In this section, we present and discuss the data from our survey regarding social differences in the learning conditions of Catalan children and the impact of these conditions on learning opportunities during lockdown. Inequalities in families’ economic, social and cultural capital impacted on student learning opportunities by different means, including school responses to the lockdown, access to digital facilities and the level of parental learning support. This section reviews how these factors are drivers of inequalities in the three domains of learning: formal, non-formal and informal.
Learning conditions at home: social and technological differences
Learning conditions at home differ on the basis of a number of variables. For example, the amount of physical space and access to technological devices both have an impact on the learning conditions of children.
Our survey included questions about the size of the household and the outdoor spaces available, to serve as indicators of the physical conditions of confinement. The responses showed that most homes of confined families had a balcony or other outdoor space/s. However, there were significant differences among residents depending on the size of the municipality (families living in cities had less access to outdoor spaces) and other social indicators, such as parental education attainment. For instance, 13% of families with an adult who had completed compulsory education did not have outdoor spaces, while this was only the case for 4% of households in which at least one adult held a university degree. Likewise, 45% of households in the poorest income quintile (Q1)Footnote 10 had less than 80 square metres of space, reducing to 14% in the case of the richest income quintile (Q5).
Students also had different internet connectivity conditions and unequal opportunities to access technological devices to carry out their schoolwork. Since we could only implement an online survey, we were unable to grasp the full extent of the actual digital divide. Data from the Catalan Department of Education estimate that there are currently approximately 55,000 school children without access to an internet connection (Vallespín 2020), which would situate the digital gap at between 10% and 15% of all children in the Catalan education system. Our survey revealed that 3.5% of our sample had only a mobile phone internet connection or no connection at all. Most families in our survey had access to a high-speed internet connection. However, there were important differences regarding the “possibilities of use” of technology. For example, 15.3% of respondents declared that they had access to a single device at home or only had access to a mobile phone. We calculated the number of devices per person and found that in 56% of cases there was less than one device per person. The digital divide can also be expressed in terms of access to devices based on the composition of the household. In our survey, 12% of households with two children had only one device available; 32% of households with three children had two or fewer devices available; and 48% of households with three children had three or fewer devices available.
Access to technology depends on the level of family income. While 25% of surveyed families in Q1 (the lowest income quintile) had access to only one digital device, for families in Q5 (the highest quintile), the corresponding figure was only 4%. Furthermore, while 20% of families in Q1 had access to four or more devices, this applied to 54% of families in Q5. Taking into account the size of the household, 71% of families in Q1 did not have access to one device per person. Among families in Q5, the number of households with less than one device per person reduced to 37%. Figure 1 shows the proportion of households for each income quintile that had access to one or more device per person. Differences are sorted by income, with an inequality factor of 2.5 between Q5 and Q1.
In addition, the unequal impact of the crisis on parents’ working situation also altered the social and psychological conditions that ensured an adequate learning process. Our survey revealed that before lockdown, 13% of adults were unemployed, while 80% were working full-time. When we asked about the impact of the COVID-19 crisis on their working situation, these figures changed dramatically: 23% of respondents indicated that they had lost their job. Of those who were still working, only 21.5% were able to go to work “normally”. The rest (39%) were working from home, either with the same schedule or with a more flexible schedule. Of those still working, 17% considered it likely that they would lose their job. Of those who were already or became unemployed, 50% knew that they were entitled to unemployment benefits, while the other 50% either knew that they were not entitled or did not know.
Schoolwork and opportunities to learn
Our survey included questions regarding how much time children invested in schoolwork every day since the beginning of the school lockdown, how frequent the contact was with their school and teacher/s, how often they received online teaching lessons, whether they had to complete specific homework tasks, and how often these tasks were reviewed and returned to children. Taking into account the intensity of all these tasks, we composed an index of opportunities to learn (OTL). To compose the index, which ranged from 0 to 100 points, we normalised indicators and aggregated (combined) frequencies. We only used this index for a subsample of the older children aged between 10 and 18, since assigned school tasks or online teaching were more unlikely for younger age groups.
In terms of the index, 28.3% of students had an OTL equal to 0, meaning that they dedicated less than one hour a day to school tasks, had almost no communication with teachers and did not have homework to do or to be reviewed. At the other end of the index, 7.7% of students had a maximum OTL of 100, meaning that they dedicated more than four hours per day to schoolwork, had frequent contact with their teachers and received regular feedback for school assignments. The majority (80.2%) of all surveyed students in this subsample had an OTL score below 60 points.
Interestingly, we found the OTL score to be positively related to a number of variables. Having greater access to digital devices, being enrolled in more advanced courses (older students had a higher OTL), being native to Spain or living in a higher-income household were all factors associated with higher OTL scores. Students enrolled in private schools, both independent and private subsidised ones, had significantly higher OTL scores than those enrolled in public schools. There are explanations for this difference. For example, the Catalan Department of Education announced that the first two weeks after the approval of the state of alarm would be a non-school period. Therefore, a significant number of public schools did not develop school tasks during these two weeks, waiting for new instructions from the department. Despite this announcement, private subsidised and independent schools did not stop their teaching activity. One of the plausible explanations for this difference lies in the economic dependency of private schools on fees. They needed to keep providing a service to users despite the exceptional circumstances.
Figure 2 shows the distribution of the OTL index across school sectors for different educational levels. The bar chart reveals strong differences by school sector for students enrolled in the last years of primary education and for those in lower secondary education. The chart also shows how students in vocational education and training (VET) had the lowest OTL of post-compulsory education.
