essay about online learning in this pandemic

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Students’ experience of online learning during the COVID‐19 pandemic: A province‐wide survey study

Lixiang yan.

1 Centre for Learning Analytics at Monash, Faculty of Information Technology, Monash University, Clayton VIC, Australia

Alexander Whitelock‐Wainwright

2 Portfolio of the Deputy Vice‐Chancellor (Education), Monash University, Melbourne VIC, Australia

Quanlong Guan

3 Department of Computer Science, Jinan University, Guangzhou China

Gangxin Wen

4 College of Cyber Security, Jinan University, Guangzhou China

Dragan Gašević

Guanliang chen, associated data.

The data is not openly available as it is restricted by the Chinese government.

Online learning is currently adopted by educational institutions worldwide to provide students with ongoing education during the COVID‐19 pandemic. Even though online learning research has been advancing in uncovering student experiences in various settings (i.e., tertiary, adult, and professional education), very little progress has been achieved in understanding the experience of the K‐12 student population, especially when narrowed down to different school‐year segments (i.e., primary and secondary school students). This study explores how students at different stages of their K‐12 education reacted to the mandatory full‐time online learning during the COVID‐19 pandemic. For this purpose, we conducted a province‐wide survey study in which the online learning experience of 1,170,769 Chinese students was collected from the Guangdong Province of China. We performed cross‐tabulation and Chi‐square analysis to compare students’ online learning conditions, experiences, and expectations. Results from this survey study provide evidence that students’ online learning experiences are significantly different across school years. Foremost, policy implications were made to advise government authorises and schools on improving the delivery of online learning, and potential directions were identified for future research into K‐12 online learning.

Practitioner notes

What is already known about this topic

• Online learning has been widely adopted during the COVID‐19 pandemic to ensure the continuation of K‐12 education.
• Student success in K‐12 online education is substantially lower than in conventional schools.
• Students experienced various difficulties related to the delivery of online learning.

What this paper adds

• Provide empirical evidence for the online learning experience of students in different school years.
• Identify the different needs of students in primary, middle, and high school.
• Identify the challenges of delivering online learning to students of different age.

Implications for practice and/or policy

• Authority and schools need to provide sufficient technical support to students in online learning.
• The delivery of online learning needs to be customised for students in different school years.

INTRODUCTION

The ongoing COVID‐19 pandemic poses significant challenges to the global education system. By July 2020, the UN Educational, Scientific and Cultural Organization (2020) reported nationwide school closure in 111 countries, affecting over 1.07 billion students, which is around 61% of the global student population. Traditional brick‐and‐mortar schools are forced to transform into full‐time virtual schools to provide students with ongoing education (Van Lancker & Parolin,  2020 ). Consequently, students must adapt to the transition from face‐to‐face learning to fully remote online learning, where synchronous video conferences, social media, and asynchronous discussion forums become their primary venues for knowledge construction and peer communication.

For K‐12 students, this sudden transition is problematic as they often lack prior online learning experience (Barbour & Reeves,  2009 ). Barbour and LaBonte ( 2017 ) estimated that even in countries where online learning is growing rapidly, such as USA and Canada, less than 10% of the K‐12 student population had prior experience with this format. Maladaptation to online learning could expose inexperienced students to various vulnerabilities, including decrements in academic performance (Molnar et al.,  2019 ), feeling of isolation (Song et al.,  2004 ), and lack of learning motivation (Muilenburg & Berge,  2005 ). Unfortunately, with confirmed cases continuing to rise each day, and new outbreaks occur on a global scale, full‐time online learning for most students could last longer than anticipated (World Health Organization,  2020 ). Even after the pandemic, the current mass adoption of online learning could have lasting impacts on the global education system, and potentially accelerate and expand the rapid growth of virtual schools on a global scale (Molnar et al.,  2019 ). Thus, understanding students' learning conditions and their experiences of online learning during the COVID pandemic becomes imperative.

Emerging evidence on students’ online learning experience during the COVID‐19 pandemic has identified several major concerns, including issues with internet connection (Agung et al.,  2020 ; Basuony et al.,  2020 ), problems with IT equipment (Bączek et al.,  2021 ; Niemi & Kousa,  2020 ), limited collaborative learning opportunities (Bączek et al.,  2021 ; Yates et al.,  2020 ), reduced learning motivation (Basuony et al.,  2020 ; Niemi & Kousa,  2020 ; Yates et al.,  2020 ), and increased learning burdens (Niemi & Kousa,  2020 ). Although these findings provided valuable insights about the issues students experienced during online learning, information about their learning conditions and future expectations were less mentioned. Such information could assist educational authorises and institutions to better comprehend students’ difficulties and potentially improve their online learning experience. Additionally, most of these recent studies were limited to higher education, except for Yates et al. ( 2020 ) and Niemi and Kousa’s ( 2020 ) studies on senior high school students. Empirical research targeting the full spectrum of K‐12students remain scarce. Therefore, to address these gaps, the current paper reports the findings of a large‐scale study that sought to explore K‐12 students’ online learning experience during the COVID‐19 pandemic in a provincial sample of over one million Chinese students. The findings of this study provide policy recommendations to educational institutions and authorities regarding the delivery of K‐12 online education.

LITERATURE REVIEW

Learning conditions and technologies.

Having stable access to the internet is critical to students’ learning experience during online learning. Berge ( 2005 ) expressed the concern of the divide in digital‐readiness, and the pedagogical approach between different countries could influence students’ online learning experience. Digital‐readiness is the availability and adoption of information technologies and infrastructures in a country. Western countries like America (3rd) scored significantly higher in digital‐readiness compared to Asian countries like China (54th; Cisco,  2019 ). Students from low digital‐readiness countries could experience additional technology‐related problems. Supporting evidence is emerging in recent studies conducted during the COVID‐19 pandemic. In Egypt's capital city, Basuony et al. ( 2020 ) found that only around 13.9%of the students experienced issues with their internet connection. Whereas more than two‐thirds of the students in rural Indonesia reported issues of unstable internet, insufficient internet data, and incompatible learning device (Agung et al.,  2020 ).

Another influential factor for K‐12 students to adequately adapt to online learning is the accessibility of appropriate technological devices, especially having access to a desktop or a laptop (Barbour et al., 2018 ). However, it is unlikely for most of the students to satisfy this requirement. Even in higher education, around 76% of students reported having incompatible devices for online learning and only 15% of students used laptop for online learning, whereas around 85% of them used smartphone (Agung et al.,  2020 ). It is very likely that K‐12 students also suffer from this availability issue as they depend on their parents to provide access to relevant learning devices.

Technical issues surrounding technological devices could also influence students’ experience in online learning. (Barbour & Reeves,  2009 ) argues that students need to have a high level of digital literacy to find and use relevant information and communicate with others through technological devices. Students lacking this ability could experience difficulties in online learning. Bączek et al. ( 2021 ) found that around 54% of the medical students experienced technical problems with IT equipment and this issue was more prevalent in students with lower years of tertiary education. Likewise, Niemi and Kousa ( 2020 ) also find that students in a Finish high school experienced increased amounts of technical problems during the examination period, which involved additional technical applications. These findings are concerning as young children and adolescent in primary and lower secondary school could be more vulnerable to these technical problems as they are less experienced with the technologies in online learning (Barbour & LaBonte,  2017 ). Therefore, it is essential to investigate the learning conditions and the related difficulties experienced by students in K‐12 education as the extend of effects on them remain underexplored.

Learning experience and interactions

Apart from the aforementioned issues, the extent of interaction and collaborative learning opportunities available in online learning could also influence students’ experience. The literature on online learning has long emphasised the role of effective interaction for the success of student learning. According to Muirhead and Juwah ( 2004 ), interaction is an event that can take the shape of any type of communication between two or subjects and objects. Specifically, the literature acknowledges the three typical forms of interactions (Moore,  1989 ): (i) student‐content, (ii) student‐student, and (iii) student‐teacher. Anderson ( 2003 ) posits, in the well‐known interaction equivalency theorem, learning experiences will not deteriorate if only one of the three interaction is of high quality, and the other two can be reduced or even eliminated. Quality interaction can be accomplished by across two dimensions: (i) structure—pedagogical means that guide student interaction with contents or other students and (ii) dialogue—communication that happens between students and teachers and among students. To be able to scale online learning and prevent the growth of teaching costs, the emphasise is typically on structure (i.e., pedagogy) that can promote effective student‐content and student‐student interaction. The role of technology and media is typically recognised as a way to amplify the effect of pedagogy (Lou et al.,  2006 ). Novel technological innovations—for example learning analytics‐based personalised feedback at scale (Pardo et al.,  2019 ) —can also empower teachers to promote their interaction with students.

Online education can lead to a sense of isolation, which can be detrimental to student success (McInnerney & Roberts,  2004 ). Therefore, integration of social interaction into pedagogy for online learning is essential, especially at the times when students do not actually know each other or have communication and collaboration skills underdeveloped (Garrison et al.,  2010 ; Gašević et al.,  2015 ). Unfortunately, existing evidence suggested that online learning delivery during the COVID‐19 pandemic often lacks interactivity and collaborative experiences (Bączek et al.,  2021 ; Yates et al.,  2020 ). Bączek et al., ( 2021 ) found that around half of the medical students reported reduced interaction with teachers, and only 4% of students think online learning classes are interactive. Likewise, Yates et al. ( 2020 )’s study in high school students also revealed that over half of the students preferred in‐class collaboration over online collaboration as they value the immediate support and the proximity to teachers and peers from in‐class interaction.

Learning expectations and age differentiation

Although these studies have provided valuable insights and stressed the need for more interactivity in online learning, K‐12 students in different school years could exhibit different expectations for the desired activities in online learning. Piaget's Cognitive Developmental Theory illustrated children's difficulties in understanding abstract and hypothetical concepts (Thomas,  2000 ). Primary school students will encounter many abstract concepts in their STEM education (Uttal & Cohen,  2012 ). In face‐to‐face learning, teachers provide constant guidance on students’ learning progress and can help them to understand difficult concepts. Unfortunately, the level of guidance significantly drops in online learning, and, in most cases, children have to face learning obstacles by themselves (Barbour,  2013 ). Additionally, lower primary school students may lack the metacognitive skills to use various online learning functions, maintain engagement in synchronous online learning, develop and execute self‐regulated learning plans, and engage in meaningful peer interactions during online learning (Barbour,  2013 ; Broadbent & Poon,  2015 ; Huffaker & Calvert, 2003; Wang et al.,  2013 ). Thus, understanding these younger students’ expectations is imperative as delivering online learning to them in the same way as a virtual high school could hinder their learning experiences. For students with more matured metacognition, their expectations of online learning could be substantially different from younger students. Niemi et al.’s study ( 2020 ) with students in a Finish high school have found that students often reported heavy workload and fatigue during online learning. These issues could cause anxiety and reduce students’ learning motivation, which would have negative consequences on their emotional well‐being and academic performance (Niemi & Kousa,  2020 ; Yates et al.,  2020 ), especially for senior students who are under the pressure of examinations. Consequently, their expectations of online learning could be orientated toward having additional learning support functions and materials. Likewise, they could also prefer having more opportunities for peer interactions as these interactions are beneficial to their emotional well‐being and learning performance (Gašević et al., 2013 ; Montague & Rinaldi, 2001 ). Therefore, it is imperative to investigate the differences between online learning expectations in students of different school years to suit their needs better.

Research questions

By building upon the aforementioned relevant works, this study aimed to contribute to the online learning literature with a comprehensive understanding of the online learning experience that K‐12 students had during the COVID‐19 pandemic period in China. Additionally, this study also aimed to provide a thorough discussion of what potential actions can be undertaken to improve online learning delivery. Formally, this study was guided by three research questions (RQs):

RQ1 . What learning conditions were experienced by students across 12 years of education during their online learning process in the pandemic period? RQ2 . What benefits and obstacles were perceived by students across 12 years of education when performing online learning? RQ3 . What expectations do students, across 12 years of education, have for future online learning practices ?

Participants

The total number of K‐12 students in the Guangdong Province of China is around 15 million. In China, students of Year 1–6, Year 7–9, and Year 10–12 are referred to as students of primary school, middle school, and high school, respectively. Typically, students in China start their study in primary school at the age of around six. At the end of their high‐school study, students have to take the National College Entrance Examination (NCEE; also known as Gaokao) to apply for tertiary education. The survey was administrated across the whole Guangdong Province, that is the survey was exposed to all of the 15 million K‐12 students, though it was not mandatory for those students to accomplish the survey. A total of 1,170,769 students completed the survey, which accounts for a response rate of 7.80%. After removing responses with missing values and responses submitted from the same IP address (duplicates), we had 1,048,575 valid responses, which accounts to about 7% of the total K‐12 students in the Guangdong Province. The number of students in different school years is shown in Figure  1 . Overall, students were evenly distributed across different school years, except for a smaller sample in students of Year 10–12.

The number of students in each school year

Survey design

The survey was designed collaboratively by multiple relevant parties. Firstly, three educational researchers working in colleges and universities and three educational practitioners working in the Department of Education in Guangdong Province were recruited to co‐design the survey. Then, the initial draft of the survey was sent to 30 teachers from different primary and secondary schools, whose feedback and suggestions were considered to improve the survey. The final survey consisted of a total of 20 questions, which, broadly, can be classified into four categories: demographic, behaviours, experiences, and expectations. Details are available in Appendix.

All K‐12 students in the Guangdong Province were made to have full‐time online learning from March 1, 2020 after the outbreak of COVID‐19 in January in China. A province‐level online learning platform was provided to all schools by the government. In addition to the learning platform, these schools can also use additional third‐party platforms to facilitate the teaching activities, for example WeChat and Dingding, which provide services similar to WhatsApp and Zoom. The main change for most teachers was that they had to shift the classroom‐based lectures to online lectures with the aid of web‐conferencing tools. Similarly, these teachers also needed to perform homework marking and have consultation sessions in an online manner.

The Department of Education in the Guangdong Province of China distributed the survey to all K‐12 schools in the province on March 21, 2020 and collected responses on March 26, 2020. Students could access and answer the survey anonymously by either scan the Quick Response code along with the survey or click the survey address link on their mobile device. The survey was administrated in a completely voluntary manner and no incentives were given to the participants. Ethical approval was granted by the Department of Education in the Guangdong Province. Parental approval was not required since the survey was entirely anonymous and facilitated by the regulating authority, which satisfies China's ethical process.

The original survey was in Chinese, which was later translated by two bilingual researchers and verified by an external translator who is certified by the Australian National Accreditation Authority of Translators and Interpreters. The original and translated survey questionnaires are available in Supporting Information. Given the limited space we have here and the fact that not every survey item is relevant to the RQs, the following items were chosen to answer the RQs: item Q3 (learning media) and Q11 (learning approaches) for RQ1, item Q13 (perceived obstacle) and Q19 (perceived benefits) for RQ2, and item Q19 (expected learning activities) for RQ3. Cross‐tabulation based approaches were used to analyse the collected data. To scrutinise whether the differences displayed by students of different school years were statistically significant, we performed Chi‐square tests and calculated the Cramer's V to assess the strengths of the association after chi‐square had determined significance.

For the analyses, students were segmented into four categories based on their school years, that is Year 1–3, Year 4–6, Year 7–9, and Year 10–12, to provide a clear understanding of the different experiences and needs that different students had for online learning. This segmentation was based on the educational structure of Chinese schools: elementary school (Year 1–6), middle school (Year 7–9), and high school (Year 10–12). Children in elementary school can further be segmented into junior (Year 1–3) or senior (Year 4–6) students because senior elementary students in China are facing more workloads compared to junior students due to the provincial Middle School Entry Examination at the end of Year 6.

Learning conditions—RQ1

Learning media.

The Chi‐square test showed significant association between school years and students’ reported usage of learning media, χ 2 (55, N  = 1,853,952) = 46,675.38, p  < 0.001. The Cramer's V is 0.07 ( df ∗ = 5), which indicates a small‐to‐medium effect according to Cohen’s ( 1988 ) guidelines. Based on Figure  2 , we observed that an average of up to 87.39% students used smartphones to perform online learning, while only 25.43% students used computer, which suggests that smartphones, with widespread availability in China (2020), have been adopted by students for online learning. As for the prevalence of the two media, we noticed that both smartphones ( χ 2 (3, N  = 1,048,575) = 9,395.05, p < 0.001, Cramer's V  = 0.10 ( df ∗ = 1)) and computers ( χ 2 (3, N  = 1,048,575) = 11,025.58, p <.001, Cramer's V  = 0.10 ( df ∗ = 1)) were more adopted by high‐school‐year (Year 7–12) than early‐school‐year students (Year 1–6), both with a small effect size. Besides, apparent discrepancies can be observed between the usages of TV and paper‐based materials across different school years, that is early‐school‐year students reported more TV usage ( χ 2 (3, N  = 1,048,575) = 19,505.08, p <.001), with a small‐to‐medium effect size, Cramer's V  = 0.14( df ∗ = 1). High‐school‐year students (especially Year 10–12) reported more usage of paper‐based materials ( χ 2 (3, N  = 1,048,575) = 23,401.64, p < 0.001), with a small‐to‐medium effect size, Cramer's V  = 0.15( df ∗ = 1).

Learning media used by students in online learning

Learning approaches

School years is also significantly associated with the different learning approaches students used to tackle difficult concepts during online learning, χ 2 (55, N  = 2,383,751) = 58,030.74, p < 0.001. The strength of this association is weak to moderate as shown by the Cramer's V (0.07, df ∗ = 5; Cohen,  1988 ). When encountering problems related to difficult concepts, students typically chose to “solve independently by searching online” or “rewatch recorded lectures” instead of consulting to their teachers or peers (Figure  3 ). This is probably because, compared to classroom‐based education, it is relatively less convenient and more challenging for students to seek help from others when performing online learning. Besides, compared to high‐school‐year students, early‐school‐year students (Year 1–6), reported much less use of “solve independently by searching online” ( χ 2 (3, N  = 1,048,575) = 48,100.15, p <.001), with a small‐to‐medium effect size, Cramer's V  = 0.21 ( df ∗ = 1). Also, among those approaches of seeking help from others, significantly more high‐school‐year students preferred “communicating with other students” than early‐school‐year students ( χ 2 (3, N  = 1,048,575) = 81,723.37, p < 0.001), with a medium effect size, Cramer's V  = 0.28 ( df ∗ = 1).

Learning approaches used by students in online learning

Perceived benefits and obstacles—RQ2

Perceived benefits.

The association between school years and perceived benefits in online learning is statistically significant, χ 2 (66, N  = 2,716,127) = 29,534.23, p  < 0.001, and the Cramer's V (0.04, df ∗ = 6) indicates a small effect (Cohen,  1988 ). Unsurprisingly, benefits brought by the convenience of online learning are widely recognised by students across all school years (Figure  4 ), that is up to 75% of students reported that it is “more convenient to review course content” and 54% said that they “can learn anytime and anywhere” . Besides, we noticed that about 50% of early‐school‐year students appreciated the “access to courses delivered by famous teachers” and 40%–47% of high‐school‐year students indicated that online learning is “helpful to develop self‐regulation and autonomy” .

Perceived benefits of online learning reported by students

Perceived obstacles

The Chi‐square test shows a significant association between school years and students’ perceived obstacles in online learning, χ 2 (77, N  = 2,699,003) = 31,987.56, p < 0.001. This association is relatively weak as shown by the Cramer's V (0.04, df ∗ = 7; Cohen,  1988 ). As shown in Figure  5 , the biggest obstacles encountered by up to 73% of students were the “eyestrain caused by long staring at screens” . Disengagement caused by nearby disturbance was reported by around 40% of students, especially those of Year 1–3 and 10–12. Technological‐wise, about 50% of students experienced poor Internet connection during their learning process, and around 20% of students reported the “confusion in setting up the platforms” across of school years.

Perceived obstacles of online learning reported by students

Expectations for future practices of online learning – RQ3

Online learning activities.

The association between school years and students’ expected online learning activities is significant, χ 2 (66, N  = 2,416,093) = 38,784.81, p < 0.001. The Cramer's V is 0.05 ( df ∗ = 6) which suggests a small effect (Cohen,  1988 ). As shown in Figure  6 , the most expected activity for future online learning is “real‐time interaction with teachers” (55%), followed by “online group discussion and collaboration” (38%). We also observed that more early‐school‐year students expect reflective activities, such as “regular online practice examinations” ( χ 2 (3, N  = 1,048,575) = 11,644.98, p < 0.001), with a small effect size, Cramer's V  = 0.11 ( df ∗ = 1). In contrast, more high‐school‐year students expect “intelligent recommendation system …” ( χ 2 (3, N  = 1,048,575) = 15,327.00, p < 0.001), with a small effect size, Cramer's V  = 0.12 ( df ∗ = 1).

Students’ expected online learning activities

Regarding students’ learning conditions, substantial differences were observed in learning media, family dependency, and learning approaches adopted in online learning between students in different school years. The finding of more computer and smartphone usage in high‐school‐year than early‐school‐year students can probably be explained by that, with the growing abilities in utilising these media as well as the educational systems and tools which run on these media, high‐school‐year students tend to make better use of these media for online learning practices. Whereas, the differences in paper‐based materials may imply that high‐school‐year students in China have to accomplish a substantial amount of exercise, assignments, and exam papers to prepare for the National College Entrance Examination (NCEE), whose delivery was not entirely digitised due to the sudden transition to online learning. Meanwhile, high‐school‐year students may also have preferred using paper‐based materials for exam practice, as eventually, they would take their NCEE in the paper format. Therefore, these substantial differences in students’ usage of learning media should be addressed by customising the delivery method of online learning for different school years.

Other than these between‐age differences in learning media, the prevalence of smartphone in online learning resonates with Agung et al.’s ( 2020 ) finding on the issues surrounding the availability of compatible learning device. The prevalence of smartphone in K‐12 students is potentially problematic as the majority of the online learning platform and content is designed for computer‐based learning (Berge,  2005 ; Molnar et al.,  2019 ). Whereas learning with smartphones has its own unique challenges. For example, Gikas and Grant ( 2013 ) discovered that students who learn with smartphone experienced frustration with the small screen‐size, especially when trying to type with the tiny keypad. Another challenge relates to the distraction of various social media applications. Although similar distractions exist in computer and web‐based social media, the level of popularity, especially in the young generation, are much higher in mobile‐based social media (Montag et al.,  2018 ). In particular, the message notification function in smartphones could disengage students from learning activities and allure them to social media applications (Gikas & Grant,  2013 ). Given these challenges of learning with smartphones, more research efforts should be devoted to analysing students’ online learning behaviour in the setting of mobile learning to accommodate their needs better.

The differences in learning approaches, once again, illustrated that early‐school‐year students have different needs compared to high‐school‐year students. In particular, the low usage of the independent learning methods in early‐school‐year students may reflect their inability to engage in independent learning. Besides, the differences in help seeking behaviours demonstrated the distinctive needs for communication and interaction between different students, that is early‐school‐year students have a strong reliance on teachers and high‐school‐year students, who are equipped with stronger communication ability, are more inclined to interact with their peers. This finding implies that the design of online learning platforms should take students’ different needs into account. Thus, customisation is urgently needed for the delivery of online learning to different school years.

In terms of the perceived benefits and challenges of online learning, our results resonate with several previous findings. In particular, the benefits of convenience are in line with the flexibility advantages of online learning, which were mentioned in prior works (Appana,  2008 ; Bączek et al.,  2021 ; Barbour,  2013 ; Basuony et al.,  2020 ; Harvey et al.,  2014 ). Early‐school‐year students’ higher appreciation in having “access to courses delivered by famous teachers” and lower appreciation in the independent learning skills developed through online learning are also in line with previous literature (Barbour,  2013 ; Harvey et al.,  2014 ; Oliver et al.,  2009 ). Again, these similar findings may indicate the strong reliance that early‐school‐year students place on teachers, while high‐school‐year students are more capable of adapting to online learning by developing independent learning skills.

Technology‐wise, students’ experience of poor internet connection and confusion in setting up online learning platforms are particularly concerning. The problem of poor internet connection corroborated the findings reported in prior studies (Agung et al.,  2020 ; Barbour,  2013 ; Basuony et al.,  2020 ; Berge,  2005 ; Rice,  2006 ), that is the access issue surrounded the digital divide as one of the main challenges of online learning. In the era of 4G and 5G networks, educational authorities and institutions that deliver online education could fall into the misconception of most students have a stable internet connection at home. The internet issue we observed is particularly vital to students’ online learning experience as most students prefer real‐time communications (Figure  6 ), which rely heavily on stable internet connection. Likewise, the finding of students’ confusion in technology is also consistent with prior studies (Bączek et al.,  2021 ; Muilenburg & Berge,  2005 ; Niemi & Kousa,  2020 ; Song et al.,  2004 ). Students who were unsuccessfully in setting up the online learning platforms could potentially experience declines in confidence and enthusiasm for online learning, which would cause a subsequent unpleasant learning experience. Therefore, both the readiness of internet infrastructure and student technical skills remain as the significant challenges for the mass‐adoption of online learning.

