peer reviewed articles online education

• Review article
• Open access
• Published: 09 November 2022

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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Looking back to move forward: comparison of instructors’ and undergraduates’ retrospection on the effectiveness of online learning using the nine-outcome influencing factors

• Yujie Su   ORCID: orcid.org/0000-0003-1444-1598 1 ,
• Xiaoshu Xu   ORCID: orcid.org/0000-0002-0667-4511 1 ,
• Yunfeng Zhang 2 ,
• Xinyu Xu 1 &
• Shanshan Hao 3  

Humanities and Social Sciences Communications volume  11 , Article number:  594 ( 2024 ) Cite this article

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This study delves into the retrospections of undergraduate students concerning their online learning experiences after the COVID-19 pandemic, using the nine key influencing factors: behavioral intention, instruction, engagement, interaction, motivation, self-efficacy, performance, satisfaction, and self-regulation. 46 Year 1 students from a comprehensive university in China were asked to maintain reflective diaries throughout an academic semester, providing first-person perspectives on the strengths and weaknesses of online learning. Meanwhile, 18 college teachers were interviewed with the same questions as the students. Using thematic analysis, the research identified 9 factors. The research revealed that instruction ranked highest among the 9 factors, followed by engagement, self-regulation, interaction, motivation, and others. Moreover, teachers and students had different attitudes toward instruction. Thirdly, teacher participants were different from student participants given self-efficacy and self-regulation due to their variant roles in online instruction. Lastly, the study reflected students were not independent learners, which explained why instruction ranked highest in their point of view. Findings offer valuable insights for educators, administrators, and policy-makers involved in higher education. Recommendations for future research include incorporating a more diverse sample, exploring relationships between the nine factors, and focusing on equipping students with skills for optimal online learning experiences.

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Introduction.

The outbreak of the COVID-19 pandemic has had a profound impact on education worldwide, leading to the widescale adoption of online learning. According to the United Nations Educational, Scientific and Cultural Organization (UNESCO), at the peak of the pandemic, 192 countries had implemented nationwide closures, affecting approximately 99% of the world’s student population (UNESCO 2020 a). In response, educational institutions, teachers, and students quickly adapted to online learning platforms, leveraging digital technologies to continue education amidst the crisis (Marinoni et al. 2020 ).

The rapid and unexpected shift to online learning brought about a surge in research aiming to understand its impact, effectiveness, and challenges. Researchers across the globe have been investigating various dimensions of online learning. Some focus on students’ experiences and perspectives (Aristovnik et al. 2021 ), technological aspects (Bao 2020 ), pedagogical strategies (Hodges et al. 2020 ), and the socio-emotional aspect of learning (Ali 2020 ). Tan et al. ( 2021 ) found that motivation and satisfaction were mostly positively perceived by students, and lack of interaction was perceived as an unfavorable online instruction perception. Some center on teachers’ perceptions of the benefits and challenges (Lucas and Vicente, 2023 ; Mulla et al. 2023 ), post-pandemic pedagogisation (Rapanta et al. 2021 ), and post-pandemic further education (Kohnke et al. 2023 ; Torsani et al. 2023 ). It was worth noting that elements like interaction and engagement were central to the development and maintenance of the learning community (Lucas and Vincente 2023 ),

The rise of online learning has also posed unprecedented challenges. Studies have pointed out the digital divide and accessibility issues (Crawford et al. 2020 ), students’ motivation and engagement concerns (Martin and Bolliger 2018 ), and the need for effective online instructional practices (Trust and Whalen 2020 ). The rapid transition to online learning has highlighted the need for robust research to address these challenges and understand the effectiveness of online learning in this new educational paradigm.

Despite the extensive research on online learning during and after the COVID-19 pandemic, there remains a notable gap in understanding the retrospective perspectives of both undergraduates and teachers. Much of the current literature has focused on immediate response strategies to the transition to online learning, often overlooking the detailed insights that reflective retrospection can provide (Marinoni et al. 2020 ; Bao 2020 ). In addition, while many studies have examined isolated aspects of online learning, they have not often employed a comprehensive framework, leaving undergraduates’ voices, in particular, underrepresented in the discourse (Aristovnik et al. 2021 ; Crawford et al. 2020 ). This study, situated in the context of the COVID-19 pandemic’s impetus toward online learning, seeks to fill this crucial gap. By exploring online learning from the perspectives of both instructors and undergraduates, and analyzing nine key factors that include engagement, motivation, and self-efficacy, the research contributes vital insights into the dynamics of online education (Wang and Wang 2021 ). This exploration is especially pertinent as digital learning environments become increasingly prevalent worldwide (UNESCO 2020b ). The findings of our study are pivotal for shaping future educational policies and enhancing online education strategies in this continuously evolving educational landscape (Greenhow et al. 2021 ). Thus, three research questions were raised:

Q1: How do undergraduates and teachers in China retrospectively perceive the effectiveness of online learning after the COVID-19 pandemic?

Q2: Which of the nine outcome influencing factors had the most significant impact on online learning experiences after the pandemic, and why?

Q3: What recommendations can be proposed to enhance the effectiveness of online learning in the future?

The research takes place at a comprehensive university in China, with a sample of 46 Year 1 students and 18 experienced teachers. Their reflections on the effectiveness of online learning were captured through reflective diaries guided by four questions. These questions investigated the students’ online learning states and attitudes, identified issues and insufficiencies in online learning, analyzed the reasons behind these problems, and proposed improvements. By assessing their experiences and perceptions, we seek to explore the significant factors that shaped online learning outcomes after the pandemic and the means to enhance its effectiveness.

This paper first presents a review of the existing literature, focusing on the impact of the pandemic on online learning and discussing the nine significant factors influencing online learning outcomes. Following this, the methodology utilized for this study is detailed, setting the stage for a deeper understanding of the research process. Subsequently, we delve into the results of the thematic analysis conducted based on undergraduate students and teachers’ retrospections. Finally, the paper concludes by offering meaningful implications of the findings for various stakeholders and suggesting directions for future research in this critical area.

Literature review

Online learning application and evaluation in higher education.

Online learning, also known as e-learning or distance learning, refers to education that takes place over the Internet rather than in a traditional classroom setting. It has seen substantial growth over the past decade and has been accelerated due to the COVID-19 pandemic (Trust and Whalen 2020 ). Online learning allows for a flexible learning environment, breaking the temporal and spatial boundaries of traditional classroom settings (Bozkurt and Sharma 2020 ). In response to the COVID-19 pandemic, educational institutions globally have embraced online learning at an unprecedented scale. This has led to an immense surge in research focusing on the effects of the pandemic on online learning (Crawford et al. 2020 ; Marinoni et al. 2020 ).

Researchers were divided in their attitudes toward the effects of online learning, including positive, neutral, and negative. Research by Bahasoan et al. ( 2020 ), Bernard et al. ( 2004 ), Hernández-Lara and Serradell-López ( 2018 ), and Paechter and Maier ( 2010 ) indicated the effectiveness of online learning, including improved outcomes and engagement in online formats, providing flexibility and enhancing digital skills for instance. Research, including studies by Dolan Hancock and Wareing ( 2015 ) and Means et al. ( 2010 ), indicates that under equivalent conditions and with similar levels of support, there is frequently no substantial difference in learning outcomes between traditional face-to-face courses and completely online courses.

However, online learning was not without its challenges. Research showing less favorable results for specific student groups can be referenced in Dennen ( 2014 ), etc. The common problems faced by students included underdeveloped independent learning ability, lack of motivation, difficulties in self-regulation, student engagement and technical issues (Aristovnik et al. 2021 ; Martin and Bolliger 2018 ; Song et al. 2004 ; Zheng et al. 2022 ).

Moreover, factors like instructional strategies, course design, etc. were also linked to learning outcomes and successful online learning (Ali 2020 ; Hongsuchon et al. 2022 ). Careaga-Butter et al. ( 2020 ) critically analyze online education in pandemic and post-pandemic contexts, focusing on digital tools and resources for teaching in synchronous and asynchronous learning modalities. They discuss the swift adaptation to online learning during the pandemic, highlighting the importance of technological infrastructure, pedagogical strategies, and the challenges of digital divides. The article emphasizes the need for effective online learning environments and explores trends in post-pandemic education, providing insights into future educational strategies and practices.

Determinants of online learning outcomes

Online learning outcomes in this paper refer to the measurable educational results achieved through online learning methods, including knowledge acquisition, skill development, changes in attitudes or behaviors, and performance improvements (Chang 2016 ; Panigrahi et al. 2018 ). The literature review identified key factors influencing online learning outcomes, emphasizing their significant role in academic discourse. These factors, highlighted in scholarly literature, include student engagement, instructional design, technology infrastructure, student-teacher interaction, and student self-regulation.

Student Engagement: The level of a student’s engagement significantly impacts their learning outcomes. The more actively a student is engaged with the course content and activities, the better their performance tends to be. This underscores the importance of designing engaging course content and providing opportunities for active learning in an online environment (Martin and Bolliger 2018 ).

Instructional Design: How an online course is designed can greatly affect student outcomes. Key elements such as clarity of learning objectives, organization of course materials, and the use of diverse instructional strategies significantly impact student learning (Bozkurt and Sharma 2020 ).

Technology Infrastructure: The reliability and ease of use of the learning management system (LMS) also play a significant role in online learning outcomes. When students experience technical difficulties, it can lead to frustration, reduced engagement, and lower performance (Johnson et al. 2020 ).

Student-Teacher Interaction: Interaction between students and teachers in an online learning environment is a key determinant of successful outcomes. Regular, substantive feedback from instructors can promote student learning and motivation (Boling et al. 2012 ).

Student Self-Regulation: The autonomous nature of online learning requires students to be proficient in self-regulated learning, which involves setting learning goals, self-monitoring, and self-evaluation. Students who exhibit strong self-regulation skills are more likely to succeed in online learning (Broadbent 2017 ).

While many studies have investigated individual factors affecting online learning, there is a paucity of research offering a holistic view of these factors and their interrelationships, leading to a fragmented understanding of the influences on online learning outcomes. Given the multitude of experiences and variables encompassed by online learning, a comprehensive framework like is instrumental in ensuring a thorough investigation and interpretation of the breadth of students’ experiences.

Students’ perceptions of online learning

Understanding students’ perceptions of online learning is essential for enhancing its effectiveness and student satisfaction. Studies show students appreciate online learning for its flexibility and convenience, offering personalized learning paths and resource access (Händel et al. 2020 ; Johnson et al. 2020 ). Yet, challenges persist, notably in maintaining motivation and handling technical issues (Aristovnik et al. 2021 ; Händel et al. 2020 ). Aguilera-Hermida ( 2020 ) reported mixed feelings among students during the COVID-19 pandemic, including feelings of isolation and difficulty adjusting to online environments. Boling et al. ( 2012 ) emphasized students’ preferences for interactive and communicative online learning environments. Additionally, research indicates that students seek more engaging content and innovative teaching approaches, suggesting a gap between current online offerings and student expectations (Chakraborty and Muyia Nafukho 2014 ). Students also emphasize the importance of community and peer support in online settings, underlining the need for collaborative and social learning opportunities (Lai et al. 2019 ). These findings imply that while online learning offers significant benefits, addressing its shortcomings is critical for maximizing its potential.

The pandemic prompted a reconsideration of instructional modalities, with many students favoring face-to-face instruction due to the immediacy and focus issues (Aristovnik et al. 2021 ; Trust and Whalen 2020 ). Despite valuable insights, research gaps remain, particularly in long-term undergraduate reflections and the application of nine factors of comprehensive frameworks, indicating a need for more holistic research in online learning effectiveness.

Teachers’ perceptions of online learning

The pandemic has brought attention to how teachers manage instruction in virtual learning environments. Teachers and students are divided in terms of their attitudes toward online learning. Some teachers and students looked to the convenience and flexibility of online learning (Chuenyindee et al. 2022 ; Al-Emran and Shaalan 2021 ). They conceived that online learning provided opportunities to improve educational equality as well (Tenório et al. 2016 ). Even when COVID-19 was over, the dependence on online learning was likely here to stay, for some approaches of online learning were well-received by students and teachers (Al-Rahmi et al. 2019 ; Hongsuchon et al. 2022 ).

Teachers had shown great confidence in delivering instruction in an online environment in a satisfying manner. They also agreed that the difficulty of teaching was closely associated with course structures (Gavranović and Prodanović 2021 ).

Not all were optimistic about the effects of online learning. They sought out the challenges facing teachers and students during online learning.

A mixed-method study of K-12 teachers’ feelings, experiences, and perspectives that the major challenges faced by teachers during the COVID-19 pandemic were lack of student participation and engagement, technological support for online learning, lack of face-to-face interactions with students, no work-life balance and learning new technology.

The challenges to teachers’ online instruction included instruction technology (Maatuk et al. 2022 ; Rasheed et al. 2020 ), course design (Khojasteh et al. 2023 ), and teachers’ confidence (Gavranović and Prodanović 2021 ).

Self-regulation challenges and challenges in using technology were the key challenges to students, while the use of technology for teaching was the challenge facing teachers (Rasheed et al. 2020 ).

The quality of course design was another important factor in online learning. A research revealed the competency of the instructors and their expertise in content development contributed a lot to students’ satisfaction with the quality of e-contents.

Theoretical framework

The theoretical foundation of the research is deeply rooted in multifaceted framework for online learning, which provides a comprehensive and interwoven model encompassing nine critical factors that collectively shape the educational experience in online settings. This framework is instrumental in guiding our analysis and enhances the comparability and interpretability of our results within the context of existing literature.

Central to Yu’s framework is the concept of behavioral intention, which acts as a precursor to student engagement in online learning environments. This engagement, inherently linked to the students’ intentions and motivations, is significantly influenced by the quality of instruction they receive. Instruction, therefore, emerges as a pivotal element in this model, directly impacting not only student engagement but also fostering a sense of self-efficacy among learners. Such self-efficacy is crucial as it influences both the performance of students and their overall satisfaction with the learning process.

The framework posits that engagement, a derivative of both strong behavioral intention and effective instruction, plays a vital role in enhancing student performance. This engagement is tightly interlaced with self-regulation, an indispensable skill in the autonomous and often self-directed context of online learning. Interaction, encompassing various forms such as student-teacher and peer-to-peer communications, further enriches the learning experience. It significantly contributes to the development of motivation and self-efficacy, both of which are essential for sustaining engagement and fostering self-regulated learning.

Motivation, especially when intrinsically driven, acts as a catalyst, perpetuating engagement and self-regulation, which ultimately leads to increased satisfaction with the learning experience. In this framework, self-efficacy, nurtured through effective instruction and meaningful interactions, has a positive impact on students’ performance and satisfaction, thereby creating a reinforcing cycle of learning and achievement.

Performance in this model is viewed as a tangible measure of the synergistic interplay of engagement, instructional quality, and self-efficacy, while satisfaction reflects the culmination of the learning experience, shaped by the quality of instruction, the extent and nature of interactions, and the flexibility of the learning environment. This satisfaction, in turn, influences students’ future motivation and their continued engagement with online learning.

Yu’s model thus presents a dynamic ecosystem where changes in one factor can have ripple effects across the entire spectrum of online learning. It emphasizes the need for a holistic approach in the realm of online education, considering the complex interplay of these diverse yet interconnected elements to enhance both the effectiveness and the overall experience of online learning.

The current study employed a qualitative design to explore teachers’ and undergraduates’ retrospections on the effectiveness of online learning during the first semester of the 2022–2023 school year, which is in the post-pandemic period. Data were collected using reflective diaries, and thematic analysis was applied to understand the experiences based on the nine factors.

Sample and sampling

The study involved 18 teachers and 46 first-year students from a comprehensive university in China, selected through convenience sampling to ensure diverse representation across academic disciplines. To ensure a diverse range of experiences in online learning, the participant selection process involved an initial email inquiry about their prior engagement with online education. The first author of this study received ethics approval from the department research committee, and participants were informed of the study’s objectives two weeks before via email. Only those participants who provided written informed consent were included in the study and were free to withdraw at any time. Pseudonyms were used to protect participants’ identities during the data-coding process. For direct citations, acronyms of students’ names were used, while “T+number” was used for citations from teacher participants.

The 46 students are all first-year undergraduates, 9 females and 37 males majoring in English and non-English (see Table 1 ).

The 18 teachers are all experienced instructors with at least 5 years of teaching experience, 13 females and 5 male, majoring in English and Non-English (see Table 2 ).

Data collection

Students’ data were collected through reflective diaries in class during the first semester of the 2022–2023 school year. Each participant was asked to maintain a diary over the course of one academic semester, in which they responded to four questions.

The four questions include:

What was your state and attitude toward online learning?

What were the problems and shortcomings of online learning?

What do you think are the reasons for these problems?

What measures do you think should be taken to improve online learning?

This approach provided a first-person perspective on the participants’ online teaching or learning experiences, capturing the depth and complexity of their retrospections.

Teachers were interviewed separately by responding to the four questions the same as the students. Each interview was conducted in the office or the school canteen during the semester and lasted about 20 to 30 min.

Data analysis

We utilized thematic analysis to interpret the reflective diaries, guided initially by nine factors. This method involved extensive engagement with the data, from initial coding to the final report. While Yu’s factors provided a foundational structure, we remained attentive to new themes, ensuring a comprehensive analysis. Our approach was methodical: familiarizing ourselves with the data, identifying initial codes, systematically searching and reviewing themes, and then defining and naming them. To validate our findings, we incorporated peer debriefing, and member checking, and maintained an audit trail. This analysis method was chosen for its effectiveness in extracting in-depth insights from undergraduates’ retrospections on their online learning experiences post-pandemic, aligning with our research objectives.

According to the nine factors, the interviews of 18 teachers and 46 Year 1 undergraduates were catalogued and listed in Table 3 .

Behavioral intention towards online learning post-pandemic

Since the widespread of the COVID-19 pandemic, both teachers and students have experienced online learning. However, their online teaching or learning was forced rather than planned (Baber 2021 ; Bao 2020 ). Students more easily accepted online learning when they perceived the severity of COVID-19.

When entering the post-pandemic era, traditional teaching was resumed. Students often compared online learning with traditional learning by mentioning learning interests, eye contact, face-to-face learning and learning atmosphere.

“I don’t think online learning is a good form of learning because it is hard to focus on learning.” (DSY) “In unimportant courses, I would let the computer log to the platform and at the same time do other entertains such as watching movies, listening to the music, having snacks or do the cleaning.” (XYN) “Online learning makes it impossible to have eye contact between teachers and students and unable to create a face-to-face instructional environment, which greatly influences students’ initiative and engagement in classes.” (WRX)

They noted that positive attitudes toward online learning usually generated higher behavioral intention to use online learning than those with negative attitudes, as found in the research of Zhu et al. ( 2023 ). So they put more blame on distractions in the learning environment.

“Online learning relies on computers or cell phones which easily brings many distractions. … I can’t focus on studying, shifting constantly from study and games.” (YX) “When we talk about learning online, we are hit by an idea that we can take a rest in class. It’s because everyone believes that during online classes, the teacher is unable to see or know what we are doing.” (YM) “…I am easily disturbed by external factors, and I am not very active in class.” (WZB)

Teachers reported a majority of students reluctantly turning on their cameras during online instruction and concluded the possible reason for such behavior.

“One of the reasons why some students are unwilling to turn on the camera is that they are worried about their looks and clothing at home, or that they don’t want to become the focus.” (T4)

They also noticed students’ absent-mindedness and lazy attitude during online instruction.

“As for some students who are not self-regulated, they would not take online learning as seriously as offline learning. Whenever they are logged onto the online platform, they would be unable to stay focused and keep their attention.” (T1)

Challenges and opportunities in online instruction post-pandemic

Online teaching brought new challenges and opportunities for students during and after the pandemic. The distractions at home seemed to be significantly underestimated by teachers in an online learning environment (Radmer and Goodchild 2021 ). It might be the reason why students greatly expected and heavily relied on teachers’ supervision and management.

“The biggest problem of online learning is that online courses are as imperative as traditional classes, but not managed face to face the same as the traditional ones.” (PC) “It is unable to provide some necessary supervision.” (GJX) “It is incapable of giving timely attention to every student.” (GYC) “Teachers can’t understand students’ conditions in time in most cases so teachers can’t adjust their teaching plan.” (MZY) “Some courses are unable to reach the teaching objectives due to lack of experimental conduction and practical operation.” (YZH) “Insufficient teacher-student interaction and the use of cell phones make both groups unable to engage in classes. What’s more, though online learning doesn’t put a high requirement for places, its instructional environment may be crucial due to the possible distractions.” (YCY)

Teachers also viewed online instruction as an addition to face-to-face instruction.

“Online learning cannot run as smoothly as face-to-face instruction, but it can provide an in-time supplement to the practical teaching and students’ self-learning.” (T13, T17) “Online instruction is an essential way to ensure the normal function of school work during the special periods like the pandemic” (T1, T15)

Factors influencing student engagement in online learning

Learning engagement was found to contribute to gains in the study (Paul and Diana 2006 ). It was also referred to as a state closely intertwined with the three dimensions of learning, i.e., vigor, dedication, and absorption (Schaufeli et al. 2002 ). Previous studies have found that some key factors like learning interaction, self-regulation, and social presence could influence learning engagement and learning outcomes (Lowenthal and Dunlap 2020 ; Ng 2018 ). Due to the absence of face-to-face interaction like eye contact, facial expressions and body language, both groups of interviewees agreed that the students felt it hard to keep their attention and thus remain active in online classes.

“Students are unable to engage in study due to a lack of practical learning environment of online learning.” (ZMH, T12) “Online platforms may not provide the same level of engagement and interaction as in-person classrooms, making it harder for students to ask questions or engage in discussions.” (HCK) “The Internet is cold, lack of emotional clues and practical connections, which makes it unable to reproduce face-to-face offline learning so that teachers and students are unlikely to know each other’s true feelings or thoughts. In addition, different from the real-time learning supervision in offline learning, online learning leaves students more learning autonomy.” (XGH) “Lack of teachers’ supervision and practical learning environment, students are easily distracted.” (LMA, T9)

Just as Zhu et al. ( 2023 ) pointed out, we had been too optimistic about students’ engagement in online learning, because online learning relied more on students’ autonomy and efforts to complete online learning.

Challenges in teacher-student interaction in online learning

Online learning has a notable feature, i.e., a spatial and temporal separation among teachers and students. Thus, online teacher-student interactions, fundamentals of relationship formation, have more challenges for both teachers and students. The prior studies found that online interaction affected social presence and indirectly affected learning engagement through social presence (Miao and Ma 2022 ). In the present investigation, both teachers and students noted the striking disadvantage of online interaction.

“Online learning has many problems such as indirect teacher-student communication, inactive informative communication, late response of students and their inability to reflect their problems. For example, teachers cannot evaluate correctly whether the students have mastered or not.” (YYN) “Teachers and students are separated by screens. The students cannot make prompt responses to the teachers’ questions via loudspeakers or headphones. It is not convenient for students to participate in questioning and answering. …for most of the time, the students interact with teachers via typing.” (ZJY) “While learning online, students prefer texting the questions to answering them via the loudspeaker.”(T7)

Online learning interaction was also found closely related to online learning engagement, performance, and self-efficacy.

“Teachers and students are unable to have timely and effective communication, which reduces the learning atmosphere. Students are often distracted. While doing homework, the students are unable to give feedback to teachers.” (YR) “Students are liable to be distracted by many other side matters so that they can keep their attention to online learning.” (T15)

In the online learning environment, teachers need to make efforts to build rapport and personalizing interactions with students to help them perform better and achieve greater academic success (Harper 2018 ; Ong and Quek 2023 ) Meanwhile, teachers should also motivate students’ learning by designing the lessons, giving lectures and managing the processes of student interactions (Garrison 2003 ; Ong and Quek 2023 ).

Determinants of self-efficacy in online learning

Online learning self-efficacy refers to students’ perception of their abilities to fulfill specific tasks required in online learning (Calaguas and Consunji 2022 ; Zimmerman and Kulikowich 2016 ). Online learning self-efficacy was found to be influenced by various factors including task, learner, course, and technology level, among which task level was found to be most closely related (Xu et al. 2022 ). The responses from the 46 student participants reveal a shared concern, albeit without mentioning specific tasks; they highlight critical aspects influencing online learning: learner attributes, course structure, and technological infrastructure.

One unifying theme from the student feedback is the challenge of self-regulation and environmental distractions impacting learning efficacy. For instance, participant WSX notes the necessity for students to enhance time management skills due to deficiencies in self-regulation, which is crucial for successful online learning. Participant WY expands on this by pointing out the distractions outside traditional classroom settings, coupled with limited teacher-student interaction, which hampers idea exchange and independent thought, thereby undermining educational outcomes. These insights suggest a need for strategies that bolster students’ self-discipline and interactive opportunities in virtual learning environments.

On the technological front, participants WT and YCY address different but related issues. Participant WT emphasizes the importance of up-to-date course content and learning facilities, indicating that outdated materials and tools can significantly diminish the effectiveness of online education. Participant YCY adds to this by highlighting problems with online learning applications, such as subpar functionalities that can introduce additional barriers to learning.

Teacher participants, on the other hand, shed light on objective factors predominantly related to course content and technology. Participant T5’s response underscores the heavy dependency on technological advancement in online education and points out the current inability of platforms or apps to adequately monitor student engagement and progress. Participant T9 voices concerns about course content not being updated or aligned with contemporary trends and student interests, suggesting a disconnect between educational offerings and learner needs. Meanwhile, participant T8 identifies unstable network services as a significant hindrance to online teaching, highlighting infrastructure as a critical component of online education’s success.

Teachers also believed the insufficient mastery of facilities and unfamiliarity with online instruction posed difficulty.

