learning, social interaction, and prompt feedback as critical indicators of online teaching quality (e.g. Bigatel et al., 2012 ; Crews et al., 2015 ). The findings suggest that lecturers’ student engagement strategies aligned with these standards, but they also needed to adjust practical skills training, assessment, learning access channels, and classroom teaching strategies. Students’ online participation and positive coping strategies reflected how online learners could effectively manage routines, schedules and their sense of isolation (Roper, 2007 ). Since most students had no choice over online learning during the pandemic (Dodson & Blinn, 2021 ), those lacking personal motivation or adequate infrastructure had to develop online participation and online access strategies to cope with the situation.

The eight teaching and learning strategies effectively maintained test scores and attendance/completion rates, but many challenges surfaced during teaching, learning, and assessment. Turnbull et. al. ( 2021 ) attribute lecturers’ and students’ pandemic challenges to online competency gaps, particularly in digital literacy or competencies for accessing information, analysing data, and communicating with technology (Blayone et al., 2018 ). However, the study findings show that digital literacy may not be enough for students to overcome infrastructure and home environment challenges in their learning environment. Lecturers can try helping students mitigate these challenges by providing asynchronous resource access through access equity strategies. Yet, students may not successfully learn asynchronously unless they can effectively self-direct learning. Lecturers may have pedagogical knowledge to create engaging active online learning experiences. How these strategies effectively counteract students’ inhibitions to turn on webcams and speak up during class remains challenging. Lectures may also have the skills to set up different online communication channels, but students may not actively engage if care and empathy are perceived to be lacking. Furthermore, lecturers’ online assessment strategies may not always balance academic integrity with test validity.

These findings show that online competencies are not just standardised technical or pedagogical skills (e.g. Goodyear et al., 2001 ) but “socially situated” (Alvarez et al., 2009 , p. 322) abilities for manoeuvring strategies according to situation and context (Hatano & Inagaki, 1986 ). It encompasses “dexterity” or finesse with skill performance (Merriam-Webster, n.d.). The pandemic demands one to be “flexible and adaptable” (Ally, 2019 , p. 312) amidst shifting national, institutional and learning contexts. Online dexterity is needed in several areas. Online learning during the pandemic is rarely unimodal. Establishing the appropriate synchronous-asynchronous blend is a critical pedagogical decision for lecturers. They need dexterity across learning modalities to create the “right” blend in different student, content, and technological contexts (Baran et al., 2013 ; Martin et al., 2019 ). Lecturers also need domain-related dexterity to preserve authentic learning experiences while converting subject content online (Fayer, 2014 ). Especially when teaching skill-based content under different social distancing requirements, competencies to maintain learning authenticity through simulations, alternative locations, or equipment may be critical (e.g. Schirmel, 2021 ). Dexterity with online assessment is also essential. Besides preventing cheating, lecturers need to ensure that online assessments retain test validity, improve learning processes and are effective for performance evaluation (AERA, 2014 ; Sadler & Reimann, 2018 ). Another area is the dexterity to engage in online communication that appropriately manifests care and empathy (Baran et al., 2013 ). Since online teaching increases lecturers’ workload (Watermeyer et al., 2021 ), dexterity to balance student care and self-care without compromising learning quality is also crucial.

Access to conducive learning environments critically affects students’ online learning success (Kapasia et al., 2020 ). While some infrastructure challenges cannot be prevented, students should have the dexterity to mitigate their effects. For example, when disconnected from class because of bandwidth fluctuations, students should be able to find alternative ways of catching up with the lecturer rather than remaining passive and frustrated (Ezra et al., 2021 ). Self-direction is critical during online learning because it is the ability to set learning goals, self-manage learning processes, self-monitor, self-motivate, and adjust learning strategies (Garrison, 1997 ). Students need the dexterity to manage self-direction processes across different courses, learning modalities, and learning schedules. Dexterity to create an active learning presence through using appropriate learning etiquette and optimising the affordances of text, audio, video, and shared documents during class is also essential. This can support students' cognitive, social, and emotional engagement across synchronous and asynchronous modalities, individually or in groups (Zilvinskis et al., 2017 ).

Future directions

Online learning is highly diverse and increasingly dynamic, making it challenging to cover all published work for review. In this study, we have analysed pandemic-related teaching and learning strategies and their outcomes but recognise that a third of the studies were from the United States and close to half from natural or health science programmes. The findings cannot fully elucidate the strategies implemented in unrepresented countries or disciplines. Recognising these limitations, we propose the following as future directions for higher education:

Validate post-pandemic relevance of online teaching and learning strategies

The eight strategies can be validated through longitudinal empirical studies, theoretical analyses or meta-synthesis of literature to establish their relevance for post-pandemic teaching and learning. Studies outside the United States and the natural and health science disciplines are especially needed. This could address the paucity of theoretical framing in the articles reviewed, even with theories developed before the pandemic (e.g. Garrison et al., 2010 ; Moore, 1989 ; Zimmerman, 2002 ).

Demarcate post-pandemic online competencies

The plethora of descriptive studies in the articles reviewed is inadequate for understanding the online competencies driving lecturers’ pedagogical decision-making and students’ learning processes. In situ studies adopting qualitative methods such as grounded theory or phenomenology can better demarcate lecturers’ and students’ competencies for “why and under which conditions certain methods have to be used, or new methods have to be devised” (Bohle Carbonell et al., 2014 , p. 15). A longitudinal comparison of these studies can provide a better understanding of relevant post-pandemic competencies.

Develop dexterity with respect to application of online competencies

Higher education institutions use technology workshops, mentoring, and instructional consultation to develop competencies in technology-enhanced learning (e.g. Baran, 2016 ). However, dexterity to manoeuvre contextual differences may be better fostered through exploration, discovery, and exposure to varied contexts of practice (Mylopoulos et al., 2018 ). Innovative ways of developing dexterity with respect to how online competencies can be applied and the efficacy of these methodologies are areas for further research.

The COVID-19 pandemic has significantly increased the adoption and utilisation of online learning. While the present review findings suggest that the strategies lecturers and students employed to shift online during the pandemic have contributed to maintaining educational continuity and test scores but many outstanding issues remained unresolved. These include failure for students to gain an enhanced learning experience, problems encountered in designing and implementing robust assessment and online examinations, cases of academic misconduct, inequitable access to digital technologies, and increased faculty workload. Lecturers and institutions need to tackle these issues to fully leverage the opportunities afforded by online teaching and learning. Further, our findings revealed that the level of online dexterity for both students and teachers need to be enhanced. Therefore, higher education institutions must understand and develop online dexterity institutional frameworks to ensure that pedagogical innovation through online learning can be continually sustained, both during the pandemic and beyond.

Availability of data and materials

All data generated or analysed during this study are included in this published article.

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Koh, J.H.L., Daniel, B.K. Shifting online during COVID-19: A systematic review of teaching and learning strategies and their outcomes. Int J Educ Technol High Educ 19 , 56 (2022). https://doi.org/10.1186/s41239-022-00361-7

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DOI : https://doi.org/10.1186/s41239-022-00361-7

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• Online learning
• Emergency response teaching
• Online dexterity
• Online pedagogy

ORIGINAL RESEARCH article

Challenges of online learning amid the covid-19: college students’ perspective.

• 1 Education College, Shanghai Normal University, Shanghai, China
• 2 Environmental and Geographical College, Shanghai Normal University, Shanghai, China
• 3 Foreign Languages College, Shanghai Normal University, Shanghai, China

Universities in China’s transition to online education in response to the COVID-19 pandemic have spawned several research studies. However, studies exploring college students’ technological skills, relationships with their peers and instructors, and collaborative learning experiences during the pandemic are scarce. Three aspects were explored in this mixed study: (1) changes in students’ engagement in class and the main factors involved; (2) students’ feelings and reactions during online learning; and (3) how students related to their peers and instructors. Data were collected through a qualitative survey supplemented by quantitative data about students’ attitudes to online learning using the SAROL scale. This paper argues that online learning may not produce the desired results due to lack of interaction with instructors, no campus socialization or well-trained technology skills, and appropriate content for online courses and group work. The findings further revealed that online learning offers college students new ways to learn independently, collaborate and build relationships with their peers. It encourages them to reconsider ways to improve their technology skills, learning methods, communication skills and reconceptualize their responsibilities as team members.

1. Introduction

The sudden outbreak of COVID-19 has affected the lives of people all over the world since 2019 ( Ayittey et al., 2020 ; Villela et al., 2021 ). Health and safety concerns forced many schools to close temporarily ( Jena, 2020 ). In China, the need for online learning increased rapidly, causing the traditional face-to-face learning mode to change to online learning as educators have strived to ensure students receive their formal education programs ( Lei and Medwell, 2021 ).

The pandemic has brought unprecedented challenges to the education system, placing higher demands on emergency preparations as schools need to adapt to the changing environment and repeated outbreaks ( Xue et al., 2020 ) - the so-called “new normal” ( Wang, 2020 p.11). Educational institutions struggle to find alternative options to face-to-face education to deal with this challenging situation ( Rieley, 2020 ). They shut down campuses to enable students keep a social distance from each other ( Toquero, 2020 ). However, it is impossible to make a smooth transition from a traditional educational environment to online learning in a very short time. The rapid transition has brought many obstacles and challenges ( Crawford et al., 2020 ). Students appear unable to understand the educational role of online technologies and consider them irrelevant or even an obstacle to learning ( Ginns and Ellis, 2007 ; Ellis and Bliuc, 2019 ). For instance, on a learning platform called Xuexitong, the target students were not involved in virtual class activities and unable to achieve the desired improvement to their studies ( Lei and Medwell, 2021 ). Cui et al. (2020) study showed that the proportion of students who completed their courses and homework on time decreased over time. Although the strength of the impact of the COVID-19 outbreak on education may take time to become fully apparent, educational institutions around the world are currently doing everything they can to create better online learning environments and resources for students in all academic fields by utilizing their limited resources to their utmost ( Kaur, 2020 ).

An important aspect of assessing online learning is discovering how to identify problems from a student’s viewpoint in order to improve the quality of online courses. Students’ perspectives are invaluable, and their first-hand input comes from their experiences and expectations ( Dawson et al., 2019 ). Furthermore, how college students reacted to online courses during the epidemic plays a crucial role in helping education professionals to meet the learning needs of students better in future when teaching modes of delivery change and new technologies emerge ( Crews and Butterfield, 2014 ; Van Wart et al., 2020 ). Therefore, it is essential that the students’ perspective is central. Pragmatically, many valuable and practical findings and insights have been achieved through studies on teachers’ teaching efficiency, constraints, and challenges during COVID-19 ( Arora and Chauhan, 2021 ; Ober et al., 2022 ). However, the students’ standpoint has received less attention than the teachers’ perspective in the assessment of online education’s effectiveness presented in previous studies.

The findings of this study can give university administrators and teachers a better understanding of what needs to be done to adjust to the future of online learning and help students overcome common challenges they are likely to face so they have a better learning experience. Due to the sudden transition in learning mode and learning environment, we consider in-depth insights into college students’ feelings and in-class performance, vital. Our study addresses the following research questions:

1. What factors affected students’ engagement in online learning?

2. What were college students’ feelings/reactions during online learning?

3. How did college students’ relationships with their peers and instructors change during online learning?

2. Literature review

2.1. challenges presented by online learning before covid-19.

The rapid development of electronic technologies has made distance education easier ( McBrien et al., 2009 ), but sometimes there can be many obstacles. Often, difficulties and problems associated with modern technology come from downloading errors, issues with installation, login problems, problems with audio and video, etc. Previous research has shown that some features like file sharing, whiteboards, and annotation are not easy to use, resulting in the underutilization of conferencing functions ( Ming et al., 2021 ). In asynchronous learning environments, learning content cannot be provided in the same format as in offline classes, that is, it is impossible to provide real-time feedback and responses ( Littlefield, 2018 ). At the same time, students feel a lack of learning community, experience technical problems, and have difficulty understanding instructional goals, which are the major barriers to online learning ( Song et al., 2004 ). It is worth mentioning that certain challenges experienced in online courses are due to educators’ lack of online teaching skills or lesson preparation in the form of detailed teaching plans, lack of appropriate support from technical teams, and traffic overload in online education platforms.

One big problem of online courses is the monotonous learning scenario and the easy visual fatigue of the learners ( Zhou and Ren, 2019 ). Sometimes, students found online teaching boring and unappealing because online teaching videos were too long, reducing learners’ enthusiasm and interests in learning ( Li and Wang, 2019 ). Although asynchronous online learning provides a lot of response time and high degrees of flexibility for students, they still have difficulty finding enough time to complete tasks ( Knox, 2016 ). Moreover, mediocre course content is also a major issue. Students’ level of preparedness in using Learning Management Systems ( Parkes et al., 2014 ) is low. Online programs need to be designed to be creative, interactive, relevant, student-centered, and group-based ( Partlow and Gibbs, 2003 ).

Not only teachers but students also face challenges due to a lack of appropriate learning materials, their attitude to learning, lack of self-discipline, and the inadequate learning environment in some of their homes during self-isolation ( Brazendale et al., 2017 ). Furthermore, Willging and Johnson (2009) found that students may not have been interested in the learning materials used because they lacked pre-knowledge of the course, so were unable to follow the learning material offered ( Pierrakeas et al., 2004 ).

2.2. Challenges of online learning during COVID-19 isolation

COVID-19 was a blow to traditional learning methods in academic institutions around the world. The administration systems of educational institutions around the world chose online course tuition to restore education provision when the physical presence of students and tutors was impossible. Online learning during COVID-19 could be delivered synchronously or asynchronously. Obviously, the current situation is not like traditional online learning but more like crisis learning and has posed huge challenges for students. They may be faced with unstable Internet connections, which makes it impossible to ensure equity between students through online learning ( la Velle et al., 2020 ; Xue et al., 2020 ). At the same time, this causes attendance and engagement issues in online sessions, so online education can be less adaptable than supposed. Moreover, students had to rapidly turn to unfamiliar learning methods, while responding as individuals and members of social groups to the impact of the epidemic on their daily lives, physical and mental health ( Macintyre et al., 2020 ). It is not hard to understand why teachers’ techno-pedagogical skills appear to be the major factor affecting student engagement during this time. Researchers have found a positive correlation between the students’ grades and their technological abilities—if teachers are not proficient in using the functions of network equipment, students’ learning is correspondingly negatively affected ( Masry-Herzallh and Stavissky, 2021 ). Therefore, in future, teachers need to improve their teaching skills to facilitate the transfer of knowledge and their communication with students ( Palanisamy et al., 2020 ), and it is necessary to explore online teaching strategies that focus on students’ interests as a way to ensure higher levels of student engagement.

Most importantly, the uncertainty about when the outbreak restrictions will end has led to much anxiety and fear among students isolated at home. Research has revealed that personal challenges (such as economic and psychological stress) have reduced students’ willingness to learn online in future, while the quality of the online experience (including instructional and assessment quality) has improved their attitude to learning online in future ( Al-Salman and Haider, 2021 ). Therefore, teachers need to communicate with their students regularly to help alleviate any inner turmoil and cater to their other psychological needs during these stressful times ( Anderson, 2020 ; Snelling and Fingal, 2020 ; Tate, 2020 ). It is suggested that closely monitoring students’ feelings can have a positive impact on their learning ( Morgan, 2020 ).

2.3. Effectiveness of online learning

While online learning has been shown to help protect students and faculty from infection during the COVID-19 pandemic, it has not been as effective as traditional learning. Five common criteria have been proposed for assessing the effectiveness of the digital transformation in higher education institutions; the changes, their speed, technology involved, users and system capacity, and economic implications ( Kopp et al., 2019 ). Online learning means the use of technological devices, the Internet as a tool. Adedoyin and Soykan’s research ( Adedoyin and Soykan, 2020 ) noted that technical issues, socio-economic factors, human and pet intrusion, digital competence, assessment and supervision, and heavy workload can affect the effectiveness of online learning.

The intervention of teachers can improve students’ learning efficiency to a certain extent. Ahmad’s (2020) study found that most students struggled with online learning, particularly in underdeveloped locations with poor connectivity ( Ming et al., 2021 ). In addition, the content of the online course material discussed in class requires students to type messages through the chat box of the virtual conferencing applications, which requires responding within time limits ( Zhong, 2020 ).

2.4. Changes of students’ relationships with others in online learning

Online learning lacks the physical presence of a face-to-face interactive relationship between fellow students, and students and their educators ( Means et al., 2009 ; Alawamleh et al., 2020 ), so how students and instructors interact and how students collaborate with each other has to change. Although there are a variety of online applications, many tutors cannot provide students with remote care and timely feedback on their academic performance ( Collazos et al., 2021 ). This makes students dissatisfied with online learning. Research has found that Arab students, for instance, have negative feelings about online learning ( Masry-Herzallh and Stavissky, 2021 ). Likewise, college students from Pakistan perceive conventional learning as more motivating than online learning; for example, they enjoy participating in conventional learning activities and become more easily immersed in the atmosphere of conventional interaction ( Muhammad and Kainat, 2020 ). In essence, students are “social learners” who long for interaction with their peers and instructors; they can be easily distracted and pay less attention to the content of online courses ( Bozkurt and Sharma, 2020 ) and have difficulty maintaining self-discipline ( Nishimwe et al., 2022 ). Generally, students tend to prefer face-to-face teaching and learning.

Specifically, research has found that the learning performance of students who participated in online discussion activities was significantly better than those who did not, even when their other learning experiences were similar ( Du et al., 2019 ). Collaborative learning among peers can also facilitate the exchange of ideas and information to improve their knowledge level ( Luaran et al., 2014 ). However, group collaborative learning appears to be less effective because students have weak cooperative aims ( Stahl, 2005 ; Collazos et al., 2007 ). Therefore, many instructors employed more technology and applications for synchronous learning to increase student motivation and improve learning efficiency and learning achievement (e.g., PowerPoint voiceover slides for uploading course content, using the lounge feature in video conferencing to increase interaction with students and encourage communication between students, using WeChat for class discussion and group collaboration; Gao and Zhang, 2020 ; Farrell and Stanclik, 2021 ; Gan et al., 2022 ; Moorhouse and Wong, 2022 ).

3. Methodology

The purpose of the study is to explore the effectiveness and challenges of online learning during the COVID-19 pandemic and to propose possible solutions derived from analyzing the underlying causes of the challenges faced by higher education students in an eastern city in China. The present study employed a mixed-mode research design to answer the research questions. The researchers used a qualitative survey as the primary data collection tool and supplemented it with quantitative data from a students’ attitudes regarding online learning (SAROL) scale ( Muhammad and Kainat, 2020 ) to investigate the attitudes of Chinese higher education students during the COVID-19 pandemic to the online learning mode compared to the traditional learning mode, as well as the challenges and opportunities this new online learning mode presented.

3.1. Sampling strategy and participants

The researchers used purposive sampling for the qualitative phase by sending an invitation email to college students who were following online courses using online learning platforms like Tencent Conference and Xuexitong. There were 102 male and 128 female participants from five universities in an eastern city in China. The participants’ ages ranged from 18 to 20 years old. Snowball sampling was also adopted in the quantitative phase. The researchers shared the questionnaire links with currently enrolled research participants and encouraged them to spread the project on social media platforms such as WeChat, QQ, and Weibo to capture a growing chain of participants ( Creswell, 2011 ).

3.2. Data collection instruments

Data were collected through a demographic questionnaire, qualitative survey, and a SAROL instrument. The demographic section included questions about the participants’ age, gender, grades, and online learning experience.

The qualitative survey adopted a semi-structured interview ( Bryman, 2016 ) that focused on students’ course engagement, relationship with their peers and instructors, their experience of collaborative learning, and the effectiveness of online learning. Research instruments were designed collaboratively by the researchers. During the pilot, researchers wrote open questions about students’ online engagement, students’ relatedness, and the experience of collaborative learning from the perception of students. For example, “what do you think has affected your group work completion?” The research instruments were then refined into several main themes—views on learning, collaborative learning, and active learning. These are detailed in Table 1 .

Table 1 . Interview questions.

To explore the effectiveness and challenges of online learning from the perception of college students, we modified the SAROL scale from Muhammad and Kainat’s (2020) study to investigate students’ attitudes toward online learning during the epidemic. SAROL has been widely used to explore higher education students’ responses to online learning (e.g., Coman et al., 2020 ; Guo et al., 2020 ; Serhan, 2020 ). The questionnaire consists of eight questions, the first question multiple-choice to elicit the major challenges of online education during the COVID-19 outbreak, the second to eighth rated on the Likert Scale as strongly agreeing, generally agreeing, or disagreeing to investigate the respondents’ attitudes toward online teaching. The questionnaire format and items were piloted and revised with a group of 20 students at S University (anonymized). The researchers used the SAROL results to better understand participants’ responses to the open-ended questions.

3.2.1. Modifications to the SAROL scale

Considering the differences in cultural background and technological level between Pakistan and China, the necessary modifications were made.

Online learning can be effective in digitally developed countries, such as China. However, in some underdeveloped countries, such as Pakistan, much of the learning and teaching, as well as the management of academic institutions, is handled manually. The lack of fast, affordable, and reliable Internet connections has hampered the progress of online learning in that context. The original questionnaire cited by Muhammad and Kainat (2020) asked students in Pakistan about their attitudes toward online learning based on factors about students’ limited access to the Internet, such as inability to use electronic devices and price; these factors were removed in the context of this research based in China. Familiarity with online functions, privacy concerns, and signal strength issues were added to illustrate the main reasons for the low frequency of online learning software functions.

While the COVID-19 pandemic has prompted Chinese universities to turn to online education, little is known about the impact of students’ skill in using virtual conferencing functions on their views of teaching quality. Therefore, the researchers changed the second question to “I am proficient with conferencing applications functions.” Table 2 shows the questionnaire’s final version.

Table 2 . Students’ attitudes regarding online learning.

To exclude the interference of gender in this study, the researchers conducted a Chi-square test. The results in Table 3 indicate no significant difference between gender and students’ attitudes to online learning [ r (230) = 0.93, p > 0.05, representing a small effect].

Table 3 . Pearson correlation; Sarol and gender.

3.2.2. Refining the scale

An item analysis was done to remove any items which did not meet the statistical standard. Of the 7 items in the initial SAROL scale, items VarA2 and VarA8’s association with the total score of all variables were 0.269 and − 0.166, so each failed to reach the required level of significance ( p  < 0.01) and were removed. The remaining 5 items demonstrated good differentiation.