On the other hand, students’ experience of eyestrain from extended screen time provided empirical evidence to support Spitzer’s ( 2001 ) speculation about the potential ergonomic impact of online learning. This negative effect is potentially related to the prevalence of smartphone device and the limited screen size of these devices. This finding not only demonstrates the potential ergonomic issues that would be caused by smartphone‐based online learning but also resonates with the aforementioned necessity of different platforms and content designs for different students.

A less‐mentioned problem in previous studies on online learning experiences is the disengagement caused by nearby disturbance, especially in Year 1–3 and 10–12. It is likely that early‐school‐year students suffered from this problem because of their underdeveloped metacognitive skills to concentrate on online learning without teachers’ guidance. As for high‐school‐year students, the reasons behind their disengagement require further investigation in the future. Especially it would be worthwhile to scrutinise whether this type of disengagement is caused by the substantial amount of coursework they have to undertake and the subsequent a higher level of pressure and a lower level of concentration while learning.

Across age‐level differences are also apparent in terms of students’ expectations of online learning. Although, our results demonstrated students’ needs of gaining social interaction with others during online learning, findings (Bączek et al.,  2021 ; Harvey et al.,  2014 ; Kuo et al.,  2014 ; Liu & Cavanaugh,  2012 ; Yates et al.,  2020 ). This need manifested differently across school years, with early‐school‐year students preferring more teacher interactions and learning regulation support. Once again, this finding may imply that early‐school‐year students are inadequate in engaging with online learning without proper guidance from their teachers. Whereas, high‐school‐year students prefer more peer interactions and recommendation to learning resources. This expectation can probably be explained by the large amount of coursework exposed to them. Thus, high‐school‐year students need further guidance to help them better direct their learning efforts. These differences in students’ expectations for future practices could guide the customisation of online learning delivery.

Implications

As shown in our results, improving the delivery of online learning not only requires the efforts of policymakers but also depend on the actions of teachers and parents. The following sub‐sections will provide recommendations for relevant stakeholders and discuss their essential roles in supporting online education.

Technical support

The majority of the students has experienced technical problems during online learning, including the internet lagging and confusion in setting up the learning platforms. These problems with technology could impair students’ learning experience (Kauffman,  2015 ; Muilenburg & Berge,  2005 ). Educational authorities and schools should always provide a thorough guide and assistance for students who are experiencing technical problems with online learning platforms or other related tools. Early screening and detection could also assist schools and teachers to direct their efforts more effectively in helping students with low technology skills (Wilkinson et al.,  2010 ). A potential identification method involves distributing age‐specific surveys that assess students’ Information and Communication Technology (ICT) skills at the beginning of online learning. For example, there are empirical validated ICT surveys available for both primary (Aesaert et al.,  2014 ) and high school (Claro et al.,  2012 ) students.

For students who had problems with internet lagging, the delivery of online learning should provide options that require fewer data and bandwidth. Lecture recording is the existing option but fails to address students’ need for real‐time interaction (Clark et al.,  2015 ; Malik & Fatima,  2017 ). A potential alternative involves providing students with the option to learn with digital or physical textbooks and audio‐conferencing, instead of screen sharing and video‐conferencing. This approach significantly reduces the amount of data usage and lowers the requirement of bandwidth for students to engage in smooth online interactions (Cisco,  2018 ). It also requires little additional efforts from teachers as official textbooks are often available for each school year, and thus, they only need to guide students through the materials during audio‐conferencing. Educational authority can further support this approach by making digital textbooks available for teachers and students, especially those in financial hardship. However, the lack of visual and instructor presence could potentially reduce students’ attention, recall of information, and satisfaction in online learning (Wang & Antonenko,  2017 ). Therefore, further research is required to understand whether the combination of digital or physical textbooks and audio‐conferencing is appropriate for students with internet problems. Alternatively, suppose the local technological infrastructure is well developed. In that case, governments and schools can also collaborate with internet providers to issue data and bandwidth vouchers for students who are experiencing internet problems due to financial hardship.

For future adoption of online learning, policymakers should consider the readiness of the local internet infrastructure. This recommendation is particularly important for developing countries, like Bangladesh, where the majority of the students reported the lack of internet infrastructure (Ramij & Sultana,  2020 ). In such environments, online education may become infeasible, and alternative delivery method could be more appropriate, for example, the Telesecundaria program provides TV education for rural areas of Mexico (Calderoni,  1998 ).

Other than technical problems, choosing a suitable online learning platform is also vital for providing students with a better learning experience. Governments and schools should choose an online learning platform that is customised for smartphone‐based learning, as the majority of students could be using smartphones for online learning. This recommendation is highly relevant for situations where students are forced or involuntarily engaged in online learning, like during the COVID‐19 pandemic, as they might not have access to a personal computer (Molnar et al.,  2019 ).

Customisation of delivery methods

Customising the delivery of online learning for students in different school years is the theme that appeared consistently across our findings. This customisation process is vital for making online learning an opportunity for students to develop independent learning skills, which could help prepare them for tertiary education and lifelong learning. However, the pedagogical design of K‐12 online learning programs should be differentiated from adult‐orientated programs as these programs are designed for independent learners, which is rarely the case for students in K‐12 education (Barbour & Reeves,  2009 ).

For early‐school‐year students, especially Year 1–3 students, providing them with sufficient guidance from both teachers and parents should be the priority as these students often lack the ability to monitor and reflect on learning progress. In particular, these students would prefer more real‐time interaction with teachers, tutoring from parents, and regular online practice examinations. These forms of guidance could help early‐school‐year students to cope with involuntary online learning, and potentially enhance their experience in future online learning. It should be noted that, early‐school‐year students demonstrated interest in intelligent monitoring and feedback systems for learning. Additional research is required to understand whether these young children are capable of understanding and using learning analytics that relay information on their learning progress. Similarly, future research should also investigate whether young children can communicate effectively through digital tools as potential inability could hinder student learning in online group activities. Therefore, the design of online learning for early‐school‐year students should focus less on independent learning but ensuring that students are learning effective under the guidance of teachers and parents.

In contrast, group learning and peer interaction are essential for older children and adolescents. The delivery of online learning for these students should focus on providing them with more opportunities to communicate with each other and engage in collaborative learning. Potential methods to achieve this goal involve assigning or encouraging students to form study groups (Lee et al.,  2011 ), directing students to use social media for peer communication (Dabbagh & Kitsantas,  2012 ), and providing students with online group assignments (Bickle & Rucker,  2018 ).

Special attention should be paid to students enrolled in high schools. For high‐school‐year students, in particular, students in Year 10–12, we also recommend to provide them with sufficient access to paper‐based learning materials, such as revision booklet and practice exam papers, so they remain familiar with paper‐based examinations. This recommendation applies to any students who engage in online learning but has to take their final examination in paper format. It is also imperative to assist high‐school‐year students who are facing examinations to direct their learning efforts better. Teachers can fulfil this need by sharing useful learning resources on the learning management system, if it is available, or through social media groups. Alternatively, students are interested in intelligent recommendation systems for learning resources, which are emerging in the literature (Corbi & Solans,  2014 ; Shishehchi et al.,  2010 ). These systems could provide personalised recommendations based on a series of evaluation on learners’ knowledge. Although it is infeasible for situations where the transformation to online learning happened rapidly (i.e., during the COVID‐19 pandemic), policymakers can consider embedding such systems in future online education.

Limitations

The current findings are limited to primary and secondary Chinese students who were involuntarily engaged in online learning during the COVID‐19 pandemic. Despite the large sample size, the population may not be representative as participants are all from a single province. Also, information about the quality of online learning platforms, teaching contents, and pedagogy approaches were missing because of the large scale of our study. It is likely that the infrastructures of online learning in China, such as learning platforms, instructional designs, and teachers’ knowledge about online pedagogy, were underprepared for the sudden transition. Thus, our findings may not represent the experience of students who voluntarily participated in well‐prepared online learning programs, in particular, the virtual school programs in America and Canada (Barbour & LaBonte,  2017 ; Molnar et al.,  2019 ). Lastly, the survey was only evaluated and validated by teachers but not students. Therefore, students with the lowest reading comprehension levels might have a different understanding of the items’ meaning, especially terminologies that involve abstract contracts like self‐regulation and autonomy in item Q17.

In conclusion, we identified across‐year differences between primary and secondary school students’ online learning experience during the COVID‐19 pandemic. Several recommendations were made for the future practice and research of online learning in the K‐12 student population. First, educational authorities and schools should provide sufficient technical support to help students to overcome potential internet and technical problems, as well as choosing online learning platforms that have been customised for smartphones. Second, customising the online pedagogy design for students in different school years, in particular, focusing on providing sufficient guidance for young children, more online collaborative opportunity for older children and adolescent, and additional learning resource for senior students who are facing final examinations.

CONFLICT OF INTEREST

There is no potential conflict of interest in this study.

ETHICS STATEMENT

The data are collected by the Department of Education of the Guangdong Province who also has the authority to approve research studies in K12 education in the province.

Supporting information

Supplementary Material

ACKNOWLEDGEMENTS

This work is supported by the National Natural Science Foundation of China (62077028, 61877029), the Science and Technology Planning Project of Guangdong (2020B0909030005, 2020B1212030003, 2020ZDZX3013, 2019B1515120010, 2018KTSCX016, 2019A050510024), the Science and Technology Planning Project of Guangzhou (201902010041), and the Fundamental Research Funds for the Central Universities (21617408, 21619404).

SURVEY ITEMS

Yan, L , Whitelock‐Wainwright, A , Guan, Q , Wen, G , Gašević, D , & Chen, G . Students’ experience of online learning during the COVID‐19 pandemic: A province‐wide survey study . Br J Educ Technol . 2021; 52 :2038–2057. 10.1111/bjet.13102 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

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The COVID-19 pandemic has changed education forever. This is how 

With schools shut across the world, millions of children have had to adapt to new types of learning. Image:  REUTERS/Gonzalo Fuentes

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Stay up to date:, education, gender and work.

• The COVID-19 has resulted in schools shut all across the world. Globally, over 1.2 billion children are out of the classroom.
• As a result, education has changed dramatically, with the distinctive rise of e-learning, whereby teaching is undertaken remotely and on digital platforms.
• Research suggests that online learning has been shown to increase retention of information, and take less time, meaning the changes coronavirus have caused might be here to stay.

While countries are at different points in their COVID-19 infection rates, worldwide there are currently more than 1.2 billion children in 186 countries affected by school closures due to the pandemic. In Denmark, children up to the age of 11 are returning to nurseries and schools after initially closing on 12 March , but in South Korea students are responding to roll calls from their teachers online .

With this sudden shift away from the classroom in many parts of the globe, some are wondering whether the adoption of online learning will continue to persist post-pandemic, and how such a shift would impact the worldwide education market.

Even before COVID-19, there was already high growth and adoption in education technology, with global edtech investments reaching US$18.66 billion in 2019 and the overall market for online education projected to reach $350 Billion by 2025 . Whether it is language apps , virtual tutoring , video conferencing tools, or online learning software , there has been a significant surge in usage since COVID-19.

How is the education sector responding to COVID-19?

In response to significant demand, many online learning platforms are offering free access to their services, including platforms like BYJU’S , a Bangalore-based educational technology and online tutoring firm founded in 2011, which is now the world’s most highly valued edtech company . Since announcing free live classes on its Think and Learn app, BYJU’s has seen a 200% increase in the number of new students using its product, according to Mrinal Mohit, the company's Chief Operating Officer.

Tencent classroom, meanwhile, has been used extensively since mid-February after the Chinese government instructed a quarter of a billion full-time students to resume their studies through online platforms. This resulted in the largest “online movement” in the history of education with approximately 730,000 , or 81% of K-12 students, attending classes via the Tencent K-12 Online School in Wuhan.

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Other companies are bolstering capabilities to provide a one-stop shop for teachers and students. For example, Lark, a Singapore-based collaboration suite initially developed by ByteDance as an internal tool to meet its own exponential growth, began offering teachers and students unlimited video conferencing time, auto-translation capabilities, real-time co-editing of project work, and smart calendar scheduling, amongst other features. To do so quickly and in a time of crisis, Lark ramped up its global server infrastructure and engineering capabilities to ensure reliable connectivity.

Alibaba’s distance learning solution, DingTalk, had to prepare for a similar influx: “To support large-scale remote work, the platform tapped Alibaba Cloud to deploy more than 100,000 new cloud servers in just two hours last month – setting a new record for rapid capacity expansion,” according to DingTalk CEO, Chen Hang.

Some school districts are forming unique partnerships, like the one between The Los Angeles Unified School District and PBS SoCal/KCET to offer local educational broadcasts, with separate channels focused on different ages, and a range of digital options. Media organizations such as the BBC are also powering virtual learning; Bitesize Daily , launched on 20 April, is offering 14 weeks of curriculum-based learning for kids across the UK with celebrities like Manchester City footballer Sergio Aguero teaching some of the content.

What does this mean for the future of learning?

While some believe that the unplanned and rapid move to online learning – with no training, insufficient bandwidth, and little preparation – will result in a poor user experience that is unconducive to sustained growth, others believe that a new hybrid model of education will emerge, with significant benefits. “I believe that the integration of information technology in education will be further accelerated and that online education will eventually become an integral component of school education,“ says Wang Tao, Vice President of Tencent Cloud and Vice President of Tencent Education.

There have already been successful transitions amongst many universities. For example, Zhejiang University managed to get more than 5,000 courses online just two weeks into the transition using “DingTalk ZJU”. The Imperial College London started offering a course on the science of coronavirus, which is now the most enrolled class launched in 2020 on Coursera .

Many are already touting the benefits: Dr Amjad, a Professor at The University of Jordan who has been using Lark to teach his students says, “It has changed the way of teaching. It enables me to reach out to my students more efficiently and effectively through chat groups, video meetings, voting and also document sharing, especially during this pandemic. My students also find it is easier to communicate on Lark. I will stick to Lark even after coronavirus, I believe traditional offline learning and e-learning can go hand by hand."

These 3 charts show the global growth in online learning

The challenges of online learning.

There are, however, challenges to overcome. Some students without reliable internet access and/or technology struggle to participate in digital learning; this gap is seen across countries and between income brackets within countries. For example, whilst 95% of students in Switzerland, Norway, and Austria have a computer to use for their schoolwork, only 34% in Indonesia do, according to OECD data .

In the US, there is a significant gap between those from privileged and disadvantaged backgrounds: whilst virtually all 15-year-olds from a privileged background said they had a computer to work on, nearly 25% of those from disadvantaged backgrounds did not. While some schools and governments have been providing digital equipment to students in need, such as in New South Wales , Australia, many are still concerned that the pandemic will widenthe digital divide .

Is learning online as effective?

For those who do have access to the right technology, there is evidence that learning online can be more effective in a number of ways. Some research shows that on average, students retain 25-60% more material when learning online compared to only 8-10% in a classroom. This is mostly due to the students being able to learn faster online; e-learning requires 40-60% less time to learn than in a traditional classroom setting because students can learn at their own pace, going back and re-reading, skipping, or accelerating through concepts as they choose.

Nevertheless, the effectiveness of online learning varies amongst age groups. The general consensus on children, especially younger ones, is that a structured environment is required , because kids are more easily distracted. To get the full benefit of online learning, there needs to be a concerted effort to provide this structure and go beyond replicating a physical class/lecture through video capabilities, instead, using a range of collaboration tools and engagement methods that promote “inclusion, personalization and intelligence”, according to Dowson Tong, Senior Executive Vice President of Tencent and President of its Cloud and Smart Industries Group.

Since studies have shown that children extensively use their senses to learn, making learning fun and effective through use of technology is crucial, according to BYJU's Mrinal Mohit. “Over a period, we have observed that clever integration of games has demonstrated higher engagement and increased motivation towards learning especially among younger students, making them truly fall in love with learning”, he says.

A changing education imperative

It is clear that this pandemic has utterly disrupted an education system that many assert was already losing its relevance . In his book, 21 Lessons for the 21st Century , scholar Yuval Noah Harari outlines how schools continue to focus on traditional academic skills and rote learning , rather than on skills such as critical thinking and adaptability, which will be more important for success in the future. Could the move to online learning be the catalyst to create a new, more effective method of educating students? While some worry that the hasty nature of the transition online may have hindered this goal, others plan to make e-learning part of their ‘new normal’ after experiencing the benefits first-hand.

The importance of disseminating knowledge is highlighted through COVID-19

Major world events are often an inflection point for rapid innovation – a clear example is the rise of e-commerce post-SARS . While we have yet to see whether this will apply to e-learning post-COVID-19, it is one of the few sectors where investment has not dried up . What has been made clear through this pandemic is the importance of disseminating knowledge across borders, companies, and all parts of society. If online learning technology can play a role here, it is incumbent upon all of us to explore its full potential.

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• Review Article
• Published: 27 September 2021

Why lockdown and distance learning during the COVID-19 pandemic are likely to increase the social class achievement gap

• Sébastien Goudeau   ORCID: orcid.org/0000-0001-7293-0977 1 ,
• Camille Sanrey   ORCID: orcid.org/0000-0003-3158-1306 1 ,
• Arnaud Stanczak   ORCID: orcid.org/0000-0002-2596-1516 2 ,
• Antony Manstead   ORCID: orcid.org/0000-0001-7540-2096 3 &
• Céline Darnon   ORCID: orcid.org/0000-0003-2613-689X 2  

Nature Human Behaviour volume  5 ,  pages 1273–1281 ( 2021 ) Cite this article

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The COVID-19 pandemic has forced teachers and parents to quickly adapt to a new educational context: distance learning. Teachers developed online academic material while parents taught the exercises and lessons provided by teachers to their children at home. Considering that the use of digital tools in education has dramatically increased during this crisis, and it is set to continue, there is a pressing need to understand the impact of distance learning. Taking a multidisciplinary view, we argue that by making the learning process rely more than ever on families, rather than on teachers, and by getting students to work predominantly via digital resources, school closures exacerbate social class academic disparities. To address this burning issue, we propose an agenda for future research and outline recommendations to help parents, teachers and policymakers to limit the impact of the lockdown on social-class-based academic inequality.

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The widespread effects of the COVID-19 pandemic that emerged in 2019–2020 have drastically increased health, social and economic inequalities 1 , 2 . For more than 900 million learners around the world, the pandemic led to the closure of schools and universities 3 . This exceptional situation forced teachers, parents and students to quickly adapt to a new educational context: distance learning. Teachers had to develop online academic materials that could be used at home to ensure educational continuity while ensuring the necessary physical distancing. Primary and secondary school students suddenly had to work with various kinds of support, which were usually provided online by their teachers. For college students, lockdown often entailed returning to their hometowns while staying connected with their teachers and classmates via video conferences, email and other digital tools. Despite the best efforts of educational institutions, parents and teachers to keep all children and students engaged in learning activities, ensuring educational continuity during school closure—something that is difficult for everyone—may pose unique material and psychological challenges for working-class families and students.

Not only did the pandemic lead to the closure of schools in many countries, often for several weeks, it also accelerated the digitalization of education and amplified the role of parental involvement in supporting the schoolwork of their children. Thus, beyond the specific circumstances of the COVID-19 lockdown, we believe that studying the effects of the pandemic on academic inequalities provides a way to more broadly examine the consequences of school closure and related effects (for example, digitalization of education) on social class inequalities. Indeed, bearing in mind that (1) the risk of further pandemics is higher than ever (that is, we are in a ‘pandemic era’ 4 , 5 ) and (2) beyond pandemics, the use of digital tools in education (and therefore the influence of parental involvement) has dramatically increased during this crisis, and is set to continue, there is a pressing need for an integrative and comprehensive model that examines the consequences of distance learning. Here, we propose such an integrative model that helps us to understand the extent to which the school closures associated with the pandemic amplify economic, digital and cultural divides that in turn affect the psychological functioning of parents, students and teachers in a way that amplifies academic inequalities. Bringing together research in social sciences, ranging from economics and sociology to social, cultural, cognitive and educational psychology, we argue that by getting students to work predominantly via digital resources rather than direct interactions with their teachers, and by making the learning process rely more than ever on families rather than teachers, school closures exacerbate social class academic disparities.

First, we review research showing that social class is associated with unequal access to digital tools, unequal familiarity with digital skills and unequal uses of such tools for learning purposes 6 , 7 . We then review research documenting how unequal familiarity with school culture, knowledge and skills can also contribute to the accentuation of academic inequalities 8 , 9 . Next, we present the results of surveys conducted during the 2020 lockdown showing that the quality and quantity of pedagogical support received from schools varied according to the social class of families (for examples, see refs. 10 , 11 , 12 ). We then argue that these digital, cultural and structural divides represent barriers to the ability of parents to provide appropriate support for children during distance learning (Fig. 1 ). These divides also alter the levels of self-efficacy of parents and children, thereby affecting their engagement in learning activities 13 , 14 . In the final section, we review preliminary evidence for the hypothesis that distance learning widens the social class achievement gap and we propose an agenda for future research. In addition, we outline recommendations that should help parents, teachers and policymakers to use social science research to limit the impact of school closure and distance learning on the social class achievement gap.

Economic, structural, digital and cultural divides influence the psychological functioning of parents and students in a way that amplify inequalities.

The digital divide

Unequal access to digital resources.

Although the use of digital technologies is almost ubiquitous in developed nations, there is a digital divide such that some people are more likely than others to be numerically excluded 15 (Fig. 1 ). Social class is a strong predictor of digital disparities, including the quality of hardware, software and Internet access 16 , 17 , 18 . For example, in 2019, in France, around 1 in 5 working-class families did not have personal access to the Internet compared with less than 1 in 20 of the most privileged families 19 . Similarly, in 2020, in the United Kingdom, 20% of children who were eligible for free school meals did not have access to a computer at home compared with 7% of other children 20 . In 2021, in the United States, 41% of working-class families do not own a laptop or desktop computer and 43% do not have broadband compared with 8% and 7%, respectively, of upper/middle-class Americans 21 . A similar digital gap is also evident between lower-income and higher-income countries 22 .

Second, simply having access to a computer and an Internet connection does not ensure effective distance learning. For example, many of the educational resources sent by teachers need to be printed, thereby requiring access to printers. Moreover, distance learning is more difficult in households with only one shared computer compared with those where each family member has their own 23 . Furthermore, upper/middle-class families are more likely to be able to guarantee a suitable workspace for each child than their working-class counterparts 24 .

In the context of school closures, such disparities are likely to have important consequences for educational continuity. In line with this idea, a survey of approximately 4,000 parents in the United Kingdom confirmed that during lockdown, more than half of primary school children from the poorest families did not have access to their own study space and were less well equipped for distance learning than higher-income families 10 . Similarly, a survey of around 1,300 parents in the Netherlands found that during lockdown, children from working-class families had fewer computers at home and less room to study than upper/middle-class children 11 .

Data from non-Western countries highlight a more general digital divide, showing that developing countries have poorer access to digital equipment. For example, in India in 2018, only 10.7% of households possessed a digital device 25 , while in Pakistan in 2020, 31% of higher-education teachers did not have Internet access and 68.4% did not have a laptop 26 . In general, developing countries lack access to digital technologies 27 , 28 , and these difficulties of access are even greater in rural areas (for example, see ref. 29 ). Consequently, school closures have huge repercussions for the continuity of learning in these countries. For example, in India in 2018, only 11% of the rural and 40% of the urban population above 14 years old could use a computer and access the Internet 25 . Time spent on education during school closure decreased by 80% in Bangladesh 30 . A similar trend was observed in other countries 31 , with only 22% of children engaging in remote learning in Kenya 32 and 50% in Burkina Faso 33 . In Ghana, 26–32% of children spent no time at all on learning during the pandemic 34 . Beyond the overall digital divide, social class disparities are also evident in developing countries, with lower access to digital resources among households in which parental educational levels were low (versus households in which parental educational levels were high; for example, see ref. 35 for Nigeria and ref. 31 for Ecuador).

Unequal digital skills

In addition to unequal access to digital tools, there are also systematic variations in digital skills 36 , 37 (Fig. 1 ). Upper/middle-class families are more familiar with digital tools and resources and are therefore more likely to have the digital skills needed for distance learning 38 , 39 , 40 . These digital skills are particularly useful during school closures, both for students and for parents, for organizing, retrieving and correctly using the resources provided by the teachers (for example, sending or receiving documents by email, printing documents or using word processors).

Social class disparities in digital skills can be explained in part by the fact that children from upper/middle-class families have the opportunity to develop digital skills earlier than working-class families 41 . In member countries of the OECD (Organisation for Economic Co-operation and Development), only 23% of working-class children had started using a computer at the age of 6 years or earlier compared with 43% of upper/middle-class children 42 . Moreover, because working-class people tend to persist less than upper/middle-class people when confronted with digital difficulties 23 , the use of digital tools and resources for distance learning may interfere with the ability of parents to help children with their schoolwork.