“Most teachers and students are not familiar with online instruction. For example, some teachers are unable to manage online courses so they cannot design the courses well. Some students lack self-regulation, which leads to their distraction or avoidance in class.” (T9)

Influences on student performance in online learning

Students’ performance during online lessons is closely associated with their satisfaction and self-efficacy. Most of the student participants reflected on their distractions, confusion, and needs, which indicates their dissatisfaction with online learning.

“During online instruction, it is convenient for the students to make use of cell phones, but instead, cell phones bring lots of distraction.” (YSC) “Due to the limits of online learning, teachers are facing the computer screen and unable to know timely students’ needs and confusion. Meanwhile, it’s inconvenient for teachers to make clear explanations of the sample questions or problems.” (HZW)

They thought their low learning efficiency in performance was caused by external factors like the learning environment.

“The most obvious disadvantage of online learning goes to low efficiency. Students find it hard to keep attention to study outside the practical classroom or in a relaxing environment.” (WY) “Teachers are not strict enough with students, which leads to ineffective learning.” (WRX)

Teacher participants conceived students’ performance as closely related to valid online supervision and students’ self-regulation.

“Online instruction is unable to create a learning environment, which helps teachers know students’ instant reaction. Only when students well regulate themselves and stay focused during online learning can they achieve successful interactions and make good accomplishments in the class.” (T11) “Some students need teachers’ supervision and high self-regulation, or they were easily distracted.” (T16)

Student satisfaction and teaching effectiveness in online learning

Online learning satisfaction was found to be significantly and positively associated with online learning self-efficacy (Al-Nasa’h et al. 2021 ; Lashley et al. 2022 ). Around 46% of student participants were unsatisfied with teachers’ ways of teaching.

“Comparatively, bloggers are more interesting than teachers’ boring and dull voices in online learning.” (DSY) “Teachers’ voice sounds dull and boring through the internet, which may cause listeners to feel sleepy, and the teaching content is not interesting enough to the students.” (MFE)

It reflected partly that some teachers were not adapted to online teaching possibly due to a lack in experience of online teaching or learning (Zhu et al. 2022 ).

“Some teachers are not well-prepared for online learning. They are particularly unready for emergent technological problems when delivering the teaching.” (T1) “One of the critical reasons lies in the fact that teachers and students are not well trained before online learning. In addition, the online platform is not unified by the college administration, which has led to chaos and difficulty of online instruction.” (T17)

Teachers recognized their inadequate preparation and mastery of online learning as one of the reasons for dissatisfaction, but student participants exaggerated the role of teachers in online learning and ignored their responsibility in planning and managing their learning behavior, as in the research of (Xu et al. 2022 ).

The role of self-regulation in online learning success

In the context of online learning, self-regulation stands out as a crucial factor, necessitating heightened levels of student self-discipline and autonomy. This aspect, as Zhu et al. ( 2023 ) suggest, grants students significant control over their learning processes, making it a vital component for successful online education.

“Online learning requires learners to be of high discipline and self-regulation. Without good self-regulation, they are less likely to be effective in online learning.” (YZJ) “Most students lack self-control, unable to control the time of using electronic products. Some even use other electronic products during online learning, which greatly reduces their efficiency in learning.” (GPY) “Students are not well developed in self-control and easily distracted. Thus they are unable to engage fully in their study, which makes them unable to keep up with others” (XYN)

Both groups of participants had a clear idea of the positive role of self-regulation in successful learning, but they also admitted that students need to strengthen their self-regulation skills and it seemed they associated with the learning environment, learning efficiency and teachers’ supervision.

“If they are self-motivated, online learning can be conducted more easily and more efficiently. However, a majority are not strong in regulating themselves. Teachers’ direct supervision in offline learning can do better in motivating them to study hard…lack of interaction makes students less active and motivated.” (LY) “Students have a low level of self-discipline. Without teachers’ supervision, they find it hard to listen attentively or even quit listening. Moreover, in class, the students seldom think actively and independently.” (T13)

The analysis of participant responses, categorized into three distinct attitude groups – positive, neutral, and negative – reveals a multifaceted view of the disadvantages of online learning, as shown in Tables 4 and 5 . This classification provides a clearer understanding of how attitudes towards online learning influence perceptions of self-regulation and other related factors.

In Table 4 , the division among students is most pronounced in terms of interaction and self-efficacy. Those with neutral attitudes highlighted interaction as a primary concern, suggesting that it is less effective in an online setting. Participants with positive attitudes noted a lack of student motivation, while those with negative views emphasized the need for better self-efficacy. Across all attitudes, instruction, engagement, self-regulation, and behavior intention were consistently identified as areas needing improvement.

Table 5 sheds light on teachers’ perspectives, revealing a consensus on the significance and challenges of instruction, motivation, and self-efficacy in online learning. Teachers’ opinions vary most significantly on self-efficacy and engagement. Those with negative attitudes point to self-efficacy and instructional quality as critical areas needing attention, while neutral attitudes focus on the role of motivation.

Discussions

Using a qualitative and quantitative analysis of the questionnaire data showed that among the 18 college teachers and 46 year 1 undergraduate students of various majors taking part in the interview, about 38.9% of teachers and about 30.4% of students supported online learning. Only two teachers were neutral about online learning, and 50% of teachers did not support virtual learning. The percentages of students who expressed positive and neutral views on online learning were the same, i.e., 34.8%. This indicates that online learning could serve as a complementary approach to traditional education, yet it is not without challenges, particularly in terms of student engagement, self-regulation, and behavioral intention, which were often attributed to distractions inherent in online environments.

In analyzing nine factors, it was evident that both teachers and students did not perceive these factors uniformly. Instruction was a significant element for both groups, as validated by findings in Tables 3 and 5 . The absence of face-to-face interactions in online learning shifted the focus to online instruction quality. Teachers cited technological challenges as a central concern, while students criticized the lack of engaging content and teaching methods. This aligns with Miao and Ma ( 2022 ), who argued that direct online interaction does not necessarily influence learner engagement, thus underscoring the need for integrated approaches encompassing interactions, self-regulation, and social presence.

Furthermore, the role of technology acceptance in shaping self-efficacy was highlighted by Xu et al. ( 2022 ), suggesting that students with higher self-efficacy tend to challenge themselves more. Chen and Hsu ( 2022 ) noted the positive influence of using emojis in online lessons, emphasizing the importance of innovative pedagogical approaches in online settings.

The study revealed distinct priorities between teachers and students in online learning: teachers emphasized effective instruction delivery, while students valued learning outcomes, self-regulation, and engagement. This divergence highlights the unique challenges each group faces. Findings by Dennen et al. ( 2007 ) corroborate this, showing instructors focusing on content and guidance, while students prioritize interpersonal communication and individualized attention. Additionally, Lee et al. ( 2011 ) found that reduced transactional distance and increased student engagement led to enhanced perceptions of learning outcomes, aligning with students’ priorities in online courses. Understanding these differing perspectives is crucial for developing comprehensive online learning strategies that address the needs of both educators and learners.

Integrating these findings with broader contextual elements such as technological infrastructure, pedagogical strategies, socio-economic backgrounds, and environmental factors (Balanskat and Bingimlas 2006 ) further enriches our understanding. The interplay between these external factors and Yu’s nine key aspects forms a complex educational ecosystem. For example, government interventions and training programs have been shown to increase teachers’ enthusiasm for ICT and its routine use in education (Balanskat and Bingimlas 2006 ). Additionally, socioeconomic factors significantly impact students’ experiences with online learning, as the digital divide in connectivity and access to computers at home influences the ICT experience, an important factor for school achievement (OECD 2015 ; Punie et al. 2006 ).

In sum, the study advocates for a holistic approach to understanding and enhancing online education, recognizing the complex interplay between internal factors and external elements that shape the educational ecosystem in the digital age.

Conclusion and future research

This study offered a comprehensive exploration into the retrospective perceptions of college teachers and undergraduate students regarding their experiences with online learning following the COVID-19 pandemic. It was guided by a framework encompassing nine key factors that influence online learning outcomes. To delve into these perspectives, the research focused on three pivotal questions. These questions aimed to uncover how both undergraduates and teachers in China view the effectiveness of online learning post-pandemic, identify which of the nine influencing factors had the most significant impact, and propose recommendations for enhancing the future effectiveness of online learning.

In addressing the first research question concerning the retrospective perceptions of online learning’s effectiveness among undergraduates and teachers in China post-COVID-19 pandemic, the thematic analysis has delineated clear divergences in attitude between the two demographics. Participants were primarily divided into three categories based on their stance toward online learning: positive, neutral, and negative. The results highlighted a pronounced variance in attitude distribution between teachers and students, with a higher percentage of teachers expressing clear-cut opinions, either favorably or unfavorably, towards the effectiveness of online learning.

Conversely, students displayed a pronounced inclination towards neutrality, revealing a more cautious or mixed stance on the effectiveness of online learning. This prevalent neutrality within the student body could be attributed to a range of underlying reasons. It might signify students’ uncertainties or varied experiences with online platforms, differences in engagement levels, gaps in digital literacy, or fluctuating quality of online materials and teaching methods. Moreover, this neutral attitude may arise from the psychological and social repercussions of the pandemic, which have potentially altered students’ approaches to and perceptions of learning in an online context.

In the exploration of the nine influential factors in online learning, it was discovered that both teachers and students overwhelmingly identified instruction as the most critical aspect. This was closely followed by engagement, interaction, motivation, and other factors, while performance and satisfaction were perceived as less influential by both groups. However, the attitudes of teachers and students towards these factors revealed notable differences, particularly about instruction. Teachers often attributed challenges in online instruction to technological issues, whereas students perceived the quality of instruction as a major influence on their learning effectiveness. This dichotomy highlights the distinct perspectives arising from their different roles within the educational process.

A further divergence was observed in views on self-efficacy and self-regulation. Teachers, with a focus on delivering content, emphasized the importance of self-efficacy, while students, grappling with the demands of online learning, prioritized self-regulation. This reflects their respective positions in the online learning environment, with teachers concerned about the efficacy of their instructional strategies and students about managing their learning process. Interestingly, the study also illuminated that students did not always perceive themselves as independent learners, which contributed to the high priority they placed on instruction quality. This insight underlines a significant area for development in online learning strategies, emphasizing the need for fostering greater learner autonomy.

Notably, both teachers and students concurred that stimulating interest was a key factor in enhancing online learning. They proposed innovative approaches such as emulating popular online personalities, enhancing interactive elements, and contextualizing content to make it more relatable to students’ lives. Additionally, practical suggestions like issuing preview tasks and conducting in-class quizzes were highlighted as methods to boost student engagement and learning efficiency. The consensus on the importance of supervisory roles underscores the necessity for a balanced approach that integrates guidance and independence in the online learning environment.

The outcomes of our study highlight the multifaceted nature of online learning, accentuated by the varied perspectives and distinct needs of teachers and students. This complexity underscores the necessity of recognizing and addressing these nuances when designing and implementing online learning strategies. Furthermore, our findings offer a comprehensive overview of both the strengths and weaknesses of online learning during an unprecedented time, offering valuable insights for educators, administrators, and policy-makers involved in higher education. Moreover, it emphasized the intricate interplay of multiple factors—behavioral intention, instruction, engagement, interaction, motivation, self-efficacy, performance, satisfaction, and self-regulation—in shaping online learning outcomes. presents some limitations, notably its reliance on a single research method and a limited sample size.

However, the exclusive use of reflective diaries and interviews restricts the range of data collection methods, which might have been enriched by incorporating additional quantitative or mixed-method approaches. Furthermore, the sample, consisting only of students and teachers from one university, may not adequately represent the diverse experiences and perceptions of online learning across different educational contexts. These limitations suggest the need for a cautious interpretation of the findings and indicate areas for future research expansion. Future research could extend this study by incorporating a larger, more diverse sample to gain a broader understanding of undergraduate students’ retrospections across different contexts and cultures. Furthermore, research could also explore how to better equip students with the skills and strategies necessary to optimize their online learning experiences, especially in terms of the self-regulated learning and motivation aspects.

Data availability

The data supporting this study is available from https://doi.org/10.6084/m9.figshare.25583664.v1 . The data consists of reflective diaries from 46 Year 1 students from a comprehensive university in China and 18 college teachers. We utilized thematic analysis to interpret the reflective diaries, guided initially by nine factors. The results highlight the critical need for tailored online learning strategies and provide insights into its advantages and challenges for stakeholders in higher education.

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Su, Y., Xu, X., Zhang, Y. et al. Looking back to move forward: comparison of instructors’ and undergraduates’ retrospection on the effectiveness of online learning using the nine-outcome influencing factors. Humanit Soc Sci Commun 11 , 594 (2024). https://doi.org/10.1057/s41599-024-03097-z

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Review article, applying best practice online learning, teaching, and support to intensive online environments: an integrative review.

• 1 Monash Online-Psychology Education Division (MO-PED), Faculty of Medicine, Nursing and Health Sciences, School of Psychological Sciences, Monash University, Clayton, VIC, Australia
• 2 Melbourne Centre for the Study of Higher Education, The University of Melbourne, Melbourne, VIC, Australia
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Demand for flexible online offerings has continued to increase as prospective students seek to upskill, re-train, and undertake further study. Education institutions are moving to intensive modes of online study delivered in 6- to 8-week study periods which offer more frequent intake periods. Prior literature has established key success factors for non-intensive (12–13 weeks) online offerings; for teachers, skill development is critical to promote a flexible, responsive approach and maintain technological capabilities; for students, an ability to navigate the technology, interact with the learning environment in meaningful ways, and self-regulate learning is important, as the absence of physical infrastructure and opportunities for face-to-face interactions in online environments places a greater emphasis on alternate forms of communication and support. The current paper explores known best practice principles for online instructors, students, and student support and considers how these might apply to intensive online environments. It is suggested that the accelerated nature of learning in intensive settings may place additional demands on students, instructors, and support mechanisms. Further research is imperative to determine predictors of success in online intensive learning environments.

The scope and availability of online offerings continues to expand globally. Demand for more intensive, short-term courses that provide opportunities for up-skilling has increased in the wake of massive open online courses (MOOCs), and this increased demand has in turn expanded the availability of online degree programs. As many as six million students in the USA were undertaking online education in 2015, with nearly five million of these students studying an undergraduate college (tertiary) qualification ( Allen and Seaman, 2017 ). Similar trends have been noted in the Australian context. Recent scoping reports of the Australian Higher Education sector have highlighted continual, rapid growth in online enrollments, but also a degree of “blurring” of boundaries, due to the increased adoption of technologies to support the on-campus learning experience ( Norton and Cherastidtham, 2014 ; Norton and Cakitaki, 2016 ). Changes to Australian funding policy have also enabled more public universities to invest in online offerings ( Kemp and Norton, 2014 ), contributing to the continuing growth of this sector.

Online modes of study have been found to be equivalent to on-campus environments with respect to key outcomes such as student academic performance ( Magagula and Ngwenya, 2004 ; McPhee and Söderström, 2012 ) and student satisfaction ( Palmer, 2012 ). However, online offerings also pose some key differences to on-campus modes of study. Accessing course materials online allows unprecedented levels of flexibility and accessibility for students from around the world and overcomes geographical barriers that might prevent students accessing on-campus course offerings ( Brown, 1997 , 2011 ; Bates, 2005 ). The nature of the online education environment also means that course delivery needs to compensate for the lack of immediate physical infrastructure, relying more heavily on asynchronous methods of communication. There is also emerging evidence that online student cohorts differ from on-campus cohorts with respect to factors such as age and work or family commitments ( Bailey et al., 2014 ; Johnson, 2015 ), which also speaks to the demand for more flexible, career-driven online offerings. The requirements of online students as a distinct demographic are another factor for consideration when planning and developing an online course. Furthermore, from a course development perspective, there is increasing understanding that developing online courses is more complex than merely translating written materials to an online format; it requires careful planning and maximization of available online technologies to cater for a variety of individual differences, student timetables and external commitments, and assessment modes (e.g., Rovai, 2003 ; Grant and Thornton, 2007 ; Rovai and Downey, 2010 ). Online learning does not only differ for students but also carries implications for instructors. Online instruction places varying demands on delivery and feedback methods and relies on different teacher knowledge and skills than face-to-face tuition ( Alvarez et al., 2009 ). It is evident that a sensitive approach catering to both similarities and differences of both modes of study is warranted.

With the abovementioned differences between on-campus and online education in mind, there is a duty for online education providers to continue to research and implement best practice for online modes of study. As fully online offerings continue to develop, new modes of delivery necessitate continual adjustment and evaluation to ensure that courses meet student needs. One such development is the move toward intensive mode courses. Intensive online degree courses (hereafter referred to as “intensive online courses”) are those in which students complete a degree entirely online, within an accelerated timeframe compared to the typical on-campus learning experience. Units of study are also delivered in shorter timeframes than the traditional (in an Australian context) 12- or 13-week semester, sometimes comprising 6 or 8 weeks of intensive learning, where a similar amount of material is covered compared with a semester structure. Students typically complete one unit at a time (as compared to four units concurrently for a traditional on-campus semester). Intensive online degree programs have built on the success of MOOCs to help upskill, and in some cases provide certified professional development, over a faster timeframe than typical on-campus university courses ( Laurillard, 2016 ). MOOCs aside, the literature base on intensive online learning for degree programs in particular remains limited. With the potential for tertiary institutions to move more toward this mode of offering, which provides for increased student intake to meet growth demands, there is a need to more comprehensively evaluate the factors that contribute to student and instructor success in an intensive online learning environment. The present integrative review aims to bring together acknowledged best practices in online education, with a view to considering how these may apply in an intensive online education environment. In particular, the elements that comprise a successful online experience for instructors and students, and the provision of student support and well-being services are considered.

Online Teaching: Critical Factors

As online modes of study continue to expand, there is increasing awareness of the need for competent online instructors. Developing institutional competence for online instruction requires a careful approach to training online instructors and a workload investment in staff training and development ( Gregory and Lodge, 2015 ). While it is acknowledged that face-to-face teaching competencies such as knowledge of curricula and pedagogy do transfer to online contexts, it is also important to recognize the unique competencies required for online teaching success, and the role of institutions in setting instructor duties and responsibilities ( Alvarez et al., 2009 ). Despite much prior research attention exploring the notion of online student readiness, online instructor readiness is now emerging as an equally important construct ( Oomen-Early and Murphy, 2009 ).

There is consensus in prior literature that effective online instruction requires a more flexible approach to skill development, due to the variety of roles and skills applied in online contexts ( Bawane and Spector, 2009 ). Key environmental differences between online and on-campus learning environments also necessitate the development of different online teaching competencies. A sample of existing frameworks for teacher competencies in online education is summarized in Table 1 below.

Table 1 . Established teacher competency frameworks in online education.

The ability to effectively communicate, manage technology, and deliver and assess content becomes especially important in intensive online environments, where there is less available time to acclimatize to new tools and operating environments. The monitoring of student progress, identification, and follow-up of issues or barriers are also critical duties for instructors to minimize the likelihood of student disengagement or withdrawal.

Online learning systems employ a variety of online tools, systems, and software, which place new demands on the technical competence of instructors ( Volery and Lord, 2000 ). Modes of communication also differ in online courses, with a greater reliance on asynchronous communication methods ( Hung et al., 2010 ). Live, “virtual” classrooms may also involve remote but instant methods of feedback between student and instructor, facilitated through live chat, video/webcam interactions, and small-group “break-out rooms.” The development of student rapport also differs in online contexts, and the nature of how rapport is initiated and maintained in online settings is not always easily comparable to face-to-face teaching. Naturally, assessment and feedback are also delivered in different ways via asynchronous methods when teaching online. Clear assessment practices, including communication of deadlines and assessment requirements, have been found to positively influence student engagement and course completion ( Thistoll and Yates, 2016 ).

Institutional and research-based efforts to characterize the competencies required for effective online instruction (e.g., Goodyear et al., 2001 ; Dennis et al., 2004 ; Darabi et al., 2006 ; International Board of Standards for Training, Performance and Instruction, http://ibstpi.org/ , as cited in Beaudoin, 2015 ) suggest a degree of overlap in the conceptualization of the core teacher competencies required for effective online instruction. Some of the most important online teacher competencies drawn from the aforementioned studies include:

• communication skills;

• technological competence;

• provision of informative feedback;

• administrative skills;

• responsiveness;

• monitoring learning;

• providing student support.

Without adequate technological skills, instructors risk being unable to resolve technology-related problems during live class, which may impact student access to learning materials. Communication skills are also paramount ( Easton, 2003 ). Effective instructor–student communication in online learning environments relies on timely and clear interactions through a variety of formats ( Easton, 2003 ), including email, chat, live class questions, and assessment and feedback provision. In the absence of more immediate feedback methods available to on-campus instructors (e.g., face-to-face consultation), the assessment and feedback provided in online learning environments needs to be as clear and valuable as possible to promote student understanding ( Darabi et al., 2006 ). Teacher support online involves effective monitoring of student progress, anticipation and resolution of key learning queries, and establishment and maintenance of rapport. Collectively, these kinds of competencies shape the effectiveness of online instructors and, in turn, the student experience. While these elements are well established as effective practice in online tuition, there exists significantly more pressure on these factors when content delivery, assessment, feedback, and communication occur within a condensed 6- to 8-week timeframe.

In addition to student-related benefits, there is evidence that online instructor training can provide benefits to instructors themselves ( Roblyer et al., 2009 ). These benefits occur both through expansion of direct skills for the instructor (i.e., professional development) to build confidence in online environments, and also through skills that are transferable to on-campus contexts ( Roblyer et al., 2009 ), providing a wider institutional benefit. Roblyer et al. (2009) note a kind of “reverse impact phenomenon” whereby teachers have experienced transferred skills improvements in face-to-face tuition by enhancing online teaching skills. While these authors based the outcomes around K-12 teachers, it is likely that the gains experienced by teachers (e.g., improved self-reflection on teaching and assessment methods; increased sensitivity toward student needs) would be similarly relevant to on-campus tertiary teachers. It is also important, however, to consider the environmental challenges posed by more intensive teaching timeframes. Instructors delivering content in shorter blocks of time have less time to reflect on, adapt and amend content before the next unit delivery, and thus unit re-design and content development can be more of a challenge in intensive online environments.

Effective online instructors have a direct and important role in influencing the student experience, since instructors are often the “face” of an online course. Prior studies have emphasized instructor presence as among the most critical of factors related to student success online ( Easton, 2003 ; Menchaca and Bekele, 2008 ; Kennette and Redd, 2015 ; Kim and Thayne, 2015 ). In the absence of the richness of interactions available to on-campus students, instructors become an even more important “ingredient” in helping to engage, retain, and graduate online students. Instructors also play a key role in motivating students throughout their online study ( Bolliger and Martindale, 2004 ), since instructors may commonly be the only personalized point of contact provided to students at any one time. Instructor responsiveness and availability has been highlighted as a key predictor of online student satisfaction, in that lack of timely feedback or slow communication timeframes from instructors detract from student satisfaction online ( Bolliger and Martindale, 2004 ). It is apparent that development of instructor training is a critical component of effective institutional preparation for wholly online courses, so that teachers can develop the range of skills required to teach online successfully.

When considering the applicability of teacher competencies to an intensive online environment, it is reasonable to assume that the faster-paced nature of intensive learning may require greater competence with respect to certain instructor skills. The building of teacher competencies is a process that requires institutional planning and reflection when considering a move to more intensive online degree offerings, so that instructors are supported to flourish and students can benefit from quality instruction. The Technological Pedagogical Content Knowledge (TPACK) model proposed by Mishra and Koehler (2006) (see Figure 1 below) provides a useful framework through which to view teacher competencies across multiple levels, and we can apply this model to consider teacher skills in intensive online environments.

Figure 1 . The Technological Pedagogical Content Knowledge (TPACK) model ( Mishra and Koehler, 2006 ). Reproduced by permission of the publisher, © 2012 by tpack.org .

The TPACK model promotes meaningful integration of technology, content knowledge, and pedagogy ( Mishra and Koehler, 2006 ). Thus, an instructor’s ability to utilize technology as the basis for timely, responsive and clear feedback becomes even more critical in an intensive online environment, which can be further exacerbated by a lack of time to resolve technical issues or system access problems. Since technology is inherently embedded in content delivery and influential in approaches to teaching, technical competence must also be highlighted alongside content proficiency and pedagogical knowledge for instructors seeking to teach online, especially in intensive environments. It is apparent that the demands on all of these skill areas are likely to be heightened in an intensive delivery setting, and further research to understand the nature of any additional skill demands in intensive online environments would be valuable.

Online Learning: Critical Factors

Effective approaches to online education must also take account of baseline learner competencies and characteristics. Demographically, there are consistent differences between on-campus and online students ( Bailey et al., 2014 ). For instance, more women than men appear to choose online modes of study ( Price, 2006 ). Further, online learners are typically older than on-campus students, with many being “mature-age” students between the ages of 25 and 50 ( Moore and Kearskey, 2005 ). This also presents a rich opportunity to enhance the learning environment through incorporation of some of the life experiences of older learners online ( Boston and Ice, 2011 ; O’Shea et al., 2015 ). Greenland and Moore (2014) also noted the potential for unexpected work commitments and/or busy work schedules to contribute to student intermissions and discontinuations.

With regard to factors that influence student choice to study online, there is evidence that students opting to study online choose flexibility (i.e., convenience) over the perceived value of studying on-campus ( Bolliger and Martindale, 2004 ). This flexibility is likely to be prioritized due to many online students being at a later life stage than younger on-campus students, whereby study must be accommodated around work and family commitments. However, the source of a requirement for flexibility also brings with it additional complications: factors such as age, gender, educational history, work obligations, and family commitments have all been found, in turn, to impact on completion rates in tertiary education settings ( Tsay et al., 2000 ; Colorado and Eberle, 2010 ).