In this study, the reliability analysis was done according to the SAROL scale. The overall Cronbach’s α coefficient was 0.702, an acceptable internal reliability ( Creswell, 2003 ), as shown in Figure 1 , the internal consistency being ideal. After removing VarA2 and VarA8, total correlations of individual items were all higher than 0.4, while deleting the two items did not lead to an increase of Cronbach’s α coefficient. This indicated that the scale’s internal consistency and reliability were acceptable.

Figure 1 . Cronbach’s alpha.

3.3. Data collection procedures

Questionnaires are considered a cost-effective and human resource-efficient method of data collection ( Creswell, 2003 ). The researchers emailed potential participants information about the study and the link to the online questionnaire platform used to collect data. Consent forms were attached to the questionnaire stating that the information provided would only be used for academic and research purposes and assuring the respondents of their rights to privacy, to be informed, and of the confidentiality of the research ( Creswell, 2003 ). The participants were informed their participation was voluntary, with the right to withdraw from the study at any stage. The second part of survey included demographic information, while the third and the final part consisted of the SAROL scale and the qualitative survey questions, respectively. The content of the interviews was recorded and transcribed professionally verbatim. Each participant was given a code to protect their identity (e.g., S1 stands for College Student 1) and participants were asked not to identify themselves to the others during recording. Sixteen participants agreed to participate in the survey and allowed their responses to be recorded.

3.4. Data analysis

3.4.1. qualitative data analysis.

We used NVivo 12.0 to conduct a thematic data induction analysis of the recorded content ( Braun and Clarke, 2006 ). We developed codes based on our literature review and research questions and modified codes when conducting the data analysis. We double coded the qualitative data to avoid unnecessary or duplicate codes, then organized the final codes into a thematic structure, and finally recoded the transcripts to ensure consistency. Examples are included in Table 4 . This inductive approach was more appropriate to the contextual and exploratory nature of this research ( Bryman, 2016 ).

Table 4 . Recommendations for practice.

3.4.2. Quantitative data analysis

The analysis of the reliability and validity of the data was completed using the Statistical Package of Social Science (SPSS 28.0) and all figures presented through excel. The percentage of students’ participation in collaborative activities and online learning and the frequency of using the conferencing applications functions were calculated through descriptive statistical analysis. Inferential analysis was used to assess the availability and convenience of online classes and the differences from traditional teaching, as the opportunities and challenges students experienced during the COVID-19 pandemic. To enhance the reliability and validity of this study, the data analysis was conducted individually by each of the researchers, followed by discussions to reach consensus on the results.

The following sections show the results of the questionnaire and interviews given together to the participants who had been experiencing COVID-19 pandemic restrictions on physical content. The data and interview feedback revealed the obstacles to online learning and emotional feedback concerning online learning. Although the responses varied, three main themes emerged. We selected a representative sample of interviewees for each main theme to give an indication of the feelings surrounding them.

4.1. The challenge from poor student engagement in online learning

4.1.1. lack of technical skills.

The reasons for the low frequency of online participation also suggest why participants were reluctant to use conferencing functions during COVID-19. The reasons include unfamiliarity with online systems and lack of confidence, poor signal or strength issues, and fear of privacy exposure. Based on the results of the questionnaire, the main reason participants rarely used voice and screen sharing in conferencing applications was they felt too shy to speak (69.57%). The other primary reason for using functions less frequently was signal reception or strength issues. 20.87% of participants responded that they sometimes could not hear others’ voices, could not see others’ shared files, or videos would stall. Another problem was that participants were afraid their privacy might be invaded (4.35%) and they were unfamiliar with numerous functions of conferencing applications (5.22%). In other words, due to the sudden outbreak of the COVID-19 epidemic, students had no time to fully explore these features and they seldom used virtual conferencing applications in offline learning settings, always arranging a time to meet and discuss assignments in person. The findings strongly suggest participants preferred offline communication to online communication when they had to attend to online courses concerns due to online uncertainties. Figure 2 highlights the reasons for the low use of the current virtual conferencing applications (Tencent Meeting). Figure 3 is a bar chart illustrating user’s familiarity with the features on virtual conferencing tools. For example, S2 stated that:

Figure 2 . Distribution of reasons for the low frequency of the virtual conferencing tools.

Figure 3 . Distribution of user’s familiarity with the features on virtual conferencing tools.

We have some virtual conferencing applications like Tencent Conference. It is not completely paperless learning although I often learn with my computer and tablet, completing homework such as courseware on them. These technological devices bring convenience, but also require self-discipline and proper use, which can affect my participation and engagement in class. (S2).

4.1.2. Low learning motivation

In response to the question of whether online and conventional learning are the same, 12.17% reported that online learning is very different from the conventional learning mode, while 58.7% felt that there was little difference between online and conventional learning. According to the questionnaire, only 18.7% of students felt that online learning was more motivating than conventional learning, while more than half the students (50.43%) disagreed that online learning was more motivating than conventional learning disrupted by the COVID-19 epidemic. Figure 4 shows the results of students’ motivation to learn during the COVID-19 pandemic.

Figure 4 . Bar chart of adaptability of online learning.

4.2. What were college students’ feelings/reactions during online learning?

4.2.1. students’ feelings/reactions during online learning.

The usability study asked participants whether they felt comfortable without voice or video features while performing collaborative activities or attending online courses. Almost half the responses (46.96%) were neutral, meaning for them, it did not matter if voice or video were on or off, while nearly half (45.65%) reported feeling more comfortable and relaxed (less nervous) without opening voice or video. Around 7.9% of participants experienced negative feelings, such as loneliness or boredom. To sum up, silent online communication seemed to alleviate anxiety during the COVID-19 pandemic, so participants preferred typed communication to online communication through voice and video, particularly during collaborative activities (when some group members did not know others very well) or attending subject classes. Figure 5 shows whether participants felt more relaxed by not opening voice or video during virtual conferencing. For example, referring to his/her feelings during online collaborative learning, as S5 stated that:

Figure 5 . Distributions of whether user feel comfortable without voice or video during a virtual conference meeting.

The access to and sharing of information and materials is more convenient, and I also communicate more closely with my team members. (S5).

4.2.2. How did students value online learning?

The questionnaire asked participants about their experiences with online collaborative learning during the COVID-19 pandemic. 44.78% of respondents thought that it was very challenging to effectively complete entire college courses through online learning. Moreover, 57.39% of students reported that they felt difficult while doing group projects or assignments through distance learning, while 23.48% of students valued their online learning experience as they found conducting group projects or assignments digitally was easy in actual practice. As further illustrated in interviews, students acknowledged that their online learning experiences had “forced” them to “continually develop technological skills to function effortlessly” (S8) and “increased their awareness of participation in a digital world” (S13). Overall, the participants rated the collaborative experience to be neutral and the efficiency of collaborative learning and the mastery of course content could be challenging more than rewarding.

Figure 6 shows the distribution of collaborative experience gained through the uses of online course platforms. When making a reference to the effectiveness of face-to-face communications with teachers, 68.7% of students agreed that face-to-face communication with teachers is necessary for online learning, this emphasizes the importance of teacher’s presence. This sense of social presence could counteract students’ loneliness when a direct interpersonal touch is missing, which can be “extremely important during the current pandemic crisis” (S6).

Figure 6 . Distribution of students’ collaborative experience during online learning.

4.3. How did college students’ relationships with their peers and instructors change during online learning?

4.3.1. face-to-face communications between college students and their instructors.

Figure 6 shows the distribution of collaborative experiences gained during the use of online class platforms. While referring to the effectiveness of face-to-face communication with their instructors, 68.7% of the students felt that face-to-face contact with their instructors is necessary in order to learn. In traditional offline classes, college students could have face-to-face communication with their instructors and ask them for guidance, but on transferring to online learning, they could only communicate through social apps and online meetings. Communicating in real time with instructors seems to help college students to “better understand their instructors’ tasks and guiding concepts” (e.g., S7, S9, and S10):

I couldn’t finish some of my academic tasks without face-to-face communications with my instructor. Sometimes I cannot get a reply in good time from my instructors when asking online. (S7)

4.3.2. Collaborative learning between peers

The majority of respondents considered that online learning is different from offline learning in terms of group collaboration. In the past, college students could conduct collaborative learning by booking group discussion rooms to complete groupwork, but after switching to online learning, they carry out collaborative learning in virtual meetings.

The questionnaire investigated the participants’ collaborative experience of online learning due to the impact of COVID-19 pandemic. 57.39% of students reported having difficulties doing group projects or assignments through online learning, while 23.48% felt able to easily finish group projects or assignments digitally. Overall, the participants rated the collaborative experience to be neutral, but the effectiveness of collaborative learning and the mastery of course content were problematic. S11’s quote is a typical example:

I think communication ability, team member responsibility, reasonable work distribution, management ability are the keys to collaborative learning. Without good communication skills, it is easy to cause internal strife, and team member’s poor sense of responsibility leads to low work involvement, which then affects the quality of work. (S11)

5. Discussion

The majority of the college students surveyed were not satisfied with online learning. Low engagement in online learning and the effectiveness of online learning were the major challenges faced by college students in this study. According to Means et al. (2009) and Alawamleh et al. (2020) , the efficiency of online learning is questionable and there are many challenges to the success of online learning ( Adedoyin and Soykan, 2020 ). This research also revealed an additional challenge faced by students, i.e., their relationships with instructors and peers.

Based on this research, lack of technology skills and low learning motivation result in students’ low engagement in online learning. Being shy or reticent about turning on voice and video is the main barrier faced by higher education students (69.57%) of S University, while unfamiliarity with virtual conferencing application functions, signal reception, strength issues, and fear of loss of privacy are additional obstacles; hence, full advantage of features in the virtual conferencing application is not taken. Students in Song et al.’s (2004) research encountered some additional technical problems like downloading errors, issues with installation, login problems with audio and video, etc. Ming et al. (2021) found that some features like file sharing, whiteboard, and annotation are not easy to use, resulting in the underapplication of conferencing functions. It is worth making clear that teachers’ mastery of technology also affects students’ engagement ( Masry-Herzallh and Stavissky, 2021 ). Therefore, students need to overcome their shyness in front of the camera, while teachers need to explore and expand their online learning strategies.

One of the less discussed areas of online education is the need to motivate students to learn online. 50.43% of participants indicated they felt a strong incentive for to learn offline. This concurs with Muhammad and Kainat’s (2020) conclusion that conventional learning was more motivating than online learning. In traditional classes, students more easily immersed themselves and participated in academic tasks actively through their face-to-face engagement with teachers. Furthermore, students believed that they cannot do their homework effectively and on time without checks and mandatory provisions by teachers, hence their tendency to procrastinate.

This research indicated that conventional learning was more effective than online learning, the same as Kopp et al.’s (2019) findings. While comparing the effectiveness of conventional and online learning, 68.7% of respondents felt that face-to-face communication with their teachers was crucial to effective learning. According to our questionnaire, 44.78% of students reported being unable to complete entire college online courses effectively through online learning. Also, most of the interviewees surveyed preferred offline learning. They asserted the most effective aspect of online learning was the easily accessible learning resources, and the least productive aspect is the lack of supervision. Such reactions have been explained by distraction ( Bozkurt and Sharma, 2020 ) and lack of discipline ( Nishimwe et al., 2022 ).

The majority of participants reflected meeting great challenges in the process of online learning. Only by switching off voice and video, did the surveyed students (45.65%) feel comfortable. A minority (7.9%) experienced negative feelings, such as loneliness or boredom, which made them sometimes uncomfortable and reduced their passion for online learning. This result is explained by the fact that today’s students seem to be shy and prefer to be alone, so shutting down video and voice functions makes them feel safer and more relaxed. However, if lack of face-to-face social interaction continues, students may suffer psychological distress at all levels ( McCarthy, 2020 ). According to Macintyre et al. (2020) , the epidemic impacts students’ daily lives, and their physical and mental health.

What’ s more, lack of face-to-face communication and collaborative learning with peers and instructors is an extra barrier, challenging college students’ relationships with their instructors and peers, even though group work online can be as effective as face-to-face learning ( Ocker and Yaverbaum, 1999 ). Due to physical limitations caused by the pandemic, 57.39% of the students think that they have difficulty in completing group projects because group study is boring and unappealing. Group study online needs to be (re)designed to be creative, interactive, relevant, student-centered, and group-based, as suggested by Partlow and Gibbs (2003) . Lack of appropriate support from instructors makes work more time-consuming, thus the importance of clear and relevant instructions in group study cannot be ignored. However, previous studies ( Gao and Zhang, 2020 ; Farrell and Stanclik, 2021 ) have shown how several instructors have made the most of technology (e.g., PowerPoint voiceover slides WeChat, and so on) to address the challenge of online communication and instruction.

6. Conclusion

Although online learning can help safeguard the health of students and faculty, it has proven to be less successful than traditional learning. The amount of student-teacher contact and campus socialization, level of technical competence, and appropriateness of learning content for online courses and group work are key factors for whether or not online learning produces the desired results. Therefore, students’ poor performance in online learning can be partly due to their dissatisfaction with the format and quality of course delivery and lack of interaction with others, leading to boredom and low motivation to learn. The findings of our study have revealed that online learning offers college students a new way to learn independently and to collaborate and build relationships with peers, which can encourage students to reconsider how to improve their technical skills, learning methods, and communication skills and review their responsibilities as team members. Technical skills training in future should be given to both faculty and students in order to improve students’ proficiency in applied skills and eliminate communication barriers based on poor skills. It is also advisable to allow students more time to find online learning methods that work for them and to provide them with guidance for following learning materials in to improve their learning efficiency and understanding and application of the content. What is more, teachers should improve their pedagogical skills and applications to increase the frequency of interaction with students by regularly checking their production and providing feedback on students’ academic performance as well as responding to psychological problems. Similarly, in a collaborative learning environment, students themselves need to develop more techniques to improve their communication with other class members and, most importantly, they need to develop a positive attitude toward group work, increase their own sense of team responsibility, and actively participate in group discussions and task completion during this difficult time. The authors hope that these findings will help students who need to learn online to better address similar challenges they encounter, since some new forms of learning, such as “blended learning” and “project-based learning,” are likely to continue to exist in post-epidemic learning.

The study’s greatest limitation is that it addresses the situation in one eastern city in China, so it is impossible to make broad claims. In the event of the epidemic’s resurgence in China, the researchers have had no opportunity to interview more college students, meaning the existing questionnaire data may not as comprehensive and detailed as desirable. To obtain broader and more reliable results, the design of the questionnaire could be improved, and more comparative studies could be conducted with colleges students in other contexts to better understand the similarities and differences through a larger capacity in sample files.

However, even though the sample size is small, the results can shed light on common challenges that students experienced in online class during COVID-19 pandemic. Understanding how students and their instructors perceive the online mode of higher education instruction in China can aid the development of more efficient ways of taking online classes and adapting better to online learning. There was a lot of agreement between students and instructors when it came to their impressions of online learning. The students and teachers’ views reflected and bolstered each other’s, so this level of agreement provides a basis for designing new online courses and improving the online teaching and learning experience.

Data availability statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

Ethics statement

The studies involving human participants were reviewed and approved by Shanghai Normal University. The patients/participants provided their written informed consent to participate in this study.

Author contributions

YX, YH, CW, and LY are undergraduates, and ML is an Assistant Professor. ML has made substantial contributions to the conception and design of the work. She supervised the project and designed the theoretical framework, and research methods of the manuscript. She has contributed to the revision of the manuscript, to the acquisition, analysis, and interpretation of data for the work. YX has made great contributions to the design of the research framework and has organized the database, drafted, and written the abstract, literature review, introduction, and conclusion. YH has written the discussion section. CW has drafted and written the interpretation of data of this manuscript. LY has helped to perform the statistical analysis and written the methodology. All authors have collected the data, helped write the first draft of the manuscript, revised the manuscript several times and approved the submitted version.

This research was sponsored by the research project “Exploring the reform and latest practice of teacher education” which was sponsored by Foreign Languages College, Shanghai Normal University.

Acknowledgments

We appreciate the constructive suggestions from the editor and reviewers.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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Keywords: COVID-19, online learning, college students, challenges, students’ engagement, relationships, students’ feelings

Citation: Xia Y, Hu Y, Wu C, Yang L and Lei M (2022) Challenges of online learning amid the COVID-19: College students’ perspective. Front. Psychol . 13:1037311. doi: 10.3389/fpsyg.2022.1037311

Received: 05 September 2022; Accepted: 05 December 2022; Published: 22 December 2022.

Reviewed by:

Copyright © 2022 Xia, Hu, Wu, Yang and Lei. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Man Lei, ✉ [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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Open Access

Peer-reviewed

Research Article

COVID-19’s impacts on the scope, effectiveness, and interaction characteristics of online learning: A social network analysis

Roles Data curation, Formal analysis, Methodology, Writing – review & editing

¶ ‡ JZ and YD are contributed equally to this work as first authors.

Affiliation School of Educational Information Technology, South China Normal University, Guangzhou, Guangdong, China

Roles Data curation, Formal analysis, Methodology, Writing – original draft

Affiliations School of Educational Information Technology, South China Normal University, Guangzhou, Guangdong, China, Hangzhou Zhongce Vocational School Qiantang, Hangzhou, Zhejiang, China

Roles Data curation, Writing – original draft

Roles Data curation

Roles Writing – original draft

Affiliation Faculty of Education, Shenzhen University, Shenzhen, Guangdong, China

Roles Conceptualization, Supervision, Writing – review & editing

* E-mail: [email protected] (JH); [email protected] (YZ)

• Junyi Zhang, 
• Yigang Ding, 
• Xinru Yang, 
• Jinping Zhong, 
• XinXin Qiu, 
• Zhishan Zou, 
• Yujie Xu, 
• Xiunan Jin, 
• Xiaomin Wu, 

• Published: August 23, 2022
• https://doi.org/10.1371/journal.pone.0273016
• Reader Comments

The COVID-19 outbreak brought online learning to the forefront of education. Scholars have conducted many studies on online learning during the pandemic, but only a few have performed quantitative comparative analyses of students’ online learning behavior before and after the outbreak. We collected review data from China’s massive open online course platform called icourse.163 and performed social network analysis on 15 courses to explore courses’ interaction characteristics before, during, and after the COVID-19 pan-demic. Specifically, we focused on the following aspects: (1) variations in the scale of online learning amid COVID-19; (2a) the characteristics of online learning interaction during the pandemic; (2b) the characteristics of online learning interaction after the pandemic; and (3) differences in the interaction characteristics of social science courses and natural science courses. Results revealed that only a small number of courses witnessed an uptick in online interaction, suggesting that the pandemic’s role in promoting the scale of courses was not significant. During the pandemic, online learning interaction became more frequent among course network members whose interaction scale increased. After the pandemic, although the scale of interaction declined, online learning interaction became more effective. The scale and level of interaction in Electrodynamics (a natural science course) and Economics (a social science course) both rose during the pan-demic. However, long after the pandemic, the Economics course sustained online interaction whereas interaction in the Electrodynamics course steadily declined. This discrepancy could be due to the unique characteristics of natural science courses and social science courses.

Citation: Zhang J, Ding Y, Yang X, Zhong J, Qiu X, Zou Z, et al. (2022) COVID-19’s impacts on the scope, effectiveness, and interaction characteristics of online learning: A social network analysis. PLoS ONE 17(8): e0273016. https://doi.org/10.1371/journal.pone.0273016

Editor: Heng Luo, Central China Normal University, CHINA

Received: April 20, 2022; Accepted: July 29, 2022; Published: August 23, 2022

Copyright: © 2022 Zhang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: The data underlying the results presented in the study were downloaded from https://www.icourse163.org/ and are now shared fully on Github ( https://github.com/zjyzhangjunyi/dataset-from-icourse163-for-SNA ). These data have no private information and can be used for academic research free of charge.

Funding: The author(s) received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

1. Introduction

The development of the mobile internet has spurred rapid advances in online learning, offering novel prospects for teaching and learning and a learning experience completely different from traditional instruction. Online learning harnesses the advantages of network technology and multimedia technology to transcend the boundaries of conventional education [ 1 ]. Online courses have become a popular learning mode owing to their flexibility and openness. During online learning, teachers and students are in different physical locations but interact in multiple ways (e.g., via online forum discussions and asynchronous group discussions). An analysis of online learning therefore calls for attention to students’ participation. Alqurashi [ 2 ] defined interaction in online learning as the process of constructing meaningful information and thought exchanges between more than two people; such interaction typically occurs between teachers and learners, learners and learners, and the course content and learners.

Massive open online courses (MOOCs), a 21st-century teaching mode, have greatly influenced global education. Data released by China’s Ministry of Education in 2020 show that the country ranks first globally in the number and scale of higher education MOOCs. The COVID-19 outbreak has further propelled this learning mode, with universities being urged to leverage MOOCs and other online resource platforms to respond to government’s “School’s Out, But Class’s On” policy [ 3 ]. Besides MOOCs, to reduce in-person gatherings and curb the spread of COVID-19, various online learning methods have since become ubiquitous [ 4 ]. Though Lederman asserted that the COVID-19 outbreak has positioned online learning technologies as the best way for teachers and students to obtain satisfactory learning experiences [ 5 ], it remains unclear whether the COVID-19 pandemic has encouraged interaction in online learning, as interactions between students and others play key roles in academic performance and largely determine the quality of learning experiences [ 6 ]. Similarly, it is also unclear what impact the COVID-19 pandemic has had on the scale of online learning.

Social constructivism paints learning as a social phenomenon. As such, analyzing the social structures or patterns that emerge during the learning process can shed light on learning-based interaction [ 7 ]. Social network analysis helps to explain how a social network, rooted in interactions between learners and their peers, guides individuals’ behavior, emotions, and outcomes. This analytical approach is especially useful for evaluating interactive relationships between network members [ 8 ]. Mohammed cited social network analysis (SNA) as a method that can provide timely information about students, learning communities and interactive networks. SNA has been applied in numerous fields, including education, to identify the number and characteristics of interelement relationships. For example, Lee et al. also used SNA to explore the effects of blogs on peer relationships [ 7 ]. Therefore, adopting SNA to examine interactions in online learning communities during the COVID-19 pandemic can uncover potential issues with this online learning model.

Taking China’s icourse.163 MOOC platform as an example, we chose 15 courses with a large number of participants for SNA, focusing on learners’ interaction characteristics before, during, and after the COVID-19 outbreak. We visually assessed changes in the scale of network interaction before, during, and after the outbreak along with the characteristics of interaction in Gephi. Examining students’ interactions in different courses revealed distinct interactive network characteristics, the pandemic’s impact on online courses, and relevant suggestions. Findings are expected to promote effective interaction and deep learning among students in addition to serving as a reference for the development of other online learning communities.