Unequal use of digital tools

A third level of digital divide concerns variations in digital tool use 18 , 43 (Fig. 1 ). Upper/middle-class families are more likely to use digital resources for work and education 6 , 41 , 44 , whereas working-class families are more likely to use these resources for entertainment, such as electronic games or social media 6 , 45 . This divide is also observed among students, whereby working-class students tend to use digital technologies for leisure activities, whereas their upper/middle-class peers are more likely to use them for academic activities 46 and to consider that computers and the Internet provide an opportunity for education and training 23 . Furthermore, working-class families appear to regulate the digital practices of their children less 47 and are more likely to allow screens in the bedrooms of children and teenagers without setting limits on times or practices 48 .

In sum, inequalities in terms of digital resources, skills and use have strong implications for distance learning. This is because they make working-class students and parents particularly vulnerable when learning relies on extensive use of digital devices rather than on face-to-face interaction with teachers.

The cultural divide

Even if all three levels of digital divide were closed, upper/middle-class families would still be better prepared than working-class families to ensure educational continuity for their children. Upper/middle-class families are more familiar with the academic knowledge and skills that are expected and valued in educational settings, as well as with the independent, autonomous way of learning that is valued in the school culture and becomes even more important during school closure (Fig. 1 ).

Unequal familiarity with academic knowledge and skills

According to classical social reproduction theory 8 , 49 , school is not a neutral place in which all forms of language and knowledge are equally valued. Academic contexts expect and value culture-specific and taken-for-granted forms of knowledge, skills and ways of being, thinking and speaking that are more in tune with those developed through upper/middle-class socialization (that is, ‘cultural capital’ 8 , 50 , 51 , 52 , 53 ). For instance, academic contexts value interest in the arts, museums and literature 54 , 55 , a type of interest that is more likely to develop through socialization in upper/middle-class families than in working-class socialization 54 , 56 . Indeed, upper/middle-class parents are more likely than working-class parents to engage in activities that develop this cultural capital. For example, they possess more books and cultural objects at home, read more stories to their children and visit museums and libraries more often (for examples, see refs. 51 , 54 , 55 ). Upper/middle-class children are also more involved in extra-curricular activities (for example, playing a musical instrument) than working-class children 55 , 56 , 57 .

Beyond this implicit familiarization with the school curriculum, upper/middle-class parents more often organize educational activities that are explicitly designed to develop academic skills of their children 57 , 58 , 59 . For example, they are more likely to monitor and re-explain lessons or use games and textbooks to develop and reinforce academic skills (for example, labelling numbers, letters or colours 57 , 60 ). Upper/middle-class parents also provide higher levels of support and spend more time helping children with homework than working-class parents (for examples, see refs. 61 , 62 ). Thus, even if all parents are committed to the academic success of their children, working-class parents have fewer chances to provide the help that children need to complete homework 63 , and homework is more beneficial for children from upper-middle class families than for children from working-class families 64 , 65 .

School closures amplify the impact of cultural inequalities

The trends described above have been observed in ‘normal’ times when schools are open. School closures, by making learning rely more strongly on practices implemented at home (rather than at school), are likely to amplify the impact of these disparities. Consistent with this idea, research has shown that the social class achievement gap usually greatly widens during school breaks—a phenomenon described as ‘summer learning loss’ or ‘summer setback’ 66 , 67 , 68 . During holidays, the learning by children tends to decline, and this is particularly pronounced in children from working-class families. Consequently, the social class achievement gap grows more rapidly during the summer months than it does in the rest of the year. This phenomenon is partly explained by the fact that during the break from school, social class disparities in investment in activities that are beneficial for academic achievement (for example, reading, travelling to a foreign country or museum visits) are more pronounced.

Therefore, when they are out of school, children from upper/middle-class backgrounds may continue to develop academic skills unlike their working-class counterparts, who may stagnate or even regress. Research also indicates that learning loss during school breaks tends to be cumulative 66 . Thus, repeated episodes of school closure are likely to have profound consequences for the social class achievement gap. Consistent with the idea that school closures could lead to similar processes as those identified during summer breaks, a recent survey indicated that during the COVID-19 lockdown in the United Kingdom, children from upper/middle-class families spent more time on educational activities (5.8 h per day) than those from working-class families (4.5 h per day) 7 , 69 .

Unequal dispositions for autonomy and self-regulation

School closures have encouraged autonomous work among students. This ‘independent’ way of studying is compatible with the family socialization of upper/middle-class students, but does not match the interdependent norms more commonly associated with working-class contexts 9 . Upper/middle-class contexts tend to promote cultural norms of independence whereby individuals perceive themselves as autonomous actors, independent of other individuals and of the social context, able to pursue their own goals 70 . For example, upper/middle-class parents tend to invite children to express their interests, preferences and opinions during the various activities of everyday life 54 , 55 . Conversely, in working-class contexts characterized by low economic resources and where life is more uncertain, individuals tend to perceive themselves as interdependent, connected to others and members of social groups 53 , 70 , 71 . This interdependent self-construal fits less well with the independent culture of academic contexts. This cultural mismatch between interdependent self-construal common in working-class students and the independent norms of the educational institution has negative consequences for academic performance 9 .

Once again, the impact of these differences is likely to be amplified during school closures, when being able to work alone and autonomously is especially useful. The requirement to work alone is more likely to match the independent self-construal of upper/middle-class students than the interdependent self-construal of working-class students. In the case of working-class students, this mismatch is likely to increase their difficulties in working alone at home. Supporting our argument, recent research has shown that working-class students tend to underachieve in contexts where students work individually compared with contexts where students work with others 72 . Similarly, during school closures, high self-regulation skills (for example, setting goals, selecting appropriate learning strategies and maintaining motivation 73 ) are required to maintain study activities and are likely to be especially useful for using digital resources efficiently. Research has shown that students from working-class backgrounds typically develop their self-regulation skills to a lesser extent than those from upper/middle-class backgrounds 74 , 75 , 76 .

Interestingly, some authors have suggested that independent (versus interdependent) self-construal may also affect communication with teachers 77 . Indeed, in the context of distance learning, working-class families are less likely to respond to the communication of teachers because their ‘interdependent’ self leads them to respect hierarchies, and thus perceive teachers as an expert who ‘can be trusted to make the right decisions for learning’. Upper/middle class families, relying on ‘independent’ self-construal, are more inclined to seek individualized feedback, and therefore tend to participate to a greater extent in exchanges with teachers. Such cultural differences are important because they can also contribute to the difficulties encountered by working-class families.

The structural divide: unequal support from schools

The issues reviewed thus far all increase the vulnerability of children and students from underprivileged backgrounds when schools are closed. To offset these disadvantages, it might be expected that the school should increase its support by providing additional resources for working-class students. However, recent data suggest that differences in the material and human resources invested in providing educational support for children during periods of school closure were—paradoxically—in favour of upper/middle-class students (Fig. 1 ). In England, for example, upper/middle-class parents reported benefiting from online classes and video-conferencing with teachers more often than working-class parents 10 . Furthermore, active help from school (for example, online teaching, private tutoring or chats with teachers) occurred more frequently in the richest households (64% of the richest households declared having received help from school) than in the poorest households (47%). Another survey found that in the United Kingdom, upper/middle-class children were more likely to take online lessons every day (30%) than working-class students (16%) 12 . This substantial difference might be due, at least in part, to the fact that private schools are better equipped in terms of online platforms (60% of schools have at least one online platform) than state schools (37%, and 23% in the most deprived schools) and were more likely to organize daily online lessons. Similarly, in the United Kingdom, in schools with a high proportion of students eligible for free school meals, teachers were less inclined to broadcast an online lesson for their pupils 78 . Interestingly, 58% of teachers in the wealthiest areas reported having messaged their students or their students’ parents during lockdown compared with 47% in the most deprived schools. In addition, the probability of children receiving technical support from the school (for example, by providing pupils with laptops or other devices) is, surprisingly, higher in the most advantaged schools than in the most deprived 78 .

In addition to social class disparities, there has been less support from schools for African-American and Latinx students. During school closures in the United States, 40% of African-American students and 30% of Latinx students received no online teaching compared with 10% of white students 79 . Another source of inequality is that the probability of school closure was correlated with social class and race. In the United States, for example, school closures from September to December 2020 were more common in schools with a high proportion of racial/ethnic minority students, who experience homelessness and are eligible for free/discounted school meals 80 .

Similarly, access to educational resources and support was lower in poorer (compared with richer) countries 81 . In sub-Saharan Africa, during lockdown, 45% of children had no exposure at all to any type of remote learning. Of those who did, the medium was mostly radio, television or paper rather than digital. In African countries, at most 10% of children received some material through the Internet. In Latin America, 90% of children received some remote learning, but less than half of that was through the internet—the remainder being via radio and television 81 . In Ecuador, high-school students from the lowest wealth quartile had fewer remote-learning opportunities, such as Google class/Zoom, than students from the highest wealth quartile 31 .

Thus, the achievement gap and its accentuation during lockdown are due not only to the cultural and digital disadvantages of working-class families but also to unequal support from schools. This inequality in school support is not due to teachers being indifferent to or even supportive of social stratification. Rather, we believe that these effects are fundamentally structural. In many countries, schools located in upper/middle-class neighbourhoods have more money than those in the poorest neighbourhoods. Moreover, upper/middle-class parents invest more in the schools of their children than working-class parents (for example, see ref. 82 ), and schools have an interest in catering more for upper/middle-class families than for working-class families 83 . Additionally, the expectation of teachers may be lower for working-class children 84 . For example, they tend to estimate that working-class students invest less effort in learning than their upper/middle-class counterparts 85 . These differences in perception may have influenced the behaviour of teachers during school closure, such that teachers in privileged neighbourhoods provided more information to students because they expected more from them in term of effort and achievement. The fact that upper/middle-class parents are better able than working-class parents to comply with the expectations of teachers (for examples, see refs. 55 , 86 ) may have reinforced this phenomenon. These discrepancies echo data showing that working-class students tend to request less help in their schoolwork than upper/middle-class ones 87 , and they may even avoid asking for help because they believe that such requests could lead to reprimands 88 . During school closures, these students (and their families) may in consequence have been less likely to ask for help and resources. Jointly, these phenomena have resulted in upper/middle-class families receiving more support from schools during lockdown than their working-class counterparts.

Psychological effects of digital, cultural and structural divides

Despite being strongly influenced by social class, differences in academic achievement are often interpreted by parents, teachers and students as reflecting differences in ability 89 . As a result, upper/middle-class students are usually perceived—and perceive themselves—as smarter than working-class students, who are perceived—and perceive themselves—as less intelligent 90 , 91 , 92 or less able to succeed 93 . Working-class students also worry more about the fact that they might perform more poorly than upper/middle-class students 94 , 95 . These fears influence academic learning in important ways. In particular, they can consume cognitive resources when children and students work on academic tasks 96 , 97 . Self-efficacy also plays a key role in engaging in learning and perseverance in the face of difficulties 13 , 98 . In addition, working-class students are those for whom the fear of being outperformed by others is the most negatively related to academic performance 99 .

The fact that working-class children and students are less familiar with the tasks set by teachers, and less well equipped and supported, makes them more likely to experience feelings of incompetence (Fig. 1 ). Working-class parents are also more likely than their upper/middle-class counterparts to feel unable to help their children with schoolwork. Consistent with this, research has shown that both working-class students and parents have lower feelings of academic self-efficacy than their upper/middle-class counterparts 100 , 101 . These differences have been documented under ‘normal’ conditions but are likely to be exacerbated during distance learning. Recent surveys conducted during the school closures have confirmed that upper/middle-class families felt better able to support their children in distance learning than did working-class families 10 and that upper/middle-class parents helped their children more and felt more capable to do so 11 , 12 .

Pandemic disparity, future directions and recommendations

The research reviewed thus far suggests that children and their families are highly unequal with respect to digital access, skills and use. It also shows that upper/middle-class students are more likely to be supported in their homework (by their parents and teachers) than working-class students, and that upper/middle-class students and parents will probably feel better able than working-class ones to adapt to the context of distance learning. For all these reasons, we anticipate that as a result of school closures, the COVID-19 pandemic will substantially increase the social class achievement gap. Because school closures are a recent occurrence, it is too early to measure with precision their effects on the widening of the achievement gap. However, some recent data are consistent with this idea.

Evidence for a widening gap during the pandemic

Comparing academic achievement in 2020 with previous years provides an early indication of the effects of school closures during the pandemic. In France, for example, first and second graders take national evaluations at the beginning of the school year. Initial comparisons of the results for 2020 with those from previous years revealed that the gap between schools classified as ‘priority schools’ (those in low-income urban areas) and schools in higher-income neighbourhoods—a gap observed every year—was particularly pronounced in 2020 in both French and mathematics 102 .

Similarly, in the Netherlands, national assessments take place twice a year. In 2020, they took place both before and after school closures. A recent analysis compared progress during this period in 2020 in mathematics/arithmetic, spelling and reading comprehension for 7–11-year-old students within the same period in the three previous years 103 . Results indicated a general learning loss in 2020. More importantly, for the 8% of working-class children, the losses were 40% greater than they were for upper/middle-class children.

Similar results were observed in Belgium among students attending the final year of primary school. Compared with students from previous cohorts, students affected by school closures experienced a substantial decrease in their mathematics and language scores, with children from more disadvantaged backgrounds experiencing greater learning losses 104 . Likewise, oral reading assessments in more than 100 school districts in the United States showed that the development of this skill among children in second and third grade significantly slowed between Spring and Autumn 2020, but this slowdown was more pronounced in schools from lower-achieving districts 105 .

It is likely that school closures have also amplified racial disparities in learning and achievement. For example, in the United States, after the first lockdown, students of colour lost the equivalent of 3–5 months of learning, whereas white students were about 1–3 months behind. Moreover, in the Autumn, when some students started to return to classrooms, African-American and Latinx students were more likely to continue distance learning, despite being less likely to have access to the digital tools, Internet access and live contact with teachers 106 .

In some African countries (for example, Ethiopia, Kenya, Liberia, Tanzania and Uganda), the COVID-19 crisis has resulted in learning loss ranging from 6 months to more 1 year 107 , and this learning loss appears to be greater for working-class children (that is, those attending no-fee schools) than for upper/middle-class children 108 .

These findings show that school closures have exacerbated achievement gaps linked to social class and ethnicity. However, more research is needed to address the question of whether school closures differentially affect the learning of students from working- and upper/middle-class families.

Future directions

First, to assess the specific and unique impact of school closures on student learning, longitudinal research should compare student achievement at different times of the year, before, during and after school closures, as has been done to document the summer learning loss 66 , 109 . In the coming months, alternating periods of school closure and opening may occur, thereby presenting opportunities to do such research. This would also make it possible to examine whether the gap diminishes a few weeks after children return to in-school learning or whether, conversely, it increases with time because the foundations have not been sufficiently acquired to facilitate further learning 110 .

Second, the mechanisms underlying the increase in social class disparities during school closures should be examined. As discussed above, school closures result in situations for which students are unevenly prepared and supported. It would be appropriate to seek to quantify the contribution of each of the factors that might be responsible for accentuating the social class achievement gap. In particular, distinguishing between factors that are relatively ‘controllable’ (for example, resources made available to pupils) and those that are more difficult to control (for example, the self-efficacy of parents in supporting the schoolwork of their children) is essential to inform public policy and teaching practices.

Third, existing studies are based on general comparisons and very few provide insights into the actual practices that took place in families during school closure and how these practices affected the achievement gap. For example, research has documented that parents from working-class backgrounds are likely to find it more difficult to help their children to complete homework and to provide constructive feedback 63 , 111 , something that could in turn have a negative impact on the continuity of learning of their children. In addition, it seems reasonable to assume that during lockdown, parents from upper/middle-class backgrounds encouraged their children to engage in practices that, even if not explicitly requested by teachers, would be beneficial to learning (for example, creative activities or reading). Identifying the practices that best predict the maintenance or decline of educational achievement during school closures would help identify levers for intervention.

Finally, it would be interesting to investigate teaching practices during school closures. The lockdown in the spring of 2020 was sudden and unexpected. Within a few days, teachers had to find a way to compensate for the school closure, which led to highly variable practices. Some teachers posted schoolwork on platforms, others sent it by email, some set work on a weekly basis while others set it day by day. Some teachers also set up live sessions in large or small groups, providing remote meetings for questions and support. There have also been variations in the type of feedback given to students, notably through the monitoring and correcting of work. Future studies should examine in more detail what practices schools and teachers used to compensate for the school closures and their effects on widening, maintaining or even reducing the gap, as has been done for certain specific literacy programmes 112 as well as specific instruction topics (for example, ecology and evolution 113 ).

Practical recommendations

We are aware of the debate about whether social science research on COVID-19 is suitable for making policy decisions 114 , and we draw attention to the fact that some of our recommendations (Table 1 ) are based on evidence from experiments or interventions carried out pre-COVID while others are more speculative. In any case, we emphasize that these suggestions should be viewed with caution and be tested in future research. Some of our recommendations could be implemented in the event of new school closures, others only when schools re-open. We also acknowledge that while these recommendations are intended for parents and teachers, their implementation largely depends on the adoption of structural policies. Importantly, given all the issues discussed above, we emphasize the importance of prioritizing, wherever possible, in-person learning over remote learning 115 and where this is not possible, of implementing strong policies to support distance learning, especially for disadvantaged families.

Where face-to face teaching is not possible and teachers are responsible for implementing distance learning, it will be important to make them aware of the factors that can exacerbate inequalities during lockdown and to provide them with guidance about practices that would reduce these inequalities. Thus, there is an urgent need for interventions aimed at making teachers aware of the impact of the social class of children and families on the following factors: (1) access to, familiarity with and use of digital devices; (2) familiarity with academic knowledge and skills; and (3) preparedness to work autonomously. Increasing awareness of the material, cultural and psychological barriers that working-class children and families face during lockdown should increase the quality and quantity of the support provided by teachers and thereby positively affect the achievements of working-class students.

In addition to increasing the awareness of teachers of these barriers, teachers should be encouraged to adjust the way they communicate with working-class families due to differences in self-construal compared with upper/middle-class families 77 . For example, questions about family (rather than personal) well-being would be congruent with interdependent self-construals. This should contribute to better communication and help keep a better track of the progress of students during distance learning.

It is also necessary to help teachers to engage in practices that have a chance of reducing inequalities 53 , 116 . Particularly important is that teachers and schools ensure that homework can be done by all children, for example, by setting up organizations that would help children whose parents are not in a position to monitor or assist with the homework of their children. Options include homework help groups and tutoring by teachers after class. When schools are open, the growing tendency to set homework through digital media should be resisted as far as possible given the evidence we have reviewed above. Moreover, previous research has underscored the importance of homework feedback provided by teachers, which is positively related to the amount of homework completed and predictive of academic performance 117 . Where homework is web-based, it has also been shown that feedback on web-based homework enhances the learning of students 118 . It therefore seems reasonable to predict that the social class achievement gap will increase more slowly (or even remain constant or be reversed) in schools that establish individualized monitoring of students, by means of regular calls and feedback on homework, compared with schools where the support provided to pupils is more generic.

Given that learning during lockdown has increasingly taken place in family settings, we believe that interventions involving the family are also likely to be effective 119 , 120 , 121 . Simply providing families with suitable material equipment may be insufficient. Families should be given training in the efficient use of digital technology and pedagogical support. This would increase the self-efficacy of parents and students, with positive consequences for achievement. Ideally, such training would be delivered in person to avoid problems arising from the digital divide. Where this is not possible, individualized online tutoring should be provided. For example, studies conducted during the lockdown in Botswana and Italy have shown that individual online tutoring directly targeting either parents or students in middle school has a positive impact on the achievement of students, particularly for working-class students 122 , 123 .

Interventions targeting families should also address the psychological barriers faced by working-class families and children. Some interventions have already been designed and been shown to be effective in reducing the social class achievement gap, particularly in mathematics and language 124 , 125 , 126 . For example, research showed that an intervention designed to train low-income parents in how to support the mathematical development of their pre-kindergarten children (including classes and access to a library of kits to use at home) increased the quality of support provided by the parents, with a corresponding impact on the development of mathematical knowledge of their children. Such interventions should be particularly beneficial in the context of school closure.

Beyond its impact on academic performance and inequalities, the COVID-19 crisis has shaken the economies of countries around the world, casting millions of families around the world into poverty 127 , 128 , 129 . As noted earlier, there has been a marked increase in economic inequalities, bringing with it all the psychological and social problems that such inequalities create 130 , 131 , especially for people who live in scarcity 132 . The increase in educational inequalities is just one facet of the many difficulties that working-class families will encounter in the coming years, but it is one that could seriously limit the chances of their children escaping from poverty by reducing their opportunities for upward mobility. In this context, it should be a priority to concentrate resources on the most deprived students. A large proportion of the poorest households do not own a computer and do not have personal access to the Internet, which has important consequences for distance learning. During school closures, it is therefore imperative to provide such families with adequate equipment and Internet service, as was done in some countries in spring 2020. Even if the provision of such equipment is not in itself sufficient, it is a necessary condition for ensuring pedagogical continuity during lockdown.

Finally, after prolonged periods of school closure, many students may not have acquired the skills needed to pursue their education. A possible consequence would be an increase in the number of students for whom teachers recommend class repetitions. Class repetitions are contentious. On the one hand, class repetition more frequently affects working-class children and is not efficient in terms of learning improvement 133 . On the other hand, accepting lower standards of academic achievement or even suspending the practice of repeating a class could lead to pupils pursuing their education without mastering the key abilities needed at higher grades. This could create difficulties in subsequent years and, in this sense, be counterproductive. We therefore believe that the most appropriate way to limit the damage of the pandemic would be to help children catch up rather than allowing them to continue without mastering the necessary skills. As is being done in some countries, systematic remedial courses (for example, summer learning programmes) should be organized and financially supported following periods of school closure, with priority given to pupils from working-class families. Such interventions have genuine potential in that research has shown that participation in remedial summer programmes is effective in reducing learning loss during the summer break 134 , 135 , 136 . For example, in one study 137 , 438 students from high-poverty schools were offered a multiyear summer school programme that included various pedagogical and enrichment activities (for example, science investigation and music) and were compared with a ‘no-treatment’ control group. Students who participated in the summer programme progressed more than students in the control group. A meta-analysis 138 of 41 summer learning programmes (that is, classroom- and home-based summer interventions) involving children from kindergarten to grade 8 showed that these programmes had significantly larger benefits for children from working-class families. Although such measures are costly, the cost is small compared to the price of failing to fulfil the academic potential of many students simply because they were not born into upper/middle-class families.

The unprecedented nature of the current pandemic means that we lack strong data on what the school closure period is likely to produce in terms of learning deficits and the reproduction of social inequalities. However, the research discussed in this article suggests that there are good reasons to predict that this period of school closures will accelerate the reproduction of social inequalities in educational achievement.

By making school learning less dependent on teachers and more dependent on families and digital tools and resources, school closures are likely to greatly amplify social class inequalities. At a time when many countries are experiencing second, third or fourth waves of the pandemic, resulting in fresh periods of local or general lockdowns, systematic efforts to test these predictions are urgently needed along with steps to reduce the impact of school closures on the social class achievement gap.

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We thank G. Reis for editing the figure. The writing of this manuscript was supported by grant ANR-19-CE28-0007–PRESCHOOL from the French National Research Agency (S.G.).

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Students’ online learning challenges during the pandemic and how they cope with them: The case of the Philippines

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Recently, the education system has faced an unprecedented health crisis that has shaken up its foundation. Given today’s uncertainties, it is vital to gain a nuanced understanding of students’ online learning experience in times of the COVID-19 pandemic. Although many studies have investigated this area, limited information is available regarding the challenges and the specific strategies that students employ to overcome them. Thus, this study attempts to fill in the void. Using a mixed-methods approach, the findings revealed that the online learning challenges of college students varied in terms of type and extent. Their greatest challenge was linked to their learning environment at home, while their least challenge was technological literacy and competency. The findings further revealed that the COVID-19 pandemic had the greatest impact on the quality of the learning experience and students’ mental health. In terms of strategies employed by students, the most frequently used were resource management and utilization, help-seeking, technical aptitude enhancement, time management, and learning environment control. Implications for classroom practice, policy-making, and future research are discussed.

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1 Introduction

Since the 1990s, the world has seen significant changes in the landscape of education as a result of the ever-expanding influence of technology. One such development is the adoption of online learning across different learning contexts, whether formal or informal, academic and non-academic, and residential or remotely. We began to witness schools, teachers, and students increasingly adopt e-learning technologies that allow teachers to deliver instruction interactively, share resources seamlessly, and facilitate student collaboration and interaction (Elaish et al., 2019 ; Garcia et al., 2018 ). Although the efficacy of online learning has long been acknowledged by the education community (Barrot, 2020 , 2021 ; Cavanaugh et al., 2009 ; Kebritchi et al., 2017 ; Tallent-Runnels et al., 2006 ; Wallace, 2003 ), evidence on the challenges in its implementation continues to build up (e.g., Boelens et al., 2017 ; Rasheed et al., 2020 ).