Becoming an online learner places different demands on students. The fundamental quality and nature of the student experience shifts in online learning environments to a greater reliance on asynchronous modes of communication. Interactions also occur through a variety of methods, including learner-to-content, learner-to-instructor, and learner-to-learner (peer) interaction ( Bolliger and Martindale, 2004 ). This necessitates a more proactive, self-directed approach on the part of students ( Brown, 1997 ; Tsay et al., 2000 ; Khiat, 2015 ; Kırmızı, 2015 ). Self-regulated learning, where students use meta-cognitive skills to plan, implement, and reflect on their learning, have been increasingly associated with better academic achievements ( Johnson, 2015 ; Khiat, 2015 ). Active engagement in academic materials, and with instructors and peers, has been emphasized as a core component of successful learning for students ( Pascarella and Terenzini, 2005 ). In one study, lack of social interaction was found to be the largest single barrier to student success online ( Muilenburg and Berge, 2005 ). Meaningful connections with the institution are a key ingredient in student engagement ( Pascarella and Terenzini, 2005 ).

However, not all of the responsibility for effective engagement in online courses lies with the student. There is an institutional and faculty responsibility to create an inclusive, supportive structure where students can engage in social interactions and a sense of (online) community can be fostered, as has been apparent in research findings from Garrison and colleagues in applying and extending the Community of Inquiry model (e.g., Garrison et al., 2000 ; Aragon, 2003 ; Garrison and Cleveland-Innes, 2005 ; Garrison and Arbaugh, 2007 ) (see Figure 2 below).

Figure 2 . Community of Inquiry model ( Garrison et al., 2000 ). Reproduced with permission from the author.

This sense of belonging is a key component that impacts student engagement and can act as a buffer against attrition ( Oomen-Early and Murphy, 2009 ). As well as understanding and promoting the factors that can enhance belonging in an online community, faculty also have a responsibility to monitor student progress and address any early signs of difficulty or disengagement ( Beaudoin, 2002 ; Dennen, 2008 ).

A number of factors and situations can act as barriers to effect student engagement in online study, and online environments have long been known to face higher attrition rates than on-campus modes of study ( Oomen-Early and Murphy, 2009 ). Many of these elements stem from the unique challenges and opportunities of online learning environments discussed above:

• technical difficulties;

• perceived isolation;

• challenges balancing study;

• work and family commitments;

• confusion with content;

• poor academic performance; or

• lack of motivation.

Thus, understanding how best to gauge student readiness or preparedness for online study is a critical institutional responsibility. A range of recent studies have sought to characterize the main factors underlying readiness for online study ( Vonderwell, 2004 ; Watkins et al., 2004 ; Pillay et al., 2007 ; Mercado, 2008 ; Dray et al., 2011 ; Farid, 2014 ; Wladis et al., 2016 ). Collectively, these studies emphasize the importance of technical skills, effective time management, individual differences (especially self-directed or self-regulated learning), financial means, and online self-efficacy as elements of readiness. A range of measures have also been developed and validated to assess student readiness for online learning ( Kerr et al., 2006 ; Mercado, 2008 ; Hung et al., 2010 ; Dray et al., 2011 ), but there is scope in future research to consider the notion of student readiness more directly, as it relates to readiness for intensive online learning. In this mode, one could argue that there is an increased responsibility for faculty to screen students on commencement, to pre-empt and remedy potential barriers to a successful online study experience. Further, a more holistic approach to defining student readiness that encompasses key psychological, technological, situation, and learning-related contributors to readiness for intensive online study is recommended.

Intensive online courses are likely to involve many of the same benefits and challenges for students as non-intensive courses. However, it is of note that the faster pace of the learning environment inherent in intensive courses means that both students and instructors have less time to address any key concerns, provide remedial support, or rectify any unintended technical or learning delays. Thus, the process of monitoring student progress and potential barriers is paramount in intensive online learning environments.

Online Environment: Student Support and Well-Being Services

Consideration of student support services becomes paramount in intensive online environments, where disruptions to technology or lack of support services can pose a significant barrier to student engagement in learning. Students completing courses wholly online are often limited in their access to the entire variety of support services a university offers, compared to their on-campus counterparts ( Lee, 2010 ). The “four pillars” of supporting student success (see Figure 3 below) are often the intangibles that educators might take for granted when providing fully online courses. These pillars include online-friendly academic supports ( Coonin et al., 2011 ; Huwiler, 2015 ), assistance with navigating technology ( Lee, 2010 ), health and well-being facilities ( Anderson, 2008 ), and a sense of belongingness, or community ( Kumar and Heathcock, 2014 ).

Figure 3 . The “four pillars” to supporting student success.

Ensuring a positive and rewarding experience for online students, particularly those enrolled within intensive online courses, is contingent upon the institutional provider offering equitable support structures that are also appropriately translated into the online environment ( Pullan, 2011 ). Being already prone to higher attrition rates, fully online students adopting study via intensive modes have increased expectations of their instructors, and the course learning environment more broadly, to provide the necessary infrastructure required to manage the increased workload. Therefore, tertiary providers choosing to deliver fully online courses, particularly intensive courses, need to ensure that these four pillars are prioritized equivalently to the translation of content into online platforms in order to maximize student success and reduce risks for attrition.

The first pillar, and arguably the most crucial support an institution can offer to online students, revolves around online-friendly academic resources and ample opportunities for student–instructor interaction ( Cannady, 2015 ). The success of completing a tertiary degree online strongly depends on the student’s ability to work autonomously and manage their time effectively ( Wang et al., 2013 ). Beyond the personal qualities students must possess to succeed in an online course, as previously discussed, there is also a growing need for the institution offering the course to provide appropriate online-friendly academic scaffolding that supports their students throughout their learning ( Lee and Choi, 2011 ). This includes, but is not limited to, detailed orientation services, and comprehensive library resources.

Providing orientation services, especially for online students, is essential in order to adequately integrate incoming cohorts into their new online learning environment ( Cho, 2012 ). Research, albeit limited, has consistently shown that orientation programs have improved student retention and academic performance both on- and off-campus ( House and Kuchynka, 1997 ; Williford et al., 2001 ; Wilson, 2005 ). When looking specifically at online courses, the factors that contribute to a successful orientation include comprehensive overviews of the course structure, recommended time commitments and expectation of students, familiarization with required instructional media and software, and guidance on the communication tools needed for student–staff interactions. Delivering this information in an online environment requires a substantial rethink of the way in which these programs are designed ( Smyth and Lodge, 2012 ). Despite the challenges, providing these resources before a student commences their course has been shown to be critical for reducing early drop-out rates, increasing self-confidence, and enhancing the students’ sense of belonging ( Tomei et al., 2009 ). However, many institutions that offer online courses do not make their orientation program mandatory before commencement, while some choose not to deliver an orientation program at all. In fact, one study has suggested up to 29% of institutions only offer on-campus orientation programs, despite also offering fully online courses ( Cannady, 2015 ), perhaps due to the difficulty in developing effective online orientation. This rate is particularly concerning given there is strong evidence to show that comprehensive orientation programs are vital to supporting online student success.

Comprehensive, course-specific resources created to improve students’ academic performance are also pivotal to student success, and are best delivered when strong collaborations between online instructional staff and the institution’s librarians are prioritized ( Arnold et al., 2002 ; Kumar and Heathcock, 2014 ). Many university libraries provide an abundance of resources that assist new students transitioning into tertiary life ( Arnold et al., 2002 ). However, if online course providers are unaware of the technological and/or literacy competencies of their students, these library resources may not be properly disseminated to incoming cohorts. This is problematic for fully online courses, particularly those offered in intensive modes where demands are greater, if the only exposure to their institution required is via their course’s learning management system (LMS). Targeted training programs and easy access to comprehensive resources available online is therefore vital to improving student success in intensive online learning environments; simply providing generic resources via a course’s LMS without proper instruction may not be sufficient to meet online student needs ( Kumar and Heathcock, 2014 ). It is important that instructors gauge their student’s competencies before commencing the course so that any necessary gaps, particularly those easily fulfilled with existing library resources, can be addressed appropriately.

The second pillar, yet one of the most immediate and unique hurdles for online students, is the need to provide adequate technical scaffolding in order to prepare students for learning in an online-only environment ( Shea et al., 2005 ). Tertiary institutions offering fully online courses need to assure that all technology requirements are clearly communicated to students before commencing the course, and that ongoing technical support is provided to reduce delay in meeting course expectations. This is particularly important for intensive modes of online study where assessment deadlines leave little to no room for technical-based hurdles. The strong relationship between a student’s acceptance of technology and their perceived satisfaction with online courses is also important to consider, as this may pose additional hurdles to incoming cohorts unaccustomed to learning in an online environment ( Lee, 2010 ). As emphasized earlier in this review, where students or instructors lack the required technical competence, this can pose a significant and sometimes insurmountable barrier, contributing to student discontinuation or disengagement from the course. Thus, adopting a user-friendly learning environment and flexible online technical support is critical for intensive online courses in order to increase student retention and engagement.

Beyond the need to overcome technological obstacles are the pressures of academic achievement, transitioning to university life and time management; all which benefit from the third pillar that is health and well-being support. These factors create increasing stress among students, both on- and offline ( Robotham and Julian, 2006 ). University student cohorts have been found to have concerning rates of mental health issues ( Andrews and Wilding, 2004 ; Bayram and Bilgel, 2008 ; Hjeltnes et al., 2015 ), and online student cohorts, particularly those adjusting to intensive study modes, face comparable challenges. In response, several efforts have been made by universities to support students and promote positive mental health and well-being in an attempt to combat increasing psychological distress ( Regehr et al., 2013 ). One example is the effort to extend support programs to online students which are already available to on-campus students, such as personal counseling and career services ( Dare et al., 2005 ; Lapadula, 2010 ). However, this solution often does not account for the many online students who are not in the required geographical district needed to access these services, in person or via phone.

One potential solution to the geographical hurdle is for institutions to invest in online counseling or self-help services, to reach beyond their usual audience who utilize traditional face-to-face services ( Tokatlidis et al., 2011 ). This option holds promise as a means of creating services with sufficient flexibility to allow access for students from a diverse range of locations. Another wide-reaching strategy demonstrating increasing efficacy among university students is mindfulness. In recent years, mindfulness—the practice of bringing attention to the present moment, non-judgementally—has substantially grown in popularity, particularly within education contexts where research has shown that mindfulness can benefit students experiencing high rates of psychological distress ( Cavanagh et al., 2013 ). The efficacy of mindfulness-based practices within primary and secondary schools ( Zenner et al., 2014 ), as well as at tertiary level ( Regehr et al., 2013 ), has been well documented and shows promising results in improving resilience against common student-related stressors. The benefits of advancing technology has also seen an increasing number of online mindfulness programs rolled out, which have positive implications for the growing popularity of fully online tertiary courses ( Sable, 2010 ). Yet despite this, the benefits of integrating online mindfulness-based practices into completely online courses is scarcely researched. The need for evidence-based interventions and prevention strategies is especially crucial given that literature suggests around 50% of university students experience significant levels of psychological distress while enrolled ( Regehr et al., 2013 ). Provision of psychological services is made more difficult for online students who may not otherwise have access to any other form of mental health support ( Lapadula, 2010 ). Therefore, more research is required into appropriate prevention and intervention strategies for high rates of distress among students involved in intensive online learning, given the added pressures they face with shorter course deadlines and being physically segregated from their peers.

The last pillar required to support student success comes with prioritizing a sense of belongingness and community to any fully online cohort. Fostering open dialog between students, instructors, and their fellow classmates is essential to online learning which can often be taken for granted during the implementation of online courses ( Coomey and Stephenson, 2001 ). As alluded to earlier in this review, online students require personalized, timely feedback on assessments ( Li and Beverly, 2008 ; Lee, 2010 ), equivalent community-like interactions with peers via social networking platforms such as Facebook and Twitter ( Roblyer et al., 2010 ; Akcaoglu and Bowman, 2016 ; Tang and Hew, 2017 ), and ideally 24-h academic and technical support services ( Lorenzo and Moore, 2002 ) in order to succeed in online learning. In particular, research has identified that adequate quality and quantity of interaction between a student and their instructor is associated with increased student course satisfaction ( Lee, 2010 ; Ralston-Berg et al., 2015 ). Therefore, it is necessary for institutions to prioritize offering effective means for communication within the online learning environment, not bound by physical or geographical segregation. For example, one study has suggested that the use of asynchronous activities, such as introducing yourself via video posts and conducting online discussion forums, may be useful in combatting the issues of isolation and lack of a “sense of community” commonly found among online students ( Trespalacios and Rand, 2015 ). Given the shorter timeframe required for students to meet course deadlines via intensive modes, it becomes critical that students feel continuously supported, and that this support is fostered by the infrastructure of their online learning environment. Further research has also suggested that there are benefits to including students and instructors’ input into the development and implementation of online courses, which can assist in keeping students engaged and thus achieve success ( Roby et al., 2013 ). Each of these pillars, particularly when equally prioritized in fully online course delivery, ultimately best equip students to succeed in their course from orientation through to graduation.

Summary: Applications to Intensive Online Learning Environments

In reflecting on the discussion points raised in the current review, it is apparent that online environments and intensive online environments are likely to share many “ingredients” in common. Both contexts share similar modes of communication, structures, learning materials and methods, assessment principles, and skills requirements of both instructors and students. Nevertheless, the compressed timeframes involved in intensive online learning mean that the reliance on effective communication, technology, learning, and feedback strategies increases, and the corresponding demands on teacher and learner competencies are higher.

Instructor presence remains a critical factor in all modes of online study, and particularly so in intensive online environments, where instructors need to work to establish and maintain student engagement. Pedagogical approaches need to account for learner competencies, characteristics, and preferred learning approaches. This is especially important given the emerging demographic differences between online and on-campus cohorts. Intensive online learning environments should take account of potential barriers that can lead to increased attrition, such as perceived isolation, competing work/family commitments, poor motivation, lack of engagement with content, and technical challenges. There are particular time pressures evident in an intensive online course when needing to identify and rectify such barriers, and regular monitoring of student progress can help to quickly identify and address potential concerns. Providing comprehensive orientation services is key to ensure students are adequately informed and linked to ongoing support services. Communication plays a pivotal role in enhancing the online learning experience through peer-to-peer and student-to-instructor dialog. Ongoing flexible technical support is also vital to manage any technical issues that arise. Finally, well-being services and the provision of online well-being content such as mindfulness resources are important steps toward the prevention of online student mental health concerns.

On a more general note, a flexible and responsive approach to all activities is critical in intensive online environments. Where there are student or instructor skills gaps, it becomes more time-critical to identify and address these, or potential barriers can become a greater risk of student attrition. Likewise, if students are not able to adopt a proactive approach to time management and prioritize study deadlines, the risk of overwhelm and stress increases. Academically, understanding key content and successfully completing assessment tasks becomes of greater importance in the intensive online environment. Future research would benefit from understanding any specific factors related to student and instructor readiness for intensive online study, so that institutions adopting intensive study modes can provide the maximum chance of a successful experience for all involved.

It is apparent that intensive online courses offer a range of benefits to students and staff, including accessibility, opportunities for embracing new technologies, and promoting independent, self-regulated learning. These benefits need to be considered alongside some of the known barriers associated with online education; potential student disengagement, work-life balance difficulties for students working full-time, and technological challenges for both students and instructors. It is imperative to continue to monitor and meet student needs that are particular to the online environment, so that online courses can adapt to changing future needs. With the move for tertiary institutions to consider more intensive modes of online degree study comes an increased responsibility to understand how best to prepare students, instructors, and student support mechanisms to succeed in intensive online learning environments. Consideration of the factors discussed in the current review will guide institutions and educators to maximize student success in intensive online courses as this sector continues to rapidly evolve. Future research is well positioned to continue deepening understanding of best practice as it applies to intensive online education.

Author Contributions

CR wrote and refined the introductory, instructor- and student-focused, and conclusion sections of the review. DA wrote and refined the component relating to student support and well-being. All team members were involved in publication planning, reading of drafts and suggestions for changes, and feedback on the final publication draft. SM, MM, and JL were additionally involved in providing strategic advice on directions for the paper, and the role of the paper within the research team agenda.

Conflict of Interest Statement

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.

Acknowledgments

The authors wish to thank Professor Kim Cornish and Associate Professor Matthew Mundy for supporting the creation of the Monash Online – Psychology Education Division (MO-PED) team and associated research outputs. The authors also wish to acknowledge funding support supplied via the Monash Pearson Alliance. The team also wishes to thank Leah Braganza and Tony Mowbray for their time in providing feedback on the draft manuscript.

Completion of the current review was funded by the School of Psychological Sciences, Faculty of Medicine Nursing and Health Sciences, Monash University.

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Keywords: online education, intensive online learning, student experience, teacher education, higher education

Citation: Roddy C, Amiet DL, Chung J, Holt C, Shaw L, McKenzie S, Garivaldis F, Lodge JM and Mundy ME (2017) Applying Best Practice Online Learning, Teaching, and Support to Intensive Online Environments: An Integrative Review. Front. Educ. 2:59. doi: 10.3389/feduc.2017.00059

Received: 16 August 2017; Accepted: 26 October 2017; Published: 21 November 2017

Reviewed by:

Copyright: © 2017 Roddy, Amiet, Chung, Holt, Shaw, McKenzie, Garivaldis, Lodge and Mundy. 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) or licensor 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: Chantal Roddy, chantal.roddy@monash.edu

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Persistence and Dropout in Higher Online Education: Review and Categorization of Factors

Online learning is becoming more popular with the maturity of social and educational technologies. In the COVID-19 era, it has become one of the most utilized ways to continue academic pursuits. Despite the ease and benefits offered by online classes, their completion rates are surprisingly low. Although several past studies focused on online dropout rates, institutions and course providers are still searching for a solution to this alarming problem. It is mainly because the previous studies have used divergent frameworks and approaches. Based on empirical research since 2001, this study presents a comprehensive review of factors by synthesizing them into a logically cohesive and integrative framework. Using different combinations of terms related to persistence and dropout, the authors explored various databases to form a pool of past research on the subject. This collection was also enhanced using the snowball approach. The authors only selected empirical, peer-reviewed, and contextually relevant studies, shortlisting them by reading through the abstracts. The Constant Comparative Method (CCM) seems ideal for this research. The authors employed axial coding to explore the relationships among factors, and selective coding helped identify the core categories. The categorical arrangement of factors will give researchers valuable insights into the combined effects of factors that impact persistence and dropout decisions. It will also direct future research to critically examine the relationships among factors and suggest improvements by validating them empirically. We anticipate that this research will enable future researchers to apply the results in different scenarios and contexts related to online learning.

Introduction

Higher education is increasingly embracing online courses ( Seaman et al., 2018 ; Johnson et al., 2019 ), mainly inspired by the demands of learners and budgetary constraints ( Limperos et al., 2015 ). The popularity of online courses in the United States has increased significantly over the last two decades (see Figure 1 ), and there was a total of 6,359,121 distance learners as of Fall 2016 ( Seaman et al., 2018 ). Similarly, more than 76% of colleges and universities in Canada offer online courses in 2019, and the proportion has risen to 92% of institutions with over 7,500 students and 93% of universities ( Johnson et al., 2019 ). Online classes are considered effective as their face-to-face counterparts ( Kumar et al., 2019 ). Students enroll in online courses to accomplish their own personal and professional goals. A greater degree of flexibility and unrestricted digital access to large volumes of information is compelling and accounts for the widespread popularity of enrolment in online courses ( Sitzmann et al., 2006 ; Zimmerman, 2012 ). Accessibility to online courses empowers learners to structure their classes alongside other family and work commitments, which may not be possible otherwise ( Lee, 2017 ). Also, the ongoing pandemic of COVID-19 has heavily impacted students, instructors, and educational organizations worldwide ( Almanthari et al., 2020 ). The instructors moved their courses online, and the students remained at home in response to social distancing measures ( Toquero, 2020 ). During these times, online learning became the most utilized way to continue academic activities globally, and experts began to consider it a viable alternative to face-to-face education ( Kaur, 2020 ). Higher education institutes quickly adopted the online delivery of education, incorporating media and technology ( Rahmat et al., 2022 ). They realized the need to develop and strengthen their capacity to achieve the desired results ( Maqsood et al., 2021 ).

Rise in online learning in the United States.

Problem Statement

Despite the massive growth, persistence rates of online courses are significantly low ( Xavier and Meneses, 2020 ) compared to those offered in person ( Muljana and Luo, 2019 ; Delnoij et al., 2020 ). Online learners struggle to complete their courses ( Friðriksdóttir, 2018 ) and attrition (or termination) is the leading problem encountered in many colleges ( Bowden, 2008 ), which is a foremost challenge for online education administrators/instructors ( Clay et al., 2008 ). The issue is still very challenging ( Chiyaka et al., 2016 ; Hobson and Puruhito, 2018 ; Johnson et al., 2019 ; Li and Wong, 2019 ). Only about 15% of Open Universities students leave with degrees or other qualifications, indicating a meager persistence rate among students taking online courses ( Mishra, 2017 ). Online dropout experience results in frustration and shatters learners’ confidence preventing future enrolments ( Poellhuber et al., 2008 ), which implies inadequacy, questionable quality, and profit loss for institutions ( Willging and Johnson, 2009 ; Gomez, 2013 ).

Research Motivation

Many researchers realized the need to minimize dropout rates of online learners as beneficial for students, institutes, and companies over time ( Lee and Choi, 2011 ; Wuellner, 2013 ; Garratt-Reed et al., 2016 ; Moore and Greenland, 2017 ; Murphy and Stewart, 2017 ). Additionally, the pandemic enforced utilization of technology in the learning process has made this vital topic of online learning more critical. Therefore, a need arises for further investigation into the quality of online learning ( Basilaia and Kvavadze, 2020 ) from a new and improved perspective.

Research Question

The decision to drop out does not always link to knowledge but may result from a lack of persistence. Persistence in online courses is considered a complex phenomenon influenced by many factors ( Yang et al., 2017 ; Choi and Park, 2018 ). Any single factor cannot predict student attrition from online courses ( Gaytan, 2013 ). It is imperative to study persistence on a large scale to understand better the factors that count toward online course completion or online learners’ decision to drop out ( Choi and Park, 2018 ). The following research question guides the literature review based on the rationale provided.

What factors are positively or negatively linked with persistence in post-secondary online education settings?

Persistence: Differing Definitions and Indicators

There is a problem with the non-standardized use of the term persistence in online courses. The authors either do not provide clear indicators for persistence or provide inconsistent definitions ( Lee and Choi, 2011 ). Some authors have described persistence as an inclination to complete the currently enrolled online course ( Joo et al., 2011 ; You, 2018 ), whereas others defined persistence as an intention to enroll in more online courses in the future or successfully concluding the course securing somewhere between A to C grade ( Lee and Choi, 2011 ). Intention to persist in the currently enrolled online course is considered the most referenced indicator of persistence ( Roland et al., 2018 ). We have relied on this exact definition in this study.

Research Background

Several authors have studied persistence factors related to online courses in post-secondary educational settings ( Gazza and Hunker, 2014 ; Muljana and Luo, 2019 ; Xavier and Meneses, 2020 ). These studies have used divergent approaches and frameworks, where authors have studied the factors in isolation. There exists a gap in the literature while analyzing the combined effect of factors on persistence and examining the impact of factors upon each other. To better understand the persistence or dropout phenomena, it is imperative to identify as many factors as possible and arrange them in their logical categories. In this study, we have reflected upon the factors that correlate positively (enablers) or negatively (barriers) to persistence in an integrative manner. This study contributes to the existing literature by presenting the organization of persistence/dropout factors, identified after a comprehensive literature review, as a logically cohesive and integrative framework. We believe our results would pave the way for future studies to consider the collective effect of factors on the persistence phenomena and the relationships among the factors. An overview of the methodological framework used to conduct the review and the process adopted for categorizing factors in their respective categories is discussed in the later section.

Methodological Framework

To understand the topic in-depth, we analyzed empirical studies published in peer-reviewed journals in the context of post-secondary education over the last two decades. Most of the review studies that focus on dropout/retention factors do not go beyond 10 years period. Ideally, the review on the subject should not miss any vital factor identified with the continuous evolution of the Internet, social, and educational technologies. This approach becomes significant when the intent is to arrange the factors into their logical categories and guide future studies to focus on the relationships among factors and their combined effect on persistence, while studying retention and dropout scenarios.

Selection Criteria

Initially, the search phase explored Education Research Complete, ProQuest, ERIC, JSTOR, and PsycInfo databases, using the terms “online,” “persistence,” “dropout,” “retention,” “attrition,” and “withdrawal” in various combinations. Further, we searched with the same terms on Google Scholar and applied the snowball technique to enhance the existing pool. The screening phase concluded by analyzing the abstracts. Duplicates, non-empirical, non-peer-reviewed, and out-of-context studies were excluded.

After identifying the related factors from the final list of studies, we applied Constant Comparative Method (CCM) of Glaser and Strauss (1967 , p. 102) to assign the factors into their logical categories. The constant comparative analysis is characterized by “explicit coding and analytic procedures.” Coding is the method of labeling and categorizing concepts. A concept can be viewed as a “basic unit of analysis” ( Corbin and Strauss, 1990 , p. 7). The formation of a category occurs when items with similar characteristics are grouped. There are three stages to coding: open, axial, and selective ( Corbin and Strauss, 1990 ). In open coding, an incident is compared with other incidents based on their similarity and differences, Incidents are given conceptual labels, and the concepts are grouped into categories ( Corbin and Strauss, 1990 ). Using axial coding, we explored the relationships between categories ( Strauss, 1987 ). Authors have used selective coding to form a core category or categories and build a story that connects them. A pictorial representation of the process is given in Figure 2 .

Pictorial representation of Constant Comparative Method (CCM).

Our basic units of analysis (concepts) are the 47 individual factors identified through the literature review. Initially, we selected one factor randomly to represent the first category. Then, the similarity of the randomly chosen second factor with the previous factor was evaluated. If that second factor was not found to be similar to the first, we created a new category to represent the second factor. Two authors from this study judged the similarity of the factors to form categories of logically cohesive factors within them. We also consulted a peer de-briefer (subject expert) to mediate some of the differences between the authors in the process of factor assignment to their respective categories. The open coding process continued, creating 13 categories containing 47 individual factors. In the axial coding stage, the relationships are evaluated among the formed categories, forming the three axes (core categories), having 5, 5, and 3 categories in each axis, respectively (see Table 1 ).