2. Literature review and research questions

Interaction is deemed as central to the educational experience and is a major focus of research on online learning. Moore began to study the problem of interaction in distance education as early as 1989. He defined three core types of interaction: student–teacher, student–content, and student–student [ 9 ]. Lear et al. [ 10 ] described an interactivity/ community-process model of distance education: they specifically discussed the relationships between interactivity, community awareness, and engaging learners and found interactivity and community awareness to be correlated with learner engagement. Zulfikar et al. [ 11 ] suggested that discussions initiated by the students encourage more students’ engagement than discussions initiated by the instructors. It is most important to afford learners opportunities to interact purposefully with teachers, and improving the quality of learner interaction is crucial to fostering profound learning [ 12 ]. Interaction is an important way for learners to communicate and share information, and a key factor in the quality of online learning [ 13 ].

Timely feedback is the main component of online learning interaction. Woo and Reeves discovered that students often become frustrated when they fail to receive prompt feedback [ 14 ]. Shelley et al. conducted a three-year study of graduate and undergraduate students’ satisfaction with online learning at universities and found that interaction with educators and students is the main factor affecting satisfaction [ 15 ]. Teachers therefore need to provide students with scoring justification, support, and constructive criticism during online learning. Some researchers examined online learning during the COVID-19 pandemic. They found that most students preferred face-to-face learning rather than online learning due to obstacles faced online, such as a lack of motivation, limited teacher-student interaction, and a sense of isolation when learning in different times and spaces [ 16 , 17 ]. However, it can be reduced by enhancing the online interaction between teachers and students [ 18 ].

Research showed that interactions contributed to maintaining students’ motivation to continue learning [ 19 ]. Baber argued that interaction played a key role in students’ academic performance and influenced the quality of the online learning experience [ 20 ]. Hodges et al. maintained that well-designed online instruction can lead to unique teaching experiences [ 21 ]. Banna et al. mentioned that using discussion boards, chat sessions, blogs, wikis, and other tools could promote student interaction and improve participation in online courses [ 22 ]. During the COVID-19 pandemic, Mahmood proposed a series of teaching strategies suitable for distance learning to improve its effectiveness [ 23 ]. Lapitan et al. devised an online strategy to ease the transition from traditional face-to-face instruction to online learning [ 24 ]. The preceding discussion suggests that online learning goes beyond simply providing learning resources; teachers should ideally design real-life activities to give learners more opportunities to participate.

As mentioned, COVID-19 has driven many scholars to explore the online learning environment. However, most have ignored the uniqueness of online learning during this time and have rarely compared pre- and post-pandemic online learning interaction. Taking China’s icourse.163 MOOC platform as an example, we chose 15 courses with a large number of participants for SNA, centering on student interaction before and after the pandemic. Gephi was used to visually analyze changes in the scale and characteristics of network interaction. The following questions were of particular interest:

• (1) Can the COVID-19 pandemic promote the expansion of online learning?
• (2a) What are the characteristics of online learning interaction during the pandemic?
• (2b) What are the characteristics of online learning interaction after the pandemic?
• (3) How do interaction characteristics differ between social science courses and natural science courses?

3. Methodology

3.1 research context.

We selected several courses with a large number of participants and extensive online interaction among hundreds of courses on the icourse.163 MOOC platform. These courses had been offered on the platform for at least three semesters, covering three periods (i.e., before, during, and after the COVID-19 outbreak). To eliminate the effects of shifts in irrelevant variables (e.g., course teaching activities), we chose several courses with similar teaching activities and compared them on multiple dimensions. All course content was taught online. The teachers of each course posted discussion threads related to learning topics; students were expected to reply via comments. Learners could exchange ideas freely in their responses in addition to asking questions and sharing their learning experiences. Teachers could answer students’ questions as well. Conversations in the comment area could partly compensate for a relative absence of online classroom interaction. Teacher–student interaction is conducive to the formation of a social network structure and enabled us to examine teachers’ and students’ learning behavior through SNA. The comment areas in these courses were intended for learners to construct knowledge via reciprocal communication. Meanwhile, by answering students’ questions, teachers could encourage them to reflect on their learning progress. These courses’ successive terms also spanned several phases of COVID-19, allowing us to ascertain the pandemic’s impact on online learning.

3.2 Data collection and preprocessing

To avoid interference from invalid or unclear data, the following criteria were applied to select representative courses: (1) generality (i.e., public courses and professional courses were chosen from different schools across China); (2) time validity (i.e., courses were held before during, and after the pandemic); and (3) notability (i.e., each course had at least 2,000 participants). We ultimately chose 15 courses across the social sciences and natural sciences (see Table 1 ). The coding is used to represent the course name.

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https://doi.org/10.1371/journal.pone.0273016.t001

To discern courses’ evolution during the pandemic, we gathered data on three terms before, during, and after the COVID-19 outbreak in addition to obtaining data from two terms completed well before the pandemic and long after. Our final dataset comprised five sets of interactive data. Finally, we collected about 120,000 comments for SNA. Because each course had a different start time—in line with fluctuations in the number of confirmed COVID-19 cases in China and the opening dates of most colleges and universities—we divided our sample into five phases: well before the pandemic (Phase I); before the pandemic (Phase Ⅱ); during the pandemic (Phase Ⅲ); after the pandemic (Phase Ⅳ); and long after the pandemic (Phase Ⅴ). We sought to preserve consistent time spans to balance the amount of data in each period ( Fig 1 ).

https://doi.org/10.1371/journal.pone.0273016.g001

3.3 Instrumentation

Participants’ comments and “thumbs-up” behavior data were converted into a network structure and compared using social network analysis (SNA). Network analysis, according to M’Chirgui, is an effective tool for clarifying network relationships by employing sophisticated techniques [ 25 ]. Specifically, SNA can help explain the underlying relationships among team members and provide a better understanding of their internal processes. Yang and Tang used SNA to discuss the relationship between team structure and team performance [ 26 ]. Golbeck argued that SNA could improve the understanding of students’ learning processes and reveal learners’ and teachers’ role dynamics [ 27 ].

To analyze Question (1), the number of nodes and diameter in the generated network were deemed as indicators of changes in network size. Social networks are typically represented as graphs with nodes and degrees, and node count indicates the sample size [ 15 ]. Wellman et al. proposed that the larger the network scale, the greater the number of network members providing emotional support, goods, services, and companionship [ 28 ]. Jan’s study measured the network size by counting the nodes which represented students, lecturers, and tutors [ 29 ]. Similarly, network nodes in the present study indicated how many learners and teachers participated in the course, with more nodes indicating more participants. Furthermore, we investigated the network diameter, a structural feature of social networks, which is a common metric for measuring network size in SNA [ 30 ]. The network diameter refers to the longest path between any two nodes in the network. There has been evidence that a larger network diameter leads to greater spread of behavior [ 31 ]. Likewise, Gašević et al. found that larger networks were more likely to spread innovative ideas about educational technology when analyzing MOOC-related research citations [ 32 ]. Therefore, we employed node count and network diameter to measure the network’s spatial size and further explore the expansion characteristic of online courses. Brief introduction of these indicators can be summarized in Table 2 .

https://doi.org/10.1371/journal.pone.0273016.t002

To address Question (2), a list of interactive analysis metrics in SNA were introduced to scrutinize learners’ interaction characteristics in online learning during and after the pandemic, as shown below:

• (1) The average degree reflects the density of the network by calculating the average number of connections for each node. As Rong and Xu suggested, the average degree of a network indicates how active its participants are [ 33 ]. According to Hu, a higher average degree implies that more students are interacting directly with each other in a learning context [ 34 ]. The present study inherited the concept of the average degree from these previous studies: the higher the average degree, the more frequent the interaction between individuals in the network.
• (2) Essentially, a weighted average degree in a network is calculated by multiplying each degree by its respective weight, and then taking the average. Bydžovská took the strength of the relationship into account when determining the weighted average degree [ 35 ]. By calculating friendship’s weighted value, Maroulis assessed peer achievement within a small-school reform [ 36 ]. Accordingly, we considered the number of interactions as the weight of the degree, with a higher average degree indicating more active interaction among learners.
• (3) Network density is the ratio between actual connections and potential connections in a network. The more connections group members have with each other, the higher the network density. In SNA, network density is similar to group cohesion, i.e., a network of more strong relationships is more cohesive [ 37 ]. Network density also reflects how much all members are connected together [ 38 ]. Therefore, we adopted network density to indicate the closeness among network members. Higher network density indicates more frequent interaction and closer communication among students.
• (4) Clustering coefficient describes local network attributes and indicates that two nodes in the network could be connected through adjacent nodes. The clustering coefficient measures users’ tendency to gather (cluster) with others in the network: the higher the clustering coefficient, the more frequently users communicate with other group members. We regarded this indicator as a reflection of the cohesiveness of the group [ 39 ].
• (5) In a network, the average path length is the average number of steps along the shortest paths between any two nodes. Oliveres has observed that when an average path length is small, the route from one node to another is shorter when graphed [ 40 ]. This is especially true in educational settings where students tend to become closer friends. So we consider that the smaller the average path length, the greater the possibility of interaction between individuals in the network.
• (6) A network with a large number of nodes, but whose average path length is surprisingly small, is known as the small-world effect [ 41 ]. A higher clustering coefficient and shorter average path length are important indicators of a small-world network: a shorter average path length enables the network to spread information faster and more accurately; a higher clustering coefficient can promote frequent knowledge exchange within the group while boosting the timeliness and accuracy of knowledge dissemination [ 42 ]. Brief introduction of these indicators can be summarized in Table 3 .

https://doi.org/10.1371/journal.pone.0273016.t003

To analyze Question 3, we used the concept of closeness centrality, which determines how close a vertex is to others in the network. As Opsahl et al. explained, closeness centrality reveals how closely actors are coupled with their entire social network [ 43 ]. In order to analyze social network-based engineering education, Putnik et al. examined closeness centrality and found that it was significantly correlated with grades [ 38 ]. We used closeness centrality to measure the position of an individual in the network. Brief introduction of these indicators can be summarized in Table 4 .

https://doi.org/10.1371/journal.pone.0273016.t004

3.4 Ethics statement

This study was approved by the Academic Committee Office (ACO) of South China Normal University ( http://fzghb.scnu.edu.cn/ ), Guangzhou, China. Research data were collected from the open platform and analyzed anonymously. There are thus no privacy issues involved in this study.

4.1 COVID-19’s role in promoting the scale of online courses was not as important as expected

As shown in Fig 2 , the number of course participants and nodes are closely correlated with the pandemic’s trajectory. Because the number of participants in each course varied widely, we normalized the number of participants and nodes to more conveniently visualize course trends. Fig 2 depicts changes in the chosen courses’ number of participants and nodes before the pandemic (Phase II), during the pandemic (Phase III), and after the pandemic (Phase IV). The number of participants in most courses during the pandemic exceeded those before and after the pandemic. But the number of people who participate in interaction in some courses did not increase.

https://doi.org/10.1371/journal.pone.0273016.g002

In order to better analyze the trend of interaction scale in online courses before, during, and after the pandemic, the selected courses were categorized according to their scale change. When the number of participants increased (decreased) beyond 20% (statistical experience) and the diameter also increased (decreased), the course scale was determined to have increased (decreased); otherwise, no significant change was identified in the course’s interaction scale. Courses were subsequently divided into three categories: increased interaction scale, decreased interaction scale, and no significant change. Results appear in Table 5 .

https://doi.org/10.1371/journal.pone.0273016.t005

From before the pandemic until it broke out, the interaction scale of five courses increased, accounting for 33.3% of the full sample; one course’s interaction scale declined, accounting for 6.7%. The interaction scale of nine courses decreased, accounting for 60%. The pandemic’s role in promoting online courses thus was not as important as anticipated, and most courses’ interaction scale did not change significantly throughout.

No courses displayed growing interaction scale after the pandemic: the interaction scale of nine courses fell, accounting for 60%; and the interaction scale of six courses did not shift significantly, accounting for 40%. Courses with an increased scale of interaction during the pandemic did not maintain an upward trend. On the contrary, the improvement in the pandemic caused learners’ enthusiasm for online learning to wane. We next analyzed several interaction metrics to further explore course interaction during different pandemic periods.

4.2 Characteristics of online learning interaction amid COVID-19

4.2.1 during the covid-19 pandemic, online learning interaction in some courses became more active..

Changes in course indicators with the growing interaction scale during the pandemic are presented in Fig 3 , including SS5, SS6, NS1, NS3, and NS8. The horizontal ordinate indicates the number of courses, with red color representing the rise of the indicator value on the vertical ordinate and blue representing the decline.

https://doi.org/10.1371/journal.pone.0273016.g003

Specifically: (1) The average degree and weighted average degree of the five course networks demonstrated an upward trend. The emergence of the pandemic promoted students’ enthusiasm; learners were more active in the interactive network. (2) Fig 3 shows that 3 courses had increased network density and 2 courses had decreased. The higher the network density, the more communication within the team. Even though the pandemic accelerated the interaction scale and frequency, the tightness between learners in some courses did not improve. (3) The clustering coefficient of social science courses rose whereas the clustering coefficient and small-world property of natural science courses fell. The higher the clustering coefficient and the small-world property, the better the relationship between adjacent nodes and the higher the cohesion [ 39 ]. (4) Most courses’ average path length increased as the interaction scale increased. However, when the average path length grew, adverse effects could manifest: communication between learners might be limited to a small group without multi-directional interaction.

When the pandemic emerged, the only declining network scale belonged to a natural science course (NS2). The change in each course index is pictured in Fig 4 . The abscissa indicates the size of the value, with larger values to the right. The red dot indicates the index value before the pandemic; the blue dot indicates its value during the pandemic. If the blue dot is to the right of the red dot, then the value of the index increased; otherwise, the index value declined. Only the weighted average degree of the course network increased. The average degree, network density decreased, indicating that network members were not active and that learners’ interaction degree and communication frequency lessened. Despite reduced learner interaction, the average path length was small and the connectivity between learners was adequate.

https://doi.org/10.1371/journal.pone.0273016.g004

4.2.2 After the COVID-19 pandemic, the scale decreased rapidly, but most course interaction was more effective.

Fig 5 shows the changes in various courses’ interaction indicators after the pandemic, including SS1, SS2, SS3, SS6, SS7, NS2, NS3, NS7, and NS8.

https://doi.org/10.1371/journal.pone.0273016.g005

Specifically: (1) The average degree and weighted average degree of most course networks decreased. The scope and intensity of interaction among network members declined rapidly, as did learners’ enthusiasm for communication. (2) The network density of seven courses also fell, indicating weaker connections between learners in most courses. (3) In addition, the clustering coefficient and small-world property of most course networks decreased, suggesting little possibility of small groups in the network. The scope of interaction between learners was not limited to a specific space, and the interaction objects had no significant tendencies. (4) Although the scale of course interaction became smaller in this phase, the average path length of members’ social networks shortened in nine courses. Its shorter average path length would expedite the spread of information within the network as well as communication and sharing among network members.

Fig 6 displays the evolution of course interaction indicators without significant changes in interaction scale after the pandemic, including SS4, SS5, NS1, NS4, NS5, and NS6.

https://doi.org/10.1371/journal.pone.0273016.g006

Specifically: (1) Some course members’ social networks exhibited an increase in the average and weighted average. In these cases, even though the course network’s scale did not continue to increase, communication among network members rose and interaction became more frequent and deeper than before. (2) Network density and average path length are indicators of social network density. The greater the network density, the denser the social network; the shorter the average path length, the more concentrated the communication among network members. However, at this phase, the average path length and network density in most courses had increased. Yet the network density remained small despite having risen ( Table 6 ). Even with more frequent learner interaction, connections remained distant and the social network was comparatively sparse.

https://doi.org/10.1371/journal.pone.0273016.t006

In summary, the scale of interaction did not change significantly overall. Nonetheless, some course members’ frequency and extent of interaction increased, and the relationships between network members became closer as well. In the study, we found it interesting that the interaction scale of Economics (a social science course) course and Electrodynamics (a natural science course) course expanded rapidly during the pandemic and retained their interaction scale thereafter. We next assessed these two courses to determine whether their level of interaction persisted after the pandemic.

4.3 Analyses of natural science courses and social science courses

4.3.1 analyses of the interaction characteristics of economics and electrodynamics..

Economics and Electrodynamics are social science courses and natural science courses, respectively. Members’ interaction within these courses was similar: the interaction scale increased significantly when COVID-19 broke out (Phase Ⅲ), and no significant changes emerged after the pandemic (Phase Ⅴ). We hence focused on course interaction long after the outbreak (Phase V) and compared changes across multiple indicators, as listed in Table 7 .

https://doi.org/10.1371/journal.pone.0273016.t007

As the pandemic continued to improve, the number of participants and the diameter long after the outbreak (Phase V) each declined for Economics compared with after the pandemic (Phase IV). The interaction scale decreased, but the interaction between learners was much deeper. Specifically: (1) The weighted average degree, network density, clustering coefficient, and small-world property each reflected upward trends. The pandemic therefore exerted a strong impact on this course. Interaction was well maintained even after the pandemic. The smaller network scale promoted members’ interaction and communication. (2) Compared with after the pandemic (Phase IV), members’ network density increased significantly, showing that relationships between learners were closer and that cohesion was improving. (3) At the same time, as the clustering coefficient and small-world property grew, network members demonstrated strong small-group characteristics: the communication between them was deepening and their enthusiasm for interaction was higher. (4) Long after the COVID-19 outbreak (Phase V), the average path length was reduced compared with previous terms, knowledge flowed more quickly among network members, and the degree of interaction gradually deepened.

The average degree, weighted average degree, network density, clustering coefficient, and small-world property of Electrodynamics all decreased long after the COVID-19 outbreak (Phase V) and were lower than during the outbreak (Phase Ⅲ). The level of learner interaction therefore gradually declined long after the outbreak (Phase V), and connections between learners were no longer active. Although the pandemic increased course members’ extent of interaction, this rise was merely temporary: students’ enthusiasm for learning waned rapidly and their interaction decreased after the pandemic (Phase IV). To further analyze the interaction characteristics of course members in Economics and Electrodynamics, we evaluated the closeness centrality of their social networks, as shown in section 4.3.2.

4.3.2 Analysis of the closeness centrality of Economics and Electrodynamics.

The change in the closeness centrality of social networks in Economics was small, and no sharp upward trend appeared during the pandemic outbreak, as shown in Fig 7 . The emergence of COVID-19 apparently fostered learners’ interaction in Economics albeit without a significant impact. The closeness centrality changed in Electrodynamics varied from that of Economics: upon the COVID-19 outbreak, closeness centrality was significantly different from other semesters. Communication between learners was closer and interaction was more effective. Electrodynamics course members’ social network proximity decreased rapidly after the pandemic. Learners’ communication lessened. In general, Economics course showed better interaction before the outbreak and was less affected by the pandemic; Electrodynamics course was more affected by the pandemic and showed different interaction characteristics at different periods of the pandemic.

(Note: "****" indicates the significant distinction in closeness centrality between the two periods, otherwise no significant distinction).

https://doi.org/10.1371/journal.pone.0273016.g007

5. Discussion

We referred to discussion forums from several courses on the icourse.163 MOOC platform to compare online learning before, during, and after the COVID-19 pandemic via SNA and to delineate the pandemic’s effects on online courses. Only 33.3% of courses in our sample increased in terms of interaction during the pandemic; the scale of interaction did not rise in any courses thereafter. When the courses scale rose, the scope and frequency of interaction showed upward trends during the pandemic; and the clustering coefficient of natural science courses and social science courses differed: the coefficient for social science courses tended to rise whereas that for natural science courses generally declined. When the pandemic broke out, the interaction scale of a single natural science course decreased along with its interaction scope and frequency. The amount of interaction in most courses shrank rapidly during the pandemic and network members were not as active as they had been before. However, after the pandemic, some courses saw declining interaction but greater communication between members; interaction also became more frequent and deeper than before.

5.1 During the COVID-19 pandemic, the scale of interaction increased in only a few courses

The pandemic outbreak led to a rapid increase in the number of participants in most courses; however, the change in network scale was not significant. The scale of online interaction expanded swiftly in only a few courses; in others, the scale either did not change significantly or displayed a downward trend. After the pandemic, the interaction scale in most courses decreased quickly; the same pattern applied to communication between network members. Learners’ enthusiasm for online interaction reduced as the circumstances of the pandemic improved—potentially because, during the pandemic, China’s Ministry of Education declared “School’s Out, But Class’s On” policy. Major colleges and universities were encouraged to use the Internet and informational resources to provide learning support, hence the sudden increase in the number of participants and interaction in online courses [ 46 ]. After the pandemic, students’ enthusiasm for online learning gradually weakened, presumably due to easing of the pandemic [ 47 ]. More activities also transitioned from online to offline, which tempered learners’ online discussion. Research has shown that long-term online learning can even bore students [ 48 ].

Most courses’ interaction scale decreased significantly after the pandemic. First, teachers and students occupied separate spaces during the outbreak, had few opportunities for mutual cooperation and friendship, and lacked a sense of belonging [ 49 ]. Students’ enthusiasm for learning dissipated over time [ 50 ]. Second, some teachers were especially concerned about adapting in-person instructional materials for digital platforms; their pedagogical methods were ineffective, and they did not provide learning activities germane to student interaction [ 51 ]. Third, although teachers and students in remote areas were actively engaged in online learning, some students could not continue to participate in distance learning due to inadequate technology later in the outbreak [ 52 ].

5.2 Characteristics of online learning interaction during and after the COVID-19 pandemic

5.2.1 during the covid-19 pandemic, online interaction in most courses did not change significantly..

The interaction scale of only a few courses increased during the pandemic. The interaction scope and frequency of these courses climbed as well. Yet even as the degree of network interaction rose, course network density did not expand in all cases. The pandemic sparked a surge in the number of online learners and a rapid increase in network scale, but students found it difficult to interact with all learners. Yau pointed out that a greater network scale did not enrich the range of interaction between individuals; rather, the number of individuals who could interact directly was limited [ 53 ]. The internet facilitates interpersonal communication. However, not everyone has the time or ability to establish close ties with others [ 54 ].

