The role of working mothers and mothers’ education in children’s education during the COVID-19 pandemic in Indonesia

ABSTRACT

This study aims to analyse the role of mothers’ education and employment status on children’s education during the COVID-19 pandemic in Indonesia. Using 2021 data (and 2018 for comparison) from the National Socio-Economic Survey (SUSENAS), the results of a logit regression showed that mothers’ education and mothers’ employment status generally had a positive and significant effect on children’s education during the study period in three categories of education, i.e. primary education, junior secondary education, and senior secondary education. This study also found that children had a lower probability of being able to join education during the COVID-19 pandemic compared to normal conditions. This study has implications for the need for educational policy, including the development of informal educational programs, as well as ease of access for mothers to enter the labour market.

KEYWORDS:

• Mother’s education
• working mother
• children’s education
• COVID-19 pandemic
• Indonesia

Introduction

The COVID-19 pandemic has caused various countries, including Indonesia, to experience difficult situations. The pandemic has had a direct impact on not only health but also other aspects of life, such as economic and social aspects, including education. From an economic perspective, the existence of the pandemic has caused the mobility of goods and services to become limited and disturbed many economic activities. An implication of this condition has been a decline in economic growth in regions which experiencing the COVID-19 pandemic (Chaplyuk et al., 2021; McKibbin & Fernando, 2020).

In terms of education, several school closures were carried out as part of the effort to contain the spread of the COVID-19 pandemic, which apparently had an impact on millions of students (UNICEF, 2021). Virtual (online) learning then become an alternative and was required for all levels of education ranging from primary school to university level. However, the learning process did not go smoothly. Difficulties were felt by numerous students, especially those who were poor and those living in remote areas. These difficulties were particularly due to limited internet access and the low availability of devices (Karana, 2021; Sifat, 2021). These children were also burdened by the economic background of their families, which forced some of them to drop out of school and help their parents with work (UNICEF, 2020).

These challenges have been well documented, in both high- and low-income countries. In Bangladesh, children have to drop out of school because they have difficulties to pay school fees as a result of their parents losing their jobs and losing sources of income during the pandemic (Sifat et al., 2022). Similar situation also applies in the case of Pakistan (M. J. Khan & Ahmed, 2021), United States (Dorn et al., 2020), in Japan (Isha & Wibawarta, 2023), and several other countries (Azevedo et al., 2021). However, the effect will be more profound in low-income families with greater learning loads and higher dropout rates (see for examples Kuhfeld et al., 2020; Chetty et al., 2020; Rogers et al., 2020; Chen et al., 2020).

Data from the 2021 National Socioeconomic Survey (SUSENAS) of Indonesia show that school of participation of children decreases particularly for primary school, while for junior and secondary education continued to increase slowly during the pandemic (Figure 1). However, the school participation is still relatively low for senior secondary education, suggesting there is a significant drop out rate during the transition from junior high education to senior high education.

Figure 1. School participation of children for different ages/school levels (%), 2018 and 2021.

Source: Central Board of Statistics (BPS)

The role of the parents is considered important in overcoming problems of education drop out among children. One of the most important aspects of education is the role of the mother. Compared to that of the father, the impact of the education of the mother is higher, suggesting that the higher the education attained by the mother is, the more beneficial this attainment is for the children’s academic achievement (Cooksey et al., 2009). Several studies have also found that the influence of a mothers’ education on a child’s schooling is stronger than that of the fathers’ education (Leibowitz, 1974; Murnane, Maynard, & Ohls, 1981; Ramadhani, 2019). The main potential reason is that mothers are more likely to spend more time with their children than fathers, which means that the mother’s education is more important; therefore, the mother’s education has a stronger effect on children than the father’s education. This outcome is also associated with good psychological conditions of children, as well as with certain cognitive aspects being supported by the mother rather than by the father. A mother will have a better understanding of her children’s educational requirements if she has a high school education (Datcher-Loury, 1988). If the mother has a higher education, then the mother will also better understand the educational needs of her children. Therefore, highly educated mothers will support decisions for their children and have a major impact on the level of education of their children in the future.

However, according to the SUSENAS, many mothers are not only stay at home with their children, but also decide to work to help the welfare of their family. Female labour force participation rates in Indonesia experiencing an increasing trend. In 2021, the percentage was 53.34%, which is the highest rate compared to the previous period since 2010 (see Figure 2). The main reason is the need to raise the family’s income (Kristiani et al., 2022). In addition, digital technology plays a very important role, especially for women entrepreneurs. Women who have limitations due to their dual roles as wives and/or mothers (which are often found to be an obstacle to their business activities) is highly supported by the internet (Rehman & Roomi, 2012). A study conducted by Mason et al. (2008); and Dettling (2017) also found that the availability of internet-based connectivity is one of the factors in the increasing number of women who are self-employed and working from home. In addition, Pratomo (2017) showed that education might affect many modern women who are working outside the home in addition to running a household.

Figure 2. Female labour force participation rate in Indonesia 2010–2021.

Source: Central Board of Statistics (BPS)

Debates about the benefits and costs of working mothers having children frequently arise from several studies. A study said that working mothers tend to be less disciplined and less self-assured, and they might have some health issues (Lei et al., 2018). With regard to children, these factors result in the disruption of the educational process (LaRocque et al., 2011), the emergence of negative behaviour, decreased test and exam scores at school (Lei et al., 2018), and decreased academic and non-academic achievements (Dunifon et al., 2013). This negative impact is a strong predictor of a child’s future well-being (McMullen et al., 2020; Rozental et al., 2018).

On the other hand, Purmini (2016) indicated that working mothers are crucial to addressing the issue of school dropout in the case of Indonesia, because working mothers can support the education of their children and enhance the households’ economy. Sofa (2019) also asserted that working mothers’ positive effects on children’s welfare outweigh the risks. Among these positive effects are also increased opportunities for higher education and children’s educational attainment, such as entering universities.

Recently in response to the COVID-19 crisis in education sector, several studies have examined the impact of maternal education and maternal employment on children’s education in various countries. Research conducted in China indicated that highly educated mothers have a positive impact on their children’s education, particularly during the pandemic (Lau et al., 2021). Similar findings were observed in Bangladesh (Sifat et al., 2022). Furthermore, a study in Pakistan found that parents’ educational status explained that educated mothers contribute more to their children’s education than educated fathers (Idris et al., 2020). Similar patterns were found in India (M. A. Khan et al., 2021) and China (Lau & Ng, 2019). Studies from