Covid-19, school closures and educational inequities: exploring lived experiences

ABSTRACT

Background

Research examining the impact of the COVID-19 pandemic on students’ learning indicates that educational inequities have increased. To strengthen the provision of support for students going forward, and contribute to efforts to reduce inequity, there is a need to deepen understanding of how emergency remote teaching (ERT) is experienced by learners.

Purpose

This study sought to explore the lived experiences of junior secondary students in China during the COVID-19 pandemic through the lens of three different groups: teachers, students and parents. It aimed to investigate how factors around schools, teachers, parents and students might relate to matters of educational equity.

Methods

Participants were eight students with a mean age of 15.5 years, the students’ mothers, and ten teachers from different schools across three different provinces in China. They took part in semi-structured interviews in which they discussed their ERT experiences and perspectives. Interview data were analysed using a qualitative, thematic approach.

Findings

According to the analysis of participants’ perceptions, differences in access to school learning resources, and extent of support and guidance from schools were noteworthy factors in relation to educational equity. In addition to parental support, encouragement and individualised feedback from teachers mattered for students’ wellbeing and their studies. Furthermore, students’ motivation, self-discipline and capacity for self-regulated learning were considered to influence learning outcomes during ERT.

Conclusion

Our study underscores the need to provide additional targeted support to disadvantaged schools and students in times of educational disruption. It also highlights the importance of pedagogical support and guidance for all teachers, parents and students. Such provision might enhance students’ capacity for self-regulated learning, and equip teachers and parents with the skills needed to support children’s learning and wellbeing in challenging circumstances.

KEYWORDS:

• COVID-19 pandemic
• school closures
• educational inequity
• emergency remote teaching (ERT)
• China
• wellbeing

Introduction

As the number of countries implementing school closures during the COVID-19 pandemic reached its highest level during 2020, learning was disrupted for the vast majority of the world’s student population (UNESCO 2023a). However, school closures did not affect all children equally: children from low-income families were more likely to be excluded from online learning, due to insufficient internet access or the lack of digital devices (HRW 2021). It is evident that the economic impact of the pandemic on many people has been devastating. Millions of households have been pushed into severe poverty, and some of the poorest children might not be able to complete primary and lower secondary education (UN 2022). Concerns about increasing educational inequities during and after the pandemic have, therefore, grown (UN 2020; UNESCO 2023b; UNICEF 2020).

In this paper, we are interested in notions of equity and inequity in relation to education and learning disruption. We adopt the term equity rather than equality because equity places emphasis on principles of fairness and justice, whereas equality centres around the equal application, allocation, or distribution of resources (GSP 2016). According to the vision of ‘a just, equitable, tolerant, open and socially inclusive world in which the needs of the most vulnerable are met’ (UN 2015, 4), no one should be left behind, regardless of their background, ability or identity. As education is crucial for inclusive societies (UNESCO 2018), better understanding the potential factors contributing to educational inequity remains of paramount importance as part of efforts to counter disadvantage and support all students’ educational journeys.

Our study focuses, in particular, on students’ experiences of emergency remote teaching¹ (ERT) in China. At the beginning of the nationwide lockdown in February 2020, about 270 million Chinese students at all levels started learning at home (Xinhuanet 2020) and an emergency policy initiative aiming to integrate learning resources² and provide high-quality online education for students was launched (MoE 2020). However, disparities in income distribution and economic growth are evident between different regions of China (Han, Zhao, and Zhang 2016), meaning that students have differential access to learning resources. Hence, as in other countries and jurisdictions internationally, there have been concerns about the negative impact of the pandemic on educational equity, resulting from factors including disparity in ICT (Information and Communication Technology) resources, the quality of online teaching, students’ self-discipline, and family-related factors (Wang 2020).

Existing studies on ERT in China during the pandemic tend to be quantitative (Liao, Ma, and Xue 2022; Zhao et al. 2022). For example, Zhao et al’.s study (2022) explored the learning outcome divide between rural and urban students and indicated that intrinsic motivation and parental support were the dominant factors. Parental education was found to have enlarged the educational gap³ among junior secondary students (Liao, Ma, and Xue 2022). Qualitative research, exploring and investigating how educational inequities in learning outcomes among students might have been exacerbated by the pandemic, is more limited. This study aims to offer a contribution in this regard by presenting an in-depth exploration of Chinese students’ lived experiences during ERT, through the lens of teachers, students and parents. More broadly, it is hoped that the research may contribute to international efforts to inform the development of more resilient educational systems. In advance of presenting our study in more detail, we situate our work in relation to the relevant research and educational context.