In addition, social science courses and natural science courses in our sample revealed disparate trends in this regard: the clustering coefficient of social science courses increased and that of natural science courses decreased. Social science courses usually employ learning approaches distinct from those in natural science courses [ 55 ]. Social science courses emphasize critical and innovative thinking along with personal expression [ 56 ]. Natural science courses focus on practical skills, methods, and principles [ 57 ]. Therefore, the content of social science courses can spur large-scale discussion among learners. Some course evaluations indicated that the course content design was suboptimal as well: teachers paid close attention to knowledge transmission and much less to piquing students’ interest in learning. In addition, the thread topics that teachers posted were scarcely diversified and teachers’ questions lacked openness. These attributes could not spark active discussion among learners.

5.2.2 Online learning interaction declined after the COVID-19 pandemic.

Most courses’ interaction scale and intensity decreased rapidly after the pandemic, but some did not change. Courses with a larger network scale did not continue to expand after the outbreak, and students’ enthusiasm for learning paled. The pandemic’s reduced severity also influenced the number of participants in online courses. Meanwhile, restored school order moved many learning activities from virtual to in-person spaces. Face-to-face learning has gradually replaced online learning, resulting in lower enrollment and less interaction in online courses. Prolonged online courses could have also led students to feel lonely and to lack a sense of belonging [ 58 ].

The scale of interaction in some courses did not change substantially after the pandemic yet learners’ connections became tighter. We hence recommend that teachers seize pandemic-related opportunities to design suitable activities. Additionally, instructors should promote student-teacher and student-student interaction, encourage students to actively participate online, and generally intensify the impact of online learning.

5.3 What are the characteristics of interaction in social science courses and natural science courses?

The level of interaction in Economics (a social science course) was significantly higher than that in Electrodynamics (a natural science course), and the small-world property in Economics increased as well. To boost online courses’ learning-related impacts, teachers can divide groups of learners based on the clustering coefficient and the average path length. Small groups of students may benefit teachers in several ways: to participate actively in activities intended to expand students’ knowledge, and to serve as key actors in these small groups. Cultivating students’ keenness to participate in class activities and self-management can also help teachers guide learner interaction and foster deep knowledge construction.

As evidenced by comments posted in the Electrodynamics course, we observed less interaction between students. Teachers also rarely urged students to contribute to conversations. These trends may have arisen because teachers and students were in different spaces. Teachers might have struggled to discern students’ interaction status. Teachers could also have failed to intervene in time, to design online learning activities that piqued learners’ interest, and to employ sound interactive theme planning and guidance. Teachers are often active in traditional classroom settings. Their roles are comparatively weakened online, such that they possess less control over instruction [ 59 ]. Online instruction also requires a stronger hand in learning: teachers should play a leading role in regulating network members’ interactive communication [ 60 ]. Teachers can guide learners to participate, help learners establish social networks, and heighten students’ interest in learning [ 61 ]. Teachers should attend to core members in online learning while also considering edge members; by doing so, all network members can be driven to share their knowledge and become more engaged. Finally, teachers and assistant teachers should help learners develop knowledge, exchange topic-related ideas, pose relevant questions during course discussions, and craft activities that enable learners to interact online [ 62 ]. These tactics can improve the effectiveness of online learning.

As described, network members displayed distinct interaction behavior in Economics and Electrodynamics courses. First, these courses varied in their difficulty: the social science course seemed easier to understand and focused on divergent thinking. Learners were often willing to express their views in comments and to ponder others’ perspectives [ 63 ]. The natural science course seemed more demanding and was oriented around logical thinking and skills [ 64 ]. Second, courses’ content differed. In general, social science courses favor the acquisition of declarative knowledge and creative knowledge compared with natural science courses. Social science courses also entertain open questions [ 65 ]. Natural science courses revolve around principle knowledge, strategic knowledge, and transfer knowledge [ 66 ]. Problems in these courses are normally more complicated than those in social science courses. Third, the indicators affecting students’ attitudes toward learning were unique. Guo et al. discovered that “teacher feedback” most strongly influenced students’ attitudes towards learning social science courses but had less impact on students in natural science courses [ 67 ]. Therefore, learners in social science courses likely expect more feedback from teachers and greater interaction with others.

6. Conclusion and future work

Our findings show that the network interaction scale of some online courses expanded during the COVID-19 pandemic. The network scale of most courses did not change significantly, demonstrating that the pandemic did not notably alter the scale of course interaction. Online learning interaction among course network members whose interaction scale increased also became more frequent during the pandemic. Once the outbreak was under control, although the scale of interaction declined, the level and scope of some courses’ interactive networks continued to rise; interaction was thus particularly effective in these cases. Overall, the pandemic appeared to have a relatively positive impact on online learning interaction. We considered a pair of courses in detail and found that Economics (a social science course) fared much better than Electrodynamics (a natural science course) in classroom interaction; learners were more willing to partake in-class activities, perhaps due to these courses’ unique characteristics. Brint et al. also came to similar conclusions [ 57 ].

This study was intended to be rigorous. Even so, several constraints can be addressed in future work. The first limitation involves our sample: we focused on a select set of courses hosted on China’s icourse.163 MOOC platform. Future studies should involve an expansive collection of courses to provide a more holistic understanding of how the pandemic has influenced online interaction. Second, we only explored the interactive relationship between learners and did not analyze interactive content. More in-depth content analysis should be carried out in subsequent research. All in all, the emergence of COVID-19 has provided a new path for online learning and has reshaped the distance learning landscape. To cope with associated challenges, educational practitioners will need to continue innovating in online instructional design, strengthen related pedagogy, optimize online learning conditions, and bolster teachers’ and students’ competence in online learning.

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Simamora, Roy M. "The Challenges of Online Learning During the COVID-19 Pandemic: an Essay Analysis of Performing ARTS Education Students." Studies in Learning and Teaching , vol. 1, no. 2, 31 Aug. 2020, pp. 86-103, doi: 10.46627/silet.v1i2.38 .

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COVID-19 pandemic has changed the way of learning in higher education. Teaching, and learning activities that are usually carried out with face-to-face meetings have turned into virtual meetings in various online learning applications. This paper aims to analyze student essays in the form of perspectives or responses about the challenges of online learning during the COVID-19 pandemic. This paper collected fifteen students as samples in the Fundamentals of Education I course who were actively involved in online learning activities. Online learning provides various instructions led by the lecturer. Instructions can be synchronous (communication where participants interact in the same time space as video conferencing, zoom, google meet, and WebEx) or asynchronous (time-separated communication such as e-mail, google form, streaming video content, posting lecture notes and social media platforms). This study used a qualitative approach. The researcher then collecting, reading and highlights each student's response that is considered relevant for analysis. This paper has shown so many responses about the challenges experienced by the students while studying online, such as, positive and negative impact of online learning, economic conditions, anxiety during online learning, government should think and planned, the risk of user data security, face-to-face class to online learning, ability, finding effective online learning media and expectations.

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• Published: 10 September 2024

From crisis to opportunity: advancements in emergency language services

• Xingrong Guo   ORCID: orcid.org/0000-0001-8672-2108 1 ,
• Di Xiao 1 &
• Yiming Guo 2  

Humanities and Social Sciences Communications volume  11 , Article number:  1170 ( 2024 ) Cite this article

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• Language and linguistics

Emergency language services play a critical role in emergency management and language services, facilitating effective information transmission, timely life-saving efforts, accurate public opinion guidance, and the maintenance of social stability during public emergencies. This study aims to comprehensively assess the current state of emergency language research, exploring recent advancements and future trends in emergency language services. Using bibliometric and content analysis, 3814 academic papers on emergency language services were systematically reviewed. Recent publications reveal a burgeoning interest in this field, particularly in the United States, Canada, the United Kingdom, and Australia. Research areas reflect a multidisciplinary approach to addressing the complex challenges of emergency language services. Keyword co-occurrence analysis unveils the pivotal research trajectories across various temporal phases. In the initial stage, emphasis was placed on unraveling communication and language hurdles within the emergency department. Transitioning into a phase of stable development, attention primarily gravitated toward natural language processing technology and the complexities of language barriers. Subsequently, during a period of rapid advancement, the spotlight shifted towards the pragmatic application of emergency language services amid the COVID-19 pandemic. This encompassed diverse domains such as distance education, telemedicine services, and exploratory investigations into social media dynamics. This evolution highlights an increasing interest in leveraging emerging technologies to enhance emergency response times and service quality. Future research should prioritize addressing key issues within the research framework and fostering interdisciplinary development.

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Introduction.

Every year, nations and regions globally are faced with many natural disasters and public health emergencies, which have a profound impact on human health (Berchtold et al., 2020 ; Goode et al., 2021 ). According to statistics, around 2 billion people globally were affected by natural disasters between 2008 and 2018 (Almukhlifi et al., 2021 ), and in 2019, the COVID-19 pandemic further captured global attention. In the process of emergency response and rescue, language barriers are one of the significant factors that affect rescue operations. In such situations, emergency language services become crucial for post-disaster relief efforts (Shao et al., 2018 ; Wang, 2021 ). Emergency language services refer to the provision of rapid language products, language technologies, or participation in language rescue operations for the prevention, monitoring, rapid response, and recovery of major natural disasters or public crisis events. These services include emergency translation of foreign languages, minority languages, dialects, and sign language for individuals with disabilities, the development of disaster language software, the dissemination of disaster information, and the management of disaster language resources for relief services. Additionally, they encompass the development of emergency language standards, emergency language training, language therapy, and rehabilitation, as well as language counseling and crisis intervention (Wang et al., 2020 ). In the context of disasters and other crises, emergency language services enable individuals to comprehend and communicate information about emergency preparedness and response systems, thereby enhancing personal safety and collectively mitigating risks faced by affected individuals (Markakis et al., 2017 ). Therefore, emergency language services are crucial in emergency situations.

At present, in terms of emergency language services, a comprehensive and clear representation of the scientific review literature is lacking. Traditional reviews in this area have mostly focused on enhancing the capabilities of emergency language services, such as the development of emergency language service systems and the training of personnel for emergency preparedness services. However, these studies have not sufficiently considered the complexity of communication during emergency response and rescue processes, and reliance solely on traditional on-site human translation proves inadequate to meet the efficiency requirements of emergency language services. Specifically, there is a scarcity of review studies that employ quantitative analysis methods to examine the complexities of emergency language services.

To address this gap, this paper employs bibliometric analysis and content analysis methods to analyze the collected effective literature related to the study of emergency language services. The analysis methods help to identify the development trends, research hotspots, and future directions of the field (Cheng, Zhang ( 2023 )). This approach advances the research on emergency language services, providing guidance for its further development and for scholars conducting research in this field.

Specifically, the study mainly addresses the following key research questions.

RQ 1. What is the current state of emergency language services research, and what progress has been made in recent years?

RQ 2. What is the distribution of core authors, journals, and institutions involved in emergency language services research?

RQ 3. What are the hotspots of emergency language services research, and what are the prospects for the field in the future?

This paper makes a comprehensive analysis of the current research situation in the field of emergency language services, that is, a comprehensive review of the literature on emergency language services in recent decades, including bibliometric analysis and quantitative visualization research. Particularly, these research results provide guidance for constructing a framework combining the latest literature and highly cited content of emergency language services, and it promotes rapid and long-term development of emergency language services research.

The remaining sections of this paper are organized as follows. Section “Methods” explains the research design, including data sources, the screening process, and the main analysis methods (bibliometric analysis and content analysis). Section “Results” presents the results of trend analysis, impact analysis, and content analysis. Firstly, it analyzes the annual publication trends of the 3814 selected literature and identifies the key influential journals of publication. Then, it introduces the analysis of author influence, country and institution analysis, disciplinary analysis, keyword co-occurrence analysis, and keyword clustering analysis using bibliometric analysis and content analysis methods. The results of the bibliometric and content analysis are further discussed in Section “Discussion”. Finally, Section “Conclusions” presents the conclusions and outlines the limitations of this paper. The overall research design framework of this study is illustrated in Fig. 1 . The process consists of three main steps: the first involves data collection and screening; the second applies bibliometric and content analysis; and the final step includes discussion and conclusions.

The framework consists of three main research steps: data collection, bibliometric analysis, and discussion and conclusion. *n=number.

Data source

In this paper, the literature used for the analysis of emergency language services research was retrieved from the core dataset of the Web of Science (WoS). WoS is one of the world’s leading science citation index databases and is widely recognized and used in academia (Wang et al., 2016 ). WoS includes high-quality articles on international research (Ciavolino et al., 2022 ), including journal articles related to emergency language services, and provides journal and article citations.

Data screening

To ensure the accuracy and representativeness of the selected literature, the inclusion criteria of the literature were established: (1) the literature source was the core dataset of WoS; (2) The publication period of the literature is from January 1, 1988–December 31, 2023; (3) The literature sources were SCI-EXPANDED, SSCI, ESCI, and A&HCI; (4) The language type of the document is English. Exclusion criteria: (1) The topic unrelated to emergency language services but only containing the keywords “emergency” and “language”; (2) Conference minutes, editorial materials and other non-academic articles. Finally, 3814 articles were obtained that were highly consistent with the research theme of this paper.

The data retrieval and cleaning process in the bibliometric analysis section is described as follows:

Using the advanced search method with the search condition “(Topic = emergency)” and “(Topic = language)”, a total of 5592 records were retrieved.

The literature retrieval type was set as “Article” or “Review article”, with the language filter set to English. The literature source categories included SCI-EXPANDED, SSCI, ESCI, and A&HCI. The retrieval period spanned from January 1, 1988, to December 31, 2023. Subsequently, book reviews, book chapters, conference proceedings, and other irrelevant materials were excluded, resulting in a final set of 4662 articles.

Further exclusions were made by reviewing and analyzing abstracts to eliminate articles unrelated to emergency language services. This included articles that only had keywords in the abstract without addressing research in the field, research papers not involving emergency language services in their descriptive topics, and data that was insufficient or findings that were unclear. In the end, a total of 848 papers were excluded, leaving 3814 papers for analysis.

Bibliometric analysis

In recent years, bibliometric research has witnessed rapid development, with its methods and tools increasingly applied in various scientific fields (Broitman and Davis, 2013 ). This study mainly focuses on bibliometric analysis, supplemented by content analysis. A total of 3814 literature articles on emergency language services published between January 1, 1988, and December 31, 2023, were analyzed from different perspectives. The first article retrieved from the WoS database on emergency language services was titled “Language Concordance as a Determinant of Compliance and Emergency Room Use in Patients with Asthma” (Manson, 1988 ). Therefore, it served as the starting point for data collection in this study.

Author influence analysis and national institution analysis were carried out after topic search and screening. This was done to identify authors with high influence and contributions in the research field of emergency language services, to pinpoint the hot research frontiers in this field, and to understand the situation of international cooperation. This analysis promotes cooperation and exchange between different national institutions and supports the international development of emergency language services research.

Various bibliometric cartographic analysis methods were applied to obtain answers to the research questions described in section “Introduction”. Each method of bibliometric cartographic analysis is designed for specific research purposes (Li et al., 2022 ). In this study, the following bibliometric network maps were created: keyword co-occurrence graph, cluster graph, and other types of tables and graphs to answer the research questions.

Content analysis

By employing content analysis, a more systematic and in-depth analysis was conducted on the disciplinary distribution, keywords co-occurrence, and clustering results related to emergency language services research. This helped identify different aspects and focal points of research in the field, providing guidance and direction for further research and practice. Content analysis and bibliometric analysis worked in tandem: bibliometric analysis identified pivotal articles and areas of focus, while content analysis delivered a detailed and objective portrayal of the research landscape of emergency language services.

Publications output distribution

The distribution of publication output is a key indicator that provides insights into research activities related to a particular set of documents (Li et al., 2020 ). In this section, the main analysis is the trend in the number of publications and journal distribution of the 3814 articles.

Analysis of annual publication volume

Figure 2 illustrates the trend in the annual publication volume since 1988. It is evident that, although the overall trend indicates growth, the annual publication volume does not consistently increase. There were some temporary declines in certain years, such as 2001, 2007, and 2009. However, the number of articles has progressively increased in the field of emergency language services research, from only 1 article in 1988 to 488 articles in 2023. This indicates that in recent decades, there has been increasing attention from researchers in the field of emergency language services, and the prominence of emergency language services has been continually rising.

Annual publication growth of research literature on emergency language services (1988-2023). Data points are represented by black diamonds ( ◆ ), with the number of publications per year indicated by blue numbers next to each data point. The three phases are demarcated by red dashed lines and labeled accordingly.

It can be observed that the average annual publication counts for research on emergency language services from 1988 to 2023 is 109 articles, with a simple average annual growth rate of 30.92%, and a compound annual growth rate (CAGR) of approximately 14.64%. Based on the annual growth rate of the articles, this indicates a continuous upward trend: an initial exploratory period (1988–2003), a stable growth period (2004–2014), and a rapid growth period (2015–2023).

During the initial exploratory period from 1988 to 2003, an average of 15 articles related to emergency language services were published each year. Among them, the highest number of articles was published in 2002, with a total of 36 articles. In the stable growth period from 2004 to 2014, the publication count showed a steady increase with minor fluctuations, averaging 74 articles per year. After 2014, there was a significant increase in the number of publications, with a total of 2779 articles published in the following nine years, averaging 309 articles per year. This is approximately eight times the number of articles published during the initial exploratory period and the stable growth period. In 2022, there were 541 published articles, accounting for 14.18% of the total, reaching its peak.

Journal distribution

Figure 3 shows the top 20 journals in terms of publication quantity related to emergency language services. It can be seen that “Academic Emergency Medicine” leads the list with a total of 80 articles. Notably, “Academic Emergency Medicine” has published significantly more papers on emergency language services ( n  = 80) than other journals, such as “Pediatric Emergency Care” ( n  = 51), “Annals of Emergency Medicine” ( n  = 48), “BMJ Open” ( n  = 47), “American Journal of Emergency Medicine” ( n  = 44), “PLoS One” ( n  = 40), “International Journal of Environmental Research and Public Health” ( n  = 36), and “Journal of General Internal Medicine” ( n  = 34). Despite the relatively small overall number of publications, the number of papers published in “Academic Emergency Medicine” is nearly double that of any other journal. This indicates that, in terms of publication quantity, the journals ranking higher are more likely to attract the attention of researchers.

The top 20 journals in terms of publication quantity related to emergency language services are listed from top to bottom in descending order.

Research power results

Author influence analysis.

Research authors play a crucial role in reflecting the research capacity of an academic field and evaluating its development (Guo et al., 2021 ). Among the 3814 analyzed articles, there were a total of 17,026 authors, with an average of 4.46 authors per article. Given the large number of core authors, this study ranked the top 20 most prolific authors in descending order based on the number of publications, as shown in Table 1 .

Table 1 reveals that, in terms of publication output, Lion, K. Casey from the University of Florida, and Topaz, Maxim from Columbia University in the United States have the highest number of publications on emergency language services research, with 13 articles each, which is significantly more than other scholars. Following closely is Camargo, Carlos A. from Massachusetts General Hospital in the United States, with 12 articles, maintaining a considerable lead over other contributors. Notably, 16 of the top 20 authors in this field are affiliated with American institutions, highlighting the significant emphasis placed by the United States and underscoring its influence in the global research landscape.

Country and institutional analysis

Analyzing the distribution of research on emergency language services across countries and institutions unveils the geographical landscape of such research, offering insights into its focus, strengths, and challenges globally. This information aids decision-makers in resource allocation and serves as a reference for international collaboration and knowledge sharing.

Table 2 presents the number and proportion of publications in the field of emergency language services research for the top 20 countries by publication count. At present, a total of 3814 articles were retrieved from 12,302 institutions studying emergency language services, covering 931 countries or regions. In terms of the number of publications and proportion, the top three countries are the United States, Canada, and the United Kingdom. Among them, the number of articles published in the United States is significantly higher than in other countries, accounting for 45.65%, which is 5.49 times and 5.58 times of Canada and the United Kingdom, ranking second and third, respectively. Therefore, the United States represents a major research force and a leading contributor to the development of the field of emergency language services research worldwide.

Figure 4 shows the collaboration institutions in emergency language services research. The size of the circle in Fig. 4 represents the number of publications by each institution in the field. The larger the circle, the more publications the institution has. Institutions such as the University of Washington, Harvard Medical School, and the University of California, San Francisco, are represented by the larger circles, signifying their significant contribution to research and publications in the field of emergency language services. These institutions demonstrate a high level of activity and influence. The top 20 institutions in the field of emergency language services, ranked by the number of publications, are listed in Table 3 .

The collaboration network of institutions is visualized using CiteSpace, with nodes representing institutions.

Table 3 provides basic information on the top 20 institutions in the field of emergency language services, ranked by the number of publications. It can be seen from this that the University of Washington, Harvard Medical School, and the University of California, San Francisco, have published the most papers. Additionally, centrality measures the importance of institutions in academic networks. Centrality was measured using a value between 0 and 1, with higher values indicating higher centrality in the academic network. The University of Washington and the University of California, San Francisco, are institutions with high centrality. These institutions hold significant research influence and occupy important positions in this field. These data reveal that institutions from the United States dominate in terms of article output and centrality in the field of emergency language services research.

Discipline analysis

In the WoS core database, each publication is classified into at least one thematic category, along with its research direction content, to indicate its research domain. This section analyzes the disciplinary knowledge and directional characteristics of 3814 retrieved literature to determine the main disciplinary directions involved in the research field of emergency language services. Considering the interdisciplinary nature, this article also explores the core disciplines in this field. Table 4 describes the Top 20 disciplinary direction rankings in emergency language services.

The 3814 literature articles retrieved so far encompass a total of 194 disciplines related to emergency language services. The top 20 disciplinary directions reveal a broad range of disciplines that contribute to this interdisciplinary field (Table 4 ). Emergency Medicine leads the list with a significant frequency of 524, followed by Public Environmental Occupational Health, Medicine General Internal, and Health Care Sciences Services.

Highly cited topics, such as Nursing and Healthcare Policy, highlight the importance of these themes in the emergency language services domain. Themes like Trauma & Emergency Surgery, Health Literacy & Telemedicine, Knowledge Engineering and Representation, Language and Linguistics, and Education Educational Research, highlight the need for effective communication and technology integration in emergency settings.

The research directions show a similar trend, with Emergency Medicine, General Internal Medicine, and Public Environmental Occupational Health leading the way. Additionally, disciplines like Computer Science and Education Educational Research indicate the increasing relevance of technological solutions and training programs in enhancing emergency response capabilities.

In summary, based on the analysis of disciplinary categories, highly cited topics, and research directions, the disciplinary theoretical foundation of emergency language services mainly concentrates on emergency medicine, environmental science, public health and preventive medicine, computer science, educational science, and language and linguistics. This interdisciplinary approach underscores the complexity of providing effective language services in emergency scenarios and the need for collaboration across multiple fields. Besides, special attention should be given to theories that integrate computer science with other fields, as these theories play a crucial role in understanding emergency language services research.