Summary of identified factors group wise.

Review Results

The scope of this review comprises a reflection of factors that correlate positively or negatively to persistence in post-secondary online settings. Prior research on persistence and dropouts has not been comprehensive and integrative, utilizing divergent frameworks and approaches. Moreover, the categorization presented in previous studies has not considered the importance of the relationship between factors. The contribution of this paper is 2-fold. Firstly, we have identified all the factors linked to persistence reported for the past 20 years. Secondly, we have presented a logically coherent and integrative framework to enable fellow researchers to examine and understand the relationships among the persistence factors in future studies. There is a definite need to study the exact relationships among the persistence factors ( Choi and Park, 2018 ). Therefore, we have focused on defining coherent categories of factors that can be used to analyze relationships among factors. Forming such categories can also provide essential insights for the institutes offering online courses, administrators of online programs, and course instructors/facilitators in improving retention and overall quality of online courses and programs.

Persistence Factors Related to Online Learners

This section presents the factors related to online learners only. A review of these factors provides insights into the consensus among scholars, their differing views, and in some cases, contrasts empirical findings. The color-coded categorical arrangement of the factors related to online learners is presented in Figure 3 .

Categorical arrangement of factors related to online learners.

Demographic Attributes

Most researchers have focused on the differences in age and gender concerning persistence or dropout decisions made by the learner.

Some researchers reported no noteworthy difference in the age of students who drop out from online courses ( Levy, 2007 ; Tello, 2008 ; Willging and Johnson, 2009 ; James et al., 2016 ), while others have noted age as an important factor ( Xenos et al., 2002 ; Pierrakeas et al., 2004 ; Wladis et al., 2015 ; Murphy and Stewart, 2017 ). It has been posited that older students tend to drop out and require more encouragement from their teachers ( Xenos et al., 2002 ). Conversely, a retention study for online (STEM) courses reveals that older students showed better performance and had more likelihood of persistence ( Wladis et al., 2015 ). Similarly, James et al. (2016) stated that more senior students (age > 26) taking only online courses were retained more than younger students (age < 26). Also, Wuellner (2013) reported that younger learners might lack the skills and readiness required for online courses.

Some researchers believe that gender differences in online courses are not significantly related to retention/dropout ( Parker, 1999 ; Kemp, 2002 ; Cochran et al., 2014 ; Wladis et al., 2015 ; James et al., 2016 ). However, some studies informed the likelihood of the male population dropping from online courses ( Packham et al., 2004 ; Pocock et al., 2009 ). Studies also reveal that older female online learners get more influenced by the expectations around domestic and family responsibilities ( Dupin-Bryant, 2004 ; Stone and O’Shea, 2013 ).

Academic Experience

Some aspects of academic experiences are linked with persistence and dropping out decisions by online learners.

Distance/Online Learning Experience

Previous experience with distance or online learning improves awareness and boosts confidence. The number of previously done online courses ( Dupin-Bryant, 2004 ) and distant learning courses ( Levy, 2007 ; Traver et al., 2014 ) has been found to be linked with persistence decisions.

Academic Standing

Academic standing in college (freshman, sophomore, junior, or senior) is found to be related to persistence in online classes. Learners with higher status have increased chances of persistence ( Packham et al., 2004 ; Tello, 2008 ). However, Traver et al. (2014) has not found the academic year significant in predicting retention in online classes.

Field Experiences

While examining past educational and professional experiences of learners enrolled in an Informatics course online, Xenos et al. (2002) discovered that learners with prior backgrounds in programming or data handling showed significantly higher persistence rates. However, Cheung and Kan (2002) have not found previous experiences significant in persistence/dropout decisions.

Faculty and learners consider GPA and grades among the five most influential factors contributing to persistence/dropout decisions ( Gaytan, 2015 ). Many researchers have indicated that learners with lower academic scores are most likely to drop out of online classes ( Packham et al., 2004 ; Aragon and Johnson, 2008 ; Harrell and Bower, 2011 ; Xu and Jaggars, 2011 ; Colorado and Eberle, 2012 ; Stewart et al., 2013 ). Conversely, others have not found grades very significant in predicting retention/dropout ( Hachey et al., 2013 ; Traver et al., 2014 ; Shaw et al., 2016 ).

Relevant Technical and Management Skills

Previous research has focused on various technical and management skills of online learners that are found to be linked with persistence in online courses.

Technological Skills

Technological skills and confidence in using the computer, college readiness, and clarity of goals influence completing an online course ( Traver et al., 2014 ; Blau et al., 2016 ). The absence or lack of technical skills related to the Internet and its applications, operating systems, and file management is an important dropout indicator ( Dupin-Bryant, 2004 ). Similarly, Blau et al. (2016) found perceived ease of using technology is linked with persistence.

Time Management

While effective time management skills have been reported to influence persistence positively, learners’ difficulty in managing time has been strongly associated with early dropouts from online classes ( Ivankova and Stick, 2007 ; Stanford-Bowers, 2008 ; Nichols, 2010 ; Traver et al., 2014 ). Good study habits such as prioritizing tasks like assignments and making efficient use of available time enable learners to continue ( Castles, 2004 ; Ivankova and Stick, 2007 ). Aragon and Johnson (2008) supported this finding but noted a modest difference in the students’ capability enrolled in more online courses. The skill and ability to balance multiple responsibilities have been seen in those learners who complete their online courses ( Müller, 2008 ; Joo et al., 2011 ). Realistic expectations about the time and effort to complete a task are reported to facilitate better academic performance and completion of online courses ( Xenos et al., 2002 ; Wladis et al., 2015 ).

Workload Management

Online learners who actively plan to accommodate their workload are more likely to persist ( Bunn, 2004 ). Realistic expectations about the workload are noted as facilitators of persistence ( Leeds et al., 2013 ). An unexpected change in the workload of an online class is also reported as a dropout reason ( Moore and Greenland, 2017 ).

Behavioral and Psychological Attributes

Online learners’ behavioral and psychological characteristics encompass various attitudes and traits that shape their decision to persist or drop out.

Locus of Control

Thoughts about where to attribute outcomes of an event and the level of control over that subsequent event ( Rotter, 1966 ) is an individual’s locus of control. Lee and Choi (2013) found the locus of control as an influencing factor related to persistence. Individuals who have an “internal locus of control” tend to believe that the result of actions depends on their decisions and effort. Internal locus of control has been reported to link with persistence in online courses ( Parker, 2003 ; Morris et al., 2005b ).

It is the most significant force that shapes learners’ perceptions about enrolling in online classes and helps them persist ( Kemp, 2002 ; Holder, 2007 ; Blau et al., 2016 ). Motivation can positively forecast dropout decisions ( Osborn, 2001 ). Self-motivation, alongside personal challenge and responsibility, is considered the intrinsic motivation to conclude an online program ( Park and Choi, 2009 ; Nichols, 2010 ). Attachment and commitment toward a goal, goal attainment, respect for career, and financial outcomes of education are linked with persistence in online education ( Nichols, 2010 ; Joo et al., 2011 ). Self-determination helps to sustain learners in the online program ( Nichols, 2010 ).

Self-Efficacy

It is a “belief that one is capable of executing certain behaviors or achieving certain goals” ( Ormrod, 2011 , p. 352). Online student self-efficacy is identified as the most influential factor linked to retention ( Ivankova and Stick, 2007 ; Liaw, 2008 ; Street, 2010 ). A higher level of self-efficacy increases resilience in the cases of obstacles and intensifies learners’ efforts ( Kemp, 2002 ). Learners’ endurance to complete is associated with self-regulation and self-efficacy ( Gomez, 2013 ). Similarly, Ivankova and Stick (2007) and Ice et al. (2011) indicated a significant correlation between online course completion and self-efficacy.

Self-Regulation

It is an individual ability to control behavior, emotions, and thoughts in the engagement toward long-term goals. Those online learners who “self-regulate” successfully practice metacognitive, motivational, and behavioral processes as part of forethought, performance, and self-reflection ( Zimmerman, 2011 ). These behaviors generally include effective time management, seeking help from online course facilitators or tutoring, and avoiding distractions. Self-regulation influences learners’ persistence ( Gomez, 2013 ; Lee et al., 2013 ; O’Neill and Sai, 2014 ). Similarly, Lee et al. (2013) report meta-cognition as an influencing factor linked with retention. Self-discipline is also an influential factor contributing to persistence ( Gaytan, 2015 ).

An ability to manage threats during online courses has been an influencing factor differentiating persistent students from dropouts ( Parker, 1999 ; Müller, 2008 ).

Active Participation

Although a mild relationship exists between learner participation and academic success in terms of final grades ( Xia et al., 2013 ), online learners who actively interact with the course content are more likely to persist. Learners who complete their course view more discussion/content pages and spend more time viewing the discussions than those who withdraw ( Morris et al., 2005a ).

Satisfaction

Satisfaction with faculty and online courses has been found to be correlated with course completion in previous studies ( Tello, 2008 ; Joo et al., 2011 ).

Learners’ attitudes toward the course and their interactions with fellow peers and facilitators (instructors) are correlated with the completion of online courses ( Tello, 2008 ).

Personal Variables

Multiple responsibilities.

Family responsibilities are seen as a hindrance and a reason to withdraw from online learning in past studies ( Parkes et al., 2015 ; Shah and Cheng, 2019 ). Employment responsibilities also create problems for learners to continue ( Lee and Choi, 2011 ; Shah and Cheng, 2019 ), and part-time learners tend to drop out more from online classes ( Boston et al., 2011 ).

Financial Issues

Issues related to finance may contribute to dropout decisions by online learners ( Aversa and MacCall, 2013 ; Parkes et al., 2015 ). Online students usually pay the tuition fees out of pocket, and this added responsibility influences persistence decisions ( Boston et al., 2011 ). Contradictorily, Cochran et al. (2014) state that learners with loans/financial assistance are more inclined to drop out having certain major subjects.

Family and Friends Support

Family support and home environment is also significant factor related to persistence ( Harris et al., 2011 ). Non-persistent learners see friends and family as unsupportive in their educational journey ( Park and Choi, 2009 ). Learners who persist score higher in having supportive partners and maintaining healthy relationships ( Kemp, 2002 ).

Health Issues

Issues related to disability and health may also cause online learners to withdraw ( Shah and Cheng, 2019 ).

Persistence Factors Related to Online Courses and Course Providers

Factors linked with online course design and institutional support are listed in this section. This includes how the course or program is structured, the complexity of the curriculum, how the learners interact with the content, and what support services they perceive important. The color-coded categorical arrangement of the factors related to online courses and course providers is presented in Figure 4 .

Categorical arrangement of factors related to online courses and course providers.

Course Design

How the courses are defined and structured in terms of their interactivity, how well they fulfill the need of the learners, and the overall quality of online courses are important predictors of persistence and dropout.

Course Organization

Bad course organization, or at worst, lack of course organization and disconnected, illogical structures of the courses are linked with dropout decisions ( Hammond and Shoemaker, 2014 ). Ice et al. (2011) noted that poor course design/organization affects learner satisfaction, thus contributing to dropout decisions.

Course Content

Well-structured courses with rigorous, relevant content and clear instructions facilitate persistence ( Nichols, 2010 ; Harris et al., 2011 ), whereas boring and unrelated course elements promote dropout decisions ( Pittenger and Doering, 2010 ; Garratt-Reed et al., 2016 ).

Course Relevancy

Course relevancy with individuals’ learning styles and career objectives is important in shaping their decision to persist or withdraw from online courses ( Perry et al., 2008 ). Street (2010) also points out that relevant course factors and design impact learners’ choice to continue or drop out.

Team-Building Activities

Courses that promote team-building activities foster increased interaction between the learners and the faculty, thus contributing to increased retention ( Bocchi et al., 2004 ).

Scaffolding

An element of scaffolding fused into the course design forms striking, motivating, and related learning elements that enhance persistence ( Pittenger and Doering, 2010 ).

Institutional Support

Institutional support services have been confirmed crucial for online course completion by the administrators and faculty ( Heyman, 2010 ; Boston et al., 2011 ). However, learners do not perceive these support services as equally important ( Gaytan, 2015 ) but admit that the absence of these services negatively impacts their academic success ( Nichols, 2010 ).

Student Support Services

These services help learners overcome barriers that result in dropout decisions. Xu and Jaggers (2011) confirms that support services for online learners are not found as effective or satisfactory as they are for regular students. However, Muilenburg and Berge (2001) acknowledged unsatisfactory support services as barriers for online learners.

Tutorial Services

The academic and emotional support provided to online learners through face-to-face sessions improved persistence in online courses significantly ( Levy, 2007 ). Similarly, online learners perceive tutorials as helpful, encouraging them to continue ( Stanford-Bowers, 2008 ).

Support Infrastructure

Muilenburg and Berge (2001) conducted a factor analysis to study barriers related to distance education and identified a 10-factor model that deters course completion. Among these, five factors were found linked to institutional support infrastructure. These five factors are: (1) Structure of administration; (2) Student-support services; (3) Access; (4) Effectiveness and Evaluation; and (5) Teacher compensation and time. These factors were confirmed to influence distant learners’ dropping out decisions through telephonic interviews ( Clay et al., 2008 ; Nichols, 2010 ).

Orientation

Course orientation facilitates the chances of online learners persisting in the course ( Clay et al., 2008 ; Aversa and MacCall, 2013 ). Online advisory counseling and web orientation provided to undergraduates significantly increase the persistence rate ( Clay et al., 2008 ).

Support for Technology

Online learners possess different levels of skills related to computers and technology, and the perception of being unsupported is more of a problem than the actual struggle with technology ( Bunn, 2004 ). Parkes et al. (2015) exposed insufficient technology support to distant learners, impacting persistence ( Ojokheta, 2010 ; Street, 2010 ). However, Ivankova and Stick (2007) have not found technical support influential but agree that non-persistent learners were not pleased with the support services. Also, it is revealed that access issues with technology and the poor speed of the Internet may also influence dropout decisions ( Osborn, 2001 ).

Learners’ Specific Needs and Circumstances

Institutional lack of understanding of online learners’ needs and their specific circumstances contribute to dropout decisions ( Parkes et al., 2015 ; Friðriksdóttir, 2018 ).

Curriculum Intricacy

The category of an online course and its complexity level has been noted as influencing elements linked to learners’ persistence.

Course Category

The category of the course (elective, distribution, and major) and retention in online settings are interlinked ( Wladis et al., 2017 ). Additionally, Wladis et al. (2014) found lower-level STEM courses and dropout rates were positively associated.

Complexity Level

Online learners tend to drop out of online programs if there are many low-level and easy assignments or if they find the program curriculum too difficult ( Willging and Johnson, 2009 ). Similarly, Boston et al. (2011) posit that online learners were more inclined to drop out if they find the curriculum very easy or very difficult.

Persistence Factors Related to Online Instructors

Universities need to inspire faculty to develop themselves to improve the quality of online courses ( Parker et al., 2013 ). The role of online course facilitators is vital in keeping learners’ interests intact, keeping them motivated to continue, and helping them to conclude online courses and programs successfully. The color-coded categorical arrangement of the factors related to online course instructors is presented in Figure 5 .

Categorical arrangement of factors related to online course instructors.

Role of Instructors

The instructor’s role is evolving in online settings, and this change is observed as a significant challenge ( Syverson and Slatin, 2010 ).

Ways of Teaching

The main challenge of teaching online courses is the “disconnect between the way teachers were taught to teach” ( Anderson et al., 2011 , p. 4). The shift toward the learner-centered approach has transformed the role of instructors into guides with the responsibility to align the content delivery according to the need of the learners.

Instructor’s Interest in Online Classes

Instructors involved in traditional face-to-face classes are found uninterested in teaching in online settings, fearing that they are replaceable with computers ( Osika et al., 2009 ). Müller (2008) has identified that students’ dissatisfaction with faculty or learning results in dropouts. More time required in preparation, design, and facilitation may also limit the interest of the faculty in online classes ( Crawley et al., 2009 ).

Time Invested by Instructors

Preparing for, planning, and teaching an online class took an extra bit of time ( Capra, 2011 ), and the amount of time spent by the instructors, while facilitating online courses are linked with student retention up to a certain extent ( Wuellner, 2013 ).

Faculty Interactions

Interaction with faculty has been nominated as the second-highest retention factor, the absence of which contributes to dissatisfaction and dropout decisions in online learning ( Heyman, 2010 ; Boston et al., 2011 ).

Learner’s Interaction With Faculty

Interaction of online learners with the faculty and dropout rates are significantly linked ( Bocchi et al., 2004 ).

Effective Communication

Online learners expect effective communication from the course facilitators, and its absence creates difficulties for them to persist ( O’Neill and Sai, 2014 ). Online learners who interact effectively with the faculty persist more ( Ivankova and Stick, 2007 ).

Feedback from the faculty, association, motivation, and perception is positively associated with online learners’ outcomes ( Ojokheta, 2010 ).

Feedback Pattern

Feedback from faculty influence the perception of students regarding course content, and feedback pattern directly affects their ability to conclude an online course positively ( Ojokheta, 2010 ).

Encouraging and Timely Feedback

Positive, timely, valuable, encouraging feedback and faculty readiness to meet learner needs are significant to students’ persistence ( Ivankova and Stick, 2007 ).

Sufficient and Personalized Feedback

Insufficient or inadequate feedback on learning affects retention ( Shah and Cheng, 2019 ). Feedback should be consistent and personalized for each student ( Bocchi et al., 2004 ).

Facilitation of Social Connectedness

A sense of social connectedness fosters interaction with peers and the learning community. It is possible for online learners to feel disconnected and isolated ( McInnerney and Roberts, 2004 ), negatively affecting their overall learning experience and persistence.

Sense of Belonging

Apparently, verbal and visual communication cues are not displayed in online learning environments as in traditional settings ( Koole, 2014 ), resulting in isolation and not being supported by peers ( Aversa and MacCall, 2013 ; Koole, 2014 ). This negative perception is linked with an inferior sense of community and deprived student bonding ( Aversa and MacCall, 2013 ) that create difficulties in breaking the ice between peers, thus influencing their decision to persist. Associating themselves with the learning community instigates learners’ sense of identity and inspires their learning ( Koole, 2014 ).

Shared Purpose and Norms

Online learners should be assisted in developing shared purpose and norms and a fit-in sense ( Lapadat, 2007 ; Nistor and Neubauer, 2010 ). Learners who do not share a common purpose and community norms usually fail to interact actively, stay quiet during discussions, and are more persuaded to drop out ( Nistor and Neubauer, 2010 ).

Fostering Online Communities

An essential role of online instructors is to promote and encourage an online community ( Drouin, 2008 ; Nichols, 2010 ), assure peer interactions ( Pigliapoco and Bogliolo, 2008 ; Alman et al., 2012 ), and facilitate effective dialogs with peers ( Alman et al., 2012 ). Becoming a valuable part of the knowledge community fosters an effective knowledge construction process, thus increasing learners’ chances of persistence ( Goodyear and Zenios, 2007 ).

Learning Facilitation

One key role of online instructors is to assist online learners in generating and achieving knowledge, facilitating the overall learning process.

Guidance and Presence

Online learners value instructors’ presence in nurturing the knowledge attainment process ( Alman et al., 2012 ). Insufficient advice about the topics is linked with low online enrolment ( Ice et al., 2011 ).

Assignments

The type of assignment presented to online learners could also affect learners’ decisions to continue with the course. Fredrickson (2015) and Garratt-Reed et al. (2016) highlights that online learners do not prefer group assignments because of limited personal interaction with the course instructor.

This review reflected upon the essential factors linked with persistence, either positively or negatively, by methodically reviewing empirical studies on the subject published in the past two decades. By applying the CCM method, we managed to classify the identified factors into three broad groups, each one containing sub-groups of factors within them. Factors related to online learners are presented in the first group having demographic properties, past educational experiences, management and technological skills, behavioral and psychological attributes of the learner, and other personal variables related to responsibilities, support, health, and finances. Persistence factors related to online learners are most discussed in the reviewed studies. Factors related to online course design and structure, support from the online course providers, and the complexity level of online courses and programs are placed in the second group. Finally, the third group presents factors related to online course instructors like their role in online settings, how well they facilitate online learning, their role in promoting various interactions, and their interest in the online mode of delivery.

Researchers found that the interaction between various factors determines whether online learners persist or drop out ( Holder, 2007 ; Perry et al., 2008 ). Therefore, the categorization provided in this review will help fellow researchers to investigate the relationship within and between categories alongside studying the combined effect of various factors on persistence or dropout decisions. The results will direct future research to critically examine the relationships among the factors and suggest improvements by validating them empirically. Future researchers may also validate the results in different scenarios and contexts related to online learning. Course instructors and providers can focus on the related problem areas to improve online courses and programs persistence.

Author Contributions

US: conception, design of the work, data collection, drafting the article, and critical revision of the article. ZA: conceptualization, design review, draft review, and improvement suggestions. US and ZA: data analysis and interpretation and final approval of the version to be published. All authors contributed to the article and approved the submitted version.

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.

Acknowledgments

The authors would like to specially thank our research fellow Shakir Karim Buksh ( kp.ude.abi@hskubs ), for contributing to mediating differences between the authors while assigning the factors in their respective categories.

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Setting a new bar for online higher education

The education sector was among the hardest hit  by the COVID-19 pandemic. Schools across the globe were forced to shutter their campuses in the spring of 2020 and rapidly shift to online instruction. For many higher education institutions, this meant delivering standard courses and the “traditional” classroom experience through videoconferencing and various connectivity tools.

The approach worked to support students through a period of acute crisis but stands in contrast to the offerings of online education pioneers. These institutions use AI and advanced analytics to provide personalized learning and on-demand student support, and to accommodate student preferences for varying digital formats.

Colleges and universities can take a cue from the early adopters of online education, those companies and institutions that have been refining their online teaching models for more than a decade, as well as the edtechs that have entered the sector more recently. The latter organizations use educational technology to deliver online education services.

To better understand what these institutions are doing well, we surveyed academic research as well as the reported practices of more than 30 institutions, including both regulated degree-granting universities and nonregulated lifelong education providers. We also conducted ethnographic market research, during which we followed the learning journeys of 29 students in the United States and in Brazil, two of the largest online higher education markets in the world, with more than 3.3 million 1 Integrated Postsecondary Education Data System, 2018, nces.ed.gov. and 2.3 million 2 School Census, Censo Escolar-INEP, 2019, ensobasico.inep.gov.br. online higher education students, respectively.

We found that, to engage most effectively with students, the leading online higher education institutions focus on eight dimensions of the learning experience. We have organized these into three overarching principles: create a seamless journey for students, adopt an engaging approach to teaching, and build a caring network (exhibit). In this article, we talk about these principles in the context of programs that are fully online, but they may be just as effective within hybrid programs in which students complete some courses online and some in person.

Create a seamless journey for students

The performance of the early adopters of online education points to the importance of a seamless journey for students, easily navigable learning platforms accessible from any device, and content that is engaging, and whenever possible, personalized. Some early adopters have even integrated their learning platforms with their institution’s other services and resources, such as libraries and financial-aid offices.

1. Build the education road map

In our conversations with students and experts, we learned that students in online programs—precisely because they are physically disconnected from traditional classroom settings—may need more direction, motivation, and discipline than students in in-person programs. The online higher education  programs that we looked at help students build their own education road map using standardized tests, digital alerts, and time-management tools to regularly reinforce students’ progress and remind them of their goals.

Brazil’s Cogna Educação, for instance, encourages students to assess their baseline knowledge at the start of the course. 3 Digital transformation: A new culture to shape our future , Kroton 2018 Sustainability Report, Kroton Educacional, cogna.com.br. Such up-front diagnostics could be helpful in highlighting knowledge gaps and pointing students to relevant tools and resources, and may be especially helpful to students who have had unequal educational opportunities. A web-based knowledge assessment allows Cogna students to confirm their mastery of certain parts of a course, which, according to our research, can potentially boost their confidence and allow them to move faster through the course material.

At the outset of a course, leaders in online higher education can help students clearly understand the format and content, how they will use what they learn, how much time and effort is required, and how prepared they are for its demands.

The University of Michigan’s online Atlas platform, for instance, gives students detailed information about courses and curricula, including profiles of past students, sample reports and evaluations, and grade distributions, so they can make informed decisions about their studies. 4 Atlas, Center for Academic Innovation, University of Michigan, umich.edu. Another provider, Pluralsight, shares movie-trailer-style overviews of its course content and offers trial options so students can get a sense of what to expect before making financial commitments.

Meanwhile, some of the online doctoral students we interviewed have access to an interactive timeline and graduation calculator for each course, which help students understand each of the milestones and requirements for completing their dissertations. Breaking up the education process into manageable tasks this way can potentially ease anxiety, according to our interviews with education experts.

2. Enable seamless connections

Students may struggle to learn if they aren’t able to connect to learning platforms. Online higher education pioneers provide a single sign-on through which students can interact with professors and classmates and gain access to critical support services. Traditional institutions considering a similar model should remember that because high-speed and reliable internet are not always available, courses and program content should be structured so they can be accessed even in low-bandwidth situations or downloaded for offline use.

The technology is just one element of creating seamless connections. Since remote students may face a range of distractions, online-course content could benefit them by being more engaging than in-person courses. Online higher education pioneers allow students to study at their own pace through a range of channels and media, anytime and anywhere—including during otherwise unproductive periods, such as while in the waiting room at the doctor’s office. Coursera, for example, invites students to log into a personalized home page where they can review the status of their coursework, complete unfinished lessons, and access recommended “next content to learn” units. Brazilian online university Ampli Pitagoras offers content optimized for mobile devices that allows students to listen to lessons, contact tutors for help, or do quizzes from wherever they happen to be.