We also found the OTL index to be clearly related to the level of parental education attainment and to family income. For instance, 49% of children in families from the richest quintile (Q5) had an OTL score of 80 points or higher. This reduced to 33% in the case of the poorest quintile (Q1).
The role of families in the learning process
The absence of schooling increases the importance of families as teacher substitutes in the learning process. Our survey included questions regarding whether adults in the family helped students in their school tasks during the relevant lockdown period. An initial remarkable result appeared in terms of gender: while 79% of female adults stated that they supported their children to do schoolwork, only 43% of male adults did.
As expected, gender differences were clearly observed, and family support was higher in the case of younger children. Figure 3 shows that for children undertaking primary education, the support of mothers who had completed compulsory education was comparable to that of mothers with higher educational (in Bourdieu’s terms) cultural capital. However, for students enrolled in lower secondary education, the differences increased dramatically: only 35% of mothers who had completed compulsory education helped with homework, while 48% of the most educated mothers did. Providing support for school tasks to students in post-compulsory education declined to close to 20% for all groups.
There are several reasons why support for schoolwork may not have been provided by adults in a student’s household. These reasons are remarkably different depending on the level of parental education attainment. In those households in our survey with children enrolled in lower secondary education, 92% of the families with an adult who had a university degree and who did not provide support for schoolwork argued that the child did not need it. This reason was only argued by 69% of respondents from those households with adults who had completed only compulsory education. In this case, a lack of knowledge was proffered as a significant reason for not giving support (by 28% of respondents), which reduced to 2% for those parents with a university degree. Differences in cultural capital are therefore reflected in the capacity and possibilities of families to help children with their school tasks.
In addition, (and not just in times of school closure) families’ cultural capital and everyday informal practices have effects on children’s learning experiences and opportunities. Interestingly, confinement, which maximises the interactive time between family members, provides ideal research conditions for assessing informal learning activities. Figure 4 reveals that in those households with children aged between 3 and 8, there were three activities in which social differences were especially acute. First, accompanying children in reading was more frequent by far in families with high cultural capital: 59% of families with an adult who had completed university studies responded that their children aged between 3 and 8 read with an adult every day. This reduced to only 37% in the case of families with an adult who had completed compulsory education. Second, differences were also visible in foreign language informal practices: 44% of families with an adult who had completed university studies responded that foreign language practice was done daily or several days a week, while this practice was carried out by only 36% of families with an adult who had completed compulsory education. Third, sporting activities were practised several times a week by 81% of families with university degrees and only by 66% of families with compulsory education.
By contrast, other activities were more frequent among families with lower cultural capital. The most relevant was playing video games: 37% of families with an adult who had completed compulsory education reported that their children of preschool age played video games every day or several times a week. This applied to only 21.5% of families with parents who had completed university studies. The differences were also significant in the frequency of watching educational television programmes (52% of households with parents who had completed compulsory education and who had children enrolled in preschool education reported that their children did so every day, versus 30% of parents with a university degree), and in following and carrying out educational activities available via social media. In such an extreme situation of school absence, it appears that families with less cultural capital made more use of external resources to support their children’s learning activities, while families with more cultural capital were more confident in their own abilities to respond to their children’s learning needs.
In the case of older children, the same differences were observed, although the gap increased in musical and other artistic activities and was less pronounced in playing video games.
Inequalities in after-school activities
Participation in after-school activities is a source of differential learning opportunities for children from different socioeconomic backgrounds (Bradley and Conway 2016; González Motos 2016; Lauer et al. 2003; Potter and Morris 2017). Our survey compared whether children participated in one or more after-school activities before and after the beginning of the lockdown. We found that the effects of COVID-19 on these kinds of activities have also increased the gap between socially advantaged and disadvantaged children.
Before lockdown, after-school activities were more frequent for students enrolled in primary education. This was particularly the case for children whose parent/s had completed a university degree (66%), compared to children from households with parent/s who had completed compulsory education (43%). This polarisation increased particularly for children enrolled in lower secondary education with at least one unversity-educated parent (81%) versus those whose parent/s had completed compulsory education (45%). We also found families’ economic, social and cultural capital to be associated with the number of after-school activities in which children participated. For example, for families with two children in lower secondary education, the average number of after-school activities for highly educated households was 3.3, compared to 1.5 for households with lower educational levels. Sports, foreign languages and artistic practices were the most frequently reported after-school activities. By income level, students in families in the lowest quintile (Q1) were more represented in sports and compensatory education activities,Footnote 11 while children from the richest quintiles were over-represented in foreign language and musical after-school activities.
As expected, we found that most after-school activities (70%) were interrupted during lockdown. However, economic and cultural inequalities were also visible in the probability of maintaining after-school activities despite the confinement. Figure 5 shows that children whose parent/s had lower educational levels already had lower participation in after-school activities before lockdown and were more likely to be unable to continue them after schools closed than children from families with higher educational levels.
There are two main reasons for this difference in after-school activities after the closure of schools. First, families with higher economic, social and cultural capital participated in activities that were more likely to continue online (e.g artistic activities, foreign languages), compared to the activities more commonly practised by families with lower capital (e.g. sports). Second, voluntary interruption of after-school activities was also higher among families with lower ecoomic, social and cultural capital, due to difficulties in coping with the costs during times of crisis. For instance, compensatory education activities – which could be undertaken online – were voluntarily interrupted by 25% of families who had previously engaged in them. This voluntary interruption was particularly high among children whose parent/s attained compulsory education (80%), compared to those whose parent/s had a university degree (62%).