Core keywords and co-occurrence analysis

Keywords provide information about the core content of an article (Liu et al., 2015 ). When two or more keywords appear together in the same paper, it is referred to as keyword co-occurrence (Fang et al., 2017 ). Keyword co-occurrence analysis can identify research hotspots and emerging frontiers in scientific knowledge domains (Liu et al., 2015 ). In a keyword co-occurrence graph, the size of the circles represents the total frequency of occurrence of keywords in the field of emergency language services research. The larger the circle, the more representative it is of research hotspots and directions in the field (Yang et al., 2020 ; Yu et al., 2020 ). Using CiteSpace software, keyword co-occurrence analysis was conducted on the text of the retrieved 3814 literature articles. The keyword co-occurrence network is shown in Fig. 5 . The parameter settings are as follows:

year (s) per slice: 1 year;

Selection criteria: g-index (k = 10), LRF = 3.0, L/N = 10, LBY = 5, e = 1.0;

Pruning: Pathfinder;

Nodes Labeled: 1.0%.

Co-occurrence network of keywords in the field of emergency language services (1988-2023). The network is visualized using CiteSpace. Each node represents a keyword, with the size of the node indicating the frequency of the keyword’s appearance.

From Fig. 5 , it can be observed that the circles containing the keywords “emergency department”, “natural language processing”, and “COVID-19 pandemic” are the largest, indicating their high frequency of occurrence. Therefore, the research hotspots in the field of emergency language services may be related to increased research in emergency medicine, natural language processing, and emergency services resulting from public health events like the COVID-19 pandemic.

To understand the co-occurrence of the keywords in Fig. 5 , the core keywords were classified according to the three stages of emergency language service development. The top 20 keywords in each stage were listed in Table 5 .

In the initial exploration stage from 1988 to 2003, “emergency department”, “communication”, “language”, “emergency medical services”, and “interpreters” were the top five keywords in terms of frequency. Among them, the “emergency department” has the highest frequency of occurrence, indicating that the emergency department was the core focus of research during this period. In addition, during this period, research on emergency language services also focused on communication issues in emergency situations, language barriers or cross-cultural communication barriers that may be encountered during communication, emergency pharmaceutical services, interpretation services, emergency management, and other aspects during emergency rescue.

During the steady growth period from 2004 to 2014, the keywords with high frequency were: “natural language processing”, “emergency medicine”, “systematic review”, “language barriers”, and “limited English proficiency”. During this period, researchers began to pay attention to the application of natural language processing technology to solve the problem of emergency language services. For example, Starlander et al. ( 2005 ) described the evaluation of an open-source medical speech translation system (MedSLT) for safety-critical applications with a view to eliminating the language barrier in emergency situations. St-Maurice, Kuo ( 2012 ) used natural language processing to analyze primary care data extracted from identification to identify inappropriate emergency room use. On the other hand, researchers are also working to overcome language barriers, focusing on public health and the harm caused by natural disasters and public health events to children or migrants with limited language skills.

During the period of rapid development from 2015 to 2023, high-frequency keywords such as “COVID-19 pandemic”, “machine learning”, “social media”, “emergency remote teaching” and “artificial intelligence” emerged. The keywords during this period covered multiple aspects of emergency language services research. Keywords such as “COVID-19 pandemic”, “emergency remote teaching”, “online learning”, “triage”, and “telemedicine” are highly likely to be related to the COVID-19 pandemic in public health in 2020. The COVID-19 pandemic has had a significant impact on research on emergency language services, and researchers have begun to pay attention to the evaluation and response of the COVID-19 pandemic to language service needs, language barriers, multilingual transmission, and cross-cultural communication.

In the field of education, emergency remote teaching and online learning have been conducted. For example, Jiang et al. ( 2023 ) conducted a case study using a renowned Chinese language university to explore how Chinese university scholars responded to the challenges of emergency remote teaching during the pandemic. In the medical field, triage and prioritization are carried out during emergency situations, considering how to provide appropriate language support during the triage process to ensure the fair allocation of resources and timely provision of language services. For instance, a natural language processing system using nursing triage records was used to predict the quantity of emergency resources needed in the future (Sterling et al., 2020 ). Analysis of spoken expressions during simulated emergency call triage processes was also conducted (Morimura et al., 2005 ). Additionally, remote medical services are provided through technologies like video conferencing to offer cross-lingual medical consultations and support, addressing language barriers and promoting healthcare accessibility. For example, the usage of remote medical services by non-elderly patients with limited English proficiency during the COVID-19 pandemic was evaluated, along with its relationship to emergency department visits and hospital encounters (Chang et al., 2023 ). Remote medical methods under low bit-rate communication conditions have also been explored (Ruminski, 2008 ).

The keywords “social media” and “Twitter” may be related to the role of social media in the field of language services. Social media platforms and Twitter can be used to disseminate emergency information, provide multilingual support, promote community participation and communication. Keywords such as “refugees”, “pediatrics”, and “accident & emergency medicine” may be related to language service needs and practices specific to refugees, pediatric patients, and emergency medical settings. Through co-occurrence analysis of keywords, the focus of emergency language services research has changed in different periods. From a focus on emergency departments, communication, and language barriers during the exploration period, to a focus on natural language processing and language barriers in emergency medicine during the stable development period, and systematic reviews of previous research, to research on emergency language services, remote education and medical services, and the application of social media during the rapidly developing COVID-19 pandemic. This reflects the development trend and evolution of research focus in the field of emergency language services, while also revealing future research directions and challenges.

Literature co-word cluster analysis

This study employed co-occurrence cluster analysis to unveil intricate relationships between words in the literature, shedding light on the research content and patterns within current emergency language services research. By applying the co-occurrence clustering analysis method, many articles were successfully classified and organized based on their content, characteristics, and word co-occurrence. This approach has the potential to reveal nuanced topics and highlight potential connections within related literature, thus facilitating the identification of interdisciplinary research opportunities (Wang et al., 2016 ). By conducting an in-depth analysis of keyword frequencies, this paper successfully constructed multiple keyword co-occurrence networks. These networks vividly outlined the diverse landscape of emergency language services research. Figure 6 shows the co-word cluster network of emergency language services, generated using CiteSpace software. Notably, the analysis produced 10 distinct clusters, each offering valuable insights into specific facets of the emergency language services domain. The parameters are set as follows:

Slice Length = 1;

Selection criteria: g-index (k = 10), LRF = 3.0, L/N = 10, LBY = −1, e = 1.0;

Network: N = 429, E = 645 (Density= 0.007);

Nodes labeled: 1.0%.

Nine large clusters of co-word in the field of emergency language services were generated by CiteSpace software. Each cluster is represented by a different color.

Based on the parameters used, 15 clusters were identified. Figure 6 displays the top 10 of these clusters. From Fig. 6 , it can be clearly observed that the symbiosis is visualized as a knowledge domain graph composed of ten keyword co-occurrence networks. Each of these networks is represented by a different color. To provide a clearer and more intuitive presentation of each cluster, Table 6 was created, which includes the labels, the number of keywords in each cluster, and some of the keywords contained in each cluster.

Cluster #0: emergency-medicine resident

This initial keyword cluster delves into the myriad challenges and complexities encountered by emergency medicine residents, specifically focusing on communication hurdles, language comprehension, and interactions with immigrant patients. The research within this cluster centers on resident physicians within the emergency medicine field, addressing various critical aspects:

Exploring communication challenges in emergency settings is urgent. This facet involves a thorough examination of the challenges and barriers that emergency medicine residents face in effectively communicating with patients. Noteworthy studies, such as those exploring emergency physicians’ awareness of language barriers within the emergency department environment (Hendry et al., 2012 ), contribute valuable insights into fostering improved communication strategies.

The exploration of health literacy levels is an important topic. Researchers within this cluster delve into how emergency medicine residents navigate patients’ health literacy levels. This includes investigating how emergency medicine residents address patients’ health literacy levels and potential obstacles in providing medical care, including issues related to patients’ understanding of diagnoses, treatment, and self-management abilities (Doty et al., 2022 ).

Addressing the unique challenges faced by emergency medicine residents when dealing with immigrant patients, including language barriers, cultural differences, and legal and policy-related issues, is necessary. For instance, assessing residents’ attitudes towards culturally competent care, their preparedness to provide quality care to diverse patient populations, as well as their experiences and educational environment regarding cross-cultural training (Betancourt et al., 2007 ). Additionally, exploring the approaches taken by emergency department physicians when facing unique barriers to accessing healthcare for undocumented residents (Samra et al., 2019 ).

The primary goal of these studies is to improve the communication skills of emergency medicine residents. Furthermore, they aim to foster a deeper understanding and trust between healthcare providers and patients, ultimately contributing to the delivery of enhanced medical services within emergency medicine settings.

Cluster #1: trial study design

This cluster primarily focuses on the application of experimental research designs in the field of emergency medicine. The research may involve evaluating health disparities among different populations (Cegala, Post ( 2006 )) and understanding differences in health status, healthcare accessibility, or health outcomes among diverse populations to promote health equity and improve healthcare strategies targeting specific groups. It may also involve assessing the effectiveness of different medications, interventions, or acute asthma management approaches to study treatment methods and strategies for acute asthma (Press et al., 2012 ). Additionally, it may explore emergency department situations related to alcohol use (Vaca et al., 2020 ), such as examining the impact of alcohol-related incidents on emergency department visits, evaluating alcohol-related emergency interventions, or studying the health consequences of acute alcohol poisoning.

The main goal of this cluster is to advance the understanding of emergency medicine through robust experimental research designs. By assessing health disparities, differences in health status, and the efficacy of interventions, researchers contribute to the ongoing efforts to refine emergency medical practices and strategies. This cluster plays a pivotal role in shaping evidence-based approaches for diverse populations within emergency medicine contexts.

Cluster #2: review article

Cluster 2 is related to literature reviews, indicating that researchers at a certain stage focused on reviewing articles in the field of emergency language services. These reviews aimed to extract lessons learned and explore new research directions. The research within this cluster can be summarized into the following two aspects:

Clinical practices, diagnostic and treatment methods in the field of emergency medicine, and emergency medical systems and processes, are important research topics. For example, improving the analytical utility of clinical trial content by integrating data innovations to provide information for health disparity research (Cohen, Unangst ( 2018 )). Systematically reviewing the differences in the usage of patient portals among vulnerable populations, with the aim of increasing the impact of interventions that promote portal use or predict factors associated with usage disparities (Grossman et al., 2019 ).

Emergency management in disaster situations, along with psychological well-being in emergency situations, deserves investigation. For example, Almukhlifi et al. ( 2021 ) conducted a comprehensive review of the literature on the perceived preparedness of emergency healthcare personnel for disaster management. The review revealed that most emergency healthcare workers appear to lack sufficient disaster preparedness, and past experiences and training have improved preparedness efforts. Future research should focus on interventions to enhance the preparedness of emergency healthcare workers for disasters. North, Pfefferbaum ( 2013 ) reviewed and summarized the evidence on how to best identify individuals in need of disaster mental health services and classify them into appropriate care. The aim is to provide a comprehensive understanding of the field of emergency medicine by synthesizing existing research and provide evidence for emergency medicine practice and policy-making.

This cluster, characterized by literature reviews, plays a crucial role in consolidating existing knowledge in emergency language services. By delving into clinical practices, diagnostics, treatment methods, and the broader spectrum of emergency management, researchers contribute to the synthesis of evidence. The outcomes of these reviews aid in informing and shaping the landscape of emergency medicine practices, paving the way for improved policies and strategic interventions.

Cluster #3: emergency call

Cluster 3 labeled “emergency call” is highly relevant to the field of emergency telephone services. The research on emergency language services within this cluster can include the following three points:

Analysis of emergency call data is a crucial theme. This involves examining the content and patterns of emergency calls to identify common issues, improve response protocols, and enhance emergency communication strategies. Researchers may investigate the relationship between emergency telephone services and patient mortality rates. For example, Cabrita et al., ( 2004 ) conducted a study on the impact of emergency medical service calls on the management of acute myocardial infarction. The study concluded that patients with symptoms of myocardial infarction underutilized emergency medical service calls and documented the beneficial effects of emergency medical service calls in reducing prehospital delays and increasing early reperfusion therapy.

Emergency telephone services provide medical support for non-healthy patients, such as those with dementia and heart failure. Research in this area includes Voss et al., ( 2018 ) qualitatively exploring the nursing experience of emergency medical services (EMS) nursing staff in dementia patients through focus groups and interviews, evaluating EMS staff’s views on dementia management. Jung et al. ( 2022 ) employed a descriptive qualitative approach to investigate 911 calls for EMS in cases of heart failure. Their findings suggest that interventions are needed to assist heart failure patients and their families in communicating more effectively during emergencies.

Emergency call response and quality assurance deserve significant attention. This includes investigating the effectiveness and efficiency of emergency call response systems, evaluating the quality of emergency services provided over the phone, and identifying areas for improvement in terms of language support and cultural sensitivity. For example, Penverne et al. ( 2019 ) reported on a strategy to reduce waiting time for emergency calls at dispatch centers. Through their research, they found that connecting dispatch centers can improve their performance, especially during periods of overload. This enables the prompt handling of emergency calls and appropriate dispatching of emergency medical services.

This cluster serves as a focal point for enriching the understanding of emergency language services within the realm of emergency telephone services. By dissecting emergency call data, addressing the medical support needs of non-healthy patients, and scrutinizing the efficiency of emergency call response systems, researchers contribute to the enhancement of emergency services, ultimately ensuring more effective and culturally sensitive outcomes.

Cluster #4: COVID-19 crisis

Cluster 4, denoted as the “COVID-19 Crisis”, is inherently tied to the challenges posed by the COVID-19 pandemic. During the COVID-19 crisis, researchers have explored the application of qualitative research methods in addressing the COVID-19 crisis. Qualitative research techniques mainly encompass the gathering and examination of data that is not expressed in numerical form, such as observations, interviews, and textual analysis. These methods aim to provide valuable insights into comprehending the COVID-19 crisis and evaluating response measures. Qualitative research in emergency language services can provide insights into various aspects of pandemic prevention and response measures (Wang et al., 2022 ), the involvement of social media in public health (Han et al., 2020 ), emergency online teaching (Adedoyin, Soykan ( 2023 )), and remote medical services (Reza Safdari et al., 2021 ).

Furthermore, qualitative research provides researchers with an opportunity to gain an in-depth understanding of emergency language services. This includes exploring the experiences of participants such as translators, staff of translation service agencies, and service users, as well as examining service quality and effectiveness, the roles and practices of service providers, cultural and cross-cultural communication, and other aspects. Such research contributes to the improvement and optimization of emergency language service practices and policies to meet diverse language needs during emergency situations. When conducting qualitative research on emergency language services, methods such as focus group interviews and text analysis are commonly employed. For instance, the use of focus group interviews can facilitate discussions within a community to understand the importance of their surrounding environment, existing resources, and assistance. This engagement of the public helps in building resilient communities to minimize the impact of disasters (Nirupama, Maula ( 2013 )). Regression text analysis, on the other hand, can be utilized to evaluate the quality and reliability of emergency language services and eliminate ambiguities in emergency response plans (Guo et al., 2020 ). These methods play a pivotal role in comprehending the diverse needs and challenges associated with emergency language services, ensuring accuracy, timeliness, and reliability in emergency situations. The insights garnered contribute not only to research advancements but also to the refinement of practices and policies in the broader landscape of emergency language services.

Cluster #5: pharmaceutical service

Cluster 5 is labeled “pharmaceutical service” and is highly relevant to pharmacy services in disaster and emergency situations. Additionally, researchers have also focused on the provision of pharmaceutical services within hospitals and issues related to healthcare inequalities. This may include studying the organization and management of pharmacy services within hospitals, the safety and efficiency of the pharmaceutical supply chain, and inequalities in accessing and utilizing pharmacy services among different populations. However, it is worth noting that the average year of research within this cluster is 1996, indicating that the studies related to pharmaceutical services in emergency language services are relatively earlier compared to other clusters.

Cluster #6: ethnic disparities

Cluster 6 is labeled “ethnic disparities”, and researchers focus on the differences among various ethnic groups in emergency language services, including variations in language needs, service access, and outcomes. Based on other keywords within the cluster, researchers also examine disparities among different ethnic groups in emergency language services related to stroke prevention, treatment, and rehabilitation, particularly in children. The aim is to improve the efficiency of treatment and rescue efforts and reduce the impact of diseases or disasters on physical health. For example, Flores, Ngui ( 2007 ) conducted a literature review to uncover several racial/ethnic disparities in pediatric patient safety and proposed a new conceptual model for understanding racial/ethnic disparities in patient safety. Lim et al. ( 2019 ) studied racial/ethnic disparities in the utilization of mental health services among Medicaid adults aged 21–64 in Hawaii. Hartford et al. ( 2022 ) explored differences in the treatment of pediatric migraines among different racial, ethnic, and language preference groups in the emergency department, highlighting another area where equity in emergency department patients must be improved.

Cluster #7: remote teaching

Cluster 7, denoted as “remote teaching”, primarily focuses on the realm of remote teaching in emergency situations, especially during the COVID-19 pandemic. Researchers within this cluster may concentrate on strategies for emergency remote teaching, online learning tools, teaching effectiveness, and the experiences of both students and teachers. For instance, Latif, Alhamad ( 2023 ) conducted a study by surveying 112 Arabic and English as a foreign language teachers and conducting semi-structured interviews with 14 teachers. The research investigated the experiences and reflective beliefs of Saudi university language teachers in emergency remote teaching, with specific attention to: a) the general educational challenges faced by teachers and how they overcome these challenges, b) the perceived difficulties of remote teaching and assessing the foreign language domain and their coping strategies, and c) a reflective evaluation of remote language teaching after three semesters. Wang et al. ( 2022 ) explored the positive emotions and language enjoyment of Chinese language learners in the context of emergency remote teaching (ERT) during the COVID-19 pandemic, adopting a positive psychology perspective. Knežević et al. ( 2022 ) surveyed the teaching practices and experiences of foreign language teachers during the “lockdown period” in 2020, as well as their self-assessment of their digital technology application skills in teaching. The results indicated a lack of pedagogical knowledge and skills among foreign language teachers in utilizing the mentioned tools in teaching. Consequently, the authors called for more attention to digital technology teaching issues in foreign language methodology courses.

Cluster #8: emergency department visit

Cluster 8 “emergency department visit”, combined with other keywords in the cluster, indicates that this cluster may focus on applying techniques such as natural language processing, machine learning, deep learning, and nursing informatics to process and analyze data related to emergency department visits. For example, Doan et al. ( 2016 ) attempted to create and test the performance of the Natural Language Processing (NLP) tool KD-NLP to identify emergency department (ED) patients who should be considered for diagnosis as Kawasaki disease Lee et al. ( 2019 ) provide an overview of machine learning related to clinical and operational scenarios in emergency medicine.

Cluster #9: systematic review

Cluster 9 centers on research involving systematic reviews and meta-analyses of specific topics or issues. Systematic review is a research method designed to systematically collect, evaluate, and synthesize existing literature to answer specific research questions. Meta-analysis, on the other hand, is a statistical analysis method within systematic reviews that involves the reanalysis and synthesis of existing statistical data from studies on a particular topic.

Through systematic review and meta-analysis, researchers can synthesize and analyze a large amount of research evidence on emergency language services, thereby obtaining more comprehensive and reliable conclusions and providing support for decision-making, policy formulation, and further research. For example, Iqbal et al. ( 2021 ) evaluate the evidence of clinical outcomes of digital alert systems in remote monitoring through system reviews and meta-analyses and call for trials of different alert protocols to understand the best alerts to guide future widespread implementation. This will further promote the development of emergency language services.

This study conducted bibliometric and content analysis on 3814 items of literature retrieved from 1988 to 2023. Furthermore, it proposed several crucial research indicators, encompassing basic analyses of publication time and quantity, notable journals, primary research contributors (authors, countries, and institutions), disciplinary direction analysis, and co-occurrence clustering of keywords. Overall, the literature in the field of emergency language services research is constantly increasing, indicating that researchers’ interest in the field of emergency language services is gradually increasing.

Research trend

In addressing RQ 1: What is the current status of emergency language services research, and what progress has been made in recent years? Section “Publications output distribution” analyzes the current status and latest progress of research on emergency language services. The examination of published literature suggests a progressive rise in the number of research journals dedicated to emergency language services, indicating a growing trend toward diversification within the field. This phenomenon can be attributed to the fact that natural disasters and public health events impact countries worldwide to different extents, such as the Lushan earthquake in China in 2013 (Lu et al., 2014 ), the East Japan earthquake in 2011 (Onuma et al., 2017 ), the Christchurch earthquake in New Zealand and the Bangkok flood in Thailand (Noy, 2015 ), the novel coronavirus pandemic in 2019 (Wang et al., 2020 ) and the Ebola epidemic in West Africa in 2014–2016 (Agnihotri et al., 2021 ), Hurricane Katrina along the Gulf of Mexico in the United States (Kahn, Barondess ( 2008 )), etc. Faced with numerous natural disasters and sudden public health emergencies, scholars from various countries have gradually enhanced the significance of research on emergency language services. Nevertheless, the multidisciplinary nature of emergency language services and the wide range of disciplines involved have contributed to a diverse trajectory of development. This emphasis on the advancement of emergency language services from various fields has fostered a diversified overall direction of progress.

Research power

Section “Research power results” analyzes the distribution of core authors and national institutions in emergency language service research, addressing RQ 2: What is the distribution of core authors, journals, and institutions involved in emergency language services research? An examination of research influence reveals that countries such as the United States, Canada, the United Kingdom, and Australia hold significant positions in publishing papers on emergency language services. Notably, the United States stands out with its dominant presence in terms of article output and centrality within the field. Institutions such as the University of Washington, Harvard Medical School, and the University of California, San Francisco, have a high research impact in the field of emergency language services. First, these countries have large populations, vast lands, and high rates of natural disasters and public health events. In this case, fast and accurate information transmission is crucial to ensure the safety of people’s lives and property. Modern technology provides a more powerful guarantee for emergency communication, effectively improves the efficiency of post-disaster emergency rescue work, and achieves good disaster reduction effects. These countries, owing to their robust economic and technological capabilities, as well as well-developed communication and information technology infrastructure, have shown a heightened focus on emergency management and response. Their ability to efficiently collect, process, and disseminate vast quantities of real-time emergency information enables them to effectively meet public demands and facilitate advancements in emergency language service research.