Background

School closures and educational inequity

Equity in education may be conceptualised as having two dimensions. The first is fairness, which indicates that ‘personal and social circumstances such as gender, socio-economic status or ethnic origin should not be an obstacle to educational success’ (Field, Kuczera, and Pont 2007, 29). The second is inclusion, which implies, among other things, ‘a minimum standard of education for all’ (Field, Kuczera, and Pont 2007, 29). Due to the context of our study, we focus particularly on the inequities that arise when policies, programmes, practices, or situations lead to disparities in educational performance and learning outcomes. Since our study examines the influence of factors linked to schools, teachers, parents, and students on educational inequities, this section will focus on inequities associated with these factors.

Internationally, research examining the impact of the pandemic on learning provides many examples of how educational inequities have intensified. For example, Haeck and Lefebvre (2020) found that school interruptions in Canada had differing impacts according to families’ socioeconomic status. Further, Bonal and González’s (2020) study in Catalonia revealed that families where parents had lower educational attainment possessed fewer resources and had limited knowledge to support their children in school-related tasks. Another study (Gu 2021) indicated that students from urban areas in China had obvious advantages in accessing ERT at home over those from rural ones. In addition, a review of the evidence of the impact of COVID-19 on learning in England suggested that, whilst the attainment of all students was negatively impacted by the disruption, it was especially the case for students from disadvantaged backgrounds. Possible contributory factors for the increase in the attainment gap included variation in: support from parents; schools’ approach to and students’ responses to remote teaching and learning; and access to technology and environments conducive to learning (EEF 2022).

In this paper, educational opportunities are understood as ‘those opportunities that aim to enable individuals to acquire knowledge and certain skills, and to cultivate certain capacities’ (Shields, Newman, and Satz 2023). During regular school time, schools typically provide key aspects that are likely to support equal learning opportunities for students, such as safe learning environments and standardised curricula (Lezotte 2001). Sudden and unexpected school closures compromise these basic elements, potentially leading to situations where children and parents encounter wider variability in terms of the learning resources and support available (Blundell et al. 2020). As students from lower socioeconomic backgrounds are less likely to have access to additional activities and parental support at home, they might need to rely more on any assistance provided by their schools and teachers (Montacute 2020), in contrast with students from higher socioeconomic backgrounds. For example, findings from a survey of parents of 4 to 15-year-old children in England completed during the pandemic (Andrew et al. 2020) indicated that students from more affluent families had greater access to customised learning support (e.g. private tutors) and superior facilities at home for remote learning during school closures.

When schools closed during the pandemic, teachers all over the world had to suddenly engage with the implementation of ERT. Many felt underequipped and unprepared to suddenly use new teaching methodologies, needing support in how to deliver education online and to develop themselves professionally. However, the amount and the quality of training, resources and guidance varied greatly across schools, regions and countries. Those from disadvantaged schools and marginalised teachers may have not received such support (UN 2020). For example, only 50% of secondary teachers in sub-Saharan Africa received a minimum level of training in teaching, often not covering basic digital skills (UN 2020). Even in contexts with adequate ICT infrastructure and connectivity, many teachers may lack basic digital skills. Hence, there are considerable inequities among teachers as far as facilitating high-quality online learning is concerned (UN 2020).

Parents play a crucial role in children’s education, as parental engagement improves children’s wellbeing and confidence and is important for academic development as well (UNICEF 2020). Familial inequity means that students may be disadvantaged in their education because of their personal and familial circumstances. For example, some children may experience relatively limited educational support or encouragement from their parents, even if the parents have aspirations for their children’s academic success (GSP 2016). Familial inequities can intersect with socioeconomic inequities. We understand parental support as referring to any support that ‘affects children’s development, learning, and subsequent educational outcomes’ (IIEP-UNESCO, IIEP 2021). This includes not only direct support for learning but also indirect facilitating of factors such as health and children’s wellbeing (IIEP-UNESCO, IIEP 2021). Different levels of parental support entail how support may vary due to a wide range of reasons. For example, parents with different levels of education and from different socioeconomic backgrounds might provide different levels of support for their children (Bonal and González 2020). Children from lower socioeconomic backgrounds are more likely to lack parental support with their homework during school closures, and this is true not only in high-income European countries, but in low-income and upper-middle-income countries as well (EC 2020). For instance, following COVID-related school closures in the Netherlands, a large gap in parental support was found between secondary school students with higher and lower-educated parents. The lack of support is likely to have impeded the learning of children from disadvantaged families during this period (Bol 2020).