Recently, the education system has faced an unprecedented health crisis (i.e., COVID-19 pandemic) that has shaken up its foundation. Thus, various governments across the globe have launched a crisis response to mitigate the adverse impact of the pandemic on education. This response includes, but is not limited to, curriculum revisions, provision for technological resources and infrastructure, shifts in the academic calendar, and policies on instructional delivery and assessment. Inevitably, these developments compelled educational institutions to migrate to full online learning until face-to-face instruction is allowed. The current circumstance is unique as it could aggravate the challenges experienced during online learning due to restrictions in movement and health protocols (Gonzales et al., 2020 ; Kapasia et al., 2020 ). Given today’s uncertainties, it is vital to gain a nuanced understanding of students’ online learning experience in times of the COVID-19 pandemic. To date, many studies have investigated this area with a focus on students’ mental health (Copeland et al., 2021 ; Fawaz et al., 2021 ), home learning (Suryaman et al., 2020 ), self-regulation (Carter et al., 2020 ), virtual learning environment (Almaiah et al., 2020 ; Hew et al., 2020 ; Tang et al., 2020 ), and students’ overall learning experience (e.g., Adarkwah, 2021 ; Day et al., 2021 ; Khalil et al., 2020 ; Singh et al., 2020 ). There are two key differences that set the current study apart from the previous studies. First, it sheds light on the direct impact of the pandemic on the challenges that students experience in an online learning space. Second, the current study explores students’ coping strategies in this new learning setup. Addressing these areas would shed light on the extent of challenges that students experience in a full online learning space, particularly within the context of the pandemic. Meanwhile, our nuanced understanding of the strategies that students use to overcome their challenges would provide relevant information to school administrators and teachers to better support the online learning needs of students. This information would also be critical in revisiting the typology of strategies in an online learning environment.

2 Literature review

2.1 education and the covid-19 pandemic.

In December 2019, an outbreak of a novel coronavirus, known as COVID-19, occurred in China and has spread rapidly across the globe within a few months. COVID-19 is an infectious disease caused by a new strain of coronavirus that attacks the respiratory system (World Health Organization, 2020 ). As of January 2021, COVID-19 has infected 94 million people and has caused 2 million deaths in 191 countries and territories (John Hopkins University, 2021 ). This pandemic has created a massive disruption of the educational systems, affecting over 1.5 billion students. It has forced the government to cancel national examinations and the schools to temporarily close, cease face-to-face instruction, and strictly observe physical distancing. These events have sparked the digital transformation of higher education and challenged its ability to respond promptly and effectively. Schools adopted relevant technologies, prepared learning and staff resources, set systems and infrastructure, established new teaching protocols, and adjusted their curricula. However, the transition was smooth for some schools but rough for others, particularly those from developing countries with limited infrastructure (Pham & Nguyen, 2020 ; Simbulan, 2020 ).

Inevitably, schools and other learning spaces were forced to migrate to full online learning as the world continues the battle to control the vicious spread of the virus. Online learning refers to a learning environment that uses the Internet and other technological devices and tools for synchronous and asynchronous instructional delivery and management of academic programs (Usher & Barak, 2020 ; Huang, 2019 ). Synchronous online learning involves real-time interactions between the teacher and the students, while asynchronous online learning occurs without a strict schedule for different students (Singh & Thurman, 2019 ). Within the context of the COVID-19 pandemic, online learning has taken the status of interim remote teaching that serves as a response to an exigency. However, the migration to a new learning space has faced several major concerns relating to policy, pedagogy, logistics, socioeconomic factors, technology, and psychosocial factors (Donitsa-Schmidt & Ramot, 2020 ; Khalil et al., 2020 ; Varea & González-Calvo, 2020 ). With reference to policies, government education agencies and schools scrambled to create fool-proof policies on governance structure, teacher management, and student management. Teachers, who were used to conventional teaching delivery, were also obliged to embrace technology despite their lack of technological literacy. To address this problem, online learning webinars and peer support systems were launched. On the part of the students, dropout rates increased due to economic, psychological, and academic reasons. Academically, although it is virtually possible for students to learn anything online, learning may perhaps be less than optimal, especially in courses that require face-to-face contact and direct interactions (Franchi, 2020 ).

2.2 Related studies

Recently, there has been an explosion of studies relating to the new normal in education. While many focused on national policies, professional development, and curriculum, others zeroed in on the specific learning experience of students during the pandemic. Among these are Copeland et al. ( 2021 ) and Fawaz et al. ( 2021 ) who examined the impact of COVID-19 on college students’ mental health and their coping mechanisms. Copeland et al. ( 2021 ) reported that the pandemic adversely affected students’ behavioral and emotional functioning, particularly attention and externalizing problems (i.e., mood and wellness behavior), which were caused by isolation, economic/health effects, and uncertainties. In Fawaz et al.’s ( 2021 ) study, students raised their concerns on learning and evaluation methods, overwhelming task load, technical difficulties, and confinement. To cope with these problems, students actively dealt with the situation by seeking help from their teachers and relatives and engaging in recreational activities. These active-oriented coping mechanisms of students were aligned with Carter et al.’s ( 2020 ), who explored students’ self-regulation strategies.

In another study, Tang et al. ( 2020 ) examined the efficacy of different online teaching modes among engineering students. Using a questionnaire, the results revealed that students were dissatisfied with online learning in general, particularly in the aspect of communication and question-and-answer modes. Nonetheless, the combined model of online teaching with flipped classrooms improved students’ attention, academic performance, and course evaluation. A parallel study was undertaken by Hew et al. ( 2020 ), who transformed conventional flipped classrooms into fully online flipped classes through a cloud-based video conferencing app. Their findings suggested that these two types of learning environments were equally effective. They also offered ways on how to effectively adopt videoconferencing-assisted online flipped classrooms. Unlike the two studies, Suryaman et al. ( 2020 ) looked into how learning occurred at home during the pandemic. Their findings showed that students faced many obstacles in a home learning environment, such as lack of mastery of technology, high Internet cost, and limited interaction/socialization between and among students. In a related study, Kapasia et al. ( 2020 ) investigated how lockdown impacts students’ learning performance. Their findings revealed that the lockdown made significant disruptions in students’ learning experience. The students also reported some challenges that they faced during their online classes. These include anxiety, depression, poor Internet service, and unfavorable home learning environment, which were aggravated when students are marginalized and from remote areas. Contrary to Kapasia et al.’s ( 2020 ) findings, Gonzales et al. ( 2020 ) found that confinement of students during the pandemic had significant positive effects on their performance. They attributed these results to students’ continuous use of learning strategies which, in turn, improved their learning efficiency.

Finally, there are those that focused on students’ overall online learning experience during the COVID-19 pandemic. One such study was that of Singh et al. ( 2020 ), who examined students’ experience during the COVID-19 pandemic using a quantitative descriptive approach. Their findings indicated that students appreciated the use of online learning during the pandemic. However, half of them believed that the traditional classroom setting was more effective than the online learning platform. Methodologically, the researchers acknowledge that the quantitative nature of their study restricts a deeper interpretation of the findings. Unlike the above study, Khalil et al. ( 2020 ) qualitatively explored the efficacy of synchronized online learning in a medical school in Saudi Arabia. The results indicated that students generally perceive synchronous online learning positively, particularly in terms of time management and efficacy. However, they also reported technical (internet connectivity and poor utility of tools), methodological (content delivery), and behavioral (individual personality) challenges. Their findings also highlighted the failure of the online learning environment to address the needs of courses that require hands-on practice despite efforts to adopt virtual laboratories. In a parallel study, Adarkwah ( 2021 ) examined students’ online learning experience during the pandemic using a narrative inquiry approach. The findings indicated that Ghanaian students considered online learning as ineffective due to several challenges that they encountered. Among these were lack of social interaction among students, poor communication, lack of ICT resources, and poor learning outcomes. More recently, Day et al. ( 2021 ) examined the immediate impact of COVID-19 on students’ learning experience. Evidence from six institutions across three countries revealed some positive experiences and pre-existing inequities. Among the reported challenges are lack of appropriate devices, poor learning space at home, stress among students, and lack of fieldwork and access to laboratories.

Although there are few studies that report the online learning challenges that higher education students experience during the pandemic, limited information is available regarding the specific strategies that they use to overcome them. It is in this context that the current study was undertaken. This mixed-methods study investigates students’ online learning experience in higher education. Specifically, the following research questions are addressed: (1) What is the extent of challenges that students experience in an online learning environment? (2) How did the COVID-19 pandemic impact the online learning challenges that students experience? (3) What strategies did students use to overcome the challenges?

2.3 Conceptual framework

The typology of challenges examined in this study is largely based on Rasheed et al.’s ( 2020 ) review of students’ experience in an online learning environment. These challenges are grouped into five general clusters, namely self-regulation (SRC), technological literacy and competency (TLCC), student isolation (SIC), technological sufficiency (TSC), and technological complexity (TCC) challenges (Rasheed et al., 2020 , p. 5). SRC refers to a set of behavior by which students exercise control over their emotions, actions, and thoughts to achieve learning objectives. TLCC relates to a set of challenges about students’ ability to effectively use technology for learning purposes. SIC relates to the emotional discomfort that students experience as a result of being lonely and secluded from their peers. TSC refers to a set of challenges that students experience when accessing available online technologies for learning. Finally, there is TCC which involves challenges that students experience when exposed to complex and over-sufficient technologies for online learning.

To extend Rasheed et al. ( 2020 ) categories and to cover other potential challenges during online classes, two more clusters were added, namely learning resource challenges (LRC) and learning environment challenges (LEC) (Buehler, 2004 ; Recker et al., 2004 ; Seplaki et al., 2014 ; Xue et al., 2020 ). LRC refers to a set of challenges that students face relating to their use of library resources and instructional materials, whereas LEC is a set of challenges that students experience related to the condition of their learning space that shapes their learning experiences, beliefs, and attitudes. Since learning environment at home and learning resources available to students has been reported to significantly impact the quality of learning and their achievement of learning outcomes (Drane et al., 2020 ; Suryaman et al., 2020 ), the inclusion of LRC and LEC would allow us to capture other important challenges that students experience during the pandemic, particularly those from developing regions. This comprehensive list would provide us a clearer and detailed picture of students’ experiences when engaged in online learning in an emergency. Given the restrictions in mobility at macro and micro levels during the pandemic, it is also expected that such conditions would aggravate these challenges. Therefore, this paper intends to understand these challenges from students’ perspectives since they are the ones that are ultimately impacted when the issue is about the learning experience. We also seek to explore areas that provide inconclusive findings, thereby setting the path for future research.

3 Material and methods

The present study adopted a descriptive, mixed-methods approach to address the research questions. This approach allowed the researchers to collect complex data about students’ experience in an online learning environment and to clearly understand the phenomena from their perspective.

3.1 Participants

This study involved 200 (66 male and 134 female) students from a private higher education institution in the Philippines. These participants were Psychology, Physical Education, and Sports Management majors whose ages ranged from 17 to 25 ( x̅  = 19.81; SD  = 1.80). The students have been engaged in online learning for at least two terms in both synchronous and asynchronous modes. The students belonged to low- and middle-income groups but were equipped with the basic online learning equipment (e.g., computer, headset, speakers) and computer skills necessary for their participation in online classes. Table 1 shows the primary and secondary platforms that students used during their online classes. The primary platforms are those that are formally adopted by teachers and students in a structured academic context, whereas the secondary platforms are those that are informally and spontaneously used by students and teachers for informal learning and to supplement instructional delivery. Note that almost all students identified MS Teams as their primary platform because it is the official learning management system of the university.

Informed consent was sought from the participants prior to their involvement. Before students signed the informed consent form, they were oriented about the objectives of the study and the extent of their involvement. They were also briefed about the confidentiality of information, their anonymity, and their right to refuse to participate in the investigation. Finally, the participants were informed that they would incur no additional cost from their participation.

3.2 Instrument and data collection

The data were collected using a retrospective self-report questionnaire and a focused group discussion (FGD). A self-report questionnaire was considered appropriate because the indicators relate to affective responses and attitude (Araujo et al., 2017 ; Barrot, 2016 ; Spector, 1994 ). Although the participants may tell more than what they know or do in a self-report survey (Matsumoto, 1994 ), this challenge was addressed by explaining to them in detail each of the indicators and using methodological triangulation through FGD. The questionnaire was divided into four sections: (1) participant’s personal information section, (2) the background information on the online learning environment, (3) the rating scale section for the online learning challenges, (4) the open-ended section. The personal information section asked about the students’ personal information (name, school, course, age, and sex), while the background information section explored the online learning mode and platforms (primary and secondary) used in class, and students’ length of engagement in online classes. The rating scale section contained 37 items that relate to SRC (6 items), TLCC (10 items), SIC (4 items), TSC (6 items), TCC (3 items), LRC (4 items), and LEC (4 items). The Likert scale uses six scores (i.e., 5– to a very great extent , 4– to a great extent , 3– to a moderate extent , 2– to some extent , 1– to a small extent , and 0 –not at all/negligible ) assigned to each of the 37 items. Finally, the open-ended questions asked about other challenges that students experienced, the impact of the pandemic on the intensity or extent of the challenges they experienced, and the strategies that the participants employed to overcome the eight different types of challenges during online learning. Two experienced educators and researchers reviewed the questionnaire for clarity, accuracy, and content and face validity. The piloting of the instrument revealed that the tool had good internal consistency (Cronbach’s α = 0.96).

The FGD protocol contains two major sections: the participants’ background information and the main questions. The background information section asked about the students’ names, age, courses being taken, online learning mode used in class. The items in the main questions section covered questions relating to the students’ overall attitude toward online learning during the pandemic, the reasons for the scores they assigned to each of the challenges they experienced, the impact of the pandemic on students’ challenges, and the strategies they employed to address the challenges. The same experts identified above validated the FGD protocol.

Both the questionnaire and the FGD were conducted online via Google survey and MS Teams, respectively. It took approximately 20 min to complete the questionnaire, while the FGD lasted for about 90 min. Students were allowed to ask for clarification and additional explanations relating to the questionnaire content, FGD, and procedure. Online surveys and interview were used because of the ongoing lockdown in the city. For the purpose of triangulation, 20 (10 from Psychology and 10 from Physical Education and Sports Management) randomly selected students were invited to participate in the FGD. Two separate FGDs were scheduled for each group and were facilitated by researcher 2 and researcher 3, respectively. The interviewers ensured that the participants were comfortable and open to talk freely during the FGD to avoid social desirability biases (Bergen & Labonté, 2020 ). These were done by informing the participants that there are no wrong responses and that their identity and responses would be handled with the utmost confidentiality. With the permission of the participants, the FGD was recorded to ensure that all relevant information was accurately captured for transcription and analysis.

3.3 Data analysis

To address the research questions, we used both quantitative and qualitative analyses. For the quantitative analysis, we entered all the data into an excel spreadsheet. Then, we computed the mean scores ( M ) and standard deviations ( SD ) to determine the level of challenges experienced by students during online learning. The mean score for each descriptor was interpreted using the following scheme: 4.18 to 5.00 ( to a very great extent ), 3.34 to 4.17 ( to a great extent ), 2.51 to 3.33 ( to a moderate extent ), 1.68 to 2.50 ( to some extent ), 0.84 to 1.67 ( to a small extent ), and 0 to 0.83 ( not at all/negligible ). The equal interval was adopted because it produces more reliable and valid information than other types of scales (Cicchetti et al., 2006 ).

For the qualitative data, we analyzed the students’ responses in the open-ended questions and the transcribed FGD using the predetermined categories in the conceptual framework. Specifically, we used multilevel coding in classifying the codes from the transcripts (Birks & Mills, 2011 ). To do this, we identified the relevant codes from the responses of the participants and categorized these codes based on the similarities or relatedness of their properties and dimensions. Then, we performed a constant comparative and progressive analysis of cases to allow the initially identified subcategories to emerge and take shape. To ensure the reliability of the analysis, two coders independently analyzed the qualitative data. Both coders familiarize themselves with the purpose, research questions, research method, and codes and coding scheme of the study. They also had a calibration session and discussed ways on how they could consistently analyze the qualitative data. Percent of agreement between the two coders was 86 percent. Any disagreements in the analysis were discussed by the coders until an agreement was achieved.

This study investigated students’ online learning experience in higher education within the context of the pandemic. Specifically, we identified the extent of challenges that students experienced, how the COVID-19 pandemic impacted their online learning experience, and the strategies that they used to confront these challenges.

4.1 The extent of students’ online learning challenges

Table 2 presents the mean scores and SD for the extent of challenges that students’ experienced during online learning. Overall, the students experienced the identified challenges to a moderate extent ( x̅  = 2.62, SD  = 1.03) with scores ranging from x̅  = 1.72 ( to some extent ) to x̅  = 3.58 ( to a great extent ). More specifically, the greatest challenge that students experienced was related to the learning environment ( x̅  = 3.49, SD  = 1.27), particularly on distractions at home, limitations in completing the requirements for certain subjects, and difficulties in selecting the learning areas and study schedule. It is, however, found that the least challenge was on technological literacy and competency ( x̅  = 2.10, SD  = 1.13), particularly on knowledge and training in the use of technology, technological intimidation, and resistance to learning technologies. Other areas that students experienced the least challenge are Internet access under TSC and procrastination under SRC. Nonetheless, nearly half of the students’ responses per indicator rated the challenges they experienced as moderate (14 of the 37 indicators), particularly in TCC ( x̅  = 2.51, SD  = 1.31), SIC ( x̅  = 2.77, SD  = 1.34), and LRC ( x̅  = 2.93, SD  = 1.31).

Out of 200 students, 181 responded to the question about other challenges that they experienced. Most of their responses were already covered by the seven predetermined categories, except for 18 responses related to physical discomfort ( N  = 5) and financial challenges ( N  = 13). For instance, S108 commented that “when it comes to eyes and head, my eyes and head get ache if the session of class was 3 h straight in front of my gadget.” In the same vein, S194 reported that “the long exposure to gadgets especially laptop, resulting in body pain & headaches.” With reference to physical financial challenges, S66 noted that “not all the time I have money to load”, while S121 claimed that “I don't know until when are we going to afford budgeting our money instead of buying essentials.”

4.2 Impact of the pandemic on students’ online learning challenges

Another objective of this study was to identify how COVID-19 influenced the online learning challenges that students experienced. As shown in Table 3 , most of the students’ responses were related to teaching and learning quality ( N  = 86) and anxiety and other mental health issues ( N  = 52). Regarding the adverse impact on teaching and learning quality, most of the comments relate to the lack of preparation for the transition to online platforms (e.g., S23, S64), limited infrastructure (e.g., S13, S65, S99, S117), and poor Internet service (e.g., S3, S9, S17, S41, S65, S99). For the anxiety and mental health issues, most students reported that the anxiety, boredom, sadness, and isolation they experienced had adversely impacted the way they learn (e.g., S11, S130), completing their tasks/activities (e.g., S56, S156), and their motivation to continue studying (e.g., S122, S192). The data also reveal that COVID-19 aggravated the financial difficulties experienced by some students ( N  = 16), consequently affecting their online learning experience. This financial impact mainly revolved around the lack of funding for their online classes as a result of their parents’ unemployment and the high cost of Internet data (e.g., S18, S113, S167). Meanwhile, few concerns were raised in relation to COVID-19’s impact on mobility ( N  = 7) and face-to-face interactions ( N  = 7). For instance, some commented that the lack of face-to-face interaction with her classmates had a detrimental effect on her learning (S46) and socialization skills (S36), while others reported that restrictions in mobility limited their learning experience (S78, S110). Very few comments were related to no effect ( N  = 4) and positive effect ( N  = 2). The above findings suggest the pandemic had additive adverse effects on students’ online learning experience.

4.3 Students’ strategies to overcome challenges in an online learning environment

The third objective of this study is to identify the strategies that students employed to overcome the different online learning challenges they experienced. Table 4 presents that the most commonly used strategies used by students were resource management and utilization ( N  = 181), help-seeking ( N  = 155), technical aptitude enhancement ( N  = 122), time management ( N  = 98), and learning environment control ( N  = 73). Not surprisingly, the top two strategies were also the most consistently used across different challenges. However, looking closely at each of the seven challenges, the frequency of using a particular strategy varies. For TSC and LRC, the most frequently used strategy was resource management and utilization ( N  = 52, N  = 89, respectively), whereas technical aptitude enhancement was the students’ most preferred strategy to address TLCC ( N  = 77) and TCC ( N  = 38). In the case of SRC, SIC, and LEC, the most frequently employed strategies were time management ( N  = 71), psychological support ( N  = 53), and learning environment control ( N  = 60). In terms of consistency, help-seeking appears to be the most consistent across the different challenges in an online learning environment. Table 4 further reveals that strategies used by students within a specific type of challenge vary.

5 Discussion and conclusions

The current study explores the challenges that students experienced in an online learning environment and how the pandemic impacted their online learning experience. The findings revealed that the online learning challenges of students varied in terms of type and extent. Their greatest challenge was linked to their learning environment at home, while their least challenge was technological literacy and competency. Based on the students’ responses, their challenges were also found to be aggravated by the pandemic, especially in terms of quality of learning experience, mental health, finances, interaction, and mobility. With reference to previous studies (i.e., Adarkwah, 2021 ; Copeland et al., 2021 ; Day et al., 2021 ; Fawaz et al., 2021 ; Kapasia et al., 2020 ; Khalil et al., 2020 ; Singh et al., 2020 ), the current study has complemented their findings on the pedagogical, logistical, socioeconomic, technological, and psychosocial online learning challenges that students experience within the context of the COVID-19 pandemic. Further, this study extended previous studies and our understanding of students’ online learning experience by identifying both the presence and extent of online learning challenges and by shedding light on the specific strategies they employed to overcome them.

Overall findings indicate that the extent of challenges and strategies varied from one student to another. Hence, they should be viewed as a consequence of interaction several many factors. Students’ responses suggest that their online learning challenges and strategies were mediated by the resources available to them, their interaction with their teachers and peers, and the school’s existing policies and guidelines for online learning. In the context of the pandemic, the imposed lockdowns and students’ socioeconomic condition aggravated the challenges that students experience.

While most studies revealed that technology use and competency were the most common challenges that students face during the online classes (see Rasheed et al., 2020 ), the case is a bit different in developing countries in times of pandemic. As the findings have shown, the learning environment is the greatest challenge that students needed to hurdle, particularly distractions at home (e.g., noise) and limitations in learning space and facilities. This data suggests that online learning challenges during the pandemic somehow vary from the typical challenges that students experience in a pre-pandemic online learning environment. One possible explanation for this result is that restriction in mobility may have aggravated this challenge since they could not go to the school or other learning spaces beyond the vicinity of their respective houses. As shown in the data, the imposition of lockdown restricted students’ learning experience (e.g., internship and laboratory experiments), limited their interaction with peers and teachers, caused depression, stress, and anxiety among students, and depleted the financial resources of those who belong to lower-income group. All of these adversely impacted students’ learning experience. This finding complemented earlier reports on the adverse impact of lockdown on students’ learning experience and the challenges posed by the home learning environment (e.g., Day et al., 2021 ; Kapasia et al., 2020 ). Nonetheless, further studies are required to validate the impact of restrictions on mobility on students’ online learning experience. The second reason that may explain the findings relates to students’ socioeconomic profile. Consistent with the findings of Adarkwah ( 2021 ) and Day et al. ( 2021 ), the current study reveals that the pandemic somehow exposed the many inequities in the educational systems within and across countries. In the case of a developing country, families from lower socioeconomic strata (as in the case of the students in this study) have limited learning space at home, access to quality Internet service, and online learning resources. This is the reason the learning environment and learning resources recorded the highest level of challenges. The socioeconomic profile of the students (i.e., low and middle-income group) is the same reason financial problems frequently surfaced from their responses. These students frequently linked the lack of financial resources to their access to the Internet, educational materials, and equipment necessary for online learning. Therefore, caution should be made when interpreting and extending the findings of this study to other contexts, particularly those from higher socioeconomic strata.

Among all the different online learning challenges, the students experienced the least challenge on technological literacy and competency. This is not surprising considering a plethora of research confirming Gen Z students’ (born since 1996) high technological and digital literacy (Barrot, 2018 ; Ng, 2012 ; Roblek et al., 2019 ). Regarding the impact of COVID-19 on students’ online learning experience, the findings reveal that teaching and learning quality and students’ mental health were the most affected. The anxiety that students experienced does not only come from the threats of COVID-19 itself but also from social and physical restrictions, unfamiliarity with new learning platforms, technical issues, and concerns about financial resources. These findings are consistent with that of Copeland et al. ( 2021 ) and Fawaz et al. ( 2021 ), who reported the adverse effects of the pandemic on students’ mental and emotional well-being. This data highlights the need to provide serious attention to the mediating effects of mental health, restrictions in mobility, and preparedness in delivering online learning.

Nonetheless, students employed a variety of strategies to overcome the challenges they faced during online learning. For instance, to address the home learning environment problems, students talked to their family (e.g., S12, S24), transferred to a quieter place (e.g., S7, S 26), studied at late night where all family members are sleeping already (e.g., S51), and consulted with their classmates and teachers (e.g., S3, S9, S156, S193). To overcome the challenges in learning resources, students used the Internet (e.g., S20, S27, S54, S91), joined Facebook groups that share free resources (e.g., S5), asked help from family members (e.g., S16), used resources available at home (e.g., S32), and consulted with the teachers (e.g., S124). The varying strategies of students confirmed earlier reports on the active orientation that students take when faced with academic- and non-academic-related issues in an online learning space (see Fawaz et al., 2021 ). The specific strategies that each student adopted may have been shaped by different factors surrounding him/her, such as available resources, student personality, family structure, relationship with peers and teacher, and aptitude. To expand this study, researchers may further investigate this area and explore how and why different factors shape their use of certain strategies.