Research content

Section “Content analysis” mainly addresses RQ 3: What are the hotspots of emergency language services research, and what are the prospects for the field in the future? This part examines the multidisciplinary nature of emergency language services and explores the current research trends and focal areas within the field. By examining disciplinary categories, highly cited topics, and research directions, the disciplinary, theoretical bases of emergency language services mainly concentrate on emergency medicine, environmental science, public health and preventive medicine, computer science, educational science, and language and linguistics. However, the research focus varies across each field. The field of emergency medicine is more focused on optimizing the collaboration in emergency medicine research (Perry et al., 2021 ), language support in emergency medical facilities, medical translation, and interpretation services in emergency situations, etc. For example, it explores the application of mobile technology in medical interpretation (Ji, 2019 ). Environmental science mainly focuses on the language exchange of environmental information and risk communication in emergency events, language support for emergency environmental monitoring and data processing, etc. For example, in order to improve the efficiency of emergency rescue, the coal mine emergency rescue communication system based on a wireless mesh network and environmental monitoring subsystem is tested (Zhao, Yang ( 2018 )). The research focuses on the field of public health and preventive healthcare science may include health information dissemination and education in emergency situations, multilingual emergency warning systems, and cross-cultural adaptation of emergency medical resources. The field of computer science primarily focuses on researching machine translation, such as evaluating two specific automatic translation techniques to assess their potential impact on improving communication in emergency situations (Turner et al., 2019 ), applying natural language processing, speech recognition, and intelligent language services. For example, the development of speech recognition technology in emergency calls (Valizada et al., 2021 ) provides online language support and emergency language services for medical translation services. The field of educational science focuses on training medical translators and interpreters, conducting cross-cultural communication, and education in emergency situations.

In terms of keyword clustering analysis, this paper elaborates on the three stages of emergency language service development to better understand its research progress. Firstly, during the exploration period, focus on emergency departments, communication, and language barriers. How should medical staff effectively communicate with patients in the emergency department when facing situations such as non-native language communication, hearing or speaking difficulties, or cultural differences between doctors and patients.

Secondly, during the stable development period, attention should be paid to natural language processing, language barriers in emergency medicine, and a systematic review of previous research. By conducting a systematic review of previous research, researchers can gain a comprehensive understanding of the current situation and development trends in the field of emergency language services, identify knowledge gaps and research challenges, and propose new research questions and directions to promote further development in the field of emergency language services. Moreover, with the continuous development of artificial intelligence (AI) technology, researchers have begun to combine some AI technologies, such as natural language processing technology, with emergency language services, to apply in emergency rescue and emergency medical care, to improve the efficiency and accuracy of language barrier handling, and make up for the shortcomings of human translation and interpretation.

Finally, during the rapid development period, attention should be paid to research on emergency language services, remote education, and medical services, as well as the application of social media during the COVID-19 pandemic. The outbreak of the COVID-19 epidemic has had a significant impact on the world. During COVID-19, emergency services such as distance learning and telemedicine developed rapidly. At the same time, social media plays an important role in information dissemination and crisis notification, multilingual support and translation services, and strengthening community cooperation. For example, Twitter is widely used in emergency situations to issue real-time emergency notifications and alerts. Many government agencies and emergency management departments use Twitter to release key information to the public, including disaster alerts, evacuation guidelines, safety tips, etc. This rapid and extensive dissemination of information helps people to promptly understand emergency situations and take appropriate action.

Emergency language services domain research shortcomings

To facilitate the disciplinary development of emergency language services research, this article presents a comprehensive synthesis of research findings and methodologies, with the goal of identifying the current limitations and shortcomings within the field.

Firstly, the analysis conducted in this paper highlights the interdisciplinary nature of emergency language services as a research field. Given the interdisciplinary nature of the subject matter, it is crucial to emphasize the comprehensive development process within this field. In the face of interdisciplinary content, it is needed to pay attention to its comprehensive development process. Currently, due to variations in disciplinary nature, there is often a tendency to overlook the holistic management of emergency information resources or the cross-disciplinary sharing of practical cases. For example, computer science can apply natural language processing technology to medical education (Chary et al., 2019 ), which can advance potential future work in the field of emergency medical education. However, the applicability of research results of these interdisciplinary theories in innovation still needs to be further increased.

Secondly, natural disasters and public health incidents often occur suddenly, and emergency rescue is extremely urgent. Therefore, the provision of emergency language services is also very urgent. Although current emergency translation technology and interpreters have made significant contributions to emergency language services, there are also significant limitations. For example, in remote areas lacking professional interpreters and basic communication facilities, hiring nonnonprofessional interpreters such as hospital employees and family members may bring great risks and cause serious medical accidents (Kletečka-Pulker et al., 2021 ). Therefore, it is necessary to further study the technological progress and practical application of emergency language services, and cultivate more professional interpreters.

Finally, the article focuses on the research focus of the three stages of emergency language services. At present, there are many applications of intelligent technologies related to emergency language services, such as natural language processing technology in emergency departments, the use of video interpretation systems during emergency rescue, and AI translation software. However, further exploration is needed to explore the differences, advantages, and disadvantages of various AI technologies in different application scenarios, and there is a lack of relevant literature. Besides, given the increasing use of AI in emergency language services, it is essential to consider the ethical implications of these technologies. Moral considerations arise, such as whether to use AI over live interpreters when cost-saving could compromise the quality of communication and patient care. The disparity in access to interpreters based on language prevalence raises equity concerns, particularly for less common languages like Karen. Rigorous testing is needed to validate the effectiveness of AI solutions for rare languages in real-world emergency scenarios to ensure they do not perpetuate disparities and meet ethical standards. Despite the challenges, the ongoing advancement of knowledge and technology will give rise to novel theories and technologies that can effectively address practical applications.

Prospects for emergency language services

To address the identified shortcomings, three targeted recommendations are proposed:

Firstly, emergency language services have interdisciplinary nature, therefore, it is necessary to strengthen cooperation and knowledge sharing between different disciplinary fields. Encourage experts in computer science, medicine, linguistics, and other fields to conduct collaborative research, promote the cross-application of technology and theory, and promote the comprehensive development of emergency language services.

Secondly, cultivate more professional interpreters and translation experts to meet the emergency needs of various situations. In addition, the efficiency and accuracy of emergency translation technology should be further improved to address translation errors caused by equipment issues.

Finally, it is necessary to explore the advantages and limitations of intelligent technology in different application scenarios, evaluate the applicability of different intelligent technologies in emergency language services, and select the most suitable technical solution based on specific circumstances. Simultaneously, active development of emergency language service technologies should be pursued, exploring the applications of technologies such as speech recognition, machine translation, and real-time video communication in emergency response.

Potential areas for future research on emergency language services

In outlining future research directions for emergency language services, this study identifies three key potential areas.

Firstly, the frequent occurrence of natural disasters has highlighted the increasing demand for emergency language services. At present, there are existing deficiencies in emergency rescue auxiliary equipment, and emerging technologies have the potential to provide essential assistance in addressing various challenges encountered during emergency rescue operations. As an example, within the healthcare domain, the application of AI algorithms and natural language processing techniques can play a critical role in identifying syncope patients within medical records of emergency departments (Dipaola et al., 2019 ). Further exploration by researchers is needed to determine how to effectively apply these state-of-the-art technologies to the field of emergency language services.

Secondly, it has been proven that social media platforms are effective in collecting information during emergencies caused by natural or man-made disasters (Khatoon et al., 2021 ). In the event of an emergency, emergency response managers need to respond quickly and handle the victim’s request for help. Citizens will use Internet social media to quickly disseminate information about the development of events, but for emergency response managers, it is difficult to select the most relevant information from a large number of data (Overbey et al., 2015 ). Therefore, it is crucial to study the application of straightforward natural language processing techniques to extract location information from social media networks and search for event-related messages. This research can greatly assist emergency response managers in making timely and accurate decisions (Nieuwenhuijse et al., 2016 ). For instance, by studying and comparing various machine learning models for the correlation classification of flood-related tweets, it becomes clear which machine learning-based method is most suitable for the correlation classification of flood-related tweets. This can assist emergency rescue personnel in identifying more effective disaster management information (Blomeier et al., 2024 ). In addition, text analysis techniques, machine learning (ML), and deep learning (DL) techniques can also be applied to automatically filter and analyze social media data in order to extract real-time information about key events and promote emergency response in crises (Khatoon et al., 2021 ).

Lastly, language models are assuming a progressively significant role in the domain of emergency language services. The current language models include acoustic and language models for automatic speech recognition, neural network language models, and multilingual speech recognition systems, which are widely used in medical emergencies and emergency rescue. For example, because of its advanced natural language processing capabilities, ChatGPT has become a tool that continues to evolve and advance in the ability to assist healthcare information. The study evaluated the accuracy of ChatGPT-3.5 and ChatGPT-4 models in solving queries related to CRRT alarm troubleshooting (Sheikh et al., 2024 ). Ungureanu et al. ( 2023 ) explore the use of automatic speech recognition models to enhance Romanian emergency services and reduce their response times. Future speech models will also have more breakthroughs and developments in the field of emergency language services.

Conclusions

This article conducts a comprehensive analysis of 3814 papers published between 1988 and 2023 on emergency language services using CiteSpace. The analysis aims to shed light on the research progress and future directions in this field. Analysis shows that there is an increasing number of published literature on emergency language services, and researchers are increasingly interested in researching emergency language services. The sources of disciplinary theory for emergency language services mainly concentrate on emergency medicine, environmental science, public health and preventive medicine, computer science, educational science, and language and linguistics. The findings of keyword clustering analysis demonstrate that current research in emergency language services leverages emerging technologies, such as natural language processing, language modeling, and machine learning. These technologies are utilized to expedite emergency response time and improve the quality of emergency services. In addition, there are also methods such as telemedicine and remote teaching to address emergency situations. Other cutting-edge areas include the adaptation and development of interdisciplinary methods for emergency language services, as well as the analysis of the important role of social media in the field of emergency language services.

Future research in emergency language services should focus on addressing pivotal issues related to research frameworks, fostering interdisciplinary and comprehensive development, and comprehending significant advancements in emerging technologies within the field. Of particular importance is the vast potential offered by social media and AI in supporting emergency language services.

This study provides a comprehensive analysis of the scope of emergency language services for research purposes. Nonetheless, it is important to acknowledge certain limitations. Specifically, this paper predominantly relies on the WoS core database and does not encompass other significant databases like Scopus and PubMed. In addition, this study is limited to the analysis of English papers and does not cover literature in other languages. Due to language limitations, this study may not be able to obtain or analyze relevant research results in other language contexts. Future research can consider expanding the language scope to include literature in more languages, to gain a more comprehensive understanding of the development and trends in the field of emergency language services.

Data availability

Data sharing is not applicable to this article, as no datasets were generated during the current study, which is based on bibliometric information from published articles in the Web of Science.

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Guo, X., Xiao, D. & Guo, Y. From crisis to opportunity: advancements in emergency language services. Humanit Soc Sci Commun 11 , 1170 (2024). https://doi.org/10.1057/s41599-024-03698-8

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IOE - Faculty of Education and Society

COVID-19: Trainee TEACHers’ challenges and barriers to mental health and WELLbeing support

The TEACHWELL research project aims to understand the impacts of the COVID-19 pandemic on trainee teacher's mental wellbeing and the types of support needed during this time of pandemic recovery.

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Project leaders

• Dr Keri Wong (PI)
• Dr Eleanor Kitto (Co-I)

Teacher attrition has long been an issue. The COVID19 pandemic has only exacerbated the situation. In a February Education Support (2021) survey, 80% of teachers reported high stress, of which 46% also voiced that their mental health has caused them to consider leaving the profession altogether. As the pandemic continues, these numbers have not improved. Over half of all education professionals felt their mental health had declined either considerably or a little. 60% of teachers reached out to family and friends for support (YouGov June-July 2021).

With the new year about to begin, it is clear that teachers need mental health support in order to maintain high standards of teaching, but also to continue to serve the children and families with whom they interact. Although traditional teacher training programs do teach trainee teachers about children’s attachment and socio-emotional development, cultivating mentally healthy environments by focusing on teacher’s mental wellbeing has rarely been achieved – this will be the focus of this project.

What mental health support do teachers need to maintain their own wellbeing, and where possible, to then support children is an under researched area. In White’s (2020) review of workplace support for mental health and wellbeing, a clear unanswered gap was how effective these methods were in education settings.

This further highlights the much-needed detailed investigation of trainee teacher’s mental health needs and a co-produced a set of support tools/resources with potential to be shared and tested more widely. Specifically, trainee teachers in the early years sector where staffing is notably unstable (11%–15% turnover rates), may need the most support, especially post-pandemic (Social Mobility Commission, 2020). 

New trainees are entering settings for the first time and those with some experience may fare slightly better yet may still find new post-pandemic challenges difficult to handle. 

The project builds on existing research led by Dr Wong et al. (2021) – see  written evidence submitted by UCL Institute of Education (PDF)  – showing that young children experience mental health issues early in development and if identified early, can prevent lifelong negative outcomes. 

This evidence was submitted to the recent UK Government’s call for children and young people’s mental health. Of relevance are two key recommendations:

• schools should be better supported to provide a central part of mental wellbeing provision and 
• teachers should be equipped with mental health first aid knowledge. To strive for mentally healthy schools and healthy children, tackling teacher’s mental wellbeing – a gap in the literature – is essential.

Related links:

• Mental health decline in schools could push more teachers to leave teaching , Education Support.
• Supporting teachers’ mental health and wellbeing: Evidence review (PDF) , NHS Health Scotland.

This project addresses the following research questions:

• What mental health support and resources do trainee teacher with zero to some experience need?
• What are the challenges faced by the trainee teachers and how have they overcome them? If they haven’t overcome them, what resources do they need?

Existing IOE early years trainee teachers who choose to take part in the study will complete: 

• Time one: 10–15 minute online survey measuring their baseline mental health, supported needed, and teaching experiences (October - December 2021). 
• Time two: a 1-on-1 online interview and focus group on the challenges faces during term 1 of teaching and what mental health support they would need. Participants will also complete the same set of mental health surveys from time 1 (January 2022).
• Time three: A focus-group reflection discussion of how the placement year went and what a short completion of a a mental health survey online (May 2022).

The TEACHWELL study: the role of mental health, support and assessments in trainee teachers’ placement experiences - presentation at UCL Education Conference, April 2022.

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Lived experiences of medical students of online learning: lessons for adopting virtual learning in medical education

Eshwar rajesh.

1 Madras Medical College, Chennai, India

Sudharshini Subramaniam

2 Institute of Community Medicine, Madras Medical College, Chennai, India

Priya Pasupathy

Tharini suresh, vijayaprasad gopichandran.

3 Rural Women’s Social Education Centre, Karumarapakkam, Chengalpet, 603109 India

Associated Data

The data that support the findings of this study are not openly available due to reasons of sensitivity and are available from the corresponding author upon reasonable request.

The COVID 19 lockdown created a shift in medical education from the traditional physical classroom to online learning.

To explore the lived experiences of students in various years of medical education attending a medical college in Chennai, India.

In this qualitative exploration of lived experiences we conducted 4 focus group discussions among students of the four years in the medical college with the help of a checklist. We recorded the interviews, transcribed them and performed a thematic content analysis.

There was a gendered impact of the lockdown on the online learning experiences with women students finding it challenging to attend classes balancing their gender roles of performing household chores. Online learning offered some advantages in the form of increased participation and engagement due to the partial anonymity. The greatest disadvantage of online learning was lack of clinical learning experience. The students resorted to fabricating case studies for discussion, which some students found useful and some commented that it can never replace real life clinical discussions. A generational gap between adoption of technology between the senior professors and the students hampered the online learning. Online assessments were challenging, and many students resorted to cheating in these exams.

Conclusions

Though online learning offers several advantages, it has serious limitations in offering the clinical learning experience. While planning adoption of online learning into routine medical education adequate time must be set aside for real life clinical exposure in addition to the online lectures and demonstrations for conceptual understanding.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12909-024-05953-7.

Introduction

The COVID 19 pandemic had a serious impact on medical education. Most countriesimposed lockdowns during the pandemic to limit the transmission of infection. This confined medical students to their homes or hostels. There was a need to shift from the traditional classroom and bedside teaching modality to a virtual space. Online classes became the norm, for both theoretical and clinical teaching [ 1 ].

Several studies conducted among students and teachers at medical colleges in India have explored the experiences, perceptions and consequences of shifting from the traditional to the virtual mode of education during the pandemic. Most studies reported that internet connectivity issues greatly hampered the smooth learning experience [ 2 – 5 ]. Many students living in low resource settings, did not have adequate space and privacy to engage in the online classes [ 2 , 3 ]. The timings of the classes were haphazard and often classes extended beyond their scheduled duration. Many studies also reported that there were disturbances in the classes due to lack of virtual learning etiquette among the students as well as teachers [ 5 , 6 ].

The virtual mode of medical education offers several advantages and opportunities. Teaching theoretical concepts and ideas online, can free up substantial time for students to engage actively in clinical learning when they come for physical classes in the college. The virtual mode also throws open the opportunity for cross learning across institutional, regional and even national borders. They are also immensely advantageous for offering continuing medical education programs for the busy practicing clinician [ 7 ]. Therefore, there is a need to understand the nuances of the online learning experience.

Despite the presence of several studies on perceptions and opinions on online learning, there is a lack of evidence on the details of the lived experiences of going through the lockdown and online classes among the students. The limitation of such perception surveys is that they do not explore the deeper meanings and experiences. Though these studies point out that the online learning experience was less than optimal for the students, it does not go into the “why” and “how” of the matter. The medical student is the key stakeholder in the medical education enterprise and their lived experiences provide important insights into designing and integrating online learning into routine medical curriculum.

With this in the background, we embarked on a qualitative study to explore the lived experiences of medical students in various years of education attending a medical college in Chennai, India.

Qualitative approach and research design

This qualitative study explored the experiences of medical students using a lived experiences research approach. We conducted focus group discussions among 4 batches of students who were studying in the college at the time of the study with 6 participants in each group.

Theoretical underpinning

While there is substantial literature on perceptions of Indian medical students about the online learning experience during COVID 19, there is a dearth of literature and theoretical frameworks on lived experiences of the online learning. Therefore, we were not informed by any theoretical frameworks for our study. From prior experience of the researchers, we knew that there were technical glitches in the online learning and there was a compromise in clinical learning opportunities. Therefore, we focused on these two dimensions and conducted an open-ended exploration of the lived experiences. As we conducted an iterative analysis of the discussions throughout the research, we identified other papers and research in support of our important findings, which we report in our discussion section.

Researcher characteristics and reflexivity

The research team who conducted the FGDs included 2 members – a female faculty member holding a doctoral degree in Community Medicine who is trained in qualitative methods and a male student member (final year medical student). Both were part of undergraduate medical training prior to and during the pandemic. The research team belonged to the same institution where the study was conducted. The faculty member was the teacher to the participants in the students’ focus groups. The student member was a class-mate or a senior in relation to the participants. Therefore both the interviewers had prior rapport with the participants. It is likely that the responses of the participants was influenced by the fact that one of the interviewers was their teacher.

The institution where the study was conducted is a government-run, tertiary care centre with around 400 faculty and 1,250 undergraduate medical students. During the pandemic, undergraduate medical training has been suspended intermittently since April 2020. Classroom lectures and clinical rotations were replaced by virtual modalities. From the experience of the past two years, the trainers and trainees have familiarised themselves with the newer modalities of medical training. This research was conducted in early 2023, after classroom classes had resumed, yet the students still vividly remembered their virtual learning experiences.

The COVID-19 pandemic severely impacted Chennai, overwhelming its healthcare system and causing widespread disruption. The institution in which the study was conducted was made the higher referral centre for dealing with Covid. All the teaching faculty were involved in providing Covid care throughout the pandemic. The city experienced multiple waves of the virus, with lockdowns and intermittent restrictions spanning from March 2020 to January 2022.

Sampling strategy

ER and TS are students in the same medical college. They identified volunteers from their classmates and their junior batches for participating in the study. They used the following criteria for selecting the volunteers – those who are articulate, those who had unique experiences and challenges in using online learning, and those who could talk about their experiences clearly. Six students from each year of medical college, first, second, third and internship year participated. Of these 24 students, 12 were men,12 women, 16 belonged to an urban background and 8 rural, 14 resided in the medical college hostel and 10 at their homes.

Data collection methods

We conducted focus group discussions among the participants which last between 45 min to an hour and 30 min. The FGDs were conducted in the college campus after class hours, based on the convenience of the students. Of the 4 FGDs, 3 were conducted by SS and notes taken by ER. One FGD was conducted by ER and notes taken by SS. Apart from the participants and moderators, there are no other people in the room during the discussions. We used semi-structured interview guides with open-ended questions. The interview guide was developed by the research team for the purpose of the study.(Supplementary material). The interview guide was developed based on literature review and prior experiences of the researchers with online learning. The categories included in the interview guides are – academic response, clinical training, barriers and enablers, health and psychological aspects and overall perceived impact. We did not particularly look for data saturation, as we believed that a representative sample of students from all the batches in the college would reflect all the lived experiences.

Data analysis

The group discussions were audio recorded, pseudonymised and transcribed verbatim in the Word processing software. All coding and analysis was performed using the Microsoft Excel spreadsheets where each FGD was assigned a code number, and codable data units were separated into the various cells in the spreadsheet. Each of these data units were assigned a specific code and this was linked to the FGD code number and the participant number. The transcripts and field notes were read repeatedly and assigned with initial codes. ER, TS and SS initially read and coded all the data. VG read all the transcripts and independently coded the data. All the codes were read and compiled and meaningful themes were derived. Any differences in coding and analysis was reconciled by discussions and consensus. Data collection and coding were performed simultaneously in an iterative manner to find new variants of information.

Trustworthiness

At the end of each FGD, the moderator summarized the discussion and confirmed for its validity. Audit trails were maintained. Both verbal and non-verbal interaction of the participants were documented. Field notes were made during the discussions by the moderator.

Ethical considerations

Approval for the study was obtained from the Institutional Ethical Committee (IEC) of Madras Medical College(Approval No. 08052022), before beginning the study. Informed written consent was obtained from the participants and permission taken for audio recording of the discussions. Consent was also obtained to use excerpts from the transcripts in the form of quotes. To preserve the participants’ confidentiality, their anonymity was maintained throughout the analysis and reporting process.

The findings can be broadly reported under the headings of overall impact of pandemic on medical education, advantages and disadvantages of the lockdown, advantages and disadvantages of online learning, strategies adopted by the teachers to enhance online learning experiences, strategies adopted by the students and student’s opinions on what could have been better with respect to online learning.