Furthermore, as many students move to online learning, access to information and technology infrastructure at home becomes increasingly important. There is significant variety in how students can access, navigate and use the internet and other new technologies, which might exacerbate educational inequities, too. Disadvantaged students are likely to be excluded entirely from online education and from their social network (Williamson, Eynon, and Potter 2020). For instance, a survey concerning 21 European countries showed that students from lower socioeconomic backgrounds were only half as likely to have access to the internet as their more advantaged peers (EC 2020). In some low-income countries, more than 90% of the poorest households do not have electricity (UN 2020). Compared to low-income households, those with higher incomes are able to afford better internet connections without compromising their spending on necessities.

Other home resources are of great importance to children’s education but are not equally available to all children (EC 2020). There are wide disparities in such home resources within and among countries. For example, in most European countries children from poorer households are more likely to lack reading opportunities and a quiet room (EC 2020). Another example is private tutoring, which might be an effective intervention for some children to reduce the impact of school closures on their learning. However, students from poorer family backgrounds are less likely to be able to access such support. This, too, can potentially lead to increased educational inequities (Montacute 2020). In terms of personal circumstances, students’ self-regulation is essential to the learning process, and motivation can have a pivotal impact on students’ academic outcomes (Zimmerman 2008). Trung et al.’s (2020) study further demonstrated that, during the COVID-19 pandemic, motivation for independent learning, self-regulatory learning skills, and consistent learning habits were very important for students’ learning experiences. Hence, differences in those factors might lead to inequities in learning outcomes.

Study setting

The Chinese educational system is state-run but has been increasingly decentralised in recent years (OECD 2016). The Ministry of Education is responsible for macro-level monitoring of the system, while county-level governments⁴ have primary responsibility for the governing and delivery of education (Central People’s Government of China 2005). The state provides nine years of compulsory education, from primary (six years in duration; for students aged approximately 6 to 12 years) to the completion of junior secondary education (three years in duration; for students aged approximately 12 to 15 years). According to the Ministry of Education, China has achieved universal compulsory education in just over 20 years (MoE 2018). Internationally, Chinese secondary education has been praised and has received much attention, due in part to findings from the OECD’s Programme for International Student Assessment (PISA), which measures 15-year-olds’ abilities in reading, mathematics and science. For example, in the 2018 PISA survey, Chinese students from Beijing, Shanghai, Jiangsu and Zhejiang scored higher in reading, science and mathematics compared with students in the other education systems that took part (Schleicher 2019).

However, it does not necessarily follow that all Chinese students have equal access to educational opportunities; providing compulsory education does not automatically lead to an even distribution of educational resources or equal access to high-quality education. Qian and Smyth (2008) concluded that disparities in access to education between rural and urban areas are the major cause of educational inequality in China. The government had been undertaking substantial measures to eliminate the urban-rural division, but possible corrective measures were not being taken to tackle such educational inequity (Yang, Huang, and Liu 2014). Furthermore, the household register system divides city and country, which has caused differences in educational resources and investment between urban and rural areas. This has led some research to conclude that ‘a relatively dominant class is enjoying greater educational opportunities and good quality educational resources⁵’ (Yang, Huang, and Liu 2014, 10).

Aiming to develop the quality of education and support innovation for several decades, the Ministry of Education has been integrating ICT into education at all levels. Considerable progress has been made in basic education, in terms of infrastructure construction, digital resources, teacher training and education for disadvantaged groups (Wang, Liu, and Zhang 2018). However, the level of ICT application varies greatly, due to uneven economic and educational development across different regions. Therefore, inequity exists, too, in the application of ICT to education. Schools in large cities have more ICT facilities than those in remote and rural areas (MoE Ministry of Education of the People’s Republic of China 2016). Many primary and secondary school teachers have not had sufficient training or lack sufficient awareness about integrating ICT in their teaching, and there are problems with equipment and funding in some areas (Zhang 2014).