Several implications can be drawn from the findings of this study. First, this study highlighted the importance of emergency response capability and readiness of higher education institutions in case another crisis strikes again. Critical areas that need utmost attention include (but not limited to) national and institutional policies, protocol and guidelines, technological infrastructure and resources, instructional delivery, staff development, potential inequalities, and collaboration among key stakeholders (i.e., parents, students, teachers, school leaders, industry, government education agencies, and community). Second, the findings have expanded our understanding of the different challenges that students might confront when we abruptly shift to full online learning, particularly those from countries with limited resources, poor Internet infrastructure, and poor home learning environment. Schools with a similar learning context could use the findings of this study in developing and enhancing their respective learning continuity plans to mitigate the adverse impact of the pandemic. This study would also provide students relevant information needed to reflect on the possible strategies that they may employ to overcome the challenges. These are critical information necessary for effective policymaking, decision-making, and future implementation of online learning. Third, teachers may find the results useful in providing proper interventions to address the reported challenges, particularly in the most critical areas. Finally, the findings provided us a nuanced understanding of the interdependence of learning tools, learners, and learning outcomes within an online learning environment; thus, giving us a multiperspective of hows and whys of a successful migration to full online learning.

Some limitations in this study need to be acknowledged and addressed in future studies. One limitation of this study is that it exclusively focused on students’ perspectives. Future studies may widen the sample by including all other actors taking part in the teaching–learning process. Researchers may go deeper by investigating teachers’ views and experience to have a complete view of the situation and how different elements interact between them or affect the others. Future studies may also identify some teacher-related factors that could influence students’ online learning experience. In the case of students, their age, sex, and degree programs may be examined in relation to the specific challenges and strategies they experience. Although the study involved a relatively large sample size, the participants were limited to college students from a Philippine university. To increase the robustness of the findings, future studies may expand the learning context to K-12 and several higher education institutions from different geographical regions. As a final note, this pandemic has undoubtedly reshaped and pushed the education system to its limits. However, this unprecedented event is the same thing that will make the education system stronger and survive future threats.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

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Barrot, J.S., Llenares, I.I. & del Rosario, L.S. Students’ online learning challenges during the pandemic and how they cope with them: The case of the Philippines. Educ Inf Technol 26 , 7321–7338 (2021). https://doi.org/10.1007/s10639-021-10589-x

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In early 2020, as the coronavirus spread, schools around the world abruptly halted in-person education. To many governments and parents, moving classes online seemed the obvious stopgap solution. In the United States, school districts scrambled to secure digital devices for students. Almost overnight, videoconferencing software like Zoom became the main platform teachers used to deliver real-time instruction to students at home. Now a report from UNESCO , the United Nations’ educational and cultural organization, says that overreliance on remote learning technology during the pandemic led to “staggering” education inequality around the world. It was, according to a 655-page report that UNESCO released on Wednesday, a worldwide “ed-tech tragedy.” The report, from UNESCO’s Future of Education division, is likely to add fuel to the debate over how governments and local school districts handled pandemic restrictions, and whether it would have been better for some countries to reopen schools for in-person instruction sooner. The UNESCO researchers argued in the report that “unprecedented” dependence on technology — intended to ensure that children could continue their schooling — worsened disparities and learning loss for hundreds of millions of students around the world, including in Kenya, Brazil, Britain and the United States. The promotion of remote online learning as the primary solution for pandemic schooling also hindered public discussion of more equitable, lower-tech alternatives, such as regularly providing schoolwork packets for every student, delivering school lessons by radio or television — and reopening schools sooner for in-person classes, the researchers said. “Available evidence strongly indicates that the bright spots of the ed-tech experiences during the pandemic, while important and deserving of attention, were vastly eclipsed by failure,” the UNESCO report said. The UNESCO researchers recommended that education officials prioritize in-person instruction with teachers, not online platforms, as the primary driver of student learning. And they encouraged schools to ensure that emerging technologies like A.I. chatbots concretely benefited students before introducing them for educational use. Education and industry experts welcomed the report, saying more research on the effects of pandemic learning was needed. “The report’s conclusion — that societies must be vigilant about the ways digital tools are reshaping education — is incredibly important,” said Paul Lekas, the head of global public policy for the Software & Information Industry Association, a group whose members include Amazon, Apple and Google. “There are lots of lessons that can be learned from how digital education occurred during the pandemic and ways in which to lessen the digital divide. ” Jean-Claude Brizard, the chief executive of Digital Promise, a nonprofit education group that has received funding from Google, HP and Verizon, acknowledged that “technology is not a cure-all.” But he also said that while school systems were largely unprepared for the pandemic, online education tools helped foster “more individualized, enhanced learning experiences as schools shifted to virtual classrooms.” ​Education International, an umbrella organization for about 380 teachers’ unions and 32 million teachers worldwide, said the UNESCO report underlined the importance of in-person, face-to-face teaching. “The report tells us definitively what we already know to be true, a place called school matters,” said Haldis Holst, the group’s deputy general secretary. “Education is not transactional nor is it simply content delivery. It is relational. It is social. It is human at its core.”

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Original research article, online learning after the covid-19 pandemic: learners’ motivations.

• Endicott College, Woosong University, Daejeon, South Korea

The COVID-19 pandemic has become a focus on reforming teaching, learning models and strategies, particularly in online teaching and learning tools. Based on the social cognitive career theory and the constructivist learning theory, the purpose of this study was to understand and explore the learning preference and experience of students’ online courses during the COVID-19 pandemic and the management after the COVID-19 pandemic from the students’ perspective. The study was guided by the following two research questions: (1) After the COVID-19 pandemic, why do the students want to continue their foreign language courses via an online platform and model? What are the motivations and reasons? (2) How would the students describe their experience of a foreign language course via an online platform and model? With the general inductive approach and sharing from 80 participants, the participants indicated that flexibilities and convenience, same outcomes and learning rigorousness, and interactive experiences with classmates from different parts of the world were the three main key points. The results of this study may provide recommendations to university leaders, department heads, and teachers to reform and upgrade their online teaching curriculum and course delivery options after the COVID-19 pandemic.

Introduction

Due to the development of technologically assisted teaching and learning tools, flexible enrolment management, and delivery options, many traditional-age students and non-traditional students may enjoy university education. A recent report by the State of Oregon Employment Department ( Wallis, 2020 ) predicted that from 2015 to 2026, enrolment of non-traditional students (25 years and older) could increase by 8.2% or 664,000, while the youth population (from 14 to 25 years old) could increase by 16.8% or 1,991,000. By 2026, the non-traditional student population could comprise nearly 40% of the university student population, while just over 60% will be youths.

Distance learning is one of the current international education trends in university environments, in both credit and non-credit courses. Many universities have established a proportion of courses and academic programs for students who cannot attend the traditional face-to-face courses that have been the norm over the past decades. Recent statistics from the National Centre for Education Statistics ( National Center for Education Statistics, 2020 ) indicate that 19,637,499 students enrolled in any undergraduate and postgraduate educational institutions in 2019. In total, 12,323,876 (about 62.8%) students studied as on-campus students without any distance learning options. Also, 7,313,623 (about 37.2%) students enrolled in any online courses at degree-granted postsecondary institutions in the United States. Of these students (37.2%), 3,863,498 students took at least one, but not all, of students; courses are distance education courses, 3,450,125 students took distance learning courses exclusively. These education trends may continue due to the flexibility and convenience of online courses, particularly following the COVID-19 pandemic.

Purpose of the study

First, the COVID-19 pandemic has become a focus on reforming teaching as well as learning models and strategies, particularly in online teaching and learning tools. Recent statistics ( Wallis, 2020 ) indicate that many university students have experienced at least one online course due to the COVID-19 pandemic and government social distancing recommendations. Although many courses will eventually return to traditional face-to-face teaching models and strategies to increase learning and on-campus experience, online teaching and learning have become options for students to complete their courses online, particularly in foreign language courses.

Second, many foreign language courses and instructions tend to focus on face-to-face and physical interactions with students, teachers, and peers in the classroom environment. Although a few literature courses may be delivered online, many language-based courses are physically delivered. Therefore, it is important to understand the voices and comments of foreign language students to upgrade and polish the online-based foreign language courses during and after the COVID-19 pandemic.

The result of this study will provide recommendations to school leaders, department heads, curriculum designers, and policymakers about the developments of online teaching and learning courses, particularly for foreign language learners at the college and university level.

Based on the social cognitive career theory and the constructivist learning theory, this study aimed to understand and explore the learning preference and experience of students’ online courses during the COVID-19 pandemic and the management after the COVID-19 pandemic from the students’ perspective. The study was guided by the following two research questions:

(1) After the COVID-19 pandemic, why do the students want to continue their foreign language courses via an online platform and model? What are the motivations and reasons?

(2) How would the students describe their experience of a foreign language course via an online platform and model?

Theoretical frameworks and literature review

The researcher employed two theoretical frameworks – the social cognitive career theory ( Lent et al., 1994 ; Lent and Brown, 1996 ) and the constructivist learning theory ( Bruner, 1973 , 1996 ) to examine online teaching and learning issues during and after the COVID-19 pandemic. The social cognitive career theory indicates that individuals’ behaviors and motivations can be impacted by both internal and external factors, which can direct the goals and achievements of individuals and groups. For details, please refer to the following section. Therefore, based on the application of the social cognitive career theory, the employment of the theory is useful because the theory may seek the motivation and decision-making processes of the individuals and groups.

Second, the constructivist learning theory ( Bruner, 1973 , 1996 ) is useful for investigating this study. In fact, previous experience, learning style, and understanding could significantly impact individuals’ and groups’ understanding, learning styles, language learning acquisition, and expectations from the classes. In this case, the researcher wanted to understand how the online learning platform and learning style could impact the experiences and expectations of the participants. Therefore, the employment of the constructivist learning theory would be appropriate.

Social cognitive career theory

The social cognitive career theory ( Lent et al., 1994 ; Lent and Brown, 1996 ) advocates that individuals’ self-efficacy beliefs, outcome expectations, and goals build decision-making and sense-making processes. Self-efficacy is an individual’s personal understanding and belief of their capacity and ability to exercise targeted behavior and a series of actions. Outcome expectation refers to the targeted and potential consequences of their decisions. Personal goals refer to intentions during the procedure and the potential aftermath of decisions. Single or multiple factors based on the social cognitive career theory may influence an individual’s decision-making and sense-making process.

Motivation and reason of online learning

COVID-19 pandemic offers the opportunities for students to take courses and complete their programs via the online platform without any physical attendance. A recent study ( Dos Santos, 2021a ) indicated that online student enrolment has increased from 30 to 70% during the COVID-19 pandemic. One hundred international students joined the study and shared positive feedback of online learning based on the social cognitive career theory. Another recent study ( Dos Santos, 2021d ) also indicated that domestic and international students enjoyed the online learning environment as many could continue their education, particularly during the lockdown and COVID-19 pandemic. The participants indicated that the online learning options should be continued to meet the needs of students from different background ( Atmojo and Nugroho, 2020 ; AbuSa’aleek and Alotaibi, 2022 ; Chen and Du, 2022 ).

Online courses and lack of on-campus services and experiences

A recent report ( Wallis, 2020 ) indicates that 78% of online students consider the online classroom environment to be as good as or better than traditional face-to-face methods, while nearly 80% of these students agreed or strongly agreed that online courses and degrees were worth the tuition fees. Student satisfaction and learning outcomes have become significant considerations for teachers, school leaders, and students. Another recent report ( Hess, 2021 ) indicated some students might argue the online courses may not completely satisfy their needs, particularly the facilities and on-campus services that they cannot use as online students. The study further indicated that over 90% of American students wanted the university to reduce a part of the tuition fee as the students could not enjoy the on-campus facilities. Based on the statistics, although many students agreed that the online courses might have similar outcomes and achievements, they would like to pay fewer tuition fees due to the on-campus services (i.e., cannot enjoy the services) ( Zvalo-Martyn, 2020 ).

Constructivist learning theory

In terms of the constructivist learning theory, Bruner (1973 , 1996) argued that learning, particularly language learning, is a model in which learners build new knowledge and language acquisition based on their previous experiences. The cognitive structure is the mental and psychological actions and behavior that provide the performance, understanding, and background from which learners organize the experience, learning expectation, and sense-making process of their new knowledge. As learning is not a standalone process but a procedure combining previous experience and current situations, learners compare the current situation with their previous experience to build up new and appropriate experiences. Bruner (1973 , 1996) identified four important factors of the constructivist learning theory: (1) teaching and learning models and strategies should focus on the connections and sense-making process between previous experience and the current situation; (2) teaching and learning models and strategies should motivate and activate learning interests and new areas of knowledge; (3) learners should be able to handle complex knowledge with no difficulties; (4) teaching and learning models, strategies, and goals should go beyond previous experience in building a new ground.

In short, the social cognitive career theory explored the motivations and reasons why individuals decide to do, continue, conduct, or discontinue a set of behavior before, during, and after some events and issues. And then, the employment of the constructivist learning theory explored the relationships and connections between the previous and current experiences and how these experiences make sense and build up the understanding and knowledge of the individuals and groups. Based on the directions of these two theoretical frameworks, the researcher advocated that the employments were useful to explore the two research questions of this study. As for the research questions, please refer to the following sub-section.

Appropriate online curriculum and activities with positive experiences

As for the feedback and opinions about the teaching and learning experiences and environments, some scholars ( Tratnik et al., 2019 ) argue that students have benefited from foreign language courses in face-to-face environments due to peer interactions and exchanges. However, other scholars ( Wei and Chou, 2020 ) have indicated that students learn actively and are satisfied with the online learning environment. Another recent report ( Zvalo-Martyn, 2020 ) by the Association of American Colleges and Universities further indicated that the sample group (i.e., 24 university students) expressed positive learning experiences from their online university courses as many could use the digital education platform as the learning tools, particularly the online learning can establish the connections between the faculty and peers without borders. Two other studies ( Brown et al., 2013 ; Kwee and Dos Santos, 2021 ) also indicated that vocational and hands-on experience courses might be delivered online as long as the university arrangements, curriculum designs, and student-centered activities may meet the needs and expectations for the achievements; students tended to express positive comments for their final evaluation.

Interactive experiences for online courses: Foreign language learning

Online teaching and learning are not new topics in university education. In 2006, scholars ( Levy and Stockwell, 2006 ) showed that due to the rapid development of technology and upgrading of the classroom environment, many schools and universities had developed computer labs and rooms as essential facilities for many subjects, such as science, technology, and foreign languages. The relationship between online classroom interaction and outcome has received special attention over the decades due to the rapid development of distance learning education ( Gok et al., 2021 ). An earlier study ( Lantolf and Thorne, 2007 ) argued that sociocultural background is key in foreign language learning as students need to absorb knowledge from social and cultural backgrounds. Another newer study ( Lin et al., 2017 ) indicated that provided the teaching and learning strategy and model were effective, the motivation of learners and the outcomes of foreign language courses remained the same. For example, a previous study ( Kurucay and Inan, 2017 ) indicated that online-based groups worked well as many students were used to the online environment and technologically assisted teaching and learning from their previous experiences. In the online classroom environment of foreign language courses, some students expressed anxiety about not receiving immediate feedback from teachers and classmates. However, the participants indicated that effective corrective feedback could meet their learning outcome expectations ( Martin and Alvarez Valdivia, 2017 ).

Concerns for the online foreign language courses

In foreign language and cultural learning, some scholars ( O’Dowd, 2011 ) argue that the sense of internationalism and sociocultural understanding are some important factors. Although textbooks and printed materials provide excellent teaching and learning models, individuals cannot gain knowledge and language acquisition beyond the classroom environment. A study ( Ozudogru and Hismanoglu, 2016 ) surveyed the understanding and beliefs of 478 university freshmen students about their online foreign language learning experience. Although some students shared negative experiences, this study outlined improvements in online foreign language courses. Another study ( VanPatten et al., 2015 ) indicated no preference among 244 university students for either online or on-campus learning in their foreign language courses as both techniques delivered their expectations and goals. Although online foreign language courses may offer the flexibilities, some scholars believed that the interactions, activities, internationalism, and sociocultural experiences may not be gained via the online learning classroom environment. Currently, only a few studies focused on the cases in the United States. It is important to investigate the problems in the United States and the American foreign language classroom environments.

The COVID-19 pandemic has been the turning point for online teaching for almost all universities internationally, particularly in foreign language learning ( Maican and Cocoradã, 2021 ). Although there are no contemporary statistics concerning the numbers of students affected by the global health crisis, almost all college and university students have had to attend online or blended courses due to government lockdown policies, particularly in the United States ( Atmojo and Nugroho, 2020 ; Dhawan, 2020 ; Alqarni, 2021 ; Lau et al., 2021 ). As foreign language courses do not require lab or internship experience, most tuition has been delivered online ( Maican and Cocoradã, 2021 ). A further study ( Atmojo and Nugroho, 2020 ) indicated that due to the COVID-19 pandemic, English language courses should be conducted online to control the risk of infection. Although teachers and students could not attend foreign language courses in person, the virtual experiences did not necessarily limit the learning experiences and outcomes.

Materials and methods

Research design.

The current study employed the general inductive approach ( Thomas, 2006 ; Dos Santos, 2020b , 2021c ) with the interpretivism social paradigm ( Burrell and Morgan, 1979 ). The general inductive approach is useful in this study because the general inductive approach allows the researcher to categorize the massive data into meaningful themes and groups. Based on the themes and groups, the researcher can further categorized the themes as the results.

First, technologically assisted teaching and learning tools and approaches have become popular methods in foreign language teaching and learning. The direction does not limit to a single or small group of schools and universities. In other words, teaching with technologically assisted tools and approaches is widely employed in the current foreign language teaching and learning arena. Therefore, the employment of the general inductive approach covered the wider situation in the current society.

Second, the COVID-19 pandemic provides opportunities for technologically assisted teaching and learning turning point(s). The teaching trends with technology may become one of the main themes in the current education systems, including foreign language subjects. Therefore, the wider perspectives and data collection procedures may be useful in this case.

Recruitment and participants

The purposive and snowball sampling strategies were employed ( Merriam, 2009 ). First of all, based on a personal network, the researcher orally invited three participants to the study. Once three participants agreed with the study, the researcher formally sent the consent form, research protocol, interview questions, focus group activity questions, data collection procedure, risk statement, and related materials to the participants. In order to expand the population, the participants were told that after the first interview session, they should try their best to refer at least one participant for this study. After several rounds of discussions, 80 participants ( N = 80) agreed to join the study. As this study was a small-scale study that only focused on the west coast states in the United States, the researcher tended to establish some limitations to upgrade the focus and aim of this study. In this case, the participants should meet all of the following points:

(1) Currently enrolled at a postsecondary education institution in the United States;

(2) Completed at least one semester of foreign language course via online method;

(3) Currently located in one of the west coast states in the United States (e.g., Oregon, California, Washington, Alaska, and Hawaii).

(4) At least 18 years old.

Data collection

Three data collection tools were employed, including virtual-based, semi-structured and one-on-one interview session, focus group activity, and member checking interview session. First, the virtual-based, semi-structured, and one-on-one interview sessions were useful. Creswell (2012) indicated that interview session is one of the common qualitative data collection tools in social sciences. Merriam (2009) advocated that the individual-based interview allows the individual(s) to share their stories and ideas in a private setting. Some individuals tend not to share their personal backgrounds in front of a group of people. Therefore, the current arrangement for interview sessions might allow the individual(s) to share their understanding and experiences with the researcher. In this case, the interview sessions were appropriate to collect rich data from the participants about their understanding and perspective of online courses in foreign language learning. Based on the theoretical frameworks and some previous studies ( Bruner, 1973 , 1996 ; Lent and Brown, 1996 ; Dos Santos, 2020a , 2021b , 2021c ), the researcher developed the interview questions. The interview session mainly concerned the experiences, learning expectations, and intentions for future online courses after the COVID-19 pandemic. The interview sessions lasted from 90 to 112 min.

After completing all interview sessions, the researcher arranged the virtual-based focus group activities with the participants. The focus group activities mainly concerned the experiences, personal stories sharing, understanding of online courses, and their intention of online courses after the COVID-19 pandemic. Both Morgan (1998) and Merriam (2009) advocated that qualitative researchers may employ more than one data collection tool, such as interview and focus group activity, to increase the participants’ data. Focus group activity is useful because a group of individuals may share similar ideas within a similar background and situation. In this case, the motivation and experiences from the online learning platform and experience. As for the focus group activities, the researcher took the role of the listener as the researcher wanted to observe and collect the in-depth understanding and lived stories of the participants (who shared similar backgrounds and experiences during the COVID-19 pandemic). The researcher developed the focus group questions based on the theoretical frameworks and some previous studies ( Bruner, 1973 , 1996 ; Lent and Brown, 1996 ; Dos Santos, 2020a , 2021a , b ). Eight participants formed an individual focus group activity. Therefore, ten focus group activities were established. The focus group activities lasted from 113 to 132 min.

After the researcher collected and categorized the data based on each participant, the researcher returned the data to the participant via email for confirmation. A follow-up member-checking interview session was hosted for each participant via virtual-based interview. During the member-checking interview sessions, all participants agreed with their materials. Each member checking interview session lasted from 34 to 41 min. All the data collection procedures were digitally recorded. All participants agreed with this arrangement and accepted the sessions were recorded.

Data analysis

The researcher (i.e., worked as the sole researcher) transcribed all the voiced messages into written transcripts. The researcher read the data multiple times to categorize the connections and themes. Therefore, the researcher employed two data analysis procedures and tools in this study, including the general inductive approach ( Thomas, 2006 ) and the grounded theory approach ( Strauss and Corbin, 1990 ) for data analysis.

First, the researcher employed the open-coding technique ( Strauss and Corbin, 1990 ) to narrow down the massive data to themes and subthemes as the first-level themes. At this point, 20 themes (e.g., flexibility, online courses with schedule, family responsibilities, the same outcomes and learning achievements, domestic learning, international learning, etc.) and 18 subthemes (e.g., skill upgrading, the online platform options, students from different states and cities, peer-to-peer exchanging, etc.) were merged.

However, researchers ( Merriam, 2009 ) suggested that further data analysis procedures should be conducted. Therefore, the axial-coding technique ( Strauss and Corbin, 1990 ) was employed. As a result, three themes (i.e., flexibilities and convenience, same outcomes and learning rigorousness, and interactive experiences with classmates from different parts of the world) and three subthemes (i.e., can listen and watch the materials multiple times without limitations, unique learning experiences but additional skills expectations, and university degree without borders) were yielded as the second-level themes. Figure 1 outlines the data analysis procedure.

Figure 1. Data analysis procedure.

Human subject protection/ethical consideration

Privacy is the most important idea in this study. Therefore, the signed consent forms, personal information, contact information, school information, grades, locations, address, email address, voiced messages, written transcripts, computer, and related information were locked in a password-protected cabinet. Only the researcher could read the information. More importantly, the study was conducted in accordance with the Declaration of Helsinki, and the protocol was supported by the Woosong University Academic Research Funding. After the researcher completed the study, all the related materials were deleted and destroyed in order to protect the information of all parties. Please note no payments were given to any parties. The study was supported by the Woosong University Academic Research Funding 2021/2022 (2021-01-01-07).

Results and findings

Although many students take their courses in different global communities, many shared similar lived stories and experiences, particularly in their foreign language learning experiences during the COVID-19 pandemic in the United States. The researcher categorized three themes and subthemes based on the qualitative data. Table 1 outlines the themes and subthemes. Please note, to provide a comprehensive comparison, the researcher combined the results chapter and discussion chapter for immediate comparison.

Table 1. Themes and subthemes.