Overall impact on medical education

Students of the final year of their course during the study were in the pre-final year when the lockdown and online learning happened. They had a broad overview of the impact of the lockdown and online classes in comparison to their prior experiences of offline learning.

“Usually , the first year of medical college is completely spent in getting used to the transition between school to college education. Then second year is usually referred to as the ‘honeymoon’ period when we relax and enjoy college life. It is during the third and final year that we usually start studying seriously. But the pandemic struck during our third year and we went on a lockdown. Online classes started. We never got the opportunity to start studying medicine seriously.” – a final year medical student .

They explained the various emotions that they went through, an initial phase of excitement and happiness, followed by adjusting to a new online learning method, through frustration and uncertainty of prolonged lockdown and finally a sense of dissatisfaction and non-productive learning. Students who had just entered the first year during the lockdown did not have a frame of reference to reflect on. But they expressed a sense of frustration, anxiety and uncertainty.

“The uncertainty was worse than taking the NEET exam 100 times over and over again and waiting for the results” – a second-year medical student .

They compared the uncertainty to writing the National Eligibility and Entrance Test (NEET) which is the qualifying examination for getting into medical college. It is a highly competitive exam. They compared the uncertainty of waiting for colleges to open to taking that exam again and again and waiting for the results.

Gendered impact of lockdown and staying at home

The experiences of staying at home during the lockdown for prolonged period of time was gendered in nature. The women students felt that being at home compelled them to participate in household chores, thus distracting them from concentrating in classes and learning. In some cases, the women students felt that they had misunderstandings within the family because their parents thought that they were using the online classes as an excuse to avoid doing household chores.

“There were too many distractions at home. I had to help in cooking and cleaning chores at home. Sometimes I would have to keep my phone next to my stove in the kitchen and listen to the online lecture as I am cooking.” – a third-year lady medical student .

The narratives of some of the students belonging to upper socio-economic class and male medical students revealed that staying at home led to unhealthy lifestyles. They reported spending too much time watching television and web series, playing video games and eating unhealthy junk food. They also reported lacking any kind of physical exercises.

“As we stayed at home , I was watching too much series and sitcoms. I was paying a lot of games.” – a second-year male medical student . “I gained a lot of weight due to overeating of junk food and lack of physical exercises” – a second-year female medical student .

Being locked down in their homes with no external interactions made them lose their motivation to study.

“Being shut down within the house was highly demotivating. I lost my motivation to study” – third-year male medical student .

In stark contrast to this narrative, some upper-class lady students reported that staying at home was very advantageous. They reported that it reduced their need to travel to college, gave them more time with their family, helped them sit in a comfortable environment at home and concentrate on studies, and develop a healthy routine including good diet, sleep and exercises.

“We would stay at home , have the AC running and have a snack in our hand as we attended the classes. This was very comfortable.” – a third-year lady medical student . “Staying at home helped us avoid the tiring journey all the way to college just to attend one hour class.” – a second-year lady medical student . “I liked staying at home. It gave me more close bonding time with my family.” – first year lady medical student .

Challenges and advantages of online classes

Logistic challenges.

The greatest challenges of online classes reported by the students were logistic issues. When the pandemic first started, the institution and households were not prepared for internet-based learning. The most important challenge was network connectivity issues. Many students struggled with internet connectivity.

“The internet connectivity would be very poor in the hostel. We had to go around the building to look for the best spot to get network. Even after searching all over , we would not get network and miss the entire class.” – second year medical student . “Sometimes five members in my house would use the WiFi. The bandwidth would not accommodate this. Sometimes the electricity supply would go and we all would get disconnected. After that , my father bought an inverter exclusively for the WiFi modem” – second year medical student .

The students also reported that even if they managed to get proper network connectivity, the institution did not have proper network and so their teacher’s connection would be patchy. They also reported that many of their older, more experienced teachers were not technology savvy and so faced challenges in setting up and teaching online.

“Many times , our senior professors who are not technology savvy would struggle with online teaching. They would start talking with the microphone on mute. Then we would ask them to unmute. Then they would repeatedly ask us to confirm if we can hear them. That would delay the starting of the class.” – a third-year medical student .

These technical glitches also led to prolonged classes which would extend beyond 1 h and sometimes even up to 2 h. This would lead to fatigue.

Many students used the mobile phone for attending online classes. It was found to be inconvenient due to challenges of holding the mobile in a stable position for prolonged time.

“I had to figure out a way to hold the mobile and listen to the class. Holding it in the hand for prolonged time made it uncomfortable. So , I had to set up my table such that I can place it on the table and attend the class.” – third year medical student .

Scheduling of the online lectures was also haphazard and challenging to follow.

“Fortunately , we had a representative who would meticulously schedule the classes and post them on our social media communication group. If not for that the scheduling would have gone haywire. Sometimes the classes would be in the morning , sometimes in the afternoon and sometimes at night. It was very confusing” – a second-year medical student .

Lack of clinical learning

Clinical learning is the core of medical education. The students perceived the lack of good clinical learning opportunities during the online classes. They resorted to watching videos online and reading from website and textbooks to learn clinical medicine. But they felt this to be highly disadvantageous.

“The online videos depict perfect situations in which the physical examination is performed. In real life there is a lot of disturbance and distraction. Performing the same physical examination in real life will be difficult. We do not get the real-life experience by watching online videos” – a final year medical student . “The online videos and textbooks are by foreign authors. They perform clinical examination on fair skinned foreigners. A clinical sign like a rash is very clearly seen in fair skin. In typical dark complexioned Indian patients such rashes are very difficult to identify. Unless we see patients in the hospital , we cannot learn properly.” – a final year medical student.

The students complained of a lack of clinical experience and feeling unprepared to practice medicine. The students who were in their final year during the lockdown said that they touched a patient for the first time during their final university examination. They also said that they knew to describe how to do a clinical examination, but never knew how to perform it.

“I touched a patient for the first time during the University clinical examination. I did not even know how to place my hands on the abdomen to palpate it.” – a final year medical student . “I had to auscultate a child during my pediatrics exam. I was placing the stethoscope on the chest of the child. The child started crying and pushed away the stethoscope. I did not know what to do. The examiner was watching me and must have been wondering what I am going to do….” – a final year medical student .

The students also felt that they lacked communication skills with patients as most of the learning was theoretical. They never got to interact with real life patients.

“We lacked experience of taking history and interacting with patients. Sometimes , I don’t even know what words to use to take certain history from patients. These things we can never learn from online videos.” – a final year medical student .

Many students reported that they fabricated fictional cases for presentation in discussions. Some felt that such fabrication was helpful for them. Others felt that it was not at all a good practice.

“Online classes has helped us learn how to fabricate cases. This is good because we can now present something even if there is no patient available to be seen.” – a third-year medical student . “Many students would just take an old record from a senior and take the details and present the case as a new one. This is not at all helpful because it never helps us understand the details of the patient” – a third-year medical student .

Lack of an enabling learning ecosystem

Students mentioned that certain good practices that existed during offline learning were lost during online learning. This greatly disturbed the learning experience.

“The habit of taking notes during a class that existed during offline learning got lost during online learning. This greatly reduced the level of understanding” – a final year medical student .

The online learning led to passing out of previously typed notes and PowerPoint presentations. This made learning passive and non-participative. Moreover, the students felt that the greatest learning experience comes from bonding with the department, the faculty and seniors in the college. This was lacking during online learning.

“Bonding with the department is very important. During online classes we don’t have any opportunity to visit the department and bond with the faculty. We would have favourite faculty in the departments. This was not possible.” – a third-year medical student . “We lost the motivation provided by seniors and post graduate students in the departments” – a third-year medical student .

Ineffective teaching learning methods

The students felt that the teaching-learning methods that were used predominantly during the online classes were ineffective. They did not engage them actively in the learning process.

“The teachers would display a PowerPoint presentation on the screen and read it out line by line. We would be so bored and go to sleep. This was there even before online teaching , but became worse during online teaching” – a second year medical student .

The students felt that the teachers who were deeply involved in treating patients with COVID 19 day in and day out would use only COVID 19 examples to teach and this made it boring for them.

“They would use COVID 19 examples to teach everything. Already the news and media were full of information about COVID 19. We did not want more of that from the classes.” – a third-year medical student .

Ineffective evaluation methods

Evaluations were done merely as formalities. In fact, many students mentioned that the evaluations were not taken seriously and the marks they obtained in these evaluations were not counted for their formative internal assessment. They also mentioned that there was no clinical assessment.

“There was no clinical examination. They only conducted theory examinations.” – a second-year medical student . “Most of the tests would be multiple choice type questions. It was easy to answer. It would be an open book test.” – a second-year medical student . “One department made us write lengthy essays all typed in the online platform. Those of us who are not fast in typing found it difficult” – a third-year medical student .

Advantages of online learning

Despite these challenges in online classes, there were several advantages as well. The students felt that the online classes helped them understand the importance and need for self-directed learning and life-long learning.

“The online classes helped us learn the importance of self-learning” – a final year medical student .

The anonymity offered by the online class platform helped many students open and actively participate and interact in classes.

“Many students who would be terrified to speak up in an offline class , gathered the courage and answered questions in the online class. This is because they would not have to stand in front of everyone” – a second-year medical student . “Asking doubts and questions is much easier in an online class. We must just unmute ourselves and ask. This made us more actively participate in the class.” – a third-year medical student .

The other great advantage of online classes was the cross-learning opportunities from teachers of other institutions and even international teachers. The online platform threw open such opportunities.

“National and international conferences opened to all. We could attend even classes by faculty and professors of other institutions and other countries” – a second-year medical student .

Integrated teaching is when faculty from different departments came together to teach different dimensions of the same topic. Online teaching facilitated integrated teaching. Students felt that they could get diverse perspectives of senior experiences teachers on topics because of the online teaching facility.

“Online integrated teaching was easier and better because different faculty from different departments , seniors and juniors would participate and share knowledge.” – first year medical student .

Strategies adopted by teachers to improve the online learning experience

The students observed that their teachers adopted some strategies to improve the quality of the online learning experience. They requested students living close to the hospital and day scholar students to come to the ward, examine patients and then present them in the online class. This way even those students living away in distant cities and towns got an opportunity to experience clinical teaching online. The teachers used mannequins to demonstrate clinical examination and clinical procedures.

“Our seniors and post graduate students took special interest and taught classes for us online. These classes were extremely useful.” – a first-year medical student .

To keep the students interested and engaged they made the students present seminars and conducted interesting quizzes on various topics. They also conducted small group discussions online with 20–30 students in each batch and one facilitator. Since many students felt that online classes were boring and as many of them disengaged from the class, they would adopt interesting strategies to keep the students interested.

“They would randomly call out a roll number and ask that student a question related to the topic they were teaching. If the student answers that correctly they mark the student as present. Otherwise , they mark them as absent. This makes all students listen to the classes” – a third-year medical student .

Many senior professors bought digital equipment, tablets, laptops and high-end mobile phones to facilitate online teaching. This was a great advantage as they started becoming technology savvy and started updating themselves. Some faculty even conducted online classes for communication skills by making the students do role-plays.

“They made us do role play to enact a doctor-patient communication scenario.” – first year medical student .

Strategies adopted by students to cope with challenges of online learning

Some students bought tablets with a stylus to take notes and attend classes. They felt that this helped them attend classes and take notes in the same device. Some students subscribed to online coaching classes and attended the lectures and videos of these coaching classes. They found this very useful, sometimes more useful than their online class lectures.

“I used the 3D dissection application for anatomy , and it was very useful. It was better than the PowerPoint presentations shown in anatomy classes.” – a first-year medical student.

The students preferred recorded lectures to live online classes. This was because they could vary the pace of the lecture, pause the lecture and engage with the thoughts and then attend them at any time of their convenience.

“Students would log in to the online class , stay online for about 5mins and then exit. They would be marked as present in the attendance. Then they would record the lecture and listen to it at their own time in 2X speed.” – a second-year medical student.

Some students overcame the limitations of lack of clinical exposure by trying to shadow local clinicians and volunteering in COVID 19 treatment facilities near their homes.

“We volunteered in the COVID 19 treatment centres , and we learned a lot from there.” – a third year medical student . “I asked my parents for permission to go and sit with our family paediatrician and see patients. But because of COVID 19 , they never permitted me to do that.” – a third-year medical student.

Some students resorted to cheating practices in online evaluations and exams.

“Though they asked us to keep our camera on while writing the exams , there are still ways in which we can cheat in the exam.” – a second-year medical student. “Students cheated on online viva evaluations. They would take the viva on behalf of their friends. If the faculty did now know you by face , then you could do that. Or else you could wear a mask and do it.” – a first-year medical student. “Some students called their friends on the phone during the viva exam , and the friend would listen to the question and answer the questions , they would just repeat the answers” – a first-year medical student.

Medical students’ suggestions for improving the online learning experience

The students gave some interesting suggestions for improving the online learning experience. They suggested that the online lectures should be conducted in small batches. That way all the participants could actively engage and participate in the discussions. If the lectures are for large groups, they should introduce periodic break out small groups to discuss, debrief and then regroup to continue the class. Rather than forcing the students to attend live online lectures, the professors should record their lectures with clinical demonstrations and post them online. Though there are several online video lectures, these recorded lectures by their professors gave the lectures a sense of authenticity. The students also suggested that recordings of heart and lung sounds could be shared and discussed in the online clinical demonstrations.

Several studies have documented the challenges and difficulties of online medical education during COVID 19 times. [ 2 – 6 ] The commonly reported challenges include under-preparedness for technology enhanced teaching, challenges in time management, behavioral challenges and challenges in digital infrastructure. [ 2 – 6 ] Several studies have focused on the benefits and challenges. However, there are very few studies which have looked at the overall experiences of online learning during COVID 19. This study explored these experiences among medical students of the 4 different batches in a medical college in Chennai, India through focus group discussions. The study found that the students faced a stressful period of uncertainty due to the prolonged lockdown. There was a gendered impact of the lockdown, with women complaining of excessive household chores preventing them from attending the online classes. The men reported binge watching television, playing video games and adopting unhealthy life styles due to lockdown. The students reported several logistic challenges in the online classes with network connectivity issues, technical glitches and lack of preparedness of the faculty to the online teaching mode. They felt that clinical teaching was severely compromised. They said that they had to use fictional cases for discussion and learning. The learning ecosystem was very different, and the students felt very much distanced from their teachers. On the other hand, some students also felt that the online classes increased their confidence and capability to actively engage and interact with the classes due to the anonymity. They preferred recorded lectures to live online sessions as it helped them play it at varying paces, pause at strategic points and engage with the lecture at their own pace. In the following paragraphs we shall discuss these issues in detail.

We analyzed the experiences of the students in two separate categories, experiences of the lockdown and experiences of the online learning method. Uncertainty of the duration of lockdown, feeling of non-productive learning experience and anxieties about not being able to learn properly were common among the students. A previous study documented the uncertainties faced by students during the COVID 19 lockdown. The students reported a sense of loss of purpose, lack of motivation and uncertainty [ 8 ]. A similar uncertainty and anxiety was observed in this study. Since the lockdown came as a sudden shock, it disturbed their plans for the 5.5 years of medical college.

One of the key findings of this study was the gendered impact of the lockdown on the lives of the medical students. Previous studies have documented that gender roles of women and men within the household heavily impacted on the work burden on women [ 9 ]. This was also seen among lady medical students who were expected to share the burden of the household chores with the other women in the house. On the other hand, the male students expressed having a lot of free time for watching television series and playing video games. A study from Morocco showed that the COVID 19 lockdown led to widening of the gender disparity in education [ 10 ]. In our study the stark gender differences in narratives about being locked down at home re-emphasized the importance of gender-based discrimination at households and its impact on medical education.

Several previous studies from India which looked at the perceptions and experiences of medical students on online learning reported challenges in internet connectivity, technical glitches in the online learning platforms, and irregular timings of the online classes [ 2 – 6 , 11 – 17 ]. This study had similar findings. In addition, the students in this study also reported the generational differences in adaptation to internet and online learning technologies between the senior teachers and the students. A previous study of experiences of online learning showed that students tend to derive better online learning experiences from teachers who adapted to digital technology better [ 18 ]. Thus, generational differences in adapting to digital learning has a substantial impact on the online learning experience.

One of the major findings of our study was that the students suffered from a critical loss in clinical learning exposure. The various manifestations of this compromise in medical education was described by the students. The drastic change in the clinical learning environment from physical to virtual greatly compromised human connections, contextual cues, and the skills that are typically developed by direct patient interactions such as empathy, compassion and sensitive communication [ 19 ]. There is in addition a social learning environment in medical education comprising of networking and co-learning with other students, senior students and postgraduates. This contributes greatly to clinical learning. This was also compromised during the COVID 19 pandemic [ 19 ]. It was also reported in this study.

Another significant finding of this study is that many students used fictional and fabricated cases for their clinical discussions. Some students felt this to be advantageous because it gave them a focus to discuss clinical material, whereas others felt it was not the same as seeing a real patient and discussing about them. While there is some evidence to show that simulation-based learning is useful in developing clinical skills, there is no evidence to support the effectiveness of fictional or fabricated case studies [ 20 ]. The anonymity offered by online learning platforms encouraged participation by the students. This was reported in a previous study of school education using a ‘voice only’ learning platform. The partial anonymity offered by the platform enhanced active participation by the students [ 21 ].

To our best knowledge this is one of the few in depth qualitative explorations of students’ perceptions and experiences of online learning during COVID 19 pandemic. The findings of this study will help understand the implications of adopting online learning methods for medical education in the long run. There are a few limitations in this study. There were only 4 focus group discussions representing the students of four years in one medical college. This limits the findings to one institution and represents the experiences unique to that institution. The institution is one of the well-resourced and staffed institutions in the country. The situation in other medical colleges is likely to be very different compared to this one.

We recommend that any future attempts at including online classes into routine medical education must consider these key points during implementation. While online lectures for teaching theoretical concepts might be extremely useful, they cannot be used for saving instructional time. Dedicated college hours must still be allocated for engaging in these online learning activities as self-directed learning sessions in order to overcome the gendered impact of the online learning interface. The technical glitches are mostly experiences in live online classes, and therefore streaming of recorded video lectures must be considered to overcome this problem. There must be adequate emphasis on clinical bedside teaching and the online teaching must be reserved for teaching theoretical concepts.

This qualitative exploration of medical students’ experiences of online learning revealed that they faced several challenges the most serious among them being a compromise in their clinical learning. There seemed to be a gendered impact of the lockdown on the learning experience. The generational difference between senior teachers and the students in adaptation to technology influenced the online teaching. These points must be borne in mind while integrating online learning techniques into medical education.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Acknowledgements

The authors would like to acknowledge all the medical students who participated in the the focus group discussions.

Abbreviations

Author contributions

ER, SS, and PP conceptualised and designed the study and developed the tools for data collection. ER, SS, PP and VG standardised the tools for data collection. ER and SS conducted the FGDs, took detailed notes, recorded and transcribed them. ER, SS, TS did the initial coding and analysis of the data. VG verified and triangulated the coding and analysis. VG drafted the manuscript. ER, SS, TS and PP gave critical inputs and edited the manuscript. ER, SS, TS and PP, and VG, all agree with the final version of the submitted manuscript.

No funding was received for this research.

Data availability

Declarations.

This research was conducted in compliance with the National Ethical Guidelines for Biomedical and Health Research involving Human Participants as recommended by the Indian Council of Medical Research in 2017. The study proposal was reviewed by the Institutional Ethics Committee of Madras Medical College, Chennai and approved. We obtained a written informed consent from all participants in the FGDs before starting data collection.

Not Applicable.

The authors declare no competing interests.

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Eshwar Rajesh and Sudharshini Subramaniam are first authors and contributed equally.

• Open access
• Published: 13 September 2024

A qualitative analysis of health service problems and the strategies used to manage them in the COVID-19 pandemic: exploiting generic and context-specific approaches

• Hania Rahimi-Ardabili 1 ,
• Farah Magrabi 1 ,
• Brenton Sanderson 1 , 2 ,
• Thilo Schuler 1 , 3 &
• Enrico Coiera 1  

BMC Health Services Research volume  24 , Article number:  1067 ( 2024 ) Cite this article

Metrics details

The COVID-19 pandemic disrupted health systems around the globe. Lessons from health systems responses to these challenges may help design effective and sustainable health system responses for future challenges. This study aimed to 1/ identify the broad types of health system challenges faced during the pandemic and 2/ develop a typology of health system response to these challenges.

Semi-structured one-on-one online interviews explored the experience of 19 health professionals during COVID-19 in a large state health system in Australia. Data were analysed using constant comparative analysis utilising a sociotechnical system lens.

Participants described four overarching challenges: 1/ System overload, 2/ Barriers to decision-making, 3/ Education or training gaps, and 4/ Limitations of existing services. The limited time often available to respond meant that specific and well-designed strategies were often not possible, and more generic strategies that relied on the workforce to modify solutions and repair unexpected gaps were common. For example, generic responses to system overload included working longer hours, whilst specific strategies utilised pre-existing technical resources (e.g. converting non-emergency wards into COVID-19 wards).

During the pandemic, it was often not possible to rely on mature strategies to frame responses, and more generic, emergent approaches were commonly required when urgent responses were needed. The degree to which specific strategies were ready-to-hand appeared to dictate how much a strategy relied on such generic approaches. The workforce played a pivotal role in enabling emergent responses that required dealing with uncertainties.

Peer Review reports

The COVID-19 pandemic has posed a significant challenge to health systems worldwide, and many have struggled to cope, especially in the early stages [ 1 ]. The global consequences of COVID-19 on health systems are measured in loss or impairment of lives [ 2 ], healthcare professional burnout [ 3 ], reduced services, and delayed care [ 4 , 5 ].

Unfortunately, it is highly probable that health systems will confront many more such crises, with climate change risks amongst these [ 6 ]. Understanding what was common to successful COVID-19 strategies, and what was shared amongst failed ones could be instructive as we prepare for the future. The pandemic affected every aspect of operations from planning and procurement to care delivery [ 7 , 8 ]. Services, processes and tools were repurposed or created ad hoc, often from the ground up [ 9 , 10 ]. Hospitals for instance, responded by repurposing existing facilities and wards, and implementing strategies to cope with sudden rises in patient numbers that overwhelmed existing critical care services such as intensive care units [ 11 , 12 ]. The initial phase of the pandemic witnessed immediate actions, some of which succeeded such as the development of mRNA vaccines [ 13 ] and others that failed such as certain COVID-19 contact tracing applications [ 14 ].