The sudden outbreak of the COVID-19 pandemic has further highlighted the problem of educational inequities. When schools throughout the country were closed in early February 2020 (the closure time varied from about 1 month up to 6 months), the Chinese government launched an emergency policy initiative: ‘Suspending Classes Without Stopping Learning’ (MoE 2020). ERT was introduced to integrate national, provincial, and local school educational resources and provide free, selectable, and high-quality online resources for students. However, there were significant differences in technology infrastructure between regions, and network coverage was insufficient in remote areas and the effectiveness of using online resources varied between regions, schools, and subjects. Teachers’ experience with teaching online differed, and many had no experience at all. Their knowledge about information technology and their capacity to learn were different, as well. Furthermore, teaching or studying at home posed a challenge for both teachers and students (Zhang et al. 2020). All such difficulties could deepen educational inequity or lead to new educational inequities.

Purpose

The research question guiding our study was: From the perspectives of students, parents and teachers, how might factors related to schools, teachers, parents and students influence educational inequities among junior secondary school students in China during the COVID-19 pandemic? By adopting a qualitative approach based on semi-structured interviews with participants from different schools across three provinces in China, this study aimed to uncover to what extent these factors might result in intensification of educational inequities in learning outcomes. By capturing the perspectives of diverse stakeholders, we sought to offer detailed insights into the experiences of Chinese students.

Methods

Ethical considerations

Before the research was conducted, approval was obtained from the ethics review board of the researchers’ university, the University of Amsterdam (approval number 2020-CDE-12495). All participants were informed about the nature and purpose of the research, and informed written consent was obtained digitally from them prior to the interviews. The participating parents gave permission for their children to be interviewed and signed their children’s consent forms. During the interviews, participants were assured that they were free to stop taking part at any moment without giving a reason for doing so. Anonymity and confidentiality were maintained throughout the research process, data management and outputs. Data were carefully processed to remove any information that could potentially disclose the identities of the participants.

Data collection

Fieldwork for the study was carried out online between October and November 2020. Potential participants were contacted online by the first two authors, using an approach based on snowball sampling (Teddlie and Yu 2007). The COVID-19 pandemic made it impossible for the authors to travel to China for the fieldwork. Hence, an open invitation was sent to the authors’ contacts in China, via a commonly used messaging app. Ten teachers who were teaching junior secondary students and eight mothers whose children were studying at junior secondary schools agreed to participate in the research. Each of the eight mothers had one child taking part in the research. One teacher taught one of the student participants, while the other nine teachers had no connection with any of the participating mothers or students.

The participants were from seven different cities/towns of three different provinces across the country. Half of the students and their mothers were from a tier-1 city⁶; two students and their mothers were from a new tier-1 city and the rest were from a tier-4 city. The student sample included four girls and four boys, with the students’ mean age being 15.5 years. Two students were in Grade 7 (the first year of junior secondary school); one was in Grade 8; and the other five were in Grade 9. The mean age of their mothers was 43.5 years, and their educational backgrounds ranged from completion of primary school to a master’s degree. All were from the middle-income group⁷ except for one mother and child, who were from a high-income family. The teacher sample included three male and seven female teachers. Four teachers were from a tier-1 city, one from a new tier-1 city, two from two different tier-4 cities, and three from three different towns. The teachers’ mean age was 40.8 years, and the mean length of their teaching experience was 19.9 years. One of them had finished professional/vocational school, and the others had obtained either a bachelor’s or a master’s degree. The subjects that they taught included Chinese, English, mathematics, physics and chemistry.

The semi-structured interview protocol was developed by the authors. It was informed by the literature review and adjusted after two pilot interviews. Interview data were collected online via video calls conducted by the first two authors. As the authors and the participants were all first language Chinese speakers, the interviews were conducted in Mandarin, or in a Chinese dialect in cases where the participants were from the same region as the interviewer. All interviews lasted between 30 and 70 minutes and were audio-recorded with the permission of the interviewees. The interviews were conducted individually, with the exception that three students participated with their mothers present, as they wished to do so. The interviews commenced by establishing information about the participants’ backgrounds (including names, gender, age, grade, years of teaching, and educational background). The interview questions then focused on the four sets of factors: 1) schools (e.g. asking students What learning resources did you receive from school during school closure?); 2) teachers (e.g. asking students How did your teachers support you in your study?); 3) parents (e.g. asking students How did you get along with your parents?); 4) students (e.g. asking students How did you manage your study during the lockdown?).