Flexibilities and convenience

…I can learn my Spanish courses in my free time…I am not a traditional student and have to work for my family…I can listen to and read my lessons and lecture notes during my break time at work…my way back home…before sleep…I can still learn the same knowledge and vocabulary without my physical attendance…I submit my assignments and projects on time as other students are…excellent learning option for us… (Participant #60, Focus Group)

All participants expressed flexibility and convenience as the strongest preferences in their online foreign language courses. A group of non-traditional, returning, adult, and evening class students indicated that the traditional face-to-face courses had always limited their selections and learning preferences as they had to work and take care of their families during the daytime ( Dos Santos, 2020a ). Although weekend and night courses are sometimes available, the options are limited. However, the COVID-19 pandemic and the online learning options offered them the same opportunities as traditional on-campus students. The researcher captured the following stories based on this preference:

…we cannot find any foreign language courses other than Spanish and French in the evening…I want to learn Chinese and Japanese…but they were only available during the morning and in the afternoon…but the online option, many evening students could take Chinese and Japanese…I hope the university can continue this online option for us… (Participant #34, Interview)

…I want to study Spanish popular literature and children’s literature as my elective courses…traditionally, based on the previous course catalog, only one professor teaches these courses…usually in the morning time…but because of the COVID…these two courses were offered online with recorded video sessions…I registered for these two courses immediately…it is a really good chance for us…to enjoy the courses as evening and part-time students… (Participant #10, Focus Group)

For example, some minority and less popular foreign language courses had only one session during each academic year. Students facing time conflicts with other courses would not be able to take either the foreign language course or their subject courses in the academic year. However, online courses provide greater flexibility. The researcher captured two stories:

…I am a double major student in Mathematics and Japanese…I have to take the Japanese literature course for my major…but only one session is there every year…if I miss it, I have to wait for another year…but at the same time, I have to take the math course for my math major…it was the advanced level course so only one course was available…this happened last year…but this year because we can take the online courses…the problem solved… (Participant #41, Interview)

The flexibility of online courses solved schedule conflicts between courses and university departments. Students who needed to take multiple foreign languages as their major requirement also expressed interest in online delivery, for example:

…in the translation studies department, we have to take at least two foreign languages beyond our native language…my native language is English…and I have to take Spanish and Italian as the second and third…but many of the translation, Spanish and Italian courses…were overlapped together before the pandemic…I am glad that the online courses…provide me with the chance…so I can finish my degree in 4 years… (Participant #3, Interview)

Can listen and watch the materials multiple times without limitations

In most online foreign language courses, instructors upload teaching and learning materials and exercises online before each lesson so that the students can read the materials before and after the lessons. All participants saw this as a positive experience because they could download and re-read the materials during their leisure time after the lesson. During driving time and breaks, they could play the audio and videos of language exercises. One said:

…in fact, commuting and travel jam waste my time…but if I could listen to the exercises in my car, I could save some time at home…and I do not have to sit in the classroom for the audio and to listen, I can sit in my car and practice the exercise…I learnt a lot because I can listen to the previous chapters and the new chapter…I connected all the vocab and sentences … (Participant #14, Interview)

For example, some participants mentioned that their instructors asked them to listen and watch earlier chapters to connect with their current grammatical structure. In this way, the learners could connect and refresh their previous work to their current materials:

…we were in chapter 34 last week, but our professor asked us to re-listen and re-watch the materials from chapter 22…we didn’t understand why. Still, when we read the old materials again, they learnt some new ideas…the grammatical structures or the slang from the videos…great practices to refresh our knowledge with some old stuff… (Participant #45, Focus Group)

Last but not least, almost all participants indicated that their instructors might release some self-made materials, speaking exercises, personal videos, and materials from the instructors’ personal library from the face-to-face lessons. However, all these materials beyond the textbook were not given to them (i.e., could only be listened to and watched inside the classroom). In this case, many indicated that their instructors uploaded these materials (i.e., materials from instructors’ personal library) on the online platform. Therefore, they could enjoy some materials with their instructors’ comments and perspectives, a story was captured:

…in contemporary literature and pop culture courses…we have to read a lot of reviewers and comments from the real speakers of the languages…but the grammatical structure and vocab…I did not understand it…they just don’t follow the textbook structures…in my intermediate courses on campus 2 years ago, my professor wrote them on the blackboard…I could download, read, listen, and watch it multiple times as it is online… (Participant #49, Focus Group)

In conclusion, the flexibility of the delivery options, flexible time for the lessons, and re-readable materials beyond the textbook were three of the main key terms under this theme and subtheme. Based on some previous studies ( Lee and Choi, 2011 ; VanPatten et al., 2015 ; Mozelius and Hettiarachchi, 2017 ), some scholars believe that students tend to take online courses due to their flexibility and busy working schedules. The results from these studies further echoed the situation before, during, and after the COVID-19 pandemic.

Same outcomes and learning rigorousness

A group of participants said that online and on-campus foreign language courses allowed them to improve their reading, writing, listening, and speaking skills with their classmates and teachers during the live online lessons. The learning outcomes and expectations were the same as they all watched the live lesson requiring virtual face-to-face interaction with others. A story was captured:

…some people told me that they could not speak in front of the computer…so they don’t want to speak…but if you don’t want to speak…in front of the computer or in front of the classroom…you are not going to speak too…this is just an exercise…I see many people speaking in their TikTok videos…just don’t give yourselves any excuses… (Participants #21, Focus Group)

In this case, all considered the role of critical thinking and time management training to be essential in university study. The current COVID-19 pandemic and the online teaching and learning arrangements provided effective training and opportunities. As one said:

…I do not think traditional on-campus courses are better than online courses…we are all here to learn the same courses and the same skills…the delivery options and models are just the models…if you want to learn the knowledge…even if you just read the textbooks without a teacher…people can still learn the greatest knowledge from the textbooks and materials…I don’t want to discriminate between these two methods… (Participant #38, Interview)

Unique learning experiences but additional skills expectations

Although current statistics ( Wallis, 2020 ) indicate that more than half of the student population has experienced the tools of distance learning and online courses, many still are new to this area. Regarding time management, almost all participants indicated that they have set up their personal goals and time schedules for each unit and exercise as they are not required to join the physical classroom environment. A participant shared the following story:

…we used to have to go to the class for the language course in the evening…but we don’t have to for now…but we still have to do the same homework, exam, project, and exercise…my professor told us that we are all adults…he would not force us to read the materials…we have to be responsible…I have learnt some skills to set up weekly goals and schedules…very good opportunities because we gained something new from the school… (Participants #58, Focus Group)

Another participant shared her story of balancing the work between family, school, and workplace as a mother with multiple responsibilities:

1…being a student, a mother, and a full-time worker is very hard…but at least for this semester, many working students could release the stress from attending all physical courses on campus in the evening…we only need to upload the materials on time…but we learn the same knowledge and complete the same exercises and exams…many of us enjoyed this online learning experiences…although a few complained about the interactions and oral communication…I don’t see there are any differences… (Participant #19, Interview)

Echoing the reflection of some scholars ( Gorbunovs et al., 2016 ), a large group of participants indicated that self-regulation and self-discipline are key to online learning experiences, regardless of age and background. The researcher captured a story:

…because we do not have to go to class and some of my courses in Spanish do not need us to attend the live lessons…I have to learn how to balance my time…also, set up goals to complete my assignment on time…my son only attended his lessons online…he also needs to complete his assignment on time and online…I have to teach my son to finish his work appropriately…and I have to be the right model…if I cannot complete mine appropriately, how can I tell my son to do so?… (Participant #7, Interview)

Interactive experiences with classmates from different parts of the world

The online courses connected domestic and international students worldwide through the online platform. All participants indicated they had at least one international student and a group of domestic students not living in their home state but connected via the online platform. This unique experience could not be acquired through on-campus experience as all are required to be on campus for physical lessons. The researcher captured two interesting stories:

…I have several students from the New England region, one from Hawaii, and one from Alaska in my French course…they should come back there on-campus…but the lockdown allowed us to connect online…we have to do homework…introduce our home city in French…I could see the view in Alaska and Hawaii…in the same 90-min lesson in life…not from the recorded videos or so…unique experiences from online learning… (Participant #27, Focus Group)

Another story was about the global connection with international students:

…we had many students from China, South Korea, Singapore, India, the United Kingdom, Pakistan, and the Middle East in our Spanish language courses over two semesters…I didn’t realize that we had many international students in my school…who are interested in the Spanish language…we exchanged a lot of knowledge and ideas from the online platforms and forums…I grouped with a Chinese student for the speaking project…I am very happy with this unique experience… (Participant #51, Interview)

University degree without borders

Besides learning experiences with students from different global communities, all expressed satisfaction with the unique experiences of non-traditional, returning, adult, and evening class students who had extensive working experience before joining university. From the perspective of the traditional age students, there was an expression of satisfaction in the experience of these less traditional classmates in the online classroom environment. Two stories were captured:

…I am so happy that I could chat with many experienced classmates who have many years of working experience in the field…although many of them learnt Spanish due to the general education requirement…they shared a lot of lived experiences in their subject courses and vocational skills to us…we could not have these chats during the daytime courses…I wish I can have these conversations in the future… (Participant #80, Focus Group)

Another participant shared ideas on the connection between foreign language and vocational knowledge from some of the experienced students in the online classroom environment:

…one of the projects was to use Spanish to do the role-play exercises based on our academic major…my major is nursing so I was paired with another public health classmate…my classmate was an evening student…she was a mother with 20 years of working experiences in a big chained hospital…I learnt a lot of speaking skills from her in English and Spanish…I am glad that we could connect because of this online course… (Participant #71, Focus Group)

Many non-traditional, returning, adult and evening class students enjoyed pairing up with traditional-age students because of their fresh ideas and similarities with their children. Many non-traditional, returning, adult, and evening class students are in their early 40s or 50s and are at school simultaneously as their college-aged children. When the researcher asked about their experience and learning motivation, many expressed a strong satisfaction and motivation in online learning. One story was given:

…my son and I did not go to the same university…but we learnt the same level of Spanish course in the same semester…I chatted with my son about the Spanish lesson…and I introduced my classmates to my son too…we all three talked together and shared some ideas …my classmate’s mother is going to school for a nursing degree, too…the online course connected two families together… (Participant #65, Focus Group)

With a reflection on a previous study about distance learning and online learning ( VanPatten et al., 2015 ), both traditional-age and non-traditional students indicated that the online-based courses allowed them to study their courses and requirements during their free time. More importantly, as some courses (e.g., elective courses) could only be offered once per year during the daytime (e.g., 9 AM), some part-time and working students could not complete the courses. Therefore, the current online arrangement met the expectations of both parties ( Jaggars, 2014 ; Tratnik et al., 2019 ). A group of non-traditional, returning, adult, and evening class students indicated that the traditional face-to-face courses had always limited their selections and learning preferences as they had to work and take care of their families during the daytime ( Dos Santos, 2020a ). However, the COVID-19 pandemic and the online learning options offered them the same opportunities as traditional on-campus students.

Besides the input from the non-traditional, returning, adult, and evening class students, many full-time students also expressed an interest in the online delivery option for their foreign language courses, particularly the flexibilities ( Dos Santos, 2020a ; Kwee, 2021 ; Maican and Cocoradã, 2021 ). However, online courses provide greater flexibility.

Many previous studies ( Pitarch, 2018 ; Liu and Li, 2019 ) have indicated that re-assessment and re-evaluation after lessons could upgrade and connect learners’ previous knowledge with their current learning materials. For example, with the reflection of a previous study ( Atmojo and Nugroho, 2020 ), all participants said they could download the audio and videos from the online learning platform to their cellphones and iPads. Based on the reflection of a previous study ( Damayanti and Rachmah, 2020 ), nearly all said that if they listened to the whole series of audios and videos at home, they could connect early chapters and exercises from previous semesters for better understanding and practice.

Based on some previous studies ( Lee and Choi, 2011 ; VanPatten et al., 2015 ; Mozelius and Hettiarachchi, 2017 ), some scholars believe that students tend to take online courses due to their flexibility and busy working schedules. The results from these studies further echoed the situation before, during, and after the COVID-19 pandemic.

Although some students may return to traditional face-to-face classroom environments after the COVID-19 pandemic, online teaching and learning options should remain active, as both traditional and non-traditional students may benefit the delivery. In the aspect of online teaching and learning, participants and previous studies ( O’Dowd, 2011 ; Chan et al., 2021 ; Iqbal and Sohail, 2021 )also argued that the online learning platform and environment should not have any significant differences in terms of outcomes and students’ achievements. In this case, many participants believed that online learning and online learning platform offered them the convenience and opportunities to gain new knowledge under the new technology.

Following social cognitive career theory ( Lent et al., 1994 ; Lent and Brown, 1996 ) and constructivist learning theory ( Bruner, 1973 , 1996 ), participants expressed their motivation for online courses due to the greater flexibility and freedom of learning. Such flexibility was unavailable under the traditional system because many courses had overlapped. Also, the online experiences further encouraged their learning experiences, motivations, and opportunities during and potentially after the COVID-19 pandemic.

Although some students may return to traditional face-to-face classroom environments after the COVID-19 pandemic, online teaching and learning options should remain active, as both traditional and non-traditional students may benefit the delivery. In the aspect of online teaching and learning, participants and previous studies ( O’Dowd, 2011 ; Chan et al., 2021 ; Iqbal and Sohail, 2021 ) also argued that the online learning platform and environment should not have any significant differences in terms of outcomes and students’ achievements. In this case, many participants believed that online learning and online learning platform offered them the convenience and opportunities to gain new knowledge under the new technology.

Some previous studies and researchers ( Al-Kumaim et al., 2021 ) have argued that online teaching and learning strategies cannot provide the same outcomes, experiences, performances, and learning rigorousness to the learners. A recent study ( Meşe and Sevilen, 2021 ) further argued that the lack of social interaction between peers and teachers could result in foreign language learners’ negative motivation and learning performance at university. However, in this case, all participants felt that the learning outcomes and expectations had been met in their online foreign language courses.

Furthermore, reflecting on a study from Güntaş et al. (2021) , almost all participants agreed that university education and experience train individuals in critical thinking skills and effective time management. All university students believed that the online foreign language courses provided them with excellent opportunities to organize their time management between their major courses and foreign language exercises ( Biletska et al., 2021 ).

Reflecting on previous studies on online and distance learning education ( Sykes and Roy, 2017 ; Gok et al., 2021 ), many participants considered the rigorous learning of both traditional and online courses equal, without any significant differences. Online courses require additional effectiveness, self-regulation, and self-motivation for their outcomes and achievements. As all completed the same exercises, exams, and homework by the deadline, all participants argued that the learning outcomes were as strong as the on-campus courses.

Many students still need time to adjust their learning expectations and personal beliefs to online courses, such as time management, self-regulation, and self-discipline ( Brown et al., 2015 ; Mozelius and Hettiarachchi, 2017 ).

The flexibility provided excellent possibilities for students to access and read the materials in their leisure time. However, the flexibility also led to some students dropping out as some could not organize and arrange their time schedules effectively ( Brown et al., 2015 ). However, the online learning achievements and outcomes do not differ based on the participants. In other words, many participants believed they could gain new knowledge and ideas in both on-campus and online classroom environments ( Yukselturk et al., 2014 ; Wright, 2017 ; Rasheed, 2020 ). More importantly, many believed the online teaching and learning environment could enhance their time management skills and interdisciplinary studies beyond the on-campus classroom environments ( Brown et al., 2013 ).

Based on the social cognitive career theory ( Lent et al., 1994 ; Lent and Brown, 1996 ), the researcher confirmed that many participants decided to learn and potentially continue their studies with online courses, motivated by the flexibility and self-arranged time schedules that fitted with their other responsibilities. Also, with a reflection on the constructivist learning theory ( Bruner, 1973 , 1996 ), participants indicated that their previous time management experience had established their current responsibilities and expectations of the online courses.

Many previous studies ( Lee and Rice, 2007 ; Choudaha, 2016 ) have highlighted the United States as a well-known destination for international students, including students in community colleges, universities, and graduate schools. Due to the COVID-19 pandemic, many international students could not return to the United States for on-campus lessons and experiences.

In conclusion, internationalism and student satisfaction are important for these participants. Firstly, reflecting on the social cognitive career theory ( Lent et al., 1994 ; Lent and Brown, 1996 ), many felt that internationalism and idea exchange played important roles in foreign language learning through listening to conversations and ideas from people in different global communities. Unlike in the past decades, students can study and attend classes and courses via online teaching and learning platforms internationally. Besides international students, non-traditional, evening, returning, and adult students also enjoy the flexibility of the online teaching and learning platform due to the development of technology ( Olesen-Tracey, 2010 ; AbuSa’aleek and Alotaibi, 2022 ). The current online learning experience provided this unique opportunity as the online platform connected students inside and outside the country, thus appropriately meeting students’ motivations.

Secondly, reflecting on the constructivist learning theory ( Bruner, 1973 , 1996 ), many participants expressed that they could improve their subject and foreign language knowledge with students from different backgrounds, such as non-traditional students, and that the learning experiences were rich. The findings of this study appropriately met the directions of two theoretical frameworks and answered the research questions.

Limitations and future research developments

Two limitations and future research developments were identified. Firstly, the current study collected data from 80 participants ( N = 80) learning and completing their foreign language requirements in the United States. Although none of their academic majors was in a foreign language, the study covered the voices and stories of many participants who had to complete a general education requirement in a foreign language via online platforms during the COVID-19 pandemic. However, students in other classes, university major(s), colleges, universities, and backgrounds may face similar issues and problems. Therefore, future research studies could cover the experience of other students, such as students in foreign language majors, to capture a broader understanding and perspective.

Secondly, the United States has over a million active student enrolments annually. The current study only covered students’ voices in the Pacific states and regions. In the future, scholars with greater funding and samples should expand the population to other American regions, such as the New England region, to capture a wider perspective.

Contributions to the practice and conclusion

First, the current study used foreign language courses and students to understand the motivations of learning and online learning experiences, particularly in American university environments. The findings of this study successfully filled up the gap in online learning, particularly the motivations and intentions of delivery methods after the COVID-19 pandemic from students’ perspectives. Students are the users of online courses. Instructors and university departments should create and design courses and delivery options that meet the demands and needs of their students. Online courses will become a popular trend in the university environment after the COVID-19 pandemic. It is important to gather the students’ voices to upgrade the teaching and learning approaches.

Second, university leaders, department heads, and teachers may use this study as the blueprint to reform and design some online courses, particularly in foreign language teaching and learning, to help non-traditional, returning, evening, and adult students who cannot attend the physical classes. As most participants advocated that online delivery does not limit their motivations and achievements, the development of online foreign language courses are greatly needed.

Third, although the participants were foreign language course takers and students, they took different online courses in their major subjects due to the COVID-19 pandemic. Based on their sharing, many advocated that the online courses and virtual learning environment were enjoyable. Based on the voices and suggestions, the curriculum planners and department leaders may expand and continue the online courses and delivery options after the COVID-19 pandemic.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

The studies involving human participants were reviewed and approved by Woosong University Academic Research Funding Department. The patients/participants provided their written informed consent to participate in this study.

Author contributions

The author confirms being the sole contributor of this work and has approved it for publication.

This research was supported by Woosong University Academic Research Funding 2021.

Conflict of interest

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

Publisher’s note

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

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Keywords : COVID-19 pandemic, computer-aided language learning, distance learning, foreign language teaching, online course, online teacher, technologically assisted teaching, technology education

Citation: Dos Santos LM (2022) Online learning after the COVID-19 pandemic: Learners’ motivations. Front. Educ. 7:879091. doi: 10.3389/feduc.2022.879091

Received: 18 February 2022; Accepted: 05 September 2022; Published: 20 September 2022.

Reviewed by:

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

*Correspondence: Luis M. Dos Santos, [email protected]

March 13, 2020

Online Learning during the COVID-19 Pandemic

What do we gain and what do we lose when classrooms go virtual?

By Yoshiko Iwai

Watchara Piriaputtanapun Getty Images

This article was published in Scientific American’s former blog network and reflects the views of the author, not necessarily those of Scientific American

I woke up an hour late Wednesday morning, and by the time I had thrown on a sweatshirt, prepared my glass of Emergen-C, and logged onto Zoom , my class had been going on for 15 minutes. The night before I had taken cough syrup for my seasonal cold, and this was the first day my school switched to virtual instruction. Over the course of the three-hour workshop, I noticed my puffy eyes on the panel of faces and became self-conscious. I turned off my video. I became distracted with the noise of sirens outside and muted my speaker, only to then realize: by the time you’re done muting-and-unmuting, the right moment to join the conversation has already passed. I found myself texting on my computer, stepping away to make coffee, running to the bathroom, writing a couple e-mails, and staring at my classmate’s dog in one of the video panels. I don’t think my experience is unique; I imagined similar situations playing out in virtual offices and classrooms across the world.

In the aftermath of the World Health Organization’s designation of the novel coronavirus as a pandemic on March 11, universities across America are shutting down in an attempt to slow its spread. On March 6, the University of Washington took the lead , canceling all in-person classes, with a wave of universities across the country following suit: University of California, Berkeley, U.C., San Diego, Stanford, Rice, Harvard, Columbia, Barnard, N.Y.U, Princeton and Duke, among many others .

This shift into virtual classrooms is the culmination of the past weeks’ efforts to prevent COVID-19 from entering university populations and spreading to local communities: cancellation of university-funded international travel for conferences , blanket bans on any international travel for spring break, canceling study-abroad programs, creating registration systems for any domestic travel.

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Columbia University, which I now attend virtually, moved all classes online starting on March 11. The following morning, president Bollinger declared that classes would be held virtually for the remainder of the school year, and suspended all university-related travel; both international and domestic. The pandemic has affected over 114 countries, killing over 4,000 and shows no sign of abating, leading to chaos in university administration and among students. I find myself obsessing over my family in Japan, especially my mother, whose lung cancer puts her at particular risk. Cancellations are affecting future students as well—admitted students’ events, open houses, and campus tours are all being canceled to minimize contagion.

The quick turn to platforms like Zoom is disrupting curricula, particularly for professors less equipped to navigate the internet and the particularities of managing a classroom mediated by a screen and microphone. I had professors cancel class because they had technical difficulties, trouble with WiFi, or were simply panicked over the prospect of teaching the full class over the new platform. With university IT services focusing efforts on providing professors with how-to webinars on using online platforms, individual student needs for these same services have been placed on hold.

While the initial shift online has created a flurry of chaos, there are benefits to a virtual classroom. Especially in a place like New York, students can continue participating in discussion sections and lectures without riding the subway for an hour, avoiding the anxiety of using public transit or being in other incubators like classrooms, public bathrooms and cafeterias. Students can “sit in” on a class while nursing a common cold or allergies that come with the season, but which can make students a target of serious threats or violence—particularly racialized harassment for Asians. I have found immense relief in not having to pay for Lyfts to campus, avoiding side-eyes for my runny nose or using the little remaining hand sanitizer I have left after holding subway poles. In some situations, online teaching may not even affect student behavior or learning. Studies have shown that medical students learn and perform equally in live versus recorded lectures, and these results are reassuring at a time like the COVID-19 outbreak.

However, the reality is that some subjects are much harder to transfer online. A biochemistry or introductory economics lecture is easier to teach virtually than a music or dance class. The creation of a film or theatrical production requires physical bodies in close proximity. Even in my creative writing workshop, responding to a colleagues’ memoir about her mother’s death is hard to do without looking her in the eye. The screen creates an emotional remove that makes it difficult to have back-and-forth dialogue between multiple people, and it’s almost impossible to provide thoughtful feedback without feeling like you’re speaking into a void.

Over the last few decades, online learning in higher education has been studied extensively. Online MBA programs are on the rise, perhaps unsurprising for a field that often requires virtual conferencing and remote collaboration. Universities now offer online master’s programs to accommodate full-time work and long commutes, or to circumvent the financial barriers of moving to a new location with family. Online bachelor’s degrees are offered by a growing number of schools: Ohio State, University of Illinois Chicago, University of Florida, Arizona State, Penn State and many more. The benefits are the same: classes can be taken anywhere, lack of commute offers more time for studying or external commitments, and the structure is more welcoming to students with physical disability or illness. And yet, online learning hasn’t threatened the traditional model of in-person learning.

A large part of this can be attributed to accountability . Online classes require significantly more motivation and attention. I found it difficult to focus on a pixelated video screen when I could browse the internet on my computer, text on my phone, watch TV in the background, have one hand in the pantry, or just lay comfortably in my bed. The problem, too, is that webinar technology doesn’t quite live up to the hype. Noise and feedback—rustling papers, ambulances, kettles, wind—make it impossible to hear people talk, and so everyone is asked to mute their microphones.

But muting your audio means you can’t jump into a conversation quickly. The “raise hand” function often goes unnoticed by teachers and the chat box is distracting. Sometimes the gallery view just doesn’t work, so you’re stuck staring at your own face or just two of your eighteen classmates. It also means another hurdle for those who hesitate to speak up, even in the best of circumstances. It means you’re just one click away from turning off your camera and being totally off the hook. In an online class over the summer, I once watched a woman—who forgot her camera was still on, though she was muted—vacuum her entire kitchen and living room during a seminar.

In a recent New York Times article, columnist Kevin Roose wrote about his experience working from home while quarantined after COVID-19 exposure. Roose, once a remote worker, cites studies that suggest remote employees are more productive , taking shorter breaks and fewer sick days. But he also writes extensively about the isolation and lack of productivity he feels: “I’ve realized that I can’t be my best, most human self in sweatpants, pretending to pay attention on video conferences between trips to the fridge.” He notes that Steve Jobs, who was a firm believer in in-person collaboration and opposed remote work, once said, “Creativity comes from spontaneous meetings, from random discussions. You run into someone, you ask what they’re doing, you say ‘Wow,’ and soon you’re cooking up all sorts of ideas.”

In educational settings, creativity is arguably one of the most important things at stake. The surprises and unexpected interactions fuel creativity—often a result of sitting in a room brushing shoulders with a classmate, running into professors in a bathroom line, or landing on ideas and insights that arise out of discomfort in the room. This unpredictability is often lost online.