Adopt an engaging approach to teaching

The pioneers in online higher education we researched pair the “right” course content with the “right” formats to capture students’ attention. They incorporate real-world applications into their lesson plans, use adaptive learning tools to personalize their courses, and offer easily accessible platforms for group learning.

3. Offer a range of learning formats

The online higher education programs we reviewed incorporate group activities and collaboration with classmates—important hallmarks of the higher education experience—into their mix of course formats, offering both live classes and self-guided, on-demand lessons.

The Georgia Institute of Technology, for example, augments live lessons from faculty members in its online graduate program in data analytics with a collaboration platform where students can interact outside of class, according to a student we interviewed. Instructors can provide immediate answers to students’ questions via the platform or endorse students’ responses to questions from their peers. Instructors at Zhejiang University in China use live videoconferencing and chat rooms to communicate with more than 300 participants, assign and collect homework assignments, and set goals. 5 Wu Zhaohui, “How a top Chinese university is responding to coronavirus,” World Economic Forum, March 16, 2020, weforum.org.

The element of personalization is another area in which online programs can consider upping their ante, even in large student groups. Institutions could offer customized ways of learning online, whether via digital textbook, podcast, or video, ensuring that these materials are high quality and that the cost of their production is spread among large student populations.

Some institutions have invested in bespoke tools to facilitate various learning modes. The University of Michigan’s Center for Academic Innovation embeds custom-designed software into its courses to enhance the experience for both students and professors. 6 “Our mission & principles,” University of Michigan Center for Academic Innovation, ai.umich.edu. The school’s ECoach platform helps students in large classes navigate content when one-on-one interaction with instructors is difficult because of the sheer number of students. It also sends students reminders, motivational tips, performance reviews, and exam-preparation materials. 7 University of Michigan, umich.edu. Meanwhile, Minerva University focuses on a real-time online-class model that supports higher student participation and feedback and has built a platform with a “talk time” feature that lets instructors balance class participation and engage “back-row students” who may be inclined to participate less. 8 Samad Twemlow-Carter, “Talk Time,” Minerva University, minervaproject.com.

4. Ensure captivating experiences

Delivering education on digital platforms opens the potential to turn curricula into engaging and interactive journeys, and online education leaders are investing in content whose quality is on a par with high-end entertainment. Strayer University, for example, has recruited Emmy Award–winning film producers and established an in-house production unit to create multimedia lessons. The university’s initial findings show that this investment is paying off in increased student engagement, with 85 percent of learners reporting that they watch lessons from beginning to end, and also shows a 10 percent reduction in the student dropout rate. 9 Increased student engagement and success through captivating content , Strayer Studios outcomes report, Strayer University, studios.strategiced.com.

Other educators are attracting students not only with high-production values but influential personalities. Outlier provides courses in the form of high-quality videos that feature charismatic Ivy League professors and are shot in a format that reduces eye strain. 10 Outlier online course registration for Calculus I, outlier.org. The course content follows a storyline, and each course is presented as a crucial piece in an overall learning journey.

5. Utilize adaptive learning tools

Online higher education pioneers deliver adaptive learning using AI and analytics to detect and address individual students’ needs and offer real-time feedback and support. They can also predict students’ requirements, based on individuals’ past searches and questions, and respond with relevant content. This should be conducted according to the applicable personal data privacy regulations of the country where the institution is operating.

Cogna Educação, for example, developed a system that delivers real-time, personalized tutoring to more than 500,000 online students, paired with exercises customized to address specific knowledge gaps. 11 Digital transformation , 2018. Minerva University used analytics to devise a highly personalized feedback model, which allows instructors to comment and provide feedback on students’ online learning assignments and provide access to test scores during one-on-one feedback sessions. 12 “Maybe we need to rethink our assumptions about ‘online’ learning,” Minerva University, minervaproject.com. According to our research, instructors can also access recorded lessons during one-on-one sessions and provide feedback on student participation during class.

6. Include real-world application of skills

The online higher education pioneers use virtual reality (VR) laboratories, simulations, and games for students to practice skills in real-world scenarios within controlled virtual environments. This type of hands-on instruction, our research shows, has traditionally been a challenge for online institutions.

Arizona State University, for example, has partnered with several companies to develop a biology degree that can be obtained completely online. The program leverages VR technology that gives online students in its biological-sciences program access to a state-of-the-art lab. Students can zoom in to molecules and repeat experiments as many times as needed—all from the comfort of wherever they happen to be. 13 “ASU online biology course is first to offer virtual-reality lab in Google partnership,” Arizona State University, August 23, 2018, news.asu.edu. Meanwhile, students at Universidad Peruana de Ciencias Aplicadas are using 3-D games to find innovative solutions to real-world problems—for instance, designing the post-COVID-19 campus experience. 14 Cleofé Vergara, “Learn by playing with Minecraft Education,” Innovación Educativa, July 13, 2021, innovacioneducativa.upc.edu.pe.

Some institutions have expanded the real-world experience by introducing online internships. Columbia University’s Virtual Internship Program, for example, was developed in partnership with employers across the United States and offers skills workshops and resources, as well as one-on-one career counseling. 15 Virtual Internship Program, Columbia University Center for Career Education, columbia.edu.

Create a caring network

Establishing interpersonal connections may be more difficult in online settings. Leading online education programs provide dedicated channels to help students with academic, personal, technological, administrative, and financial challenges and to provide a means for students to connect with each other for peer-to-peer support. Such programs are also using technologies to recognize signs of student distress and to extend just-in-time support.

7. Provide academic and nonacademic support

Online education pioneers combine automation and analytics with one-on-one personal interactions to give students the support they need.

Southern New Hampshire University (SNHU), for example, uses a system of alerts and communication nudges when its digital platform detects low student engagement. Meanwhile, AI-powered chatbots provide quick responses to common student requests and questions. 16 “SNHU turns student data into student success,” Southern New Hampshire University, May 2019, d2l.com. Strayer University has a virtual assistant named Irving that is accessible from every page of the university’s online campus website and offers 24/7 administrative support to students, from recommending courses to making personalized graduation projections. 17 “Meet Irving, the Strayer chatbot that saves students time,” Strayer University, October 31, 2019, strayer.edu.

Many of these pioneer institutions augment that digital assistance with human support. SNHU, for example, matches students in distress with personal coaches and tutors who can follow the students’ progress and provide regular check-ins. In this way, they can help students navigate the program and help cultivate a sense of belonging. 18 Academic advising, Southern New Hampshire University, 2021, snhu.edu. Similarly, Arizona State University pairs students with “success coaches” who give personalized guidance and counseling. 19 “Accessing your success coach,” Arizona State University, asu.edu.

8. Foster a strong community

The majority of students we interviewed have a strong sense of belonging to their academic community. Building a strong network of peers and professors, however, may be challenging in online settings.

To alleviate this challenge, leading online programs often combine virtual social events with optional in-person gatherings. Minerva University, for example, hosts exclusive online events that promote school rituals and traditions for online students, and encourages online students to visit its various locations for in-person gatherings where they can meet members of its diverse, dispersed student population. 20 “Join your extended family,” Minerva University, minerva.edu. SNHU’s Connect social gateway gives online-activity access to more than 15,000 members, and helps them interact within an exclusive university social network. Students can also join student organizations and affinity clubs virtually. 21 SNHU Connect, Southern New Hampshire University, snhuconnect.com.

Getting started: Designing the online journey

Building a distinctive online student experience requires significant time, effort, and investment. Most institutions whose practices we reviewed in this article took several years to understand student needs and refine their approaches to online education.

For those institutions in the early stages of rethinking their online offerings, the following three steps may be useful. Each will typically involve various functions within the institution, including but not necessarily limited to, academic management, IT, and marketing.

The diagnosis could be performed through a combination of focus groups and quantitative surveys, for example. It’s important that participants represent various student segments, which are likely to have different expectations, including young-adult full-time undergraduate students, working-adult part-time undergraduate students, and graduate students. The eight key dimensions outlined above may be helpful for structuring groups and surveys, in addition to self-evaluation of institution performance and potential benchmarks.

• Set a strategic vision for your online learning experience. The vision should be student-centric and link tightly to the institution’s overarching manifesto. The function leaders could evaluate the costs/benefits of each part of the online experience to ensure that the costs are realistic. The online model may vary depending on each school’s market, target audience, and tuition price point. An institution with high tuition, for example, is more likely to afford and provide one-on-one live coaching and student support, while an institution with lower tuition may need to rely more on automated tools and asynchronous interactions with students.
• Design the transformation journey. Institutions should expect a multiyear journey. Some may opt to outsource the program design and delivery to dedicated program-management companies. But in our experience, an increasing number of institutions are developing these capabilities internally, especially as online learning moves further into the mainstream and becomes a source of long-term strategic advantage.

We have found that leading organizations often begin with quick wins that significantly raise student experiences, such as stronger student support, integrated technology platforms, and structured course road maps. In parallel, they begin the incremental redesign of courses and delivery models, often focusing on key programs with the largest enrollments and tapping into advanced analytics for insights to refine these experiences.

Finally, institutions tackle key enabling factors, such as instructor onboarding and online-teaching training, robust technology infrastructure, and advanced-analytics programs that enable the institutions to understand which features of online education are performing well and generating exceptional learning experiences for their students.

The question is no longer whether the move to online will outlive the COVID-19 lockdowns but when online learning will become the dominant means for delivering higher education. As digital transformation accelerates across all industries, higher education institutions will need to consider how to develop their own online strategies.

Felipe Child is a partner in McKinsey’s Bogotá office, Marcus Frank is a senior practice expert in the São Paulo office, Mariana Lef is an associate in the Buenos Aires office, and Jimmy Sarakatsannis is a partner in the Washington, DC, office.

References to specific products, companies, or organizations are solely for information purposes and do not constitute any endorsement or recommendation.

This article was edited by Justine Jablonska, an editor in the New York office.

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• Open access
• Published: 10 May 2024

Challenges and opportunities of English as the medium of instruction in diploma midwifery programs in Bangladesh: a mixed-methods study

• Anna Williams 1 ,
• Jennifer R. Stevens 2 ,
• Rondi Anderson 3 &
• Malin Bogren 4  

BMC Medical Education volume  24 , Article number:  523 ( 2024 ) Cite this article

111 Accesses

Metrics details

English is generally recognized as the international language of science and most research on evidence-based medicine is produced in English. While Bangla is the dominant language in Bangladesh, public midwifery degree programs use English as the medium of instruction (EMI). This enables faculty and student access to the latest evidence-based midwifery content, which is essential for provision of quality care later. Yet, it also poses a barrier, as limited English mastery among students and faculty limits both teaching and learning.

This mixed-methods study investigates the challenges and opportunities associated with the implementation of EMI in the context of diploma midwifery education in Bangladesh. Surveys were sent to principals at 38 public midwifery education institutions, and 14 English instructors at those schools. Additionally, ten key informant interviews were held with select knowledgeable stakeholders with key themes identified.

Surveys found that English instructors are primarily guest lecturers, trained in general or business English, without a standardized curriculum or functional English language laboratories. Three themes were identified in the key informant interviews. First, in addition to students’ challenges with English, faculty mastery of English presented challenges as well. Second, language labs were poorly maintained, often non-functional, and lacked faculty. Third, an alternative education model, such as the English for Specific Purposes (ESP) curriculum,  has potential to strengthen English competencies within midwifery schools.

Conclusions

ESP, which teaches English for application in a specific discipline, is one option available in Bangladesh for midwifery education. Native language instruction and the middle ground of multilingualism are also useful options. Although a major undertaking, investing in an ESP model and translation of technical midwifery content into relevant mother tongues may provide faster and more complete learning. In addition, a tiered system of requirements for English competencies tied to higher levels of midwifery education could build bridges to students to help them access global evidence-based care resources. Higher levels might emphasize English more heavily, while the diploma level would follow a multilingualism approach, teach using an ESP curriculum, and have complementary emphasis on the mother tongue.

Peer Review reports

Introduction

As the international language of science, English holds an important position in the education of healthcare professionals. Globally, most scientific papers are published in English. In many non-native English-speaking countries, English is used as the language of instruction in higher education [ 1 ]. The dominant status held by the English language in the sciences is largely considered to increase global access to scientific information by unifying the scientific community under a single lingua franca [ 2 ].

In Bangladesh, where the mother tongue is Bangla and midwifery diploma programs are taught in English, knowledge of English facilitates student and instructor access to global, continuously updated evidence-based practice guidance. This includes basic and scientific texts, media-based instructional materials (including on life-saving skills), professional journals, and proceedings of medical conferences. Many of these resources are available for free online, which can be particularly useful in healthcare settings that have not integrated evidence-based practice.

In addition to opportunity though, English instruction also creates several challenges. Weak student and faculty English competency may impede midwifery education quality in Bangladesh. Globally, literature has linked limited instructor competency in the language of instruction with reduced depth, nuance, and accuracy in conveying subject matter content [ 3 ]. This can lead to the perpetuation of patterns of care in misalignment with global evidence. In addition, students’ native language proficiency in their topic of study can decline when instruction is in English, limiting native language communication between colleagues on the job later on [ 4 , 5 ].

In this paper, we examine the current status of English language instruction within public diploma midwifery programs in Bangladesh. Midwifery students are not required to demonstrate a certain skill level in English to enter the program. However, they are provided with English classes in the program. Midwifery course materials are in English, while—for ease and practicality—teaching aids and verbal classroom instruction are provided in Bangla. Following graduation, midwifery students must pass a national licensing exam given in English to practice. Upon passing, some new midwives are deployed as public employees and are posted to sub-district health facilities where English is not used by either providers or clients. Others will seek employment as part of non-governmental organization (NGO) projects where English competency can be of value for interacting with global communities, and for participating in NGO-specific on-the-job learning opportunities. The mix of both challenge and opportunity in this context is complex.

Our analysis examines the reasons for the identified English competency gaps within midwifery programs, and potential solutions. We synthesize the findings and discuss solutions in the context of the global literature. Finally, we present a set of viable options for strengthening English competencies among midwifery faculty and students to enable better quality teaching and greater learning comprehension among students.

Study design

We employed a mixed-methods study design [ 6 ] in order to assess the quality of English instruction within education programs, and options for its improvement. Data collection consisted of two surveys of education institutes, a web-search of available English programs in Bangladesh, and key informant interviews. Both surveys followed a structured questionnaire with a combination of open- and closed-ended questions and were designed by the authors. One survey targeted the 38 institute principals and the other targeted 14 of the institutes’ 38 English instructors (those for whom contact information was shared). The web-search focused on generating a list of available English programs in Bangladesh that had viable models that could be tapped into to strengthen English competencies among midwifery faculty and students. Key informant interviews were unstructured and intended to substantiate and deepen understanding of the survey and web-search findings.

No minimum requirements exist for students’ English competencies upon entry into midwifery diploma programs. Students enter directly from higher secondary school (12th standard) and complete the midwifery program over a period of three years. Most students come from modest economic backgrounds having completed their primary and secondary education in Bangla. While English instruction is part of students’ secondary education, skill attainment is low, and assessment standards are not in place to ensure student mastery. To join the program, midwifery students are required to pass a multi-subject entrance exam that includes a component on English competency. However, as no minimum English standard must be met, the exam does not screen out potential midwifery students. Scoring, for instance, is not broken down by subject. This makes it possible to answer zero questions correctly in up to three of the subjects, including English, and pass the exam.

Processes/data collection

Prior to the first survey, principals were contacted by UNFPA with information about the survey and all provided verbal consent to participate. The survey of principals collected general information about the resources available for English instruction at the institutes. It was a nine-item questionnaire with a mix of Yes/No, multiple choice and write-in questions. Specific measures of interest were whether and how many English instructors the institutes had, instructors’ hiring criteria, whether institutes had language labs and if they were in use, and principals’ views on the need for English courses and their ideal mode of delivery (e.g., in-person, online, or a combination). This survey also gathered contact information of institute English instructors. These measures were chosen as they were intended to provide a high-level picture of institutes’ English resources such as faculty availability and qualifications, and use of language labs. To ensure questions were appropriately framed, a pilot test was conducted with two institute principals and small adjustments were subsequently made. Responses were shared via an electronic form sent by email and were used to inform the second survey as well as the key informant interviews. Of the 38 principals, 36 completed the survey.

The second survey, targeting English instructors, gathered information on instructors’ type of employment (e.g., institute faculty or adjunct lecturers); length of employment; student academic focus (e.g., midwifery or nursing); hours of English instruction provided as part of the midwifery diploma program; whether a standard English curriculum was used and if it was tailored toward the healthcare profession; use of digital content in teaching; education and experience in English teaching; and their views on student barriers to learning English. These measures were chosen to provide a basic criterion for assessing quality of English instruction, materials and resources available to students. For instance, instructors’ status as faculty would indicate a stronger degree of integration and belonging to the institute midwifery program than a guest lecturer status which allows for part time instruction with little job security. In addition, use of a standard, professionally developed English curriculum and integration of digital content into classroom learning would be indicative of higher quality than learning materials developed informally by instructors themselves without use of listening content by native speakers in classrooms. The survey was piloted with two English instructors. Based on their feedback, minor adjustments were made to one question, and it was determined that responses were best gathered by phone due to instructors’ limited internet access. Of the 14 instructors contacted, 11 were reached and provided survey responses by phone.

The web-search gathered information on available English language instruction programs for adults in Bangladesh, and the viability of tapping into any of them to improve English competency among midwifery students and faculty. Keywords Bangladesh  +  English courses , English training , English classes , study English and learn English were typed into Google’s search platform. Eleven English language instruction programs were identified. Following this, each program was contacted either by phone or email and further detail about the program’s offerings was collected.

Unstructured key informant interviews were carried out with select knowledgeable individuals to substantiate and enhance the credibility of the survey and web-search findings. Three in-country expert English language instructors and four managers of English language teaching programs were interviewed. In addition, interviews were held with three national-level stakeholders knowledgeable about work to make functional technologically advanced English language laboratories that had been installed at many of the training institutes. Question prompts included queries such as, ‘In your experience, what are the major barriers to Bangla-medium educated students studying in English at the university level?’, ‘What effective methods or curricula are you aware of for improving student English to an appropriate competency level for successful learning in English?’, and, ‘What options do you see for the language lab/s being used, either in their originally intended capacity or otherwise?’

Data analysis

All data were analyzed by the lead researcher. Survey data were entered into a master Excel file and grouped descriptively to highlight trends and outliers, and ultimately enable a clear description of the structure and basic quality attributes (e.g., instructors’ education, hours of English instruction, and curriculum development resources used). Web-search findings were compiled in a second Excel file with columns distinguishing whether they taught general English (often aimed at preparing students for international standard exams), Business English, or English for Specific Purposes (ESP). This enabled separation of standalone English courses taught by individual instructors as part of vocational or academic programs of study in other fields, and programs with an exclusive focus on English language acquisition. Key informant interviews were summarized in a standard notes format using Word. An inductive process of content analysis was carried out, in which content categories were identified and structured to create coherent meaning [ 7 ]. From this, the key overall findings and larger themes that grew from the initial survey and web-search results were drawn out.

The surveys (Tables  1 and 2 ) found that English instructors are primarily long-term male guest lecturers employed at each institute for more than two years. All principal respondents indicated that there is a need for English instruction—18 of the 19 reported that this is best done through a combination of in-person and computer-based instruction. Ten institutes reported that they have an English language lab, but none were used as such. The other institutes did not have language labs. The reported reasons for the labs not being in use were a lack of trained staff to operate them and some components of the technology not being installed or working properly. The findings from the instructors’ survey indicated that English instructors typically develop their own learning materials and teach general English without tailoring content to healthcare contexts. Only two mentioned using a standard textbook to guide their instruction and one described consulting a range of English textbooks to develop learning content. None reported using online or other digital tools for language instruction in their classrooms. Most instructors had an advanced degree (i.e., master’s degree) in English, and seven had received training in teaching English. Interviews with instructors also revealed that they themselves did not have mastery of English, as communication barriers in speaking over the phone appeared consistently across 10 of the 11 instructor respondents.

The web-search and related follow up interviews found that most English instruction programs (10 out of the 11) were designed for teaching general English and/or business English. The majority were offered through private entities aiming to reach individuals intending to study abroad, access employment that required English, or improve their ability to navigate business endeavors in English. One program, developed by the British Council, had flexibility to tailor its structure and some of its content to the needs of midwifery students. However, this was limited in that a significant portion of the content that would be used was developed for global audiences and thus not tailored to a Bangladeshi audience or to any specific discipline. One of the university English programs offered a promising ESP model tailored to midwifery students. It was designed by BRAC University’s Institute of Language for the university’s private midwifery training program.

Three themes emerged from the other key informant interviews (Table  3 ). The first was that, in addition to students’ challenges with English, faculty mastery of English presented challenges as well. Of the 34 faculty members intending to participate in the 2019–2020 cohort for the Dalarna master’s degree, half did not pass the prerequisite English exam. Ultimately, simultaneous English-Bangla translation was necessary for close to half of the faculty to enable their participation in the master’s program. English language limitations also precluded one faculty member from participating in an international PhD program in midwifery.

The second theme highlighted the language labs’ lack of usability. The language labs consisted of computers, an interactive whiteboard, audio-visual equipment, and associated software to allow for individualized direct interactions between teacher and student. However, due to the lack of appropriately trained staff to manage, care for and use the language lab equipment, the investment required to make the labs functional appeared to outweigh the learning advantages doing so would provide. Interviews revealed that work was being done, supported by a donor agency, on just one language lab, to explore whether it could be made functional. The work was described as costly and challenging, and required purchasing a software license from abroad, thus likely being impractical to apply to the other labs and sustain over multiple years.

The third theme was around the ESP curriculum model. The program developers had employed evidence-informed thinking to develop the ESP learning content and consulted student midwives on their learning preferences. Due to the student input, at least 80% of the content was designed to directly relate to the practice of midwifery in Bangladesh, while the remaining 10–20% references globally relevant content. This balance was struck based on students’ expressed interest in having some exposure to English usage outside of Bangladesh for their personal interest. For conversation practice, the modules integrated realistic scenarios of midwives interacting with doctors, nurses and patients. Also built into written activities were exercises where students were prompted to describe relevant health topics they are concurrently studying in their health, science or clinical classes. Given the midwifery students’ educational backgrounds and intended placements in rural parts of Bangladesh, an ESP curriculum model appeared to be the most beneficial existing program to pursue tapping into to strengthen English competencies within midwifery programs. This was because the content would likely be more accessible to students than a general English course by having vocabulary, activities and examples directly relevant to the midwifery profession.

The study findings demonstrate key weaknesses in the current model of English instruction taught in public midwifery programs. Notably, the quantitative findings revealed that some English instructors do not have training in teaching English, and none used standard curricula or online resources to structure and enhance their classroom content. In addition, weak mastery of English among midwifery faculty was identified in the qualitative data, which calls into question faculty’s ability to fully understand and accurately convey content from English learning materials. Global literature indicates that this is not a unique situation. Many healthcare faculty and students in low-resource settings, in fact, are faced with delivering and acquiring knowledge in a language they have not sufficiently mastered [ 8 ]. As a significant barrier to knowledge and skill acquisition for evidence-based care, this requires more attention from global midwifery educators [ 9 ].

Also holding back students’ English development is the finding from both the quantitative and qualitative data that none of the high-tech language labs were being used as intended. This indicates a misalignment with the investment against the reality of the resources at the institutes to use them. While setting up the costly language labs appears to have been a large investment with little to no return, it does demonstrate that strengthening English language instruction in post-secondary public education settings is a priority that the Bangladesh government is willing to invest in. However, scaling up access to an ESP curriculum model tailored to future midwifery practitioners in Bangladesh may be a more worthwhile investment than language labs [ 10 ]. 

The ESP approach teaches English for application in a specific discipline. It does this by using vocabulary, examples, demonstrations, scenarios and practice activities that are directly related to the context and professions those studying English live and work (or are preparing to work) in. One way ESP has been described, attributed to Hutchinson and Waters (1987), is, “ESP should properly be seen not as any particular language product but as an approach to language teaching in which all decisions as to content and method are based on the learner’s reason for learning” [ 11 ]. It is proposed by linguistic education researchers as a viable model for strengthening language mastery and subject matter comprehension in EMI university contexts [ 12 ].

Though it did not arise as a finding, reviewing the literature highlighted that Bangla language instruction may be an additional, potentially viable option. Linguistic research has long shown that students learn more thoroughly and efficiently in their mother tongue [ 12 ]. Another perhaps more desirable option may be multilingualism, which entails recognizing native languages as complementary in EMI classrooms, and using them through verbal instruction and supplemental course materials. Kirkpatrick, a leading scholar of EMI in Asia, suggests that multilingualism be formally integrated into EMI university settings [ 13 ]. This approach is supported by evidence showing that the amount of native language support students need for optimal learning is inversely proportional to their degree of English proficiency [ 14 ].

Ultimately, despite the language related learning limitations identified in this study, and the opportunities presented by native language and multilingualism approaches, there remains a fundamental need for members of the midwifery profession in Bangladesh to use up-to-date guidance on evidence-based midwifery care [ 11 ]. Doing that currently requires English language competence. Perhaps a tiered system of requirements for English competencies that are tied to diploma, Bachelor’s, Master’s and PhD midwifery programs could build bridges for more advanced students to access global resources. Higher academic levels might emphasize English more heavily, while the diploma level could follow a multilingualism approach—teaching using an ESP curriculum and integrating Bangla strategically to support optimal knowledge acquisition for future practice in rural facilities. Ideally, scores on a standard English competency exam would be used to assess students’ language competencies prior to entrance in English-based programs and that this would require more stringent English skill development prior to entering a midwifery program.