Data analysis

All the interviews were transcribed verbatim in Chinese. The collected data were analysed thematically (Braun and Clarke 2006) and qualitative data analysis software was employed to facilitate the process. Initial codes were created and developed by the first two authors; these were based on the concepts and topics from the literature review. At this point, the first author read the transcripts of five interviews and labelled relevant content in the data, following the initial code list. Meanwhile, some new codes were added to the list, based on evidence emerging from the data. The codes were then cross-checked by the second author. During this process, the data were re-read and some codes were adjusted. A final list of codes was created through a process involving the first two authors arriving at a consensus. The first author continued coding, based on this list, until the data from all the other interviews were coded. Finally, all the coded data were checked by the second author again. Summaries were made for each theme, and main findings were established based on this analysis.

Findings

Using the methods set out above, we were able to gain detailed insight into the study’s research question. Specifically, it allowed us to further our understanding, from the perspectives of students, parents and teachers, of the relationships between particular factors and potential educational inequities. The findings presented below are organised based on the three major themes explored through the data analysis: (1) socioeconomic inequity; (2) staffing inequity; and (3) familial inequity. To give context and help illuminate key points, translated and anonymised quotations from the data are included.

Theme 1: socioeconomic inequity

It was evident from the analysis that schools varied significantly in the resources they offered to students and teachers. This encompassed learning resources for ERT, ICT resources, and activities to support students’ wellbeing. Findings related to these areas are presented in further detail in the paragraphs below.

In terms of learning resources for ERT, it was evident that all the schools where the participants studied or worked implemented ERT immediately, once the lockdown started. Students received two different forms of digital learning resources: live online lessons and recorded lessons. Compared with live online teaching and learning, participants felt that recorded lessons generated less satisfactory learning experiences. This appeared to be because such lessons were developed according to the average academic level of students within a district or city. For example, a teacher of chemistry explained that recorded lessons were not individualised to meet the needs of students with different academic levels, and reflected that there was no guarantee that students actually watched the videos. One of the mother’s observations is particularly relevant here, too:

Students couldn’t have interactions with teachers in recorded lessons. My daughter found such lessons too boring. A warm and lively learning atmosphere was more beneficial for her learning.

However, not all students received digital resources. For example, a teacher of mathematics explained that students were sent learning and assessment materials from teachers to their homes, with the expectation that parents would assist them in their studies.

It was evident from those who received live lessons that schools’ access to different online platforms could have an impact on teaching quality, as well. More than half of the schools accessed what were generally regarded as better-developed platforms, while other schools, mainly those from tier-4 cities and towns, used platforms that were recently developed in China. According to participants, more problems seemed to occur on the newly-developed platforms: for example, it was said that teaching and interaction were disturbed frequently when one such platform could not work as efficiently as it should do. Moreover, two teachers recalled that they had to postpone their teaching whilst their schools transitioned from using one platform to another, due to the associated high costs.

The analysis revealed that ICT resources was another significant subtheme. According to some teachers, the lack of ICT training or support, and a sense of unfamiliarity with digital resources, were the main obstacles to high-quality online teaching. However, it was considered that most of the schools where the teachers worked provided sufficient ICT support and training, which helped to optimise online teaching quality. For example, a teacher of Chinese recounted how the school created technical groups with ICT professionals who could assist teachers in improving their ICT and platform utilisation skills. Schools with limited training resources, though, found it difficult to train teachers, especially those without much ICT experience.

It was evident from the data that activities to support students’ wellbeing were provided, in some cases. Specifically, some schools created supportive communities and engaged students in various activities, such as online class meetings and mental health courses, which gave information about the virus and helped address students’ worries. As a Grade 9 student recalled:

Support from my school and my class was important to me during that time. It encouraged me to be positive and ambitious. It was a crucial time because I was in Grade 9. Such support helped me learn more during the school closure.

A few schools invited psychologists to give online lectures, and school psychologists provided consultancy services for students. However, although most of the schools emphasised the significance of the physical and psychological wellbeing of students, the analysis suggested that more than half of the schools where the teachers were working did not have such supporting resources.