In the essay “Sim Life,” from her book, Make It Scream, Make it Burn , Leslie Jamison writes about the shortcomings of virtual life: “So much of lived experience is composed of what lies beyond our agency and prediction, beyond our grasp, in missteps and unforeseen obstacles and the textures of imperfection: the grit and grain of a sidewalk with its cigarette butts and faint summer stench of garbage and taxi exhaust, the possibility of a rat scuttling from a pile of trash bags, the lilt and laughter of nearby strangers’ voices.”

Classrooms offer these opportunities for riffs and surprise, and a large part of being a student is learning to deliver critique through uncomfortable eye contact, or negotiating a room full of voices and opinions that create friction with your own. When I Zoomed into class from my apartment, I missed being interrupted by classmates who complicated my ideas about a poem or short story. I missed being in workshop and bouncing ideas off of each other to find the best structure for a piece. I missed handwritten critiques, and felt limited in Word: no check pluses, no smiley faces, “Wow” feels flat when it’s not handwritten in the margins, and "Great" feels sarcastic in 10-point Calibri. I was frustrated that I could sleep in because online class meant I could wake up five minutes before class and pretend like I’d been ready all morning.

The COVID-19 pandemic will likely continue presenting challenges beyond those that come up in the course of routine virtual education. Even if this viral spread subsides, or a vaccination becomes readily available, the shift from online classes back to in-person learning may create disruptions of its own—adjusting back to higher standards of accountability, weaning off of phone-checking habits, and transferring comments back to hard copies instead of digital notes. Hopefully, these phases of trouble shooting can provide universities, professors and students the opportunity to practice adaptability, patience and resilience. And hopefully, these experiences will serve as preparation for future challenges that come with the next epidemic, pandemic and other disaster.

For now, I am trying to not look at myself in the gallery of faces, stop being distracted by my expressions, resisting the impulses to check my phone or e-mail, or at least recognize these urges when they arise.

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Open Access

Peer-reviewed

Research Article

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

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

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

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

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

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

Roles Data curation, Writing – original draft

Roles Data curation

Roles Writing – original draft

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

Roles Conceptualization, Supervision, Writing – review & editing

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

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

• Published: August 23, 2022
• https://doi.org/10.1371/journal.pone.0273016
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The COVID-19 outbreak brought online learning to the forefront of education. Scholars have conducted many studies on online learning during the pandemic, but only a few have performed quantitative comparative analyses of students’ online learning behavior before and after the outbreak. We collected review data from China’s massive open online course platform called icourse.163 and performed social network analysis on 15 courses to explore courses’ interaction characteristics before, during, and after the COVID-19 pan-demic. Specifically, we focused on the following aspects: (1) variations in the scale of online learning amid COVID-19; (2a) the characteristics of online learning interaction during the pandemic; (2b) the characteristics of online learning interaction after the pandemic; and (3) differences in the interaction characteristics of social science courses and natural science courses. Results revealed that only a small number of courses witnessed an uptick in online interaction, suggesting that the pandemic’s role in promoting the scale of courses was not significant. During the pandemic, online learning interaction became more frequent among course network members whose interaction scale increased. After the pandemic, although the scale of interaction declined, online learning interaction became more effective. The scale and level of interaction in Electrodynamics (a natural science course) and Economics (a social science course) both rose during the pan-demic. However, long after the pandemic, the Economics course sustained online interaction whereas interaction in the Electrodynamics course steadily declined. This discrepancy could be due to the unique characteristics of natural science courses and social science courses.

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

Editor: Heng Luo, Central China Normal University, CHINA

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

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

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

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

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

1. Introduction

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

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

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

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

2. Literature review and research questions

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

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

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

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

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

3. Methodology

3.1 research context.

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

3.2 Data collection and preprocessing

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

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

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

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

3.3 Instrumentation

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

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

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

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

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

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

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

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

3.4 Ethics statement

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

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

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

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

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

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

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

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

4.2 Characteristics of online learning interaction amid COVID-19

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

4.3 Analyses of natural science courses and social science courses

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

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

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

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

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

4.3.2 Analysis of the closeness centrality of Economics and Electrodynamics.

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

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

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

5. Discussion

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

6. Conclusion and future work

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

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

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Online Learning During the Pandemic

Today’s rapid shift in the traditional patterns of social lifestyle caused by the COVID-19 pandemic outbreak has resulted in the necessity to define possible approaches to living a full-scale life while respecting the need for social distancing. Thus, one of the major challenges in the context was to define the patterns of work and education process during the global lockdown. When it comes to the notion of education, the process of online learning has become a salvation to the problem of education access and efficiency. The definition of online learning stands for an umbrella term that encompasses a series of machine-learning techniques that allow learners to acquire relevant knowledge with the help of technology in a certain sequence [1]. Although the process of online learning has become widely popular due to an ongoing emergency, the term genesis can be traced back to decades prior to COVID-19, as machine learning is also regarded as a scientific outbreak besides being an urgent problem solution [2]. Thus, once the necessity of technological intervention in education became an absolute necessity, there had already been a variety of devices and software applications to implement.

Over the times of the pandemic, the concept of educational technology (EdTech) has become widely popular with software developers and investors. In fact, EdTech, despite a relatively long existence in the market, has now introduced a variety of software applications like Classplus and Edmingle that would facilitate the process of education in both developing and developed countries [3]. Moreover, the already existing educational sources powered by Microsoft and Google are also of great efficiency for today’s learners, as their plain yet efficient design helps students accommodate quickly to the process. Hence, taking everything into consideration, it might be concluded that the process for online education that was rapidly facilitated by a pandemic outbreak is likely to develop greatly over the next few years, creating a full-scale competition for conventional patterns of learning.

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A. Muhammad, and K. Anwar. “Online learning amid the COVID-19 pandemic: Students’ perspectives.” Online Submission , vol. 2, no. 1, pp. 45-51, 2020.

D. Shivangi. “Online learning: A panacea in the time of COVID-19 crisis.” Journal of Educational Technology Systems , vol. 49, no.1, pp. 5-22, 2020.

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4 lessons from online learning that should stick after the pandemic

Assistant Professor of Innovation Finance, Athabasca University

Associate Professor, Work and Organization Studies, Athabasca University

Professor of Organizational Analysis and Project Management, Athabasca University

Professor of Open, Digital, and Distance Education , Athabasca University

Disclosure statement

Deborah Hurst receives funding from RBC and CPA to build and launch the AI powered virtual cooperative program.

Janice Thomas received funding from the Project Management Institute for earlier research projects exploring the professionalization of project management, the value of project management to organizations, and the implementation of project management as a management innovation.

Martha Cleveland-Innes has received funding from, and acts in support of, the Social Sciences and Humanities Research Council. She is an appointed member of the Athabasca University Board of Governors.

F. Haider Alvi does not work for, consult, own shares in or receive funding from any company or organisation that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

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One of the many changes COVID-19 brought those in education was an almost immediate switch to online learning.

Overnight, institutions scrambled to keep education moving, while bridging the physical distance between teacher and learner. Traditionally trained teachers made valiant efforts to adjust to digital by recording lessons, posting videos and creating breakout rooms, using whatever technology they had available.

These efforts resulted in digitally mediated physical classrooms using the internet — not online education.

While these two options sound the same, they are not . Bridging physical distance through technology alone doesn’t address additional adjustments required to address learner needs. Posting materials online, recording lectures and discussions themselves don’t create a coached, collaborative and supported learning environment.

So what have we really learned about online education? And what do we do now?

Online learning isn’t new, and lessons can be drawn from existing research and experience. Athabasca University — where we are all professors — pioneered the world’s first online MBA, M.Nursing and M.Ed progams over 28 years ago. And today, it’s one of Canada’s leading online universities .

The experience of online pioneers highlights four distinct aspects of online learning that should stick post-pandemic: learning to learn online, designing online teaching with purpose, blending space and time online and continued disruption with AI.

1. Learning to learn online

The pandemic highlighted that one-size-fits-all educational approaches fail to address student needs. Younger learners may seek physical spaces to promote socialization, with supervision and teacher-led content delivery. Others, like Athabasca’s mostly adult learners, value the convenience of connecting with classmates and instructors online during times of their choosing.

Common inequities like poor access to the internet, lack of financial resources and needed digital competence plague online learning. However, online education offers access for students facing geospacial barriers to traditional classrooms, and further issues of inequality are addressed via multi-modal distance education, financial support structures and orientation on how to learn online .

Read more: Online learning during COVID-19: 8 ways universities can improve equity and access

Emergency online education used blunt-edged instruments, ignoring student and program differences . The pandemic takeaway, however, is the importance of preparing all students to learn, whether online or in a physical classroom.

2. Designing online teaching with purpose

Quality teaching and learning design must incorporate active, engaging roles for individual students, whether designed for traditional or distance education .

Meaningful teaching varies by setting and requires different approaches . Online course and teaching design is learner rather than content centred, incorporating high engagement in collaborative learning groups that fosters active learning.

Producing effective online course materials requires an approach involving both instructors and skilled course developers and takes months rather than weeks. Course materials are painstakingly detailed, and include writing everything the instructor would expect to say in a physical classroom, clearly describing all course requirements and linking students to readings, video and online resources.

Because of the pandemic, instructors had to translate classroom delivery into technology-mediated delivery — it worked for some, but was not easily tailored to unique learning needs.

Technological tools, combined with independent and joint working opportunities, should be brought back to the physical or hybrid classroom in conjunction with online pedagogical approaches that increase active, collaborative learning and learner-generated choices.

3. Blending space and time online

Pandemic education popularized the vocabulary of “synchronous” and “asynchronous” learning. Synchronous replicated physical classrooms through real-time, digitally mediated teaching, while asynchronous meant working independently, usually with materials designed for a physical classroom. Moving forward we need to think about how timing and presence impacts learning.

At Athabasca, students come together in time and space through blended, collaborative, synchronous and asynchronous online learning . Instructors coach students individually at a student led pace.

This is different from traditional undergraduate classrooms, where students absorb material on a fixed schedule. Our graduate programs use paced programming, requiring students to work independently while regularly coming together in active online discussion.

More flexible teaching allows students to receive instructor support when they need it. Building in synchronous, collaborative learning allows for reflection, rather than real time responses.

4. COVID-19 began the disruption, AI will continue it

The pandemic revealed how education approaches can change after instructors had to search for innovative ways to improve student learning outcomes outside the physical classroom.

At Athabasca, a virtual co-operative program allowed us to introduce a co-op program in the middle of a pandemic.

Students accessed a simulated work experience in a paced structure, irrespective of location. They were able to practise working as a team, problem solving, conflict resolution, ethical reasoning and leadership while working on an assigned project. Students received immediate, detailed feedback from an AI coach, allowing for extensive experimentation and revision to master concepts honed in reflective discussion with the instructor.

Research suggests that adopting online and AI tools needs to be deliberate, coupled with supportive digital infrastructure and highly responsive student support. Planned carefully and taken together, these steps improve on traditional approaches by making education truly open, accessible and inclusive.

Now, the question for all educators should be: How do we capitalize on COVID-19 initiated change to build better education systems for the future?

This is an updated version of a story originally published May 1, 2022. It clarifies emergency online education made it difficult to address student differences.

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• The Internet and the Pandemic

90% of Americans say the internet has been essential or important to them, many made video calls and 40% used technology in new ways. But while tech was a lifeline for some, others faced struggles

Table of contents.

• 1. How the internet and technology shaped Americans’ personal experiences amid COVID-19
• 2. Parents, their children and school during the pandemic
• 3. Navigating technological challenges
• 4. The role of technology in COVID-19 vaccine registration
• Acknowledgments
• Methodology

Pew Research Center has a long history of studying technology adoption trends and the impact of digital technology on society. This report focuses on American adults’ experiences with and attitudes about their internet and technology use during the COVID-19 outbreak. For this analysis, we surveyed 4,623 U.S. adults from April 12-18, 2021. Everyone who took part is a member of the Center’s American Trends Panel (ATP), an online survey panel that is recruited through national, random sampling of residential addresses. This way nearly all U.S. adults have a chance of selection. The survey is weighted to be representative of the U.S. adult population by gender, race, ethnicity, partisan affiliation, education and other categories. Read more about the  ATP’s methodology .

Chapter 1 of this report includes responses to an open-ended question and the overall report includes a number of quotations to help illustrate themes and add nuance to the survey findings. Quotations may have been lightly edited for grammar, spelling and clarity. The first three themes mentioned in each open-ended response, according to a researcher-developed codebook, were coded into categories for analysis. 

Here are the questions used for this report , along with responses, and its methodology .

The  coronavirus  has transformed many aspects of Americans’ lives. It  shut down  schools, businesses and workplaces and forced millions to  stay at home  for extended lengths of time. Public health authorities recommended  limits on social contact  to try to contain the spread of the virus, and these profoundly altered the way many worked, learned, connected with loved ones, carried out basic daily tasks, celebrated and mourned. For some, technology played a role in this transformation.  

Results from a new Pew Research Center survey of U.S. adults conducted April 12-18, 2021, reveal the extent to which people’s use of the internet has changed, their views about how helpful technology has been for them and the struggles some have faced. 

The vast majority of adults (90%) say the internet has been at least important to them personally during the pandemic, the survey finds. The share who say it has been  essential  – 58% – is up slightly from 53% in April 2020. There have also been upticks in the shares who say the internet has been essential in the past year among those with a bachelor’s degree or more formal education, adults under 30, and those 65 and older. 

A large majority of Americans (81%) also say they talked with others via video calls at some point since the pandemic’s onset. And for 40% of Americans, digital tools have taken on new relevance: They report they used technology or the internet in ways that were new or different to them. Some also sought upgrades to their service as the pandemic unfolded: 29% of broadband users did something to improve the speed, reliability or quality of their high-speed internet connection at home since the beginning of the outbreak.

Still, tech use has not been an unmitigated boon for everyone. “ Zoom fatigue ” was widely speculated to be a problem in the pandemic, and some Americans report related experiences in the new survey: 40% of those who have ever talked with others via video calls since the beginning of the pandemic say they have felt worn out or fatigued often or sometimes by the time they spend on them. Moreover,  changes in screen time  occurred for  Americans generally  and for  parents of young children . The survey finds that a third of all adults say they tried to cut back on time spent on their smartphone or the internet at some point during the pandemic. In addition, 72% of parents of children in grades K-12 say their kids are spending more time on screens compared with before the outbreak. 1

For many, digital interactions could only do so much as a stand-in for in-person communication. About two-thirds of Americans (68%) say the interactions they would have had in person, but instead had online or over the phone, have generally been useful – but not a replacement for in-person contact. Another 15% say these tools haven’t been of much use in their interactions. Still, 17% report that these digital interactions have been just as good as in-person contact.

Some types of technology have been more helpful than others for Americans. For example, 44% say text messages or group messaging apps have helped them a lot to stay connected with family and friends, 38% say the same about voice calls and 30% say this about video calls. Smaller shares say social media sites (20%) and email (19%) have helped them in this way.

The survey offers a snapshot of Americans’ lives just over one year into the pandemic as they reflected back on what had happened. It is important to note the findings were gathered in April 2021, just before  all U.S. adults became eligible for coronavirus vaccine s. At the time, some states were  beginning to loosen restrictions  on businesses and social encounters. This survey also was fielded before the delta variant  became prominent  in the United States,  raising concerns  about new and  evolving variants . 

Here are some of the key takeaways from the survey.

Americans’ tech experiences in the pandemic are linked to digital divides, tech readiness 

Some Americans’ experiences with technology haven’t been smooth or easy during the pandemic. The digital divides related to  internet use  and  affordability  were highlighted by the pandemic and also emerged in new ways as life moved online.

For all Americans relying on screens during the pandemic,  connection quality  has been important for school assignments, meetings and virtual social encounters alike. The new survey highlights difficulties for some: Roughly half of those who have a high-speed internet connection at home (48%) say they have problems with the speed, reliability or quality of their home connection often or sometimes. 2

Beyond that, affordability  remained a persistent concern  for a portion of digital tech users as the pandemic continued – about a quarter of home broadband users (26%) and smartphone owners (24%) said in the April 2021 survey that they worried a lot or some about paying their internet and cellphone bills over the next few months. 

From parents of children facing the “ homework gap ” to Americans struggling to  afford home internet , those with lower incomes have been particularly likely to struggle. At the same time, some of those with higher incomes have been affected as well.

Affordability and connection problems have hit broadband users with lower incomes especially hard. Nearly half of broadband users with lower incomes, and about a quarter of those with midrange incomes, say that as of April they were at least somewhat worried about paying their internet bill over the next few months. 3 And home broadband users with lower incomes are roughly 20 points more likely to say they often or sometimes experience problems with their connection than those with relatively high incomes. Still, 55% of those with lower incomes say the internet has been essential to them personally in the pandemic.

At the same time, Americans’ levels of formal education are associated with their experiences turning to tech during the pandemic. 

Those with a bachelor’s or advanced degree are about twice as likely as those with a high school diploma or less formal education to have used tech in new or different ways during the pandemic. There is also roughly a 20 percentage point gap between these two groups in the shares who have made video calls about once a day or more often and who say these calls have helped at least a little to stay connected with family and friends. And 71% of those with a bachelor’s degree or more education say the internet has been essential, compared with 45% of those with a high school diploma or less.

More broadly, not all Americans believe they have key tech skills. In this survey, about a quarter of adults (26%) say they usually need someone else’s help to set up or show them how to use a new computer, smartphone or other electronic device. And one-in-ten report they have little to no confidence in their ability to use these types of devices to do the things they need to do online. This report refers to those who say they experience either or both of these issues as having “lower tech readiness.” Some 30% of adults fall in this category. (A full description of how this group was identified can be found in  Chapter 3. )

These struggles are particularly acute for older adults, some of whom have had to  learn new tech skills  over the course of the pandemic. Roughly two-thirds of adults 75 and older fall into the group having lower tech readiness – that is, they either have little or no confidence in their ability to use their devices, or generally need help setting up and learning how to use new devices. Some 54% of Americans ages 65 to 74 are also in this group. 

Americans with lower tech readiness have had different experiences with technology during the pandemic. While 82% of the Americans with lower tech readiness say the internet has been at least important to them personally during the pandemic, they are less likely than those with higher tech readiness to say the internet has been essential (39% vs. 66%). Some 21% of those with lower tech readiness say digital interactions haven’t been of much use in standing in for in-person contact, compared with 12% of those with higher tech readiness. 

46% of parents with lower incomes whose children faced school closures say their children had at least one problem related to the ‘homework gap’

As school moved online for many families, parents and their children experienced profound changes. Fully 93% of parents with K-12 children at home say these children had some online instruction during the pandemic. Among these parents, 62% report that online learning has gone very or somewhat well, and 70% say it has been very or somewhat easy for them to help their children use technology for online instruction.

Still, 30% of the parents whose children have had online instruction during the pandemic say it has been very or somewhat difficult for them to help their children use technology or the internet for this. 

The survey also shows that children from households with lower incomes who faced school closures in the pandemic have been especially likely to encounter tech-related obstacles in completing their schoolwork – a phenomenon contributing to the “ homework gap .”

Overall, about a third (34%) of all parents whose children’s schools closed at some point say their children have encountered at least one of the tech-related issues we asked about amid COVID-19: having to do schoolwork on a cellphone, being unable to complete schoolwork because of lack of computer access at home, or having to use public Wi-Fi to finish schoolwork because there was no reliable connection at home. 

This share is higher among parents with lower incomes whose children’s schools closed. Nearly half (46%) say their children have faced at least one of these issues. Some with higher incomes were affected as well – about three-in-ten (31%) of these parents with midrange incomes say their children faced one or more of these issues, as do about one-in-five of these parents with higher household incomes.

Prior Center work has documented this “ homework gap ” in other contexts – both  before the coronavirus outbreak  and  near the beginning of the pandemic . In April 2020, for example, parents with lower incomes were particularly likely to think their children would face these struggles amid the outbreak.

Besides issues related to remote schooling, other changes were afoot in families as the pandemic forced many families to shelter in place. For instance, parents’ estimates of their children’s screen time – and family rules around this – changed in some homes. About seven-in-ten parents with children in kindergarten through 12th grade (72%) say their children were spending more time on screens as of the April survey compared with before the outbreak. Some 39% of parents with school-age children say they have become less strict about screen time rules during the outbreak. About one-in-five (18%) say they have become more strict, while 43% have kept screen time rules about the same. 

More adults now favor the idea that schools should provide digital technology to all students during the pandemic than did in April 2020

Americans’ tech struggles related to digital divides gained attention from policymakers and news organizations as the pandemic progressed.

On some policy issues, public attitudes changed over the course of the outbreak – for example, views on what K-12 schools should provide to students shifted. Some 49% now say K-12 schools have a responsibility to provide all students with laptop or tablet computers in order to help them complete their schoolwork during the pandemic, up 12 percentage points from a year ago.

The shares of those who say so have increased for both major political parties over the past year: This view shifted 15 points for Republicans and those who lean toward the GOP, and there was a 9-point increase for Democrats and Democratic leaners.

However, when it comes to views of policy solutions for internet access more generally, not much has changed. Some 37% of Americans say that the government has a responsibility to ensure all Americans have high-speed internet access during the outbreak, and the overall share is unchanged from April 2020 – the first time Americans were asked this specific question about the government’s pandemic responsibility to provide internet access. 4

Democrats are more likely than Republicans to say the government has this responsibility, and within the Republican Party, those with lower incomes are more likely to say this than their counterparts earning more money. 

Video calls and conferencing have been part of everyday life

Americans’ own words provide insight into exactly how their lives changed amid COVID-19. When asked to describe the new or different ways they had used technology, some Americans mention video calls and conferencing facilitating a variety of virtual interactions – including attending events like weddings, family holidays and funerals or transforming where and how they worked. 5 From family calls, shopping for groceries and placing takeout orders online to having telehealth visits with medical professionals or participating in online learning activities, some aspects of life have been virtually transformed: 

“I’ve gone from not even knowing remote programs like Zoom even existed, to using them nearly every day.” – Man, 54

“[I’ve been] h andling … deaths of family and friends remotely, attending and sharing classical music concerts and recitals with other professionals, viewing [my] own church services and Bible classes, shopping. … Basically, [the internet has been] a lifeline.”  – Woman, 69

“I … use Zoom for church youth activities. [I] use Zoom for meetings. I order groceries and takeout food online. We arranged for a ‘digital reception’ for my daughter’s wedding as well as live streaming the event.” – Woman, 44

When asked about video calls specifically, half of Americans report they have talked with others in this way at least once a week since the beginning of the outbreak; one-in-five have used these platforms daily. But how often people have experienced this type of digital connectedness varies by age. For example, about a quarter of adults ages 18 to 49 (27%) say they have connected with others on video calls about once a day or more often, compared with 16% of those 50 to 64 and just 7% of those 65 and older. 

Even as video technology became a part of life for users, many  accounts of burnout  surfaced and some speculated that “Zoom fatigue” was setting in as Americans grew weary of this type of screen time. The survey finds that some 40% of those who participated in video calls since the beginning of the pandemic – a third of all Americans – say they feel worn out or fatigued often or sometimes from the time they spend on video calls. About three-quarters of those who have been on these calls several times a day in the pandemic say this.

Fatigue is not limited to frequent users, however: For example, about a third (34%) of those who have made video calls about once a week say they feel worn out at least sometimes.

These are among the main findings from the survey. Other key results include:

Some Americans’ personal lives and social relationships have changed during the pandemic:  Some 36% of Americans say their own personal lives changed in a major way as a result of the coronavirus outbreak. Another 47% say their personal lives changed, but only a little bit.   About half (52%) of those who say major change has occurred in their personal lives due to the pandemic also say they have used tech in new ways, compared with about four-in-ten (38%) of those whose personal lives changed a little bit and roughly one-in-five (19%) of those who say their personal lives stayed about the same.

Even as tech helped some to stay connected, a quarter of Americans say they feel less close to close family members now compared with before the pandemic, and about four-in-ten (38%) say the same about friends they know well. Roughly half (53%) say this about casual acquaintances.

The majority of those who tried to sign up for vaccine appointments in the first part of the year went online to do so:  Despite early problems with  vaccine rollout  and  online registration systems , in the April survey tech problems did  not  appear to be major struggles for most adults who had tried to sign up online for COVID-19 vaccines. The survey explored Americans’ experiences getting these vaccine appointments and reveals that in April 57% of adults had tried to sign themselves up and 25% had tried to sign someone else up. Fully 78% of those who tried to sign themselves up and 87% of those who tried to sign others up were online registrants. 

When it comes to difficulties with the online vaccine signup process, 29% of those who had tried to sign up online – 13% of all Americans – say it was very or somewhat difficult to sign themselves up for vaccines at that time. Among five reasons for this that the survey asked about, the most common  major  reason was lack of available appointments, rather than tech-related problems. Adults 65 and older who tried to sign themselves up for the vaccine online were the most likely age group to experience at least some difficulty when they tried to get a vaccine appointment.