Methodological considerations

One of the limitations of this study is that it relied on self-reports and observation, rather than tested language and subject matter competencies. Its strengths though are in the relatively large number of education institutes that participated in the study, and the breadth of knowledge about faculty and student subject matter expertise among study co-authors. It was recognized that the lead researcher might be biased toward pre-determined perceptions of English competencies being a barrier to teaching and learning held by the lead institution (UNFPA). It was also recognized that due to the inherent power imbalance between researcher and participants, the manner of gathering data and engaging with stakeholders may contribute to confirmation bias, with respondents primarily sharing what they anticipated the researcher wished to hear (e.g., that English needed strengthening and the lead agency should take action to support the strengthening). The researcher thus engaged with participants independently of UNFPA and employed reflexivity by designing and carrying out the surveys to remotely collect standard data from institutes, as well as casting a wide net across institutes to increase broad representation. In addition, while institutes were informed that the surveys were gathering information about the English instruction within the institutes, no information was shared about potential new support to institutes. Finally, the researcher validated and gathered further details on the relevant information identified in the surveys through key informant interviews, which were held with stakeholders independent of UNFPA.

Adapting and scaling up the existing ESP modules found in this study, and integrating Bangla where it can enhance subject-matter learning, may be a useful way to help midwifery students and faculty improve their knowledge, skills, and critical thinking related to the field of midwifery. Given the educational backgrounds and likely work locations of most midwives in Bangladesh and many other LMICs, practitioners may want to consider investing in more opportunities for local midwives to teach and learn in their mother tongue. This type of investment would ideally be paired with a tiered system in which more advanced English competencies are required at higher-levels of education to ensure integration of global, evidence-based approaches into local standards of care.

Declarations.

Data availability

The datasets used and analyzed during the current study are available from the corresponding author upon reasonable request.

Abbreviations

Bangladesh Rehabilitation Assistance Committee

English medium instruction

English for Specific Purposes

Low- and Middle-Income Countries

Ministry of Health and Family Welfare

United Nations Population Fund

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Acknowledgements

The authors acknowledge Farida Begum, Rabeya Basri, and Pronita Raha for their contributions to data collection for this assessment.

This project under which this study was carried out was funded by funded by the Foreign Commonwealth and Development Office.

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Williams, A., Stevens, J., Anderson, R. et al. Challenges and opportunities of English as the medium of instruction in diploma midwifery programs in Bangladesh: a mixed-methods study. BMC Med Educ 24 , 523 (2024). https://doi.org/10.1186/s12909-024-05499-8

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The digital transformation in pharmacy: embracing online platforms and the cosmeceutical paradigm shift

• Ahmad Almeman   ORCID: orcid.org/0000-0002-6521-9463 1  

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In the face of rapid technological advancement, the pharmacy sector is undergoing a significant digital transformation. This review explores the transformative impact of digitalization in the global pharmacy sector. We illustrated how advancements in technologies like artificial intelligence, blockchain, and online platforms are reshaping pharmacy services and education. The paper provides a comprehensive overview of the growth of online pharmacy platforms and the pivotal role of telepharmacy and telehealth during the COVID-19 pandemic. Additionally, it discusses the burgeoning cosmeceutical market within online pharmacies, the regulatory challenges faced globally, and the private sector’s influence on healthcare technology. Conclusively, the paper highlights future trends and technological innovations, underscoring the dynamic evolution of the pharmacy landscape in response to digital transformation.

Introduction

Digital technology is driving a massive shift in the worldwide pharmacy industry with the goal of improving productivity, efficiency, and flexibility in healthcare delivery. In the pharmacy industry, implementing digital technologies like automation, computerization, and robotics is essential to cutting expenses and enhancing service delivery​​ [ 1 ]. With a predicted 14.42% annual growth rate, the digital pharmacy market is expanding significantly and is expected to reach a market volume of about $35.33 billion by 2026. This expansion reflects the pharmacy industry’s growing reliance on and promise for digital technologies​ [ 2 ].

Pharmacy services have always been focused on face-to-face communication and paper-based procedures. However, the drive for more effective, transparent, and patient-centered healthcare is clear evidence of the growing need for digital transformation. Breakthroughs like mobile communications, cloud computing, advanced analytics, and the Internet of Things (IoT) are reshaping the healthcare sector. These breakthroughs have the potential to greatly improve patient care and service delivery, as demonstrated in other industries including banking, retail, and media [ 3 ].

In the pharmacy industry, a number of significant factors are hastening this digital transition. Important concerns include the desire for cost-effectiveness, enhanced patient care, and more transparency and efficiency in medication development and manufacture. This change has been made even more rapid by the COVID-19 pandemic, which has highlighted the necessity for digital solutions to address the difficulties associated with providing healthcare in emergency situations [ 4 ].

In terms of specific technologies being adopted, artificial intelligence (AI) and machine learning are playing a pivotal role. The McKinsey Global Institute estimates that AI in the pharmaceutical industry could generate nearly $100 billion annually across the U.S. healthcare system. The use of AI and machine learning enhances decision-making, optimizes innovation, and improves the efficiency of research and clinical trials. This results in more effective patient care and a more streamlined drug development process​ [ 5 ].

The digital transformation in the pharmacy sector represents a pivotal shift in the delivery and experience of healthcare services. This evolution is more than a transient trend; it’s a fundamental alteration in the healthcare landscape [ 6 ]. The adoption of digital technologies is reshaping aspects of healthcare, including patient engagement and medication adherence, leading to enhanced healthcare outcomes. Research indicates that digital tools in pharmacy practices have resulted in more individualized and efficient patient care. Telehealth platforms, exemplified by companies like HealthTap, are being increasingly incorporated by pharmacies to augment patient care via technological solutions. The contribution of digital health technology to medication adherence is notable, employing a variety of tools such as SMS, mobile applications, and innovative devices like virtual pillboxes and intelligent pill bottles. These advancements are pivotal in addressing the critical issue of medication nonadherence in healthcare. Furthermore, digital health tools are empowering pharmacists with expanded clinical responsibilities, particularly in the management of chronic diseases like diabetes, where apps and smart devices provide essential features such as blood glucose tracking and medication reminders. This comprehensive integration of digital health into pharmacy practice signifies a transformative era in healthcare delivery and patient management [ 7 ].

Online platforms are being used increasingly by the pharmaceutical sector and educational institutions to improve efficiency, flexibility, and accessibility. The telepharmacy program at CVS Pharmacy is an example of how telepharmacy services, which provide remote counseling and prescription verification, bring pharmaceutical care to underprivileged communities [ 8 ]. Prescription accuracy and drug management are enhanced by e-prescribing software like Epic’s MyChart and digital health apps like Medisafe [ 9 ; 10 ]. Blockchain technology is also being investigated for transparent and safe supply chain management. Continuous learning and professional networking are made possible in education by Virtual Learning Environments (VLEs) like Moodle [ 11 ], simulation software like SimMan 3G Plus [ 12 ], Continuing Professional Development (CPD) platforms like the American Pharmacists Association [ 13 ], and online conference platforms, as shown in Fig.  1 . While these platforms offer significant benefits like enhanced access and cost-effectiveness, they also present challenges, including addressing the digital divide and ensuring the quality and credibility of online services to maintain professional standards and patient safety.

In this review, we summarized the digital transformation in the pharmacy sector, emphasizing the integration of online platforms and the emerging significance of cosmeceuticals. We discussed the global shift towards digital healthcare, including telehealth and online pharmacy services, and how these changes have been accelerated by the COVID-19 pandemic. The paper also examined the impact of digital technologies on pharmacy practice and education, with a focus on telepharmacy services, e-prescribing software, and digital health apps. Additionally, it addresses the challenges and opportunities presented by this transformation, including regulatory and safety concerns, and the need for continuous professional development in the digital era.

Comprehensive overview of different platforms in the pharmaceutical industry and education illustrating purposes and exemplary cases

The global impact of online pharmacy platforms

In recent years, the landscape of pharmacy practice and education has undergone a significant transformation, driven by technological advancements and catalyzed by the global COVID-19 pandemic. A study highlighting the increasing consumer trust in online medication purchases pre, during, and post-pandemic reveals a shift in consumer behavior towards online pharmacies [ 14 ]. This trend underscores a greater reliance on these platforms, where the perceived benefits significantly outweigh the perceived risks, indicating a positive reception and growing trust in digital healthcare solutions.

The adoption of telehealth, including telepharmacy, exemplifies this shift. In the United States, patient adoption of telehealth services surged from 11% in 2019 to 46%, with healthcare providers expanding their telehealth visits [ 15 ]. This shift is a reflection of how adaptable the healthcare sector is to digital platforms and how customer acceptance is increasing. The epidemic has also served as a catalyst, hastening the creation and uptake of online telepharmacy services throughout the world. The “new normal” has forced the addition of new platforms to support established sources of health information. The creation and evaluation of an online telepharmacy service in the Philippines during the pandemic serves as an example of this, demonstrating how quickly the global pharmacy industry adopted digital solutions. These services are essential for providing and elucidating pharmaceutical information within the context of primary healthcare delivery; they are not merely supplementary [ 16 ].

Simultaneously, pharmacist-led companies such as MedEssist and MedMehave, innovated digital platforms to facilitate services like flu shots or COVID-19 tests, reflecting a move towards customer-centric, digital-first services [ 17 ]. This transition enhances convenience and access to care but also introduces significant regulatory challenges. As the growth of online medicine sales disrupts traditional pharmacy markets, navigating these challenges becomes crucial for maintaining patient safety, quality standards, and fostering a trustworthy online healthcare environment [ 18 ].

Parallel to the practice changes, educational platforms for pharmacy have also evolved, especially under the impetus of the pandemic. These platforms have integrated a mix of traditional and student-centered teaching methodologies, including remote didactic lectures and on-site experiential training. The implementation of blended learning approaches, which combine remote lectures with on-site laboratory classes, reflects a broader educational trend towards hybrid models. This approach aims to leverage the advantages of both online and traditional methods, offering a more flexible and potentially more effective educational experience [ 19 ].

It takes more than just implementing new tools to integrate educational technology into pharmacy education, it also requires understanding how these technologies affect instruction and student learning. To effectively improve the educational experience, their utilization must have a purpose. There is an increasing amount of scholarly interest in this field, as evidenced by systematic reviews of the effects of new technologies on undergraduate pharmacy teaching and learning [ 20 ]. These digital platforms will probably become more significant in the future of pharmacy education, helping to mold the profession and guaranteeing that pharmacists are equipped to fulfill the ever-changing demands of the healthcare system. This development is indicative of a larger trend in the healthcare industry toward a more flexible, patient-focused, and technologically advanced environment [ 21 ].

Digital transformation in global healthcare

The recent advancements in digital transformation within global healthcare are significantly reshaping the landscape of healthcare and pharmacy services. These transformations are largely driven by the integration of digital technologies, which are redefining the tools and methods used in health, medicine, and biomedical science, ultimately aiming to create a healthier future for people worldwide [ 22 ]. In a 2018 report [ 23 ], Amazon’s potential entry into the $500 billion U.S. pharmacy market, the second-largest retail category, through mail-order and online pharmacies was highlighted as a significant industry disruptor. With licenses in at least 12 states in the US and a strategy focused on bypassing middlemen, Amazon’s historical success positions it to transform the pharmacy landscape, promising enhanced efficiency and cost savings for consumers.

One of the critical areas identified in recent research is the establishment of five priorities of e-health policy making: strategy, consensus-building, decision-making, implementation, and evaluation. These priorities emerged from stakeholders’ perceptions and are crucial for the effective integration and adoption of digital health technologies​ [ 24 ]. This holistic approach is increasingly relevant for scholars and practitioners, suggesting a focus on how multiple stakeholders implement digital technologies for management and business purposes in the healthcare sector [ 25 ]​​. The deployment of technological modalities, encompassed within five distinct clusters, can facilitate the development of a digital transformation model. This model ensures operational efficiency through several dimensions: enhanced operational efficacy by healthcare providers, the adoption of patient-centered methodologies, the integration of organizational factors and managerial implications, the refinement of workforce practices, and the consideration of socio-economic factors [ 25 ].

Studies focusing on value creation through digital means suggest healthcare as a consumer-centric realm ripe for center-edge transformations, characterized by self-service and feedback cycles. These transformations are vital in addressing inherent tensions between patients and physicians, steering the focus towards value co-creation and service-dominant logic [ 26 ]. Participatory design and decision-making approaches are emphasized for enhancing health information technology’s performance and institutional healthcare innovation. Such approaches are particularly crucial in developing national electronic medical record systems and improving chronic disease treatment through electronic health records. Additionally, telehealth research integrates patients’ perceptions, contributing to the understanding of technology, bureaucracy, and professionalism within healthcare [ 27 ].

The impact of health information technology (HIT) on operational efficiencies is profound. Empirical studies, such as those by Hong and Lee [ 28 ], Laurenza et al. [ 29 ], and Mazor et al. [ 30 ], demonstrate positive correlations between HIT and patient satisfaction, quality of care, and operational efficiency. However, challenges remain, as Rubbio et al. [ 31 ] highlight deficiencies in resilience-oriented practices for patient safety. Organizational and managerial factors in digital healthcare transformation also receive significant attention. Hikmet et al. [ 32 ] and Agarwal et al. [ 33 ] investigate the role of organizational variables and barriers in HIT adoption, whereas Cucciniello et al. [ 34 ] delve into the interdependence between implementing electronic medical records (EMR) systems and organizational conditions. Further, Eden et al. [ 35 ] and Huber and Gärtner [ 36 ] explore workforce adaptations and the implications of health information systems in hospitals that can increases transparency of work processes and accountability. Lastly, examining healthcare financialization and digital division provides an international perspective, contrasting the regulated environment in the EU with the US’s use of online medical crowdfunding as a potential solution to reduce bankruptcy [ 37 ; 38 ]. Collectively, these studies suggest a comprehensive model where stakeholders leverage digital transformation for management, enhancing operational efficiency in healthcare service providers.

Marques and Ferreira [ 39 ] performed a systematic literature review of digital transformation in healthcare, spanning the period from 1973 to 2018. Utilizing the SMARTER (Simple Multi-attribute Rating Technique Exploiting Ranks) method, 749 potential articles were analyzed, culminating in the prioritization and selection of 53 articles for detailed examination. The literature was organized into seven thematic areas: (1) Integrated management of IT in healthcare, (2) Medical images, (3) Electronic medical records, (4) IT and portable devices in healthcare, (5) Access to e-health, (6) Telemedicine, and (7) Privacy of medical data. It was observed that the predominant focus of research resides in the domains of integrated management, electronic medical records, and medical images. Concurrently, emerging trends were identified, notably the utilization of portable devices, the proliferation of virtual services, and the escalating concerns surrounding privacy. See Fig.  2 for visual representation of multifaceted digital transformation in healthcare.

Visual representation of multifaceted digital transformation in healthcare: a synthesis of provider-patient dynamics, HIT impact, and strategic management. HIT; health information technology, HC; healthcare, EMR; electronic medical records. IT; information technology, Pt.; patient

Telehealth and online pharmacy advancements in pandemic management

In the realm of online pharmacies and telehealth, digital health technologies have been instrumental in managing the COVID-19 pandemic through surveillance, contact tracing, diagnosis, treatment, and prevention. These technologies ensure that healthcare, including pharmacy services, is delivered more effectively, addressing the challenges of accessibility and timely care. The role of telemedicine and e-pharmacies, in particular, has been emphasized in improving access to care worldwide. By enabling remote consultations and drug delivery, these platforms are making healthcare more accessible, especially in regions where traditional healthcare infrastructure is limited or overstretched [ 40 ].

The Canadian Virtual Care Policy Framework advocates for the swift adoption and integration of virtual care, propelled by the COVID-19 pandemic. It emphasizes enhancing access and quality, ensuring equity and privacy, and devising appropriate remuneration models, employing a collaborative, patient-centered approach while addressing digital disparities. During the COVID-19 pandemic, Canadian provinces and territories rapidly adopted virtual health care, leading to 60% of visits being virtual by April 2020, up from 10 to 20% in 2019. However, these implementations were often temporary and not fully integrated into healthcare systems. By August 2020, virtual visits decreased to 40%, with variations across regions, while provinces and territories used temporary billing codes for these services. The framework’s “Diagnostique” provides a thorough analysis of policy enablers and strategies for virtual care, underscoring the need for comprehensive policy and partnership engagement [ 41 ]. In the context of digital transformation in pharmacy, the Hospital News article outlines the application and infrastructure of telepharmacy services in Canada, highlighting the geographical challenges and the early adoption of telepharmacy in certain regions since 2003. It notes the use of various technologies like Medication Order Management, Videoconferencing, and Remote Camera Verification. Although lacking specific quantitative data, the article underscores the necessity for expanded telepharmacy services to ensure uniform care quality across diverse locations [ 42 ].

Similarly, Telehealth offers extensive resources for patients and providers in the United States, emphasizing programs like the Affordable Connectivity Program and Lifeline to facilitate access. The Health Resources and Services Administration enhances telehealth through support services, research, and technical assistance, reflecting a significant outreach impact [ 43 ]. The Office for the Advancement of Telehealth (OAT) under Health Resources and Services Administration (HRSA) works to improve access to quality health care through integrated telehealth services in the US. It supports direct services, research, and technical assistance, with over 6,000 telehealth technical assistance requests sent to Telehealth Resource Centers and approximately 22,000 patients served [ 44 ].

Internationally, In the UK, the National Health Service (NHS) spearheads digital health and care, providing significant innovation opportunities through vast data management. Support for digital health spans various stages, from discovery with organizations like Biotechnology and Biological Sciences Research Council (BBSRC) and Intelligent Data Analysis (IDA) research group, to development with networks such as Catapults and CPRD, and delivery with entities like the Academic Health Science Networks (AHSNs) and DigitalHealth.London. Regulatory bodies like the Medicines and Healthcare products Regulatory Agency (MHRA) and NICE ensure safety and efficacy. The collaborative ecosystem involves academic, healthcare, and industry stakeholders, aiming to enhance health and care services through technology and innovation [ 45 ].

In Australia, the government’s investment of over $4 billion into COVID-19 telehealth measures has facilitated universal access to quality healthcare. This initiative has provided over 85 million telehealth services to more than 16 million patients, with approximately 89,000 healthcare providers engaging in this service delivery. From 1 January 2022, telehealth services, initially introduced in response to COVID-19, will become an ongoing part of Medicare. This will allow eligible patients across Australia continued access to general practice (GP), nursing, midwifery, and allied health services via telehealth, deemed clinically appropriate by the health professional [ 46 ].

European nations such as the Netherlands, Austria, and Italy are at the forefront of implementing cross-organizational patient records, significantly enhancing telehealth communication and facilitating cross-border healthcare. The role of strong government support in advancing telehealth is pivotal. Ursula von der Leyen, the President of the European Commission, has been a prominent advocate for eHealth. She proposed the establishment of a European Health Data Space to streamline health data exchange across member states. France, a leader in telehealth legislation for nearly a decade, has pioneered a public funding scheme for tele-expertise at a national scale. Despite these advancements, challenges like legislative barriers and the lack of consistent political direction continue to impede progress in the telehealth domain​ [ 47 ].

The Asia-Pacific region anticipates a surge in telehealth adoption driven by digital demand and pandemic-induced behavioral changes, while South East Asia exhibits widespread telehealth growth across healthcare aspects [ 48 ]. The telehealth adoption across the Asia-Pacific region has shown remarkable growth between 2019 and 2021 and is projected to continue rising by 2024. China’s adoption nearly doubled to 47% and is expected to reach 76%. Indonesia’s usage more than doubled to 51%, with a forecast of 72%. Malaysia and the Philippines both anticipate reaching a 70% adoption rate, increasing from 30% to 29%, respectively. India’s adoption is projected to more than double to 68%, while Singapore, which had a significant increase from 5 to 45%, is expected to achieve a 60% adoption rate. This trend indicates a robust uptake of telehealth services in the region [ 48 ].

Global telemedicine and E-pharmacy policy dynamics

In the context of telemedicine and e-pharmacy regulations within South East Asia, a notable distinction emerges with Singapore, Malaysia, and Indonesia being the only countries to have formalized legal frameworks governing both telemedicine practices and the dissemination of electronic information. In these countries, tele-consultation is restricted to patients already under the care of healthcare practitioners or as part of ongoing treatment, specifically in Singapore and Malaysia. Additionally, for scenarios requiring more intensive medical intervention, such as new referrals, emergency cases, or invasive procedures, both Malaysia and Indonesia mandate physical presence and face-to-face consultations, emphasizing a cautious and regulated approach to remote healthcare. In Malaysia, the regulations further stipulate that online prescriptions, excluding narcotics and psychotropic substances, are permissible solely under the continuation of care model, reflecting a judicious use of digital prescription services [ 49 ].

In Central and Eastern Europe (CEE), telemedicine has experienced substantial growth, primarily catalyzed by the COVID-19 pandemic, which necessitated rapid advancements in technology and alterations in healthcare practices. The region’s robust digital infrastructure, coupled with the innovative drive of local companies and the challenges posed by an aging demographic, has significantly contributed to this expansion. According to the European Commission’s Market Study on Telemedicine, the global telemedicine market was projected to grow annually by 14% by 2021, a rate that was likely surpassed due to the pandemic’s impact. More specifically, the Europe Telehealth Market, valued at US $6,185.4 million in 2019, is anticipated to witness an annual growth rate of 18.9% from 2020 to 2030. This trend underscores the increasing reliance on and potential of telemedicine in addressing healthcare needs in the CEE region [ 50 ].

In the Middle East, telehealth and telepharmacy, have seen varied degrees of adoption and progress. Despite attempts to reform healthcare delivery in the region, the progress of telemedicine has been somewhat slow, with certain expectations yet to be fully realized. However, there has been notable development in the use and adoption of these technologies [ 51 ]​. In a survey comparing the utilization of digital-health applications in Saudi Arabia and the United Arab Emirates (UAE), it was observed that a higher percentage of Saudi participants have utilized online pharmacy services (48%) compared to the UAE (36%). Conversely, awareness of teleconsultation services without prior use was higher in the UAE (43%) than in Saudi Arabia (35%). Retention data indicates that a significant proportion of users in both countries continue to engage with these services, with 80% of Saudi participants and 71% of UAE participants using teleconsultations at varying frequencies. Notably, a substantial majority of users in Saudi Arabia reported regular use of online pharmacies (90%), slightly higher than the UAE (78%), reflecting robust ongoing engagement with these digital health modalities. Notably, consumer adoption of telehealth products is primarily driven by time savings (48%) and convenience (47%), with 24-hour accessibility and efficacy both influencing 34% of users. Affordability and personal recommendations are also notable factors, while a wide range of options and quality are lesser but relevant considerations [ 52 ].

In response to the COVID-19 pandemic, a cross-sectional study was conducted among 391 licensed community pharmacists in the United Arab Emirates to assess the adoption and impact of telepharmacy services. The study revealed a predominant use of telepharmacy services, particularly via phone (95.6%) and messaging applications (80.0%). The findings highlighted that pharmacies with more pharmacists and those operating as part of a group or chain were more likely to implement a diverse range of telepharmacy services. The study identified significant barriers to telepharmacy adoption in individual pharmacies, including limited time, inadequate training, and financial constraints. There was a noticeable shift in service provision during the lockdown, with an increased reliance on telepharmacy, especially among pharmacies serving 50–100 patients per day. However, a reduction in services such as managing mild diseases and selling health products was observed during the lockdown period. The study concluded that telepharmacy played a pivotal role in supporting community pharmacies during the pandemic, with its expansion facilitated by the UAE’s advanced internet infrastructure, supportive health policies, and widespread digital connectivity [ 53 ]. Collectively, these insights reflect a global shift towards integrating and enhancing telehealth services as a response to emerging healthcare needs and technological advancements.

Unni et al. [ 54 ] provided an extensive review of telepharmacy initiatives adopted globally during the COVID-19 pandemic. Predominantly, virtual consultations were utilized to enable at-risk patients and others to remotely access pharmacists, thereby monitoring chronic illnesses, optimizing medication usage, and providing educational support [ 55 ]. Home delivery of medicines was widely implemented to decrease the necessity for in-person visits and mitigate exposure risks [ 56 ]. Additionally, patient education was prioritized to ensure effective management of health conditions from a distance [ 57 ]. Notably, a network of hospitals in China developed cloud-pharmacy care, allowing patients to consult pharmacists via text and the internet, while Spain utilized information and communication technologies for remote pharmaceutical care [ 58 ; 59 ]. Zero-contact pharmaceutical care, introduced in China, facilitated online medication consultations, eliminating direct contact [ 60 ]. The Kingdom of Saudi Arabia and other regions adapted new e-tools and teleprescriptions to enhance service accessibility [ 61 ]. The U.S. focused on credentialing pharmacists for telehealth to ensure competent service provision, and New Zealand implemented hotline numbers for phone consultations to further reduce physical visits [ 62 ; 63 ]. These initiatives reflect a significant shift towards innovative, technology-driven solutions in pharmaceutical care during a global health crisis. Refer to Fig.  3 for a graphical depiction of the worldwide distribution and applications of telepharmacy initiatives.

The global distribution of telepharmacy programs with an analysis of geographical distribution, technological applications, and associated benefits

Tracing the Private Sector’s Impact on Healthcare’s Technological Transformation

The role of the private sector in the fourth industrial revolution.

The World Economic Forum underscores the private sector’s leading role in digital inclusion and the acceleration of actions pertinent to the Fourth Industrial Revolution. This revolution affects economies, industries, and global issues profoundly, indicating the private sector’s critical role in driving technological advancements and digital platforms that deliver impactful healthcare solutions [ 64 ].

Mapping digital transformation in healthcare

A comprehensive analysis performed by Dal Mas et al. [ 65 ] meticulously maps the intricate terrain of digital transformation in healthcare, spotlighting the private sector’s instrumental role. Initially, the investigation encompassed an extensive array of diverse studies, leading to the identification of five main areas of digital technologies: smart health technologies, data-enabled and data collection technologies, Industry 4.0 tools and technologies, cognitive technologies, and drug & disease technologies. These domains frame the future research pathways, primarily steered by the private sector’s innovative drive. A significant proportion of the literature addresses healthcare broadly, suitable for both private and public sectors, yet a notable segment specifically focuses on the private sector’s endeavors, with a pronounced emphasis on the pharmaceutical domain [ 66 ; 67 ].