Theme 2: staffing inequity

Most of the participants mentioned that their online classrooms consisted of 40 to 50 students. Some schools from economically disadvantaged areas arranged online lessons for a whole grade instead of one class. As one Grade 9 student observed, students had to attend lessons with more than 1,000 students from the same grade. Such large class sizes meant that it was not possible for students to have interactions with their teachers.

Instructional inequity was suggested by the data analysis, as there was evidently variation in the amount of content that teachers were able to provide in their courses, and the extent to which they were prepared to assist students in their studies. Some teachers, potentially due to the lack of remote teaching skills, required more time to plan and set up their lessons. This could reduce the amount of teaching content, especially if the time needed had to be balanced with family responsibilities. Consequently, some students might have experienced reduced levels of teaching and learning compared with others. The extent to which teachers were available to give feedback on students’ assignments, and respond to their questions, varied greatly, too. For instance, although most teachers were able to give timely feedback on their students’ assignments, a few teachers reviewed only parts of assignments, with one of the reasons being that it could be tiring to do this on phones or computers. In terms of responding to students’ individual queries, it was apparent from the analysis that some teachers devoted much time to it, as they recognised it as crucial for students’ learning. This sense is reflected in one mother’s observations:

My son’s teachers spent much time and effort replying to questions, and sometimes they stayed up quite late at night. They were in Grade 9 at that time, so his teachers were very supportive – they were always available on their phones for students’ questions.

Nevertheless, not all students considered that their teachers responded to individual questions, or gave timely feedback; hence, they felt that they experienced some difficulty in identifying problems with their own studying.

It was evident from the analysis that many students found teachers’ support and encouragement necessary and essential for their wellbeing, and that there were some activities to support students’ wellbeing. However, this was not invariably the case. Some teachers had limited contact with students regarding their mental health concerns. As a teacher of physics explained, students tended to prefer to talk to their class teachers about such problems. Comments from one of the mothers illuminate the reasons for some of the difficulties:

My daughter’s teachers had too many students. They taught four classes with more than 200 students. I am not even sure if they knew my daughter well enough. So, they couldn’t offer individualised suggestions.

It was clear that most teachers tried to offer as much support as possible in various ways, including, for example, sharing videos with students about how to relieve stress, talking to students regularly about their problems to help them release anxiety, or becoming personal mentors and being available for students who might be in need. For instance, as a teacher of Chinese explained:

We were all mentors for four to five students. We would call them regularly, and contact their parents frequently, so we knew if our students were in a good emotional state. We also wanted to let them know that we really cared about them.

Overall, most mothers and their children confirmed that their teachers’ encouragement and additional support were extremely helpful and meaningful for them.

Theme 3: familial inequity

The analysis identified several aspects of familial inequity that could have influenced students’ learning outcomes. These included home resources, parental support, and students’ self-management. Each of these subthemes is considered in turn below.

It was evident that the availability of home resources, such as physical space and access to technological devices, differed between students. Whilst many students had one or two digital devices (e.g. smart phones, tablets and personal computers), this was not the case for all. Moreover, some students did not have their own study space. Teachers reported being aware of students who did not have digital devices or the internet at home. As one mathematics teacher observed:

Some students were indeed from poor families who could not afford digital devices or internet. However, I do know some parents from better economic backgrounds, but they were not willing to invest in [their] children’s education. For example, they just did not want to spend money on digital devices for their children.

All the teachers agreed that parental support was one of the main factors that could help students achieve good learning outcomes. However, the level of engagement among parents varied widely. For instance, some parents provided direct support for children’s learning, including participating in all school lessons daily and actively seeking help from teachers. One Grade 9 student recalled the significance of receiving such support:

My mother often helped me when I had difficulty understanding the class content. She also encouraged me to participate in school projects. It was hard for me to do these alone, especially [when] I was not at school. But my mother helped me, sometimes technically, for example, making [electronic] presentations, and sometimes we did research together for my presentations.

The analysis suggested, though, that five out of the eight participating students were not supported in this direct way. Reasons for this included students’ own preferences for only asking teachers (rather than parents) for support, or mothers’ belief in their children’s ability to manage studies well on their own. Moreover, according to the teachers, the level of parental support could be related to parents’ educational background. For example, a teacher of chemistry felt that some parents from rural schools, who had themselves left school after completion of primary or secondary education, lacked motivation to support their children’s studies. However, it is important to note that, according to teachers, educational background was not always the determining factor. It was observed that some parents with relatively low educational levels played an active role in supporting their children’s studies: even though they might not be able to help with lessons, they would check if their children had finished their homework, and cooperated with their children’s teachers.