Tech struggles and usefulness alike vary by race and ethnicity.  Americans’ experiences also have varied across racial and ethnic groups. For example, Black Americans are more likely than White or Hispanic adults to meet the criteria for having “lower tech readiness.” 6 Among broadband users, Black and Hispanic adults were also more likely than White adults to be worried about paying their bills for their high-speed internet access at home as of April, though the share of Hispanic Americans who say this declined sharply since April 2020. And a majority of Black and Hispanic broadband users say they at least sometimes have experienced problems with their internet connection. 

Still, Black adults and Hispanic adults are more likely than White adults to say various technologies – text messages, voice calls, video calls, social media sites and email – have helped them a lot to stay connected with family and friends amid the pandemic.

Tech has helped some adults under 30 to connect with friends, but tech fatigue also set in for some.  Only about one-in-five adults ages 18 to 29 say they feel closer to friends they know well compared with before the pandemic. This share is twice as high as that among adults 50 and older. Adults under 30 are also more likely than any other age group to say social media sites have helped a lot in staying connected with family and friends (30% say so), and about four-in-ten of those ages 18 to 29 say this about video calls. 

Screen time affected some negatively, however. About six-in-ten adults under 30 (57%) who have ever made video calls in the pandemic say they at least sometimes feel worn out or fatigued from spending time on video calls, and about half (49%) of young adults say they have tried to cut back on time spent on the internet or their smartphone.

• Throughout this report, “parents” refers to those who said they were the parent or guardian of any children who were enrolled in elementary, middle or high school and who lived in their household at the time of the survey. ↩
• People with a high-speed internet connection at home also are referred to as “home broadband users” or “broadband users” throughout this report. ↩
• Family incomes are based on 2019 earnings and adjusted for differences in purchasing power by geographic region and for household sizes. Middle income is defined here as two-thirds to double the median annual family income for all panelists on the American Trends Panel. Lower income falls below that range; upper income falls above it. ↩
• A separate  Center study  also fielded in April 2021 asked Americans what the government is responsible for on a number of topics, but did not mention the coronavirus outbreak. Some 43% of Americans said in that survey that the federal government has a responsibility to provide high-speed internet for all Americans. This was a significant increase from 2019, the last time the Center had asked that more general question, when 28% said the same. ↩
• Quotations in this report may have been lightly edited for grammar, spelling and clarity. ↩
• There were not enough Asian American respondents in the sample to be broken out into a separate analysis. As always, their responses are incorporated into the general population figures throughout this report. ↩

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The pandemic has had devastating impacts on learning. What will it take to help students catch up?

Subscribe to the brown center on education policy newsletter, megan kuhfeld , megan kuhfeld senior research scientist - nwea @megankuhfeld jim soland , jim soland assistant professor, school of education and human development - university of virginia, affiliated research fellow - nwea @jsoland karyn lewis , and karyn lewis director, center for school and student progress - nwea @karynlew emily morton emily morton research scientist - nwea @emily_r_morton.

March 3, 2022

As we reach the two-year mark of the initial wave of pandemic-induced school shutdowns, academic normalcy remains out of reach for many students, educators, and parents. In addition to surging COVID-19 cases at the end of 2021, schools have faced severe staff shortages , high rates of absenteeism and quarantines , and rolling school closures . Furthermore, students and educators continue to struggle with mental health challenges , higher rates of violence and misbehavior , and concerns about lost instructional time .

As we outline in our new research study released in January, the cumulative impact of the COVID-19 pandemic on students’ academic achievement has been large. We tracked changes in math and reading test scores across the first two years of the pandemic using data from 5.4 million U.S. students in grades 3-8. We focused on test scores from immediately before the pandemic (fall 2019), following the initial onset (fall 2020), and more than one year into pandemic disruptions (fall 2021).

Average fall 2021 math test scores in grades 3-8 were 0.20-0.27 standard deviations (SDs) lower relative to same-grade peers in fall 2019, while reading test scores were 0.09-0.18 SDs lower. This is a sizable drop. For context, the math drops are significantly larger than estimated impacts from other large-scale school disruptions, such as after Hurricane Katrina—math scores dropped 0.17 SDs in one year for New Orleans evacuees .

Even more concerning, test-score gaps between students in low-poverty and high-poverty elementary schools grew by approximately 20% in math (corresponding to 0.20 SDs) and 15% in reading (0.13 SDs), primarily during the 2020-21 school year. Further, achievement tended to drop more between fall 2020 and 2021 than between fall 2019 and 2020 (both overall and differentially by school poverty), indicating that disruptions to learning have continued to negatively impact students well past the initial hits following the spring 2020 school closures.

These numbers are alarming and potentially demoralizing, especially given the heroic efforts of students to learn and educators to teach in incredibly trying times. From our perspective, these test-score drops in no way indicate that these students represent a “ lost generation ” or that we should give up hope. Most of us have never lived through a pandemic, and there is so much we don’t know about students’ capacity for resiliency in these circumstances and what a timeline for recovery will look like. Nor are we suggesting that teachers are somehow at fault given the achievement drops that occurred between 2020 and 2021; rather, educators had difficult jobs before the pandemic, and now are contending with huge new challenges, many outside their control.

Clearly, however, there’s work to do. School districts and states are currently making important decisions about which interventions and strategies to implement to mitigate the learning declines during the last two years. Elementary and Secondary School Emergency Relief (ESSER) investments from the American Rescue Plan provided nearly $200 billion to public schools to spend on COVID-19-related needs. Of that sum, $22 billion is dedicated specifically to addressing learning loss using “evidence-based interventions” focused on the “ disproportionate impact of COVID-19 on underrepresented student subgroups. ” Reviews of district and state spending plans (see Future Ed , EduRecoveryHub , and RAND’s American School District Panel for more details) indicate that districts are spending their ESSER dollars designated for academic recovery on a wide variety of strategies, with summer learning, tutoring, after-school programs, and extended school-day and school-year initiatives rising to the top.

Comparing the negative impacts from learning disruptions to the positive impacts from interventions

To help contextualize the magnitude of the impacts of COVID-19, we situate test-score drops during the pandemic relative to the test-score gains associated with common interventions being employed by districts as part of pandemic recovery efforts. If we assume that such interventions will continue to be as successful in a COVID-19 school environment, can we expect that these strategies will be effective enough to help students catch up? To answer this question, we draw from recent reviews of research on high-dosage tutoring , summer learning programs , reductions in class size , and extending the school day (specifically for literacy instruction) . We report effect sizes for each intervention specific to a grade span and subject wherever possible (e.g., tutoring has been found to have larger effects in elementary math than in reading).

Figure 1 shows the standardized drops in math test scores between students testing in fall 2019 and fall 2021 (separately by elementary and middle school grades) relative to the average effect size of various educational interventions. The average effect size for math tutoring matches or exceeds the average COVID-19 score drop in math. Research on tutoring indicates that it often works best in younger grades, and when provided by a teacher rather than, say, a parent. Further, some of the tutoring programs that produce the biggest effects can be quite intensive (and likely expensive), including having full-time tutors supporting all students (not just those needing remediation) in one-on-one settings during the school day. Meanwhile, the average effect of reducing class size is negative but not significant, with high variability in the impact across different studies. Summer programs in math have been found to be effective (average effect size of .10 SDs), though these programs in isolation likely would not eliminate the COVID-19 test-score drops.

Figure 1: Math COVID-19 test-score drops compared to the effect sizes of various educational interventions

Source: COVID-19 score drops are pulled from Kuhfeld et al. (2022) Table 5; reduction-in-class-size results are from pg. 10 of Figles et al. (2018) Table 2; summer program results are pulled from Lynch et al (2021) Table 2; and tutoring estimates are pulled from Nictow et al (2020) Table 3B. Ninety-five percent confidence intervals are shown with vertical lines on each bar.

Notes: Kuhfeld et al. and Nictow et al. reported effect sizes separately by grade span; Figles et al. and Lynch et al. report an overall effect size across elementary and middle grades. We were unable to find a rigorous study that reported effect sizes for extending the school day/year on math performance. Nictow et al. and Kraft & Falken (2021) also note large variations in tutoring effects depending on the type of tutor, with larger effects for teacher and paraprofessional tutoring programs than for nonprofessional and parent tutoring. Class-size reductions included in the Figles meta-analysis ranged from a minimum of one to minimum of eight students per class.

Figure 2 displays a similar comparison using effect sizes from reading interventions. The average effect of tutoring programs on reading achievement is larger than the effects found for the other interventions, though summer reading programs and class size reduction both produced average effect sizes in the ballpark of the COVID-19 reading score drops.

Figure 2: Reading COVID-19 test-score drops compared to the effect sizes of various educational interventions

Source: COVID-19 score drops are pulled from Kuhfeld et al. (2022) Table 5; extended-school-day results are from Figlio et al. (2018) Table 2; reduction-in-class-size results are from pg. 10 of Figles et al. (2018) ; summer program results are pulled from Kim & Quinn (2013) Table 3; and tutoring estimates are pulled from Nictow et al (2020) Table 3B. Ninety-five percent confidence intervals are shown with vertical lines on each bar.

Notes: While Kuhfeld et al. and Nictow et al. reported effect sizes separately by grade span, Figlio et al. and Kim & Quinn report an overall effect size across elementary and middle grades. Class-size reductions included in the Figles meta-analysis ranged from a minimum of one to minimum of eight students per class.

There are some limitations of drawing on research conducted prior to the pandemic to understand our ability to address the COVID-19 test-score drops. First, these studies were conducted under conditions that are very different from what schools currently face, and it is an open question whether the effectiveness of these interventions during the pandemic will be as consistent as they were before the pandemic. Second, we have little evidence and guidance about the efficacy of these interventions at the unprecedented scale that they are now being considered. For example, many school districts are expanding summer learning programs, but school districts have struggled to find staff interested in teaching summer school to meet the increased demand. Finally, given the widening test-score gaps between low- and high-poverty schools, it’s uncertain whether these interventions can actually combat the range of new challenges educators are facing in order to narrow these gaps. That is, students could catch up overall, yet the pandemic might still have lasting, negative effects on educational equality in this country.

Given that the current initiatives are unlikely to be implemented consistently across (and sometimes within) districts, timely feedback on the effects of initiatives and any needed adjustments will be crucial to districts’ success. The Road to COVID Recovery project and the National Student Support Accelerator are two such large-scale evaluation studies that aim to produce this type of evidence while providing resources for districts to track and evaluate their own programming. Additionally, a growing number of resources have been produced with recommendations on how to best implement recovery programs, including scaling up tutoring , summer learning programs , and expanded learning time .

Ultimately, there is much work to be done, and the challenges for students, educators, and parents are considerable. But this may be a moment when decades of educational reform, intervention, and research pay off. Relying on what we have learned could show the way forward.

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How the pandemic made private online tutors a go-to for NJ's public schools

5-minute read.

It started as a clever use of technology to help overburdened teachers and students as they juggled remote lessons during the COVID-19 pandemic.  

Now, online tutoring has become standard “edtech” — and gaining popularity in New Jersey’s K-12 schools. 

Online tutoring — in which students interact with a human tutor on a computer screen — has become key as districts struggle to help students catch up from pandemic-related learning gaps amid an ongoing teacher shortage. On-screen tutoring is predominantly used after school hours, but that could change to fit into the school day. 

The Edison school district in Middlesex County is paying for online tutoring using federal Title I funds that districts receive based on the size of their low-income student population, but which must be used to serve any student who is at risk academically.

The Denville school district in Morris County used $68,000 in federal COVID relief funds for online tutoring through AirTutor.com, said Assistant Superintendent Sandra Cullis. She sees online tutoring as a "game changer" that stayed on after masks and COVID restrictions went away.

With pandemic relief dollars running out, districts like Denville are also considering using Title I funds for online tutoring. 

“If funding allows, having additional supports ready to address student needs in a timely manner is a game changer for some students,” Cullis said.

Online tutoring provides personalized, differentiated learning

Schools are still using the technology only to support students who need extra help — outside class hours, and not in place of classroom instruction.

But it also offers districts the option of providing personalized, differentiated learning — buzzwords in education as schools try to address individual needs instead of using one-size-fits-all lessons that may not reach every student in the same way. 

“We now know that the more individualized, the more personalized the educational program you can deliver, the better it is,” said Rick Cohen, chief academic officer for secondary education at Edison Public Schools. 

“It's not a magic bullet, and you don’t get 100%,” he said, “but because of the personalized aspect of it — the one-to-one tutoring — we get a good response.”

The district has spent $333,662 this academic year on math tutoring for high school students through Varsity Tutors, he said. That's about $17 an hour. 

24/7 anonymous chat-based tutoring help

An add-on service from online tutors is 24/7 chat-based help. The sessions are anonymous but use interactive whiteboards to work out problems and share notes on the chat screen. Students get help with homework and concepts without face-to-face interaction.

The Paterson school district offers its sixth to 12th grade students the service through Tutor.com. 

Many tutoring companies grabbed the opportunity created by the pandemic's temporary shift to K-12 remote learning. In March 2021, the state announced the bridging of the digital divide in public schools, ensuring that every student had a laptop and internet access.

Companies such as Varsity Tutors had a 16-year-old core business tutoring families and individuals. Now they had a new niche: the public school.

“About two years ago we started to realize the need to help districts and provide individualized support, both to help with teacher burnout and learning loss recovery,” said Anthony Salcito, chief institution business officerfor Varsity Tutors.

The company said it provides personal online tutoring and a 24/7 chat to K-12 students in 13 charter schools and school districts in New Jersey, including Mine Hill and Randolph in Morris County, Orange and Livingston in Essex County, and Edison.

In Edison, parents sign up their children for tutoring sessions to match their family schedules. Varsity Tutors also offers district- and teacher-assigned tutoring, in which schools could potentially have students meet online with a tutor during study hall or as an in-class support to teachers.

Schools have yet to buy in to these options, possibly also because teachers’ unions would have to agree. The company said one New Jersey district is considering in-school tutoring support. 

Online tutors best for math and reading

Denville students received one-on-one online math help in the summer, to bridge the gap between advanced and grade-level courses. Tutoring was more effective for fourth through eighth grade students and for math and basic reading skills, like phonemic awareness, said Cullis, the assistant superintendent.

Cohen, from the Edison district, agreed that the model works better for math. “I saw substantial gains for our students in math that participated in at least 12 or more hours of online tutoring,” he said, after comparing test scores for students who were tutored in math and in English for the same number of hours. 

Tutoring platforms refer to weeks-long, intensive sessions as “high-dosage” tutoring, which research shows is highly effective for learning gains in students who are falling behind. “High-dosage” usually refers to in-person tutoring, with a child or a small group meeting with the same tutor for up to 90 minutes a week. But the model is also moving online. 

No substitute for classroom, teachers say

For all the hype, online tutoring is no substitute for in-person classroom teachers, say school leaders and teachers’ unions.

The state’s largest teachers’ union, the New Jersey Education Association, pushed last year for laws that would require schools to get approval from the Department of Education for virtual instructors or vendors to deliver remote instruction for courses other than on financial, business and entrepreneurship literacy.

The measure did not pass, but the state’s K-12 stakeholders are trying to find common ground on regulating online instruction. 

Flexibility, a wide pool of tutors for all subjects and multilingual tutors for non-English-speaking students are other benefits. “Some students are more confident with virtual tutors," Cullis said. 

“One disadvantage of virtual tutoring is the inability to read the whole child,” especially body language, she said.  

Difficulty filling teaching jobs

But the pandemic left administrators stretched thin. Cohen, who worked for the Metuchen school district at the time, said it was hard enough finding teachers for kids who were quarantining and those needing extra help.

Then came the COVID omicron variant in January 2022, sending even more kids and staff into quarantine. 

“I was like, OK, we can't maintain this," Cohen said. "We can't sustain and anticipate the number of kids who are going to need support beyond quarantine instruction. That's when I began to search for third-party vendors.”

But federal relief funds for high-dosage online tutoring was reserved for academically at-risk students in vulnerable demographic sub-groups, including Black and Hispanic students, those receiving special education services, low-income students and English language learners.

The district was also hearing from families that said their kids did not qualify for the high-dosage tutoring but wanted extra help. It decided to use Varsity Tutors’ 24/7 chat as a support for all students, Cohen said.

Ultimately, online tutoring has “empowered” schools to be personalized and on-demand, without pressuring teachers, Cohen said. 

Advice for Choosing an Online J.D. Program

Online legal education is on the rise, but applicants should look before they leap.

Advice About Online J.D. Programs

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Online law programs enable students to have a more convenience and flexible option when earning their degree.

A small but growing number of law schools now offer law students the ability to earn a J.D. partly or fully online, which has undoubtedly made legal education more accessible for a range of students.

The American Bar Association, the professional organization that sets legal education standards, first allowed one-third of a law school's required credits to be taught online in 2018. Three years later, the organization opened the doors to fully online J.D. programs as the COVID-19 pandemic accelerated trends toward online education.

The ABA maintains a list of schools with partly or fully online J.D. programs. These programs differ in their rules, requirements and the student populations they serve.

Low-Residency, Hybrid and Online Programs

Only a few law schools offer fully online J.D. programs, including St. Mary's University School of Law in Texas and the University of Hawaii—Manoa Richardson School of Law .

More than a dozen other law schools offer partly online J.D. programs. Vermont Law School offers a "Reduced-Residency" J.D. program with in-person classes required only the first three semesters. Syracuse University College of Law in New York and the University of Dayton School of Law in Ohio blend online classes with brief in-person residencies.

Some law schools within major metro areas, like the Loyola University Chicago School of Law in Illinois and Seton Hall University School of Law in New Jersey, offer hybrid J.D. programs with weekend classes. Like traditional part-time law programs , these are best suited to local students who work full time.

The Pros and Cons of Online Law Programs

Many law students may balk at the idea of paying full tuition for online law school classes. Some worry that law schools see online education as a cash cow, allowing them to accept more students at lower cost. Law schools insist that online law programs present flexible options rather than a replacement for in-person programs, but that may change in time.

On the other hand, some law students are drawn to the convenience of joining class from home. Older law students may particularly appreciate the flexibility of online classes. Online options may also appeal to students with disabilities as well as those who live far from a law school. 

As the list of partly and fully online J.D. programs grows, applicants interested in pursuing an online law program should consider the following advice.

Know That Reputation Still Matters

Since the value of an online law degree in job markets is still untested, participants may want to stick with more well-known and well-regarded programs with strong alumni networks.

For example, there are benefits of attending law school in a state where you plan to practice that may not accrue to distance learners unable to participate in on-campus opportunities. 

Note Focus Areas

Be sure to choose a program that fits your career interests.

Many online law programs focus on specific areas. For example, the University of New Hampshire Pierce School of Law offers a hybrid J.D. program with a strong focus on intellectual property .

Consider Non-J.D. Options

Applicants who already have a J.D. or a foreign equivalent might instead consider an LL.M. , which is a master's degree in law. Many schools offer fully online one-year LL.M. programs focused on legal specialties like tax or international law .

Another option to consider is an online master's degree in legal studies , which usually takes one year as well. This program does not fulfill the legal education requirements to sit for the bar exam , although a few states offer other paths to legal practice.

Prioritize Hands-On Experience

Perhaps the aspect of legal education that graduates most value is the practical experience gained from working in small groups, legal clinics and volunteer activities on campus.

Without real-life interaction, it can be hard for online students to get this taste of life as an attorney. Before applying to an online program, make sure that it will offer experiential learning opportunities in some capacity.

Even if the benefits of in-person classes cannot be fully replicated online, the expansion of degree options may help serve law school applicants with different needs and interests. But applicants should consider such programs carefully to ensure they are worth the investment of time and money.

Tips to Boost a Law School Application

Tags: law school , online education , graduate schools , education , students

About Law Admissions Lowdown

Law Admissions Lowdown provides advice to prospective students about the law school application process, LSAT prep and potential career paths. Previously authored by contributors from Stratus Admissions Counseling, the blog is currently authored by Gabriel Kuris, founder of Top Law Coach , an admissions consultancy. Kuris is a graduate of Harvard Law School and has helped hundreds of applicants navigate the law school application process since 2003. Got a question? Email [email protected] .

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Commentary | I’m a member of the class of 2024; our…

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Commentary | I’m a member of the class of 2024; our education system has failed us. | GUEST COMMENTARY

As a member of the class of 2024 at Northwood High School in Kemp Mill, I experienced the COVID-19 pandemic’s devastation of our education system. The simple fact is, through no fault of our own, students are not as engaged in class as they were before the pandemic. Online school was a disaster. Students were given little reason to come to class, and as a result, teachers had the demoralizing experience of speaking to a Zoom room full of black boxes as students, even the most well-positioned among us, got used to Googling answers on tests, not paying attention in class, and not asking or answering questions. That culture has persisted even as we have taken off our masks and returned to in-person learning.

The effects are clear: From 2020 to 2022, the Nation’s Report card showed the largest drop in reading scores since 1990, and the first-ever drop in math scores. Many of my peers rarely come to class; in Montgomery County in the 2022-’23 school year, 36% of high school students were chronically absent. Those who do show up are often disengaged. It is common to see a teacher ask a simple question and not see a single hand go up.

Confronted with such a dismal situation, most teachers have taken the route of my 10th-grade English teacher: empathy.

He would often say things like “I’m tired too. Let’s just get through this.” This is a reasonable approach, and it comes from teachers’ deep care for their students. But, in my experience, this approach yields limited results. Hearing that the teacher is apathetic reaffirms our pandemic-learned habits of disengagement. Why should we care if nobody else does?

A few teachers have taken the approach of my 11th-grade calculus teacher. Having barely made it through pre-calculus, I decided to take the easiest calculus class I could. The class was primarily composed of students who had almost completely disengaged from school. But the teacher would come in every day yelling about how he loved math and loudly cracking jokes about anything and everything. The result was astonishing. Those disengaged students began asking questions, participating in group projects and enjoying calculus (somehow).

It wasn’t until I worked as a camp counselor the following summer, that I realized how he had worked such magic on us. It was a concept we call EGE: energy generates energy. Basically, if you are energetic enough about something, the people around you will follow suit. I found that if I was enthusiastic enough, campers could have a blast doing activities as mundane as standing on one leg. The same is true in school. Because my calculus teacher was so ridiculously enthused, the whole class was more energized to learn math.

Still, it is unfair to ask underpaid and burned-out teachers with a myriad of extra responsibilities to exhibit boundless enthusiasm. Many teachers teach five or six classes each day. Increasing pay would attract more teachers, allowing them to focus more energy on each student. Those teachers also need more administrative support. Because we don’t have materials as basic as beakers, I’ve spent high school science class doing online simulations in lieu of real labs. We need more hands-on learning opportunities that excite students. Instead, my school system bought us new smartboards.

As I prepare to graduate Friday, I see that our system has failed the class of 2024. That our school systems invest in shiny new electronics but leave us without basic materials demonstrates policymakers’ ignorance of this failure. Still, I believe that if educators are given the resources to employ camp counselors’ energy-generates-energy philosophy, we can get students excited about education.

Benjamin Handelman ([email protected]) is a member of the class of 2024 at Northwood High School in Montgomery County. 

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University of Chicago settles class-action COVID tuition lawsuit for $4.95 million

The suit, filed in 2020, claimed students were entitled to partial tuition refunds after the school switched to online learning during the covid-19 pandemic. those who qualify will receive at least $25..

University of Chicago students walk to and from the main quadrangle.

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The University of Chicago will pay $4.95 million to settle a class-action lawsuit filed by students and former students seeking refunds on tuition after classes went remote amid the COVID-19 pandemic.

The lawsuit was filed in May 2020 by former student Arica Kincheloe in U.S. District Court for the Northern District of Illinois, claiming that students were entitled to partial refunds of tuition because of remote instruction instead of in-person classes beginning in the spring quarter of 2020.

The suit also claimed a breach of contract and unjust enrichment by the university.

The settlement applies to all students and former students who were enrolled in any of the university’s undergraduate and graduate programs at any time between January 1, 2020, through the end of spring quarter 2020, according to court documents. Those who qualify will receive at least $25 from the settlement.

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“The university is proud of the rigorous educational experience and support it provided to students when it moved to remote learning for spring quarter 2020 in response to the COVID-19 pandemic,” the university said in a statement. “The university believes plaintiffs’ claims are without merit and looks forward to putting this matter behind us.”

The parties entered into a settlement agreement on Nov. 21, 2023, court documents state. The court granted preliminary approval of the settlement on Dec. 7, 2023. Final approval was granted after a hearing on May 23.

The settlement agreement “should not in any event be offered or received as evidence of, a presumption, concession or an admission of liability” on the part of the university, court documents state.

Similar lawsuits have been filed against other schools both in the city and in the rest of the country in the wake of the coronavirus outbreak.

A suit filed against DePaul University in 2020 was dismissed on Feb. 2, 2021, according to court records. The judge in that case ruled that the plaintiffs failed to provide evidence that the university promised its students that classes would be held on campus or in-person in its academic materials.

Earlier this year, George Washington University reached a $5.4 million settlement with former students alleging the school broke its contract with them over online-classes during the pandemic.

Cornell University reached a $3 million settlement with students in 2023 over a similar lawsuit.