Public-private partnerships in healthcare delivery

The highlighted technologies, including digital platforms and telemedicine, exemplify the private sector’s trailblazing contributions to digital healthcare advancements. For instance, public-private partnerships (PPP) in India have emerged as a pivotal model for realizing universal healthcare (UHC), especially against the backdrop of acute healthcare shortages and urban-rural divides. Notably, mega PPP projects have successfully deployed technology-enabled remote healthcare (TeRHC), demonstrating its feasibility and impact in reaching isolated communities. These initiatives, overcoming various challenges, serve as a compelling example for global adoption, underscoring the transformative role of PPP in healthcare delivery [ 68 ].. Furthermore, a considerable majority of the literature in telemedicine underscores the necessity for profound research implications, yet a significant minority suggests policy implications [ 69 ; 70 ], reflecting a complex synergy between the private and public sectors in sculpting the digital healthcare framework [ 71 ]. This synthesis underscores the private sector’s critical influence in propelling the digital transformation in healthcare, charting a course that progressively fuses technological innovation with healthcare provision.

A study highlights Indonesia’s strategic initiatives to capitalize on telehealth business opportunities, driven by the Ministry of Research and Technology’s robust support for Technology-Based Start-up Company schemes [ 72 ]. With a demographic boon of 298 million from 2020 to 2024, escalating non-communicable diseases (71%), and a growing base of 222.4 million JKN participants, the stage is set for transformative growth. Despite a critical shortage of health workers (0.4 doctors per 1000 population), the enthusiasm for telemedicine is evident, with 71% satisfaction in hospital telemedicine and 32 million active telehealth users. The Ministry’s foresight in fostering technology start-ups, exemplified by the TEMENIN platform with its 11 health platforms, is steering Indonesia towards a future where high-quality healthcare is accessible and sustainable.

Lab@AOR: a model for PPPs in healthcare sector

The “Lab@AOR” initiative stands as a paradigmatic example of PPPs effectuating digital transformation within the healthcare sector. This strategic collaboration, between the University Hospital of Marche and Loccioni [ 73 ], a private entity, underscores the capacity of PPPs to navigate intricate challenges, stimulate international cooperation, and contribute to the development of sustainable, patient-centric healthcare solutions. Specifically, Lab@AOR was instituted to confront the nuanced challenges associated with the robotization of healthcare service delivery, highlighting the initiative’s role in fostering technological advancement through public and private sector synergy [ 74 ]. The project illustrates the evolution of Lab@AOR through three main phases: the pioneering stage, where groundwork for collaboration was laid; the nurturing stage, where collaborative exchanges were fostered; and the harvesting stage, wherein the potential of the PPP was fully unleashed. In the pioneering stage, Lab@AOR focused on a critical healthcare service component: the in-hospital preparation of medications for oncological patients. The University Hospital of Marche identified a need for innovation to improve service quality, efficiency, and safety, while Loccioni sought a real-life setting to test and refine its robotized system, APOTECAchemo [ 75 ]. This convergence of needs led to a symbiotic partnership aiming to enhance healthcare delivery through technological advancement.

During the nurturing stage, the partnership expanded the scope of APOTECAchemo to include non-oncological medications and developed additional tools like APOTECAps for manual preparation support. This phase was characterized by intensive collaboration, knowledge sharing, and continuous innovation, demonstrating the dynamic capability of the PPP to adapt and evolve in response to emerging healthcare challenges. The harvesting stage marked the international expansion of Lab@AOR, transforming it from a local initiative to an international community focused on leveraging digitalization and robotization to improve care quality and patient-centeredness. The PPP’s growth was catalyzed by its open perspective and inclusive approach, engaging entities from various cultural and institutional contexts, and fostering a network of 31 nodes across 19 countries and 3 continents.

Advancements in telehealth business models and frameworks

In their investigative study, Velayati et al. [ 76 ] delved into the articulation of emergent business models in telehealth and scrutinized the deployment of established frameworks across a variety of telehealth segments. The research spanned an extensive range of sectors, notably telemonitoring, telemedicine, mobile health, and telerehabilitation, alongside telehealth more broadly. The scope further extended to encompass niche areas such as assisted living technologies, sensor-based systems, and specific fields like mobile teledermoscopy, teleradiology, telecardiology, and teletreatment, presenting a thorough analysis of the telehealth landscape. Within the telemedicine and telehealth services sector, Barker et al. [ 77 ] introduced the Arizona Telemedicine Program (ATP) Model, a quintet-layer approach aimed at efficiently distributing telemedicine services throughout Arizona. Complementing this, Lee and Chang [ 78 ] proposed a four-component model specifically tailored for mobile health (mHealth) services pertaining to chronic kidney disease, focusing on offering a cost-effective platform for disease support and management. In the realm of telemonitoring, Dijkstra et al. [ 79 ] utilized the Freeband Business Blueprint Method (FBBM), which includes service, technological, organizational, and financial domains, to facilitate multiple telemonitoring services. Furthermore, the systemic and economic differences were explored in care coordination through Business to customer (B2C) and business (B2B) models for telemonitoring patients with chronic diseases, with the B2C model’s economic advantages were highlighted [ 80 ].

General telemedicine frameworks also received attention. Lin et al. [ 81 ] constructed a six-component framework analyzing major telemedicine projects in Taiwan, while Peters et al. [ 82 ] developed the CompBizMod Framework in Germany, encompassing value proposition, co-creation, communication and transfer, and value capture, designed to evaluate and enhance competitive advantages in telemedicine. In the specialized field of telecardiology, a comprehensive nine-component sustainable business model was crafted to facilitate mutual benefits for service providers and patients. This model emphasizes the importance of a holistic approach in ensuring the longevity and effectiveness of healthcare delivery within this domain [ 83 ]. Meanwhile, Mun et al. [ 84 ] presented a suite of five teleradiology business models aimed at providing effective, high-quality, and cost-efficient diagnoses.

The teletreatment sector saw innovative models from Kijl et al. [ 85 ], who designed a model for treating patients with chronic pain, focusing on the interrelation of components in the value network and the role of information technology. Complementarily, Fusco and Turchetti [ 86 ] introduced four models for telerehabilitation post-total knee replacement, emphasizing partnerships between care units and equipment suppliers to reduce costs and waiting lists. The mHealth and assisted living technology sector witnessed the introduction of a wearable biofeedback system model by Hidefjäll and Titkova [ 87 ], which employed Alexander Osterwalder’s Business Model Canvas and focused on a comprehensive commercialization process. Additionally, Oderanti and Li [ 88 ] presented a seven-component sustainable business model for assisted living technologies, aimed at encouraging older individuals to invest in eHealth services while reducing the pressure on health systems. These diverse clusters and models reflect the multifaceted nature of telehealth, each tailoring its approach to meet the unique demands of its domain. They collectively aim to optimize service delivery, stakeholder involvement, cost efficiency, and patient care quality, marking significant strides in the ongoing evolution of digital healthcare.

Challenges and biases in healthcare technology

One key aspect is the emergence of novel medical technologies and their potential biases. These biases are often a result of insufficient consideration of patient diversity in the development and testing phases. For example, disparities in the performance of medical devices like pulse oximeters among different racial groups have been observed, potentially due to a lack of diverse representation in clinical trials. This indicates a tendency for the development of healthcare technologies that may not adequately serve all patient populations [ 89 ]. A study on the profitability and risk-return comparison across health care industries highlights the use of return on equity (ROE) as a measure of profitability from a shareholder’s perspective. This measure combines profit margin, asset utilization, and financial leverage. The study analyzed financial data of publicly traded healthcare companies, providing insights into the financial dynamics of the healthcare sector. It revealed that while companies like Pfizer Inc. and UnitedHealth Group reported similar profitability, they had substantial differences in profit margin and asset utilization, indicating diverse financial strategies within the healthcare sector. This study underscores the complexity of financial performance in healthcare, where profitability measures need to be balanced with risk assessment and the broader impact on healthcare provision​ [ 90 ].

Additionally, an article discusses the benefits, pitfalls, and potential biases in healthcare AI. It emphasizes that as the healthcare industry adopts AI, machine learning, and other modeling techniques, it is seeing benefits for both patient outcomes and cost reduction. However, the industry must be mindful of managing the risks, including biases that may arise during the implementation of AI. Lessons from other industries can provide a framework for acknowledging and managing data, machine, and human biases in AI. This perspective is crucial in understanding how the integration of advanced technologies in healthcare can be influenced by the drive for profitability and efficiency, possibly at the expense of equitable and patient-centered care [ 91 ; 92 ].

Cosmeceuticals in the online pharmacy market

Cosmeceuticals, a term derived from the combination of cosmetics and pharmaceuticals, refer to a category of products that are formulated to provide both aesthetic improvements and therapeutic benefits. These products, typically applied topically, are designed to enhance the health and beauty of the skin, going beyond the mere cosmetic appearance. The exploration of cosmeceuticals in the online pharmacy market reveals a multifaceted and rapidly expanding industry. Bridging the gap between cosmetics and pharmaceuticals, they form a significant portion of the skincare industry. Cosmeceuticals are formulated from various ingredients, with their main categories being constantly discussed and analyzed in the scientific community [ 93 ]. They have taken a considerable share of the personal care industry globally, constituting a significant part of dermatologists’ prescriptions worldwide [ 94 ]. This surge is further fueled by increasing consumer demand for effective and safe products, including anti-aging skincare cosmeceuticals, a need which has been intensified by concerns over pollution, climate change, and the COVID-19 pandemic [ 95 ].

The global cosmeceuticals market is experiencing robust growth. Valued at USD 56.78 billion in 2022, it’s projected to expand to USD 95.75 billion by 2030, with a compound annual growth rate (CAGR) of 7.45%. This growth trajectory is propelled by the innovative integration of bioactive ingredients known for their medical benefits​ [ 96 ]. Another report confirms this upward trend, indicating the market was worth $45.56 billion in 2021 and is on a path of significant growth to USD 114 billion by 2030. The global disease burden is significantly impacted by various skin diseases, with dermatitis, psoriasis, and acne vulgaris among the most prevalent, contributing 0.38%, 0.19%, and 0.29% respectively. The pervasive nature of these conditions drives a substantial demand for effective treatments, propelling the integration of cosmeceuticals into the online pharmacy market. This integration not only offers convenient access to a range of therapeutic skincare products but also caters to the rising consumer inclination towards self-care and preventive healthcare. As a result, the online availability of cosmeceuticals is not just addressing the immediate needs of individuals suffering from skin conditions but is also reshaping the landscape of personal healthcare by making specialized treatments more accessible and customizable [ 97 ]. See Fig.  4 .

The left panel presents the market share distribution for key segments in the cosmeceuticals industry in 2021, including Skin Care Segment, and Supermarket & Specialty Stores, for Asia Pacific Revenue, with percentages for each category. The right panel displays the market value progression over time from 2021 to the projected value in 2030, with bold numbers indicating the value in billion USD for each year. The lower horizontal bar chart depicts the percentage contribution of various skin diseases to the global disease burden

Several factors are contributing to this expansion of the cosmeceuticals market. The market is driven by innovation in natural ingredients and a significant penetration of internet, smartphone, and social media applications, which attract potential consumer populations and reflect constantly changing consumer behavior [ 98 ]​​. The cosmeceuticals market’s robust CAGR and revenue share, especially in regions like Asia Pacific, further signify its burgeoning presence and potential within the global market [ 99 ]​. Integration into online pharmacies is a key aspect of this market’s evolution, offering easier access to these products for a wider customer base. As the market continues to grow, it’s anticipated that the blend of cosmeceuticals with online pharmaceutical platforms will become increasingly seamless, offering consumers a diverse range of accessible, effective, and beneficial skincare and health products. This integration is likely to be driven by the growing trend of e-commerce and digitalization in healthcare and personal care sectors.

The landscape of online pharmacies, particularly concerning cosmeceuticals, is evolving. While the overall penetration for non-specialty drugs in mail-order and online pharmacies is low, they represent a significant portion of specialty prescription revenues at 37%. Despite this, only 13% of consumers consider these as their primary pharmacy choice, indicating a growing but still emerging market​​​​. Strategies are in place to enhance the market appeal of these pharmacies, focusing on speed, convenience, and personalized experiences, such as video telehealth visits, to attract a broader consumer base [ 100 ].

The dissertation “L’Oréal Portugal: A Digital Challenge for the Active Cosmetics Division” authored by Ascenso [ 101 ] provides an in-depth examination of the impact of digital evolution on the Portuguese cosmeceutical sector and its implications for L’Oréal, a significant cosmetics company. It posits that while L’Oréal has foundational digital competencies, the rapidly evolving digital landscape presents a broad spectrum of potential risks and opportunities. The study details the operations of L’Oréal’s Active Cosmetics Division, which manages brands predominantly sold in pharmacies and parapharmacies, and explores the potential repercussions of digitalization on L’Oréal Portugal’s strategic and operational frameworks. Furthermore, the thesis highlights the expanding role of e-pharmacies and the need for legal reforms to facilitate their operation. It discusses the prevalent trends in the cosmetic industry, such as the increasing demand for natural, male-focused, and environmentally friendly products. The dissertation scrutinizes L’Oréal’s strategic pillars, including innovation, acquisition, and regional growth, emphasizing the need for the company to integrate advanced technologies and recalibrate its business methodologies in light of digital progression [ 101 ]. Although L’Oréal has initiated some digital strategies targeting consumers and pharmacies, there’s a recognized need for an intensified focus on digital marketing aimed at clients. An exploratory attempt by L’Oréal to implement an online ordering platform for pharmacies did not meet success, indicating possible industry unreadiness for such advancements. This case study serves as a critical examination of how traditional companies in the pharmaceutical and cosmetics sectors must adapt to the digital age’s challenges and opportunities [ 101 ].

In a collaborative endeavor with L’Oréal, an associated digital agency provided a comprehensive suite of services that encompasses the full management of social media pages, the development of e-commerce websites, the establishment of Customer Relationship Management (CRM) platforms tailored for pharmacies, and the execution of digital campaigns leveraging QR codes, SMS marketing, and newsletters. These digital tools confer a competitive edge, facilitating a deeper comprehension of consumer behavior and the potential to augment value extraction from customer interactions. For the laboratories, particularly those associated with cosmetics, the advantages are twofold: an increase in sell-out figures, thereby enhancing direct sales to end consumers, and a boost in sell-in metrics, reflecting a rise in transactions to pharmacies or wholesalers. The online ordering feature, as noted by João Roma, a manager at La Roche-Posay, could result in a cacophony of processes if laboratories were to individually develop distinct methods. He advocates for the utilization of pre-existing platforms, such as the established e-learning infrastructure, to spearhead ventures into the online marketplace [ 101 ].

A survey conducted specifically for L’Oréal’s e-learning platform, cosmeticaactiva.pt [ 102 ], across the Portuguese landscape garnered responses from 324 participants, comprising 71% general pharmacists, 13% technical assistants, 8% directors, 7% individuals responsible for procurement from laboratories, and 2% beauty/cosmetic advisors. The findings from this survey underscore the pervasive adoption of digital tools within the pharmacy sector: 82% of respondents affirmed the presence of their pharmacies on social media platforms, 80% reported the use of basic management software, 64% indicated the deployment of advanced management systems, 61% were conversant with online ordering systems directed at laboratories, 38% utilized a store locator, 28% had an established website presence, and a smaller segment of 12% offered online shopping facilities.

Another survey conducted within this study to evaluate the significance of dermocosmetic products in pharmacies yielded a mean importance rating of 4.38 out of 5, indicating that a majority of pharmacists consider these products to be highly important to their business operations. Factors critical to the differentiation of a proficient laboratory/supplier were innovation and cost-effectiveness, with mean scores of 1.9 and 2.7 respectively, on a scale from 1 (most important) to 5 (least important). A substantial majority of pharmacists, amounting to 81.8%, perceive their pharmacies as beacons of innovation and modernity. Detailed interviews elucidated that digital tools are indispensable in augmenting sales for cosmeceutical products by catalyzing demand—a dynamic not feasible with medicinal products. These tools are paramount in managing customer loyalty, facilitating enhanced communication with existing clients via online and mobile channels. Despite the challenges posed by digitalization, particularly in the realms of logistics and human resources, the management at L’Oréal is well-equipped to swiftly adapt to the evolving business landscape, as evidenced by the proactive adoption and integration of these digital strategies [ 101 ] as illustrated in Fig.  5 .

Results from Ascenso [ 101 ] survey assessing digital challenges for L’Oréal in the Portuguese cosmeceutical sector. Digital Tools Usage in Pharmacies (upper left) : the bar chart showing the percentage of respondents using various digital tools in pharmacies. Suppliers’ Choosing Factors (upper right) : the bar chart displaying the mean scores of factors that distinguish a good laboratory/supplier. General Pharmacists Opinion (lower left) : A line chart illustrating the mean ratings of pharmacists’ opinions on whether the pharmaceutical sector is modern, changing, conducive to innovations, adapted to consumer needs, and more developed than other sectors. Importance of Digital Development Tools for Pharmacies (lower right) : A vertical bar chart demonstrating the mean scores for the importance of different digital development tools for pharmacies

The digital transformation strategies, exemplified by companies like L’Oréal, extend beyond the mere targeting of end consumers, encompassing the perspectives of various stakeholders, including retailers. This broadened focus reflects a holistic and integrated approach to digital marketing and customer engagement, indicative of a larger trend within the market. The significance of digital channels in facilitating comprehensive customer interaction and brand development is increasingly recognized. The distinction of organizations such as L’Oréal in their digital initiatives highlights the competitive advantage that can be garnered through innovative digital strategies.

The receptiveness of industry professionals, such as pharmacists, to emerging digital trends, along with the readiness of companies to engage in non-face-to-face sales models, marks a paradigm shift in traditional sales and distribution methods. This shift is reflective of a broader market trend where digital platforms are becoming integral to the customer journey. Furthermore, the potential for online sales in specialized sectors, such as dermocosmetics, and the benefits that organizations derive from the technological advancement of their client base, underscore an escalating acknowledgment of e-commerce and digital tools as crucial elements of a business strategy. This trend, with L’Oréal as a prime example, emphasizes the broader market movement towards digital transformation, not merely as an option but as a necessity for maintaining relevance and competitiveness in an ever-evolving market landscape.

The global regulatory landscape for cosmeceuticals

Sophisticated regulatory legislation and enforcement mechanisms characterize many developed countries such as the USA, EU Member States, Canada, and Japan. These nations, along with influential organizations like the World Health Organization (WHO), significantly shape international market rules and regulations due to their market size and regulatory capacity [ 103 ]. The WHO is particularly noted for its crucial role in setting global standards, with a focus on developing and promoting international standards related to food, biological, pharmaceutical, and similar products [ 104 ]. In contrast to pharmaceuticals, the cosmetic industry necessitates a more advanced international regulatory framework due to consumers’ extensive exposure to these products. The distinction between cosmetics and pharmaceuticals varies significantly across different countries, with the USA employing a voluntary registration system for cosmetics and the EU and Japan requiring mandatory product filings prior to marketing [ 105 ]. Concerns over the safety of pharmaceutical and cosmetic products are highlighted, with an increasing consumer focus on “natural, ecological, and clean” products [ 106 ]. However, the lack of a regulatory framework for these categories underscores the need for more advanced regulations to mitigate health risks.

Intergovernmental cooperation is emphasized, with the US and EU portrayed as dominant players in the pharmaceutical and cosmetic industries, respectively. Regulatory capacity, which is essential for defining, implementing, and monitoring market rules, varies among countries and markets. This capacity depends on several factors, including staff expertise, statutory sanctioning authority, and the degree of centralization of regulatory authority [ 103 ]. The regulatory systems of the EU and US are explored, focusing on their unique approaches to medicine authorization and regulation. The European Medicines Agency (EMA) in the EU and the Food and Drug Administration (FDA) in the US serve as pivotal regulatory bodies [ 107 ; 108 ]. The EMA’s centralized procedure and the FDA’s premarket approval process are detailed, along with subsequent postmarket regulatory procedures. For instance, EU and US cosmetic regulations are compared, revealing differences in their approaches and the evolution of the EU’s regulatory landscape through various amendments and directives. In particular, directive 76/768/EC has been superseded by Regulation (EC) N° 1223/2009, serving as the principal regulatory framework for finished cosmetic products in the EU market. This regulation enhances product safety, optimizes the sector’s framework, and eases procedures to promote the internal cosmetic market. Incorporating recent technological advancements, including nanomaterials, it maintains an internationally acknowledged regime focused on product safety without altering existing animal testing prohibitions [ 109 ].

The Eurasian Economic Union’s (EAEU) regulatory framework for medicines and medical devices is detailed, including the legal framework established for regulating the circulation of these products. The conformity assessment methods, such as the EAC Declaration and the State Registration process, are required for manufacturers to demonstrate their products’ compliance with the standards [ 110 ]. Armenia is also part of the EAEU’s legal framework, which aims to unify regulations for the production and registration of pharmaceuticals and medical products by 2025. This unification is expected to reduce administrative costs for manufacturers and improve medicinal products for patients. Despite significant developments in the cosmetics industry, Armenia does not have an extensive regulatory framework for it. Prior to joining the EAEU, the only regulation concerning cosmetic products was the Order of the Minister of Health of the Republic of Armenia on “Hygiene Requirements of the Production and Safety of Perfume-Cosmetic Products.” Since joining the EAEU, Armenia has unified its national legislation with EAEU regulations, but there are challenges and gaps in the direct applicability of the EAEU’s technical regulations in the country [ 111 ].

In the context of the necessity for clear regulatory framework stems from two reasons. Firstly, cosmeceuticals - products straddling cosmetics and drugs - demand intensified regulatory attention. Examples include the 2007 FDA seizure of Jan Marini’s Age Intervention Eyelash, which contained the drug ingredient bimatoprost, and products boasting human stem cell cultured media, which claim rejuvenating effects but may pose safety risks due to minimal oversight [ 112 ]. A noted 1450% increase in FDA warnings (from 4 to 62 letters) between 2007 and 2011 and 2012–2017, with 8 targeting stem cell ingredient promotions, underscores the growing concern [ 113 ]. The FDA’s limited capacity to identify and assess potential drug-adulterated cosmetics raises concerns.

The second aspect focuses on the necessity for a more comprehensive and unbiased scientific and medical perspective in the FDA’s ingredient review process. The Personal Care Products Safety Act proposes a balanced committee formation including industry, consumer, and medical representatives, yet advocates for the inclusion of specialized professionals like chemists, dermatologists, toxicologists, and endocrinologists. Specific ingredients like diazolidinyl urea and quarternium-15, although effective antimicrobials, are flagged for potential skin allergy risks and formaldehyde release. The preservative 4-methylisothiazolinone, banned in Europe for rinse-off products, is noted for increasing allergic contact dermatitis cases in the US [ 114 ]. The lag in US cosmetic regulation compared to the EU is acknowledged, with the Personal Care Products Safety Act considered a significant advancement, albeit in need of further refinement [ 115 ].

The importance of consumer safety in the global regulatory landscape for cosmeceuticals, particularly for products that blur the line between cosmetics and pharmaceuticals, is a critical issue due to several key factors. Firstly, the cosmeceutical market is expanding rapidly, driven by new ingredients promising various skincare benefits like anti-aging and photoprotection. This growth necessitates clear regulatory guidelines to ensure that these products are safe and their claims are clinically proven. The FDA, for instance, differentiates between cosmetics and cosmeceuticals based on their intended use, particularly if a product is marketed as a cosmetic but functions in a way that affects the structure of the human body, classifying it as a cosmeceutical [ 116 ].

Secondly, the legal and regulatory distinctions between drugs and cosmetics are significant. Drugs are subject to FDA approval based on their intended use in treating diseases or affecting the body’s structure or function, whereas cosmetics are not. This difference becomes crucial when products are marketed with drug-like claims but are not regulated as drugs, potentially leading to consumer safety issues. For example, botanical cosmeceuticals, which contain natural ingredients like herbal extracts, need thorough evaluation to ensure consistency in therapeutic effects [ 117 ]. Additionally, cosmeceutical manufacturers must be careful with marketing and advertising claims to avoid legal implications. Misleading claims can lead to lawsuits and regulatory actions, as seen in past cases where companies faced consequences for unfounded product claims. Moreover, the FDA advises cosmeceutical manufacturers to follow Good Manufacturing Practices (GMP) to reduce the risk of misbranding or mislabeling. These guidelines include production practices and specific warning statement guidelines, emphasizing the importance of substantiating the safety of these products [ 118 ].

The global regulatory landscape for online pharmacy

Online pharmacies pose various risks to consumers, including the potential health hazards from counterfeit or substandard medications and the inappropriate use of prescription drugs. The regulatory landscape for these pharmacies varies significantly across nations, with some countries like the United States implementing specific laws, while others, such as France, have instituted outright bans [ 119 ]. The European Union, for instance, has implemented a mandate effective from 1 July 2015, which requires member states to adhere to legal provisions for a common logo specific to online pharmacies. This is coupled with an obligation for national regulatory authorities to maintain a registry of all registered online medicine retailers, as detailed by the European Medicines Agency [ 120 ]. Furthermore, the sale of certain medications online within the EU is permissible, contingent upon the registration of the pharmacy or retailer with respective national authorities​ [ 121 ]. Additionally, the Council of Europe’s MEDICRIME Convention introduces an international treaty that criminalizes the online sale of counterfeit medicinal products, enforcing prosecution irrespective of the country in which the crime is perpetrated [ 122 ].