Similarly, it appeared from the data that parents’ capacity to provide support for their children’s mental health, maintain a good parent-child relationship and create a warm home environment influenced their children’s learning and their wellbeing. All the participating mothers emphasised the importance of such support for their children. Whilst parents’ and students’ viewpoints varied, most mothers felt they were able to have pleasant conversations with their children that helped them release their stress from studying, or encouraged them when they felt less motivated. Some mothers were especially proud of their relationships with their children, with one explaining how she supported her son:

I always accompanied my son by working next to him, and I think my attitude towards my own work had a good influence on him. When he saw me working attentively, he would do the same … so during the whole lockdown, he was quite healthy psychologically.

It was noteworthy that some of the teachers’ observations reflected a range of parent-child relationships. For example, teachers commented that, in their view, some parents managed to build up positive relationships with their children, whilst others were less able to do so. Teachers attributed this to reasons including parents experiencing stress and anxiety themselves, during the pandemic (which adversely affected the wellbeing of their children), and parents having exceptionally high expectations for their children’s academic performance but being unable to provide practical learning support.

Students’ self-management – i.e. the extent to which students were able to manage their studies for themselves, through exercising their self-regulatory learning skills and maintaining consistent learning habits – was another important subtheme in the data. The analysis suggested that most of the student participants felt they could manage their time well, follow teachers’ online lessons and make good study plans. These students all attributed their good learning habits to the guidance of the teachers before the pandemic, and their mothers agreed.

All teachers believed that students’ own ability to manage their studies was one of the most important factors which could cause inequities in learning outcomes. Specifically, teachers thought that those students who were able to regulate and manage their studies well coped with online learning successfully. They were able to continue learning as much, or even more, than they did at school prior to the school closures. On the other hand, teachers considered that those students who had not formed good habits before the schools closed encountered many difficulties in their studies. Moreover, some students appeared completely ‘lost’, because they were used to being guided by teachers at school every day.

Furthermore, half of the student participants, all from Grade 9, tended to feel motivated and able to concentrate on their studies because they were preparing for senior secondary school entrance examinations. It was evident, though, that other students experienced difficulty in concentrating. For example, one was distracted by and spent plenty of time on her phone, while her parents thought that she was focusing on studying. As her mother recalled:

We really didn’t know that she was playing games in her room. She always managed her studying by herself, so we never needed to worry about that. During the lockdown she was in her room alone. I only went in when she needed food. We thought she was studying hard.

Many teachers felt that some students lost motivation at home because of their compulsion to play computer games and be on the internet, as their parents were not aware that their children were only pretending to be studying. In cases where parents found out, there were difficulties. As a teacher of Chinese reflected:

I do know students who went crazy about online games. When their parents tried to get their phones away, they would threaten them, saying they would give up studying or even leave home if they did not get the phones back.

In contrast, the analysis makes clear that there were students who were more motivated and would actively contact their teachers to ask for advice. Hence, teachers were better able to support such students, according to their needs.

Discussion

Our study explored the experiences and perspectives of junior secondary students, their mothers and teachers in China during the COVID-19 pandemic. It probed the question of how factors related to schools, teachers, parents and students might lead to the intensification of educational inequities, and ultimately influence learning outcomes. Through fine-grained thematic analysis of the interview data, we investigated evidence related to socioeconomic, staffing and familial inequity. In this section, we consider the study’s findings and implications in relation to the broader literature context.

In line with previous research (Bonal and González 2020; Haeck and Lefebvre 2020), our participants considered that students might have learned less remotely in comparison with their learning during regular school attendance. Students and mothers believed that there were several factors that may have been involved: less motivation and concentration when studying alone at home; difficulty in identifying problems with their own studying without teachers’ help; a lack of interaction with, and encouragement from teachers; the absence of a stimulating learning atmosphere; and distraction by internet and phones. Teacher’s accounts drew attention to the significance of students’ self-regulated learning, motivation and discipline as key elements of success during ERT. They highlighted, too, the importance of appropriate teacher guidance and parental support.