The challenges healthcare professionals experienced during the COVID-19 pandemic has had some attention in the research literature. For example, a 2021 systematic review examining the COVID-19 burden on healthcare workers from nine different countries identified four main challenges of inadequate preparedness; emotional challenges; insufficient equipment and information; and work burnout [ 15 ].

This study goes beyond describing the challenges faced, and examines the responses to these problems using the lens of sociotechnical system theory (STS) [ 16 ]. STS thinking sees system processes as the emergent outcome of interactions between people and technology [ 16 ].

Using first-hand stories from healthcare professionals, this study first describes the different health service problems experienced by health professionals during the pandemic. Next, we attempt to categorise the different strategies they employed to deal with these problems, exploring how people and technologies came together to craft responses to these problems during the pandemic. We develop a typology of responses that identifies the different roles for generic (general-purpose strategies), and specific (local or health service-specific) approaches. Identifying the circumstances in which each of these strategy types was used may assist in preparedness and guide future crisis responses.

A series of semi-structured interviews explored the firsthand experiences of healthcare professionals in either developing or making COVID-19 pandemic responses. We utilised a qualitative and interpretive approach, which aims to generate new hypotheses by exploring emergent relationships between descriptions of phenomena [ 17 , 18 ]. This manuscript follows the COREQ (Consolidated Criteria for Reporting Qualitative Research) guidelines (See Additional file 1 for the checklist).

Participants and setting

Health system staff from a variety of professional groups and levels of seniority were recruited. Health professionals who had been involved in the pandemic response in New South Wales (NSW) were eligible for interviews. These included medical specialists (e.g. respiratory physicians), nurses and midwives, general practitioners (GPs), allied health workers (e.g. physiotherapists working in ICUs), health service executives and administrative staff, and paramedics. Participants were selected from a diverse range of health professions and services, including hospitals, public health organisations, and laboratories, in both public and private sectors as well as rural and urban settings. Our target sample size of 20 was informed by a systematic review of 14 qualitative studies that explored the experiences of healthcare professionals during the pandemic and concluded that on average, past studies reached data saturation with approximately 15 participants [ 19 ].

NSW is an Australian state with over eight million people. It includes about 9,600 full-time equivalent GPs [ 20 ] and 2000 registered pharmacies [ 21 ] governed by the federal government [ 22 ]. Further, NSW Health is the public health system for the state and includes NSW Ambulance, NSW Health Pathology, eHealth NSW, Health Protection NSW (public health legislation and surveillance), and Local Health Districts (LHDs) [ 23 ]. LHDs encompass hospitals, home hospitals, hospital pharmacies, aged health and disabilities, mental health, aboriginal health, drug health, and public health including immunisation [ 24 ]. During 2020-21, NSW had a total of 228 public hospitals and 210 private hospitals [ 25 ], and over 150 pathology collection centres [ 26 ]. Participants in this study were from general practices and community pharmacies, as well as NSW Health, including NSW Ambulance, Health Pathology (including COVID-19 testing centres), eHealth NSW, hospitals, hospital pharmacies, and immunisation services.

The research team (E.C., B.S., T.S., F.M.) initiated purposive recruitment with a convenience sample [ 27 , 28 ], identifying potential participants within their health system networks. Once enrolled, we used snowballing where participants were asked to forward the study invitation email to others who might be interested. Participants did not have any pre-existing relationship with the interviewer (H.R.-A.) who invited them via email. Transcripts were deidentified by H.R.-A. before sharing them with the other core analysis team (E.C., F.M).

Ethics and consent

Ethics approval was obtained from the Macquarie University Ethics Committee (ID: 11187) prior to commencing the study. Participants provided written informed consent prior to data collection.

Data collection

Data were collected between April and September 2022. At the time of the interview, the COVID-19 vaccine was freely available to the community, and health services in NSW have been providing in-person services in addition to tele-consultation. One-on-one interviews were conducted online using videoconferencing software (Zoom Video Communications, Inc. 2023) with each session lasting an average of 51 min (range: 27–73 min). One of the researchers (H.R-A.) with experience in qualitative interviews was responsible for conducting the interviews. Interviews were transcribed using an AI-based transcription tool (rev.com). A subset of four transcripts were manually checked for transcription accuracy (H.R-A.). Data collection and preliminary analysis were concurrent, with emerging themes from initial analysis reshaping subsequent interview questions and recruitment. Emerging themes about the use of different types of strategies led to new probe questions about strategy and whether such responses were new to the setting. The bulk of the analysis was conducted after data collection.

After the interviewer introduced herself and the reasons for conducting the research (identifying potential approaches for a crises ready health system) participants were asked about: (1) The challenges they faced while providing clinical services during the entire stages of the pandemic; (2) Specific health service responses that they were involved with and (3) what they did differently to pre COVID-19 practices (See Additional file 2 for the initial version of the interview guide).

Data analysis

Data were analysed using constant comparative analysis [ 29 ]. Two early transcripts were open-coded line-by-line to identify emerging concepts and themes (By H.R-A.). To ensure generalisability, these early codes were discussed and refined with a second analyst (E.C.). Codes were further refined and extended during the study by comparing similar categories across participants. An axial coding approach was taken, looking at connections between categories in terms of causation, strategies, consequences, context, and related conditions [ 29 ]. This process continued until all transcripts were coded. Both inductive and deductive approaches were utilised for coding and conceptualising the themes and frameworks.

Data coding was supported by QRS International NVivo ® 12 Software. Visualisation of code connections, codes and data was undertaken using Microsoft Excel. Some codes were grouped into more general constructs, and others were separated into several distinct codes. H.R-A. created memos of each transcript including key quotes, cross-indexed back to the transcripts and documented all process changes in an audit trail.

Reflexivity

Authors (E.C., B.S., T.S.; males) have a clinical background (medical doctors) and two are currently in clinical practice (B.S., T.S.). E.C. (PhD), F.M. (PhD, female) and H.R-A. (PhD, female) were academic researchers at the time of the study. All authors are experienced health system researchers, with prior experience in qualitative research. The interviewer and principal analyst (H.R.-A.) who had no previous contact with any of the participants, deidentified the transcripts before sharing them with other team members. Three participants were willing to provide feedback on the initial analyses.

Analytic framework

We analysed data to identify the types of (1) problems faced by participants or their health services during the COVID-19 pandemic; and (2) the type of health service responses employed to manage these problems. The analysis of health service responses was undertaken using the lens of STS theory which emphasises that system processes are the inevitable consequence of interaction between the people and technology, and that studying either in isolation leads to reductionism that fails to explain how the real world works adequately [ 16 ]. Thus, technological processes were analysed alongside human processes, each shaping the other in a continuous process of human-technology interaction [ 30 , 31 ]. For example, if a participant discussed technology, we probed for human processes related to the technology. We sought to understand the context that led to different social and technical response patterns with specific attention to human and technology interactions. Two researchers (H. R-A. and E.C.) analysed the health service responses reported by interviewees, and differences in interpretation were resolved by discussion.

Participant characteristics

Of 28 invited health professionals, 19 participated in our study. Participants who were involved in the pandemic response were GPs ( n  = 2), pharmacists ( n  = 2), specialists (e.g. emergency physician and respiratory physician), ( n  = 3), nurses and midwives ( n  = 3), allied health workers (e.g. physiotherapist and social worker working in ICU) ( n  = 3), pathologists ( n  = 2), a paramedic ( n  = 1), a clerical officer ( n  = 1) and public health implementation officer/ managers ( n  = 2).

Health service problem types

Participants identified four broad classes of challenges faced by their health services during COVID-19. A summary of challenges is provided below, and a detailed description with example quotes from participants available in Additional File 3 .

Health system overload . The ability for health services to meet the needs of the population as the pandemic unfolded was often compromised because of an imbalance between the supply and demand for resources. System overload was often the result.

Barriers to decision-making : In the rapidly unfolding pandemic, evidence was not being generated and distributed as quickly as health services required, and the communication pathways to share information were sometimes suboptimal.

Education and training gaps : The need to train the public and health service staff as services responded to the pandemic was triggered both by the arrival of new evidence and best-practice guidance needing to be shared widely, or by staff working in roles that were new to them.

Limitations of existing services : Faced with multiple and concurrent challenges, many existing services or care models were found to be inadequate.

Health service response types

Respondents provided a rich account of the different strategies employed to meet the problems faced during the early years of the pandemic, with multiple examples across all four problem types (Additional file 4 ).

High-level analysis of these responses identified that human organisational responses were apparently shaped by the degree of technology maturity and availability. We observed differences in the use of generic responses (applicable to many settings) and specific responses (designed to serve a given service, its unique characteristics and the problems it faced). In this section below, we contrast examples of general and specific responses, presented for each problem type to explore why these strategic differences might have been adopted. Example responses are cross-referenced to relevant quote IDs in brackets, indicating each code’s cell address and item number in the Excel sheet - Additional file 4 as “([Cell address]#[item number when available])”.

Health system overload

Generic overload management strategies: Respondents described increasing the hours worked by staff (quote IDs H03#1, H20, H21), redeploying staff to critical services (quote ID H03#2), hiring new staff (quote IDs H03#3, H20#2, H21#4) or retraining existing staff (quote IDs H14#3, H15#2) to address imbalances between service supply and demand. Work pattern changes included delaying non-urgent care (quote IDs H03#9, H13#7, H66), altering staff/patient ratios in hospitals (quote IDs H03#12, H35#2,6,7), and fast-tracking patient discharge in tandem with home monitoring and support packs for COVID-19 patients (quote ID H03#11). Clinical staff working under difficult circumstances or longer hours were supported with access to accommodation, peer and mental health support (quote IDs H15#7, H21#3, H27#2, H35#5).

The choice of generic responses appeared to be driven by time constraints necessitating immediate solutions (quote ID H20#2). For example, outsourcing recruitment was more expedient than developing new internal processes: “ they hired an external company to I guess source more [staff who] didn’t have the experience that we had it was yeah that’s what effectively led for those long [vaccine] lines… the expectation was the training would come in the same day… the workforce was ignored… it would be much helpful to know that like in two months we’re wrapping up to be 1500 [vaccinations] yeah we would have tried extra hard to train more people [Pharmacist – 14].”

Specific overload management strategies: Overload strategies were sometimes quite specific to the health service experiencing stress. Batch testing of pooled samples for polymerase chain reaction (PCR) tests was undertaken to improve the throughput of otherwise overloaded laboratory services (quote ID H07#1). Rapid antigen tests (RATs) were used in hospitals to reduce the number of PCR tests for likely-negative individuals and for symptomatic positive patients, and allow ill patients to receive COVID-19 treatment without delay (quote ID H07#2):

What a rapid test would do with someone who is symptomatic would be that if you turn positive on a RAT you are COVID positive , so what that would end up doing was then that would decrease the amount of PCR that we were doing… If we had access to them [RATs] in Delta [variant phase] a testing capacity for PCRs would have dropped , identification of COVID positive patients who have been much faster , and that would have changed our treatment or discharge plans for these patients a lot quicker [ICU Nurse – 13].

Other specific responses were increasing hospital capacity by converting non-emergency wards into COVID-19 wards (quote ID H08#1), creating temporary wards (e.g. tents in hospital car parks) (quote ID H18), and facilitating hospital discharge by providing bus services to take patients home (quote ID H55). Emergency co-ordination centres assisted in identifying beds for patients across a region (quote ID H03#10), and respiratory clinics were set up in the community to support keeping patients at home (quote ID H60#2).

Barriers to decision-making

Generic decision-making strategies: Health services adopted several generic strategies to improve data capture, and dissemination of new evidence and local data. A respondent explained how a generic electronic medical record system (EMR) was customised to capture COVID-19 specific information (quote ID H56). “ We had to make EMR kind of work for us [Emergency physician – 09].” The respondent and their colleagues “ had to sort of come up with a process … to mark that you’ve had COVID and then not test you .” General purpose strategies required staff to be vigilant for problems during their application: “people were good at that. It was just realising that it [problem] was coming. So sort of working out. Oh hang on this is going to be a problem as we go forward. So what do we do? [Emergency physician – 09] . ”

Non-specific technologies such as email, Zoom, and Microsoft Teams were often used to enhance team communication. Communication processes were also enhanced by scheduling regular daily staff meetings at hospitals (quote IDs H09#1, H14#11), and weekly meetings for GPs to speak directly with those involved in pandemic management from the public health system (quote ID H09#4). Microsoft SharePoint was used to gather information about staff activities, such as where and when they treated COVID-19 patients, to assist with infection control and for patient managements (quote IDs H47, H48#2, H49).

Specific decision-making strategies: To provide local best practice guidance, expert support teams were created to assist with troubleshooting (quote ID H09#3), local protocols were developed and updated potentially daily (quote IDs H09#2, H68#1,), and interdisciplinary collaborations (e.g. pharmacists working with nurses) developed local workflow models (quote ID H17#1). Such activities required significant effort (quote ID H09#2): “ a working group that met like daily seven days a week for months and months and months to put together the [local protocol and updates] response [Transplant nephrologist – 18]. ”

Education and training gaps

Generic training strategies: Virtual training packages were used to maximise the dissemination of educational materials where local training was not feasible (quote ID H57). Peer support networks were developed to support information sharing where training was not available (quote IDs H03#4, H34 #5, H15#2). Adaptations of such solutions required significant human effort e.g. peer support meant senior staff had to be “there every step of the way [Emergency nurse – 13]. ”

Specific training strategies: Many of the responses designed to educate the health system workforce and the community were highly targeted (quote ID H15#2). Specific training programs were instituted to meet urgent needs, e.g. training clinicians in the use of PPE and hand hygiene. Consumers received highly targeted educational messages, such as requests to avoid unnecessary calling of ambulances, and simple social distancing rules and masking advice (quote IDs H22, H25, H26). Pharmacies provided in-house RATs for members of the public who did not understand the testing process (quote ID H25).

Limitations of existing services

Generic service strategies: The early stages of the pandemic saw a flurry of new or extended health services, often implemented under significant time and resource limitations. Periods of public health mandated lockdowns and work-from-home arrangements relied upon general purpose technologies (quote IDs H3#13, H14#5). Virtual consultations were delivered over channels of varying sophistication from telephone to online telecare products (quote IDs H13#3, H44#2, H52#1, H62#1). When there was lack of supply or limited access to manufactured PCR kits for COVID-19, specialised experts using general PCR techniques “try and put together a rapid PCR type of [solution/reagent] which they didn’t have [Pathology manager – 26] ” (quote ID H64#2).

Specific service strategies: Context-specific responses to service limitations included massive expansion of contact tracing capabilities, new measures such as routine COVID-19 surveillance of clinical staff (quote ID H14#6), and the use of QR (quick response) codes in public venues to support rapid contact tracing (quote ID H14#15). COVID-19 focussed respiratory clinics (quote ID H60#2) and PCR testing facilities appeared in the community for the first time. Specialist vaccination hubs and expanded community pharmacy services such as home delivery of medications were other specific responses. Hospital emergency services expanded their triage functions by creating specialised COVID-19 assessment areas with staff in full PPE, either using repurposed hospital space or in carparks outside the emergency departments or clinics (quote ID H03#11, H13#1,2, H14#13). Laboratories took advantage of manufactured PCR kits when available (quote ID H064#4): “you just opened the box and you put it together and you go [Pathology manager – 26].”

General to specific strategies . Many early responses to the pandemic involved the use of general strategies that sought to optimise responses from existing services (such as reconfiguring rostering or using general-purpose software):

The use of general solutions seemed to coincide with urgency and lack of time or resources to craft a more specific local solution (e.g. quote ID H20#2).

General solutions also could thus be seen to “buy time” whilst uncertainty remained about the best way forward, and better more specific solutions were being developed (e.g. quote IDs H03#13, H14#5). Pre-existing SARS infection control protocols were widely used early on and adapted to local circumstances or evolving knowledge. Generic information and communication tools were used to patch together information processes whilst more sophisticated solutions could be developed (e.g. quote IDs H13#3, H44#2, H52#1, H62#1) [ 32 ].

It is the nature of such generic responses that they are never a perfect fit to a specific task or context. Consequently, some adaptation or localisation is required to better meet these local needs. Such “fitting work” [ 33 ] often fell to local staff, and could take the form of workarounds (e.g. to make standard computer systems work in a new setting) or the addition of local changes (e.g. to a PPE protocol [ 34 ]) (e.g. quote IDs H47, H48#2, H49, H56).

The need for fitting work imposes additional load on staff (e.g. quote IDs H03#1, H20, H21) to “ make things work here right now ” and could be a contributor to the high levels of staff burnout reported through the pandemic.

Specific to general strategies . Highly local solutions to pandemic challenges were often needed where services provided highly specialised services. For example, the details of changes to the workflow for laboratory processing of high volumes of PCR tests would not have wide applicability beyond the laboratory setting.

The use of specific solutions appeared to coincide with unique local problems, or some capacity to develop new specific solutions whilst generic solutions “ held the fort ” (quote ID H64 #2).

Nonetheless, general lessons from such specific responses can sometimes be drawn e.g. in the approach taken to agree upon the specific solution and how it is subsequently communicated. For example, public health services had to rapidly expand their workforce in support of contact tracing, and their use of external recruitment agencies could be adopted by very different parts of the health system.

This study has examined the challenges faced during the COVID-19 pandemic, and health system responses to those challenges in Australia.

Clearly the challenges faced during the pandemic were not uniform, and different health services found themselves better or less well prepared or capable of responding than others [ 35 ]. Our analysis of these responses identified what appeared to be two quite different response pathways that played distinct roles in crisis management – the adoption of general strategies which could be used across a wide variety of settings, or the use or creation of highly targeted context specific responses.

What lessons can be learned from these broad responses? Given the nature of crises, each will bring novel and likely unanticipated challenges.

When faced with requirements to dramatically alter the duties and workflows of existing health services, especially when constrained by time, resource or knowledge, health services can turn to general-purpose strategies to reconfigure their existing workforce, and adopt ready to hand general purpose technologies. Whilst not ideal, these strategies support quick responses and buy time for more targeted solutions to emerge.

Crisis preparedness could thus focus on understanding the range of general-purpose tools and processes that can quickly be brought to hand. Adaptation protocols might provide guidance on localisation processes that optimise speed, quality, impact on staff, or cost. For example, protocols might describe processes of problem identification, workaround development, and team communication approaches that facilitate these tasks. In developing such protocols, we should not forget that while some services must develop highly localised solutions, they nevertheless can be a rich source of lessons about general approaches to identifying issues, designing solutions, and enacting them effectively. During the pandemic, innovations commonly involved combining pre-existing services.

Theoretical frameworks for system resilience describe the importance of flexibility and adaptability to respond to unexpected and escalating situations [ 36 , 37 ]. Generic competencies are often team-based and include information management, communication and coordination, decision-making, and effect control [ 36 ]. Responses when managing the early phase of health emergencies should be simple and generic, such as using generic international guidance [ 38 ]. The Interactive Systems Framework (ISF) for dissemination and implementation distinguishes innovation-specific capacity and general capacity [ 39 ]. Various implementation frameworks suggest general organisational capacity building is an essential step in the early phase of implementation [ 40 ]. Such approaches emphasise that stabilising a situation and maintaining organizational function are key to managing uncertainty while developing specific responses.

Limitations

The problems and system responses reported in this study may lack representativeness because of the small sample size of interviewees, the focus on a single albeit large health system in Australia, and the potential for recruitment biases introduced by convenience and snowballing sampling. Different nations had distinct experiences during COVID-19, such as variations in public health measures adopted, access to vaccines, lockdowns, government policy, and health impacts of the virus on their population. Thus, these findings may not be generalisable to other health system settings. Respondents detailed challenges and system responses with many examples. We anticipated achieving theoretical saturation with 20 participants but during the analysis phase did not do so. This may be due to the richness of innovations during COVID-19 or the diverse selection of participants [ 41 , 42 ]. Failure to saturate suggests that interviewing additional participants could likely identify new examples and issues that might have uncovered additional issues. However, the concept of data saturation in qualitative studies is currently under debate [ 43 ].

Health services have a range of different response strategies available to them when faced with novel challenges, and selection of a strategy can be guided by the circumstances and the availability of ready-to-hand specific strategies. The workforce is pivotal in enabling emergent responses that require dealing with uncertainties. Recognising the important role that general purpose strategies play when time is short (e.g. emergencies) and specific solutions are not yet available suggests that health services can invest in formalising protocols for solution design and focus on workforce support, including team communication and supporting solution implementation. Such capabilities should enhance health system preparedness for crises such as new pandemics or climate-change triggered events. Much can also be learnt about the construction of context-specific solutions, a deeper exploration of when to employ such approaches and how to support them to best prepare for future crises.

Data availability

The complete datasets generated and analysed during the current study are not publicly available because consent was not obtained from study participants for data to be made public but are available from the corresponding author on reasonable request subject to approval from the Macquarie University Ethics Committee. Part of the deidentified data is provided as a supplementary file.

Abbreviations

Electronic medical record system

General practitioner

Intensive care unit

Polymerase Chain Reaction

Personal protective equipment, RAT: Rapid antigen tests

Sociotechnical system

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Acknowledgements

The authors thank K-lynn Smith and Yvonne Zurynski for their valuable feedback on the manuscript.

The project was conducted with funding from the National Health and Medical Research Council: Partnership Centre for Health System Sustainability; and Centre of Research Excellence in Digital Health (APP1134919).

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Centre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Syndey, NSW, 2109, Australia

Hania Rahimi-Ardabili, Farah Magrabi, Brenton Sanderson, Thilo Schuler & Enrico Coiera

Department of Anaesthesia and Perioperative Medicine, Westmead Hospital, Sydney, NSW, Australia

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Department of Radiation Oncology, Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, NSW, Australia

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Contributions

E.C., B.S., T.S. and F.M. conceptualised the study. H.R.-A. developed the study protocol and collected data, E.C. and H.R.-A. analyzed the data. E.C. and H.R.-A. prepared the original draft, and all authors contributed to the final drafts of the manuscript.

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Correspondence to Enrico Coiera .

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Rahimi-Ardabili, H., Magrabi, F., Sanderson, B. et al. A qualitative analysis of health service problems and the strategies used to manage them in the COVID-19 pandemic: exploiting generic and context-specific approaches. BMC Health Serv Res 24 , 1067 (2024). https://doi.org/10.1186/s12913-024-11499-7

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Received : 07 March 2024

Accepted : 28 August 2024

Published : 13 September 2024

DOI : https://doi.org/10.1186/s12913-024-11499-7

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