Switzerland presents a unique stance, where Swissmedic strongly advises against the online purchase of medicines due to the high risk of illegal sourcing and poor quality. However, Swiss mail-order pharmacies with a valid cantonal license to operate a mail-order business are exempted from this advisory​ [ 123 ]. The Swiss Mail-Order Pharmacists Association and its affiliates, such as Zur Rose AG and MediService AG, actively advocate for a modern and equitable regulation of mail-order medicine sales​ [ 124 ]. The legislative framework is further bolstered by the Federal Act on Medicinal Products and Medical Devices, which regulates therapeutic products to guarantee their quality, safety, and efficacy​ [ 125 ]. In the Middle East, community pharmacy practice is predominantly governed by national Ministries of Public Health or equivalent governmental entities, with most community pharmacies being privately owned​ [ 126 ]. The region’s involvement in the Global Cooperation Group, which encompasses various international regulatory bodies like the EMA and USFDA, signifies a collaborative approach towards drug regulatory affairs in the MENA region [ 127 ]. Despite these advances in regulatory collaboration, it is notable that currently no specific regulations have been detected for online purchases from online pharmacies in the Middle East, highlighting a significant area for potential regulatory development. Furthermore, a notable transition is observed in pharmacy education across several Middle Eastern nations, with an inclination towards introducing Pharm.D degrees to replace traditional pharmacy degrees, reflective of evolving educational standards in the pharmaceutical field [ 128 ]. This shift in education parallels the need for updated regulatory frameworks, especially in the context of the burgeoning online pharmacy sector.

Furthermore, Australia permits the sale of both Prescription-Only Medicines (POMs) and Over-the-Counter (OTC) medications online, provided that brick-and-mortar pharmacies comply with all relevant laws and practice standards [ 129 ]. In contrast, South Korea maintains a stringent stance, prohibiting the online sale of both POMs and OTC medicines, with sales confined exclusively to physical stores registered with the Regulatory Authority (RA) [ 130 ]. China, Japan, Russia, Singapore, and Malaysia exhibit a more selective regulatory framework. China and Russia allow the online sale of OTC medicines only, with China imposing additional restrictions on third-party e-commerce platforms and Russia having introduced a draft law in December 2017 to formalize this practice [ 131 ; 132 ]. Japan permits the online sale of certain OTC medicines, explicitly excluding specific substances such as fexofenadine and loratadine [ 133 ]. Similarly, Singapore and Malaysia endorse the online sale of specific OTC medicines only, adopting a “buyers beware” approach to caution consumers about the associated risks [ 134 ; 135 ]. Lastly, the legal landscapes in India and Indonesia remain ambiguous. India’s RA has effectively banned the online sale of medicinal products, yet this prohibition lacks legislative backing. Indonesia, too, grapples with unclear regulations, leaving the legal status of online pharmacies indeterminate [ 136 ].

In response to these risks, several initiatives have been developed to guide and certify online pharmacies. In the United States, LegitScript offers certification to online pharmacies that comply with criteria such as appropriate licensing and registration [ 137 ]. Similarly, the Verified Internet Pharmacy Practice Sites (VIPPS) program, accredited by the National Association of Boards of Pharmacy, ensures pharmacies adhere to licensing requirements in the states where they dispense medications [ 138 ]. Internationally, the Health On the Net Foundation has introduced the HONcode, an ethical standard for health websites globally. This code certifies sites that provide transparent and qualified information. However, due to the absence of international harmonization, the HONcode’s certification is limited to US and Canadian pharmacies verified by VIPPS [ 139 ]. The lack of a harmonized international approach presents significant challenges. Consumers do not have access to a comprehensive, global repository of all certified pharmacies. The diverse certification schemes are not well articulated or interconnected, leading to consumer unawareness about their significance or existence. Moreover, enforcing standards across different legal jurisdictions is complex without a unified agreement. To enhance consumer protection, it is imperative to develop and promote a standardized, minimal international code of conduct for online pharmacies. Such a code would unify requirements and allow all initiatives to clarify their roles under a common framework. Adequate oversight in the borderless online pharmacy market can only be achieved through collaborative efforts. To visualize the infographic of the global regularity landscape for the online pharmacy see Fig.  6 .

Comprehensive representation of the regulatory landscape for global online pharmacies, detailing international and national initiatives, certification programs, and conventions aimed at minimizing risks associated with the purchase of medications via online platforms

Technological innovations and Future trends in global pharmacy

The global pharmacy sector is undergoing a transformative shift, driven by the rapid advancement of technological innovations. As the world becomes increasingly digital, the integration of cutting-edge technologies like Artificial Intelligence (AI) and blockchain is setting the stage for a new era in pharmaceutical care and management. These advancements promise to revolutionize the industry by enhancing efficiency, accuracy, and security, ultimately leading to improved patient outcomes and a more streamlined healthcare experience [ 140 ].

Walgreens, in partnership with Medline, a telehealth firm, has developed a platform for patient interaction with healthcare professionals via video chat. AI’s role extends to inventory management in retail pharmacies, allowing pharmacists to predict patient needs, stock appropriately, and use personalized software for patient reminders. Although not all inventory management software in retail pharmacies utilizes AI, some, like Blue Yonder’s software developed for Otto group, demonstrate the potential of AI in predicting product sales with high accuracy, thus enhancing supply chain efficiency [ 141 ; 142 ]. At the University of California San Francisco (UCSF) Medical Center, robotic technology is employed to improve patient safety in medication preparation and tracking. This technology has prepared medication doses with a notable error-free record and surpasses human capabilities in accuracy and efficiency. It prepares both oral and injectable medicines, including chemotherapy drugs, freeing pharmacists and nurses to focus on direct patient care. The automated system at UCSF receives electronic medication orders, with robotics handling the picking, packaging, and dispensing of individual doses. This system also assembles medications on bar-coded rings for 12-hour patient intervals and prepares sterile preparations for chemotherapy and intravascular syringes [ 143 ].

In the realm of global pharmacy, blockchain technology emerges as a pivotal force, driving advancements across various facets of healthcare and pharmaceuticals. At the forefront of its application is the enhancement of supply chain transparency [ 144 ]. Blockchain’s immutable ledger ensures the provenance and legitimacy of medical commodities, offering an unprecedented level of visibility from manufacturing to distribution. This is particularly vital in areas plagued by counterfeit drugs, where systems like MediLedger are instrumental in verifying the legality and essential details of medicines [ 145 ].

The utility of blockchain extends to the implementation of smart contracts — scripts processed on the blockchain that bolster transparency in medical studies and secure patient data management [ 146 ]. These contracts find extensive use in advanced medical settings, as evidenced by a blockchain-based telemonitoring system for remote patients and Dermonet, an online platform for dermatological consultation [ 147 ].

Furthermore, blockchain is revolutionizing patient care through patient-centric Electronic Health Records (EHRs). By decentralizing EHR maintenance, blockchain empowers patients with secure access to their historical and current health records [ 148 ]. Prototypes like MedRec and systems such as MeD Share exemplify how blockchain can provide complete, permanent access to clinical documents and facilitate the sharing of medical data between untrusted parties, respectively, ensuring high information authenticity and minimal privacy risks [ 149 ; 150 ]. In verifying medical staff credentials, blockchain again proves invaluable. Systems like ProCredEx, based on the R3 Corda blockchain protocol, streamline the credentialing process, offering rapid verification while allowing healthcare entities to leverage their existing data for enhanced transparency and assurance about medical staff experience [ 151 ].

The integration of blockchain with Internet of Things devices for remote monitoring marks another leap forward, significantly bolstering data security. By safeguarding the integrity and privacy of patient data collected by these devices, blockchain mitigates the risk of tampering and ensures that only authorized parties can access sensitive information [ 152 ]. Besides, a blockchain-based drug supply chain initiative, PharmaChain, utilizes AI for approaches against drug counterfeit and ensures the drug supply chain is more traceable, visible, and secure. For online pharmacies, this means a more reliable supply chain and assurance of drug authenticity, crucial for maintaining trust and safety [ 153 ].

In response to the COVID-19 pandemic, the PharmaGo platform has emerged as an innovative solution in Sri Lanka, revolutionizing the delivery of pharmacy services. As traditional pharmacies grapple with the challenges of meeting all customer needs in one location, PharmaGo addresses this by providing a comprehensive online pharmaceutical service. It allows customers to access a wide range of medications through a single platform, reducing the need to visit multiple pharmacies. Utilizing image processing technology, pharmacy owners can accurately identify prescribed medicines, while the system’s predictive analytics forecasts future drug demands, enhancing stock management. Additionally, PharmaGo’s AI-powered medical chatbot offers real-time guidance, ensuring a seamless and efficient customer experience. This platform represents a significant advancement in healthcare accessibility and pharmacy service delivery in the pandemic era [ 154 ]. In the same context, ontology-based medicine information system, enhancing search relevance through a chatbot interface was presented by Amalia et al. [ 155 ]. Addressing conventional search engines’ limitations in interpreting data relationships, it employs semantic technology to represent metadata informatively. The ontology as a knowledge base effectively delineates disease-medicine relationships, with evaluations indicating a 90% response validity from the chatbot, offering a robust reference for medical information retrieval and its semantic associations.

Future trends for the digital transformation of in the pharmaceutical sector

Future trends for the digital transformation of pharmacies globally are heavily influenced by the transformative impact of digital technologies on healthcare delivery. The integration of telemedicine, electronic health records, and mobile health applications is pivotal in enhancing patient care. These technologies are instrumental in improving data sharing and collaboration among healthcare professionals, increasing the efficiency of healthcare services. Additionally, they offer significant potential for personalized medicine through data analytics and play a crucial role in patient engagement and self-management of health. The importance of these technologies in creating a more connected and efficient healthcare system is underscored, marking a significant shift in the global healthcare landscape [ 156 ].

In the pharmaceutical sector, the COVID-19 pandemic has catalyzed a significant shift towards Pharmaceutical Digital Marketing (PDM), particularly for over-the-counter drugs. This shift focuses on utilizing online pharmacies and digital platforms for targeted advertising, directly reaching consumers. The trend towards purchasing OTC drugs online has grown, driven by the convenience and efficiency of digital channels. While PDM faces challenges like regulatory constraints and the need for digital proficiency, it offers substantial opportunities in enhancing customer engagement and precise marketing. The future of PDM is poised to be more consumer-centric, integrating advanced technologies like AI, and emphasizing personalized marketing strategies to strengthen brand engagement and customer interaction [ 157 ].

Artificial intelligence holds immense potential to revolutionize the field of pharmacy, offering numerous benefits that can significantly enhance efficiency and patient care. One of the primary applications of AI in this sector is the automation of routine tasks. By utilizing AI, pharmacies can automate critical processes such as prescription processing, checking for drug interactions, and managing inventory. This automation not only streamlines operations but also minimizes the likelihood of human error, thereby increasing the overall efficiency of pharmacies [ 158 ].

Furthermore, AI can play a pivotal role in personalized medication management. This is particularly beneficial for patients with chronic conditions such as diabetes who require careful management of their insulin dosages, as fluctuations in blood sugar levels can lead to serious complications. AI systems can monitor patients continuously, provide timely reminders for medication intake, and dynamically adjust treatment plans based on individual health data. Such personalized management ensures that patients receive optimal care tailored to their specific needs, potentially improving treatment outcomes. Incorporation of AI into electronic health records presents another significant advancement. By integrating AI with EHRs, healthcare providers can access real-time patient data. This integration empowers healthcare professionals to make more informed care decisions, enhancing the quality of patient care. Moreover, it significantly reduces the likelihood of medication errors, a critical concern in healthcare.

Likewise, AI’s capability to analyze extensive patient data is invaluable. It can identify patterns and trends in medication adherence, detect potential drug interactions, and pinpoint adverse drug reactions. These insights are crucial for healthcare professionals and researchers. By understanding these patterns, they can develop more effective medication adherence strategies and support systems, contributing to better patient outcomes and advancing the overall field of pharmaceutical care.

In the expansive realm of chemical space, the pharmaceutical industry faces the continual challenge of identifying new active pharmaceutical ingredients (APIs) for diverse diseases [ 159 ]. High throughput screening (HTS), despite its advancements in recent decades, remains resource-intensive and often yields unsuitable hits for drug development. The failure rate of investigational compounds remains high, with a study citing only a 6.2% success rate for orphan drugs progressing from phase I to market approval [ 160 , 161 ].

Machine learning presents a transformative approach to this challenge. It offers an alternative to manual HTS through in silico methodologies. ML-driven drug discovery boasts several advantages: it operates continuously, surpasses the capacity of manual methods, reduces costs by decreasing the number of physical compounds tested, and early identifies negative characteristics of compounds, such as off-target effects and sex-dependent variability [ 162 ].

A substantial advancement in the realm of machine learning has emerged from major pharmaceutical entities, notably AstraZeneca, in conjunction with research institutions. This progress is evidenced by the development of an innovative algorithm that demonstrates both time efficiency and effectiveness in the sphere of drug discovery. The recent introduction of this algorithm significantly enhances the process of determining binding affinities between investigational compounds and therapeutic targets. It surpasses traditional in silico methods in terms of performance. The application of this algorithm underscores the remarkable potential of machine learning in accelerating the identification and development of novel therapeutic agents [ 163 ].

Moreover, the proficiency of machine learning in managing vast and intricate datasets has rendered it indispensable in research focused on cancer targets, utilizing diverse and extensive datasets. This approach is fundamental in numerous drug discovery initiatives, especially those targeting various forms of cancer. A wide array of ML techniques, ranging from supervised to unsupervised learning, are employed to discern chemical attributes that are indicative of potential therapeutic efficacy against a spectrum of cancer targets. This methodology is crucial in identifying novel compounds that could be effective in cancer treatment, leveraging the rich and complex data available in oncological research [ 164 ].

The digital transformation in the pharmacy sector is significantly reshaping healthcare delivery, driven by the integration of cutting-edge technologies like Artificial Intelligence and blockchain. This transformation is marked by a substantial growth in the digital pharmacy market, with a projected annual growth rate of 14.42%, leading to a market volume of approximately $35.33 billion by 2026​​.

One major aspect of this transformation is the growing reliance on online pharmacy platforms, largely influenced by the COVID-19 pandemic. Consumer trust in online medication purchases has significantly increased, indicating a shift towards digital healthcare solutions. The adoption of telehealth services, including telepharmacy, has surged, with patient adoption in the United States increasing from 11% in 2019 to 46%. This shift towards digital-first services enhances convenience and access to care but also introduces regulatory challenges, particularly in maintaining patient safety and quality standards in the rapidly evolving online healthcare environment​​.

The cosmeceuticals market, a segment within online pharmacies, is experiencing robust growth. Cosmeceuticals, which bridge the gap between cosmetics and pharmaceuticals, have become a significant part of the skincare industry. The market, valued at USD 56.78 billion in 2022, is projected to expand to USD 95.75 billion by 2030. This expansion is driven by factors like innovation in natural ingredients and significant penetration of internet, smartphone, and social media applications. Despite the growth, the overall penetration for non-specialty drugs in mail-order and online pharmacies remains low, representing a significant portion of specialty prescription revenues. The evolving landscape of online pharmacies in the cosmeceuticals sector reflects a trend towards more accessible and customizable personal healthcare solutions​​.

Technological innovations are setting the stage for a new era in pharmaceutical care and management. AI’s role extends to areas like inventory management in retail pharmacies, where it predicts patient needs and enhances supply chain efficiency. Blockchain technology enhances supply chain transparency and legitimizes medical commodities, especially crucial in areas affected by counterfeit drugs. Blockchain also plays a vital role in patient-centric Electronic Health Records and telemonitoring systems. For instance, PharmaGo, an innovative platform developed in response to the pandemic, provides a comprehensive online pharmaceutical service, demonstrating the significant advancements in healthcare accessibility and pharmacy service delivery​​.

These technological advancements are instrumental in improving data sharing and collaboration among healthcare professionals. They offer significant potential for personalized medicine through data analytics, playing a crucial role in patient engagement and self-management of health. The future trends in the pharmaceutical sector, particularly influenced by the COVID-19 pandemic, indicate a shift towards Pharmaceutical Digital Marketing (PDM) and a more consumer-centric approach. AI’s potential in revolutionizing pharmacy includes automation of routine tasks, personalized medication management, real-time patient data access, and the identification of patterns in medication adherence and potential drug interactions​​.

Data availability

No datasets were generated or analysed during the current study.

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The researcher would like to thank the Deanship of Scientific Research, Qassim University for funding the publication of this project.

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Almeman, A. The digital transformation in pharmacy: embracing online platforms and the cosmeceutical paradigm shift. J Health Popul Nutr 43 , 60 (2024). https://doi.org/10.1186/s41043-024-00550-2

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• Evolutionary Biology

CLOCK evolved in cnidaria to synchronize internal rhythms with diel environmental cues

• Mieka Rinsky
• Noa Simon-Blecher
• Tirza Doniger
• Lior Appelbaum
• Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Israel ;
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Reviewer #2 (Public Review):

Author response.

• Claude Desplan
• New York University, United States
• Kristin Tessmar-Raible
• University of Vienna, Austria

In this revised manuscript Aguillon and collaborators convincingly demonstrating that CLK is required for free-running behavioral rhythms under constant conditions in the Cnidarian Nematostella. The results also convincingly show that CLK impacts rhythmic gene expression in this organism. This original work thus demonstrates that CLK was recruited very early during animal evolution in the circadian clock mechanism to optimize behavior and gene expression with the time-of-day.

The following is the authors’ response to the previous reviews.

Public Reviews: Reviewer #2 (Public Review): In this revised manuscript Aguillon and collaborators convincingly demonstrating that CLK is required for free-running behavioral rhythms under constant conditions in the Cnidarian Nematostella. The results also convincingly show that CLK impacts rhythmic gene expression in this organism. This original work thus demonstrates that CLK was recruited very early during animal evolution in the circadian clock mechanism to optimize behavior and gene expression with the time-of-day. The manuscript could still benefit from some improvements so that it is more accessible for a wide readership. Recommendations for the authors: Reviewer #2 (Recommendations For The Authors): Aguillon and collaborators have deeply revised, and in the progress significantly improved the presentation of their interesting results with the first Cnidarian circadian gene mutant. Results are now very convincingly demonstrating that CLK is required for free-running behavioral rhythms under constant conditions. The results also now more convincingly show that CLK impact rhythmic gene expression, although interpretation of the transcriptomics data is not straightforward. I think there is still improvements that are needed to make the manuscript more accessible. We authors need to keep in mind that a broad audience will read their report, not just chronobiologists. I have listed below several issues that I think should be addressed, and some editing suggestions.

General comment to Editor and Reviewers:

We are genuinely grateful to both reviewers and editors about all the feedback which helped us to make the best of our data, to question our analysis to the point we redefined our approach and end up with a great article we are proud of it. Only the name of authors is visible on the article, and considering how much the reviewing system help to improve the research it seems almost unfair. As such, we thank all of you and really appreciate the new eLife system. Bravo all.

Abstract: (1) Line 40" It should read "transcript levels" instead of "transcription". There is no measurement of transcription rates in this manuscript, only mRNA levels.

Modified accordingly.

(2) Line 41: the authors mention "constant light". Does this refer to previous work? Their data in Figure 4 were in constant darkness, not in LL.

(3) Line 46 and throughout the manuscript, the allelic nomenclature is not standard. 1-/- seems to indicate there are two different alleles. Since the allele might not be a null, I would suggest simply using 1/1, or perhaps delta/delta since the mutation results in a truncates CLK.

NvClk1-/- became NvClkΔ/Δ. Except in the .xls supplementary table were the mutant kept the NvClk-/- nomenclature. It is not possible to replace only part of a word with a different font, here generating delta sign would require to do it one by one.

(4) The last sentence of the abstract needs to be rephrased, as it suggests that CLK evolved to maintain circadian rhythms under constant conditions. Constant conditions very rarely exist on Earth, and thus cannot be an evolutionary driving force. Different explanations have been proposed on why a self-sustained clock is the evolutionary solution to timekeeping, but the purpose of the clock and of clock genes is not to maintain oscillations in constant conditions. Actually, this sentence conflicts with the title.

Modified to: the Clock gene has evolved in cnidarians to sustain 24-hour rhythmic physiology and behavior in absence of diel environmental conditions.From my actual understanding, you are right, the purpose of clock gene is not to maintain oscillation in constant conditions (this is simply the result of the experiment), but to synchronize the physiology to the day/night rhythm, and surely to sustain 24h oscillations in case the environment challenges the perception of the diel cues. The DD or LL is just an artificial experimental design to reveal the endogenous time-keeping pacemaker.

Results: (1) Line 148 and elsewhere in the MS: I would not use the word "lower" or "higher" to qualify acrophases. I would suggest advanced/delayed or earlier/later.

(2) Line 157-9: The introductory sentence does not clearly present the rationale for the 6/6 experiments.

We modified the paragraph accordingly: The presence of a 24-hour rhythm of NvClkΔ/Δ polyps under LD conditions could be attributed to either a direct light-response or the partial functioning of the circadian clock due to the nature of the mutation….

(3) At the end of the behavior section, or perhaps at the end of each paragraph in this section, it would be helpful to have a summary of the results and more clearly explain their interpretation. The authors need to guide the readers, particularly non-chronobiologist, so that they can understand what the really neat data that were obtained mean. For example, what does it mean that the acrophase is different between mutant and wild-type, why are Clk mutants rhythmic under LD12/12 or 6/6, etc.

We added a conclusion sentence to help non-specialist to understand each result.

(4) Line 172 and elsewhere" "true rhythmic genes" sounds odd to me. Either they are, or they are not rhythmic.

Modified to “rhythmic genes.”

(5) Paragraph starting with line 184: I do not follow what is important about the number of genes per time cluster. What does it tell us, beyond the simple fact that less genes are rhythmic in the Clk mutants?

We rewrote the result paragraph to make it clearer why we performed this clustering analysis. This clustering analysis became Extended Data Fig.2 with modification of the figures (see my comments in your review about Figure 3).

(6) Line 197: The authors need to explain what they saw with circadian clock genes and their expression in CLk mutants. In some case, amplitude increased in LD. This surprisingobservation deserves some explanations. "Complex regulatory effect" is too vague.

We replaced the vague “complex regulatory effect” by a more thorough description of the figure 3.a.

(7) Line 198-203: Again, help the reader understand the significance of these observations.

We rewrote the paragraph to help the reader to better understand the significance of these observations.

Discussion: (1) Line 236-40. Careful with the use of -/-, which implies that an allele is a null. The first CLk mutants in mammals and flies, which the authors refer to. were actually dominant negatives.

I went over the citations we used for this paragraph and this first mutation in fly dClkar is null, no dominant negative. Flies are still rhythmic in the dark. Unless there is an older mutation? However, you right the first mutation identified in mouse was a dominant-negative with loss of rhythmicity, while the gene deletion did not show any effect on the behavior, suggesting compensation by a paralog. I removed two references which were not relevant to the discussion.

(2) Line 265-268 are not very clear. Do the authors mean that the lack of overlap for non-cricadian pacemaker genes is because of different experimental conditions? What would be those differences? It is reassuring that the Leach/Reitzel study and the present share pacemaker genes as rhythmic, but it is also surprising that there is almost no overlap beyond these genes. How robust are those other rhythms compared to circadian clock genes?

We revised this paragraph and raised major points regarding the raising condition of our polyps between labs and their potential genetic differences which could explain these differences.

(3) Line 270. I am not sure "compensation" is the right word, since there is no overlap between the rhythmic genes in mutants under LD and wild-type under either LD or DD. Also, saying on line 273 that the transcriptional pattern is not fully reproduced is a rather striking understatement, given the absence of rhythm gene overlap

We rewrote the paragraph accordingly. We replaced by “alternative way to drive rhythmicity under LD condition”.

(4) Line 279. The authors mention the possibility of false positives. Based on the FDR, is there more rhythmic genes than by chance?

The possibility of false-positive is a risk to consider when you do not perform multiple-testing. We added within the results paragraph the number of rhythmic genes identified with BH.Q or p.adj. which both are the multiple testing for each algorithm (RAIN and JTK) we used.

(5) Line 279-82. The references to the Ray study is rather obscure. What is the point the authors are trying to make here?

Eventually, we removed the reference from this article and modify the paragraph of the discussion. Indeed, the discussion around the Ray study did not gave an interesting direction to discuss our results and analysis approach.

(6) Line 284: define BHQ and p.adj

Defined and referenced.

(7) The way Lines 283-288 are worded do not provide a good rationale for how transcriptional rhythms were analyzed. The idea to combine two different approaches (JTK and RAIN) to be selective with rhythmicity was great. The authors need however to justify these choices in a more convincing manner. The goal is to detect rhythmic genes in a reliable manner, irrespective of the number of rhythmic genes observed Also, explaining the choice of methodology belongs to the result section.

We explained our choice of methodology and moved it to the result section as suggested.

(8) Line 292-3. There are known mechanisms that explain how transcriptional time clusters are generated. In particular, the use of interlocked feedback loop with antiphase peaks of transcriptions is well documented. Actually, it seems to me the clustering shown in Fig 4 might hint at such a mechanism.

Indeed you are right the clustering shown in Fig 3 (former Fig 4) revealed such mechanism.

Figures: Figure 2: Define relative amplitude

We added the definition of the relative amplitude within the results. If this is what you asked for?

Figure 3: Some of the cycles look odd (first row of graphs in panel C). Why would the first and last data point be so different in three of these graphs?

We decided to modify this figure as we realized it was not informative and not objective enough, as we selected among multiple patterns few “representatives”. In the new figure we combined the cluster analysis to the behavior. Thus, readers can now pick a cluster according to a specific behavior activity level (or ZT/CT) and reach in supp. Table 4 the “genes of potential interest”. However generally speaking this figure does not explain more the consequences of the mutation, so we moved it into the Extended data Fig.2

Figure4: define the color coding in the correlation panels (blue to red)

These values from -1 to 1 are the Pearson correlation values. Now indicated on the figure with the color coding legend.

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