Our analysis indicated that schools provided different learning resources and supporting activities, which resonates with other studies (Blundell et al. 2020; UN 2020). This reflects how inequities may arise when students receive different amounts or quality of support and guidance from schools. Whilst schools in certain cities were able to react swiftly during the pandemic, making the transition to ERT very smoothly, other schools, especially in rural areas, found that delivery of online learning resources was sometimes less effective. Another area of difference was the provision of activities to support students’ wellbeing (e.g. counselling services to students). The extent to which teachers had capacity to provide support to students appeared to influence students’ learning as well, according to participants’ perspectives. Our findings suggest, in particular, how teacher agency might have made a difference in their support for, and engagement with, students.

The identification of parental support as another factor relating to educational inequities links with earlier studies (EC 2020; Montacute 2020; UNICEF 2020). However, notwithstanding the connections evident between parental support, parents’ different levels of education, and different socioeconomic backgrounds (Bol 2020; Bonal and González 2020), it seemed in our analysis that the degree of parental support was not necessarily related to parents’ educational levels or socioeconomic backgrounds. It is worth noting that, in our study, most of the parents intimated that they trusted that their children were able to self-direct their learning. Thus, parents’ engagement, as far as offering direct support to learning was concerned, was limited, although it was recognised that such trust was sometimes not well-founded.

In terms of home resources, in line with other studies (EC 2020; Williamson, Eynon, and Potter 2020), teachers noted that the most disadvantaged students had severely restricted access to online learning resources because of the absence of internet or devices at home. Similar to Trung et al.’s study (2020), the students themselves considered motivation for independent learning and self-regulatory learning skills to be essential for their learning. However, it seemed that students of different ages and grades reported different experiences in terms of their self-discipline and motivation, with Grade 9 students displaying higher levels of motivation, in part because they were highly motivated to succeed in what was, for them, a key transition year.

Limitations

The strength of this study lies in the insights generated through a detailed, qualitative analysis of rich data from three different groups of participants. However, due to the study’s small sample size and scope, the findings cannot be generalised. Future research could consider using quantitative research methods to analyse data from larger populations to investigate the potential significance of the themes identified in this study more widely.

Conclusion

There is no doubt that the pandemic, coupled with ERT during lockdown, influenced the learning of different students in a variety of ways, contributing to potential inequity in learning outcomes. Findings from this small-scale, qualitative study provide valuable insight into the experiences and perceptions of teachers, students and parents coping with the challenges of ERT. They highlight the importance of support for disadvantaged schools and students during times of crisis, particularly in terms of the provision of learning resources and technological aid for teachers and students. The study also illuminates the crucial need for enhanced teacher education and development, which could enable teachers to better support students’ learning and welfare in remote situations. Equally, it suggests how parents may benefit from resources to support their children during ERT. Such support could enhance students’ capacity for self-managed learning, and better equip teachers and parents with the skills needed to support to children’s learning and wellbeing in challenging circumstances.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the Amsterdam Centre for Inequality Studies at the University of Amsterdam.

Notes

1. Whilst definitions of emergency remote teaching (ERT) vary, it is understood here as ‘a temporary shift of instructional delivery to an alternate delivery mode due to crisis circumstances’ (Hodges et al. 2020, 6).

2. Learning resources refer to any resource, whether in print or digital form, which supports and enhances teaching and learning, including online/open-access resources (UNESCO-IBE, UNESCO 2013).

3. The educational gap refers to the difference in learning outcomes among students.

4. The administrative divisions of China consist of several levels of government, including the provincial, prefectural, county, and township levels.

5. In this study, the authors used teachers’ educational background as an indicator. ‘Greater educational opportunities and good quality educational resources’ refers to more teachers with a college education.

6. There are 338 Chinese cities at or above the prefectural level, which are classified into 6 tiers: tier 1, new tier 1, tier 2, tier 3, tier 4, and tier 5. This tier system represents the level of development, with tier-1 cities representing the most developed areas of the country.

7. For a typical three-person household, a yearly income of between 100,000 to 500,000 yuan (figures quoted from the website of the National Bureau of Statistics www.stats.gov.cn [Director of the National Bureau of Statistics Answers Reporters’ Questions on the Performance of the National Economy in 2018; January 21, 2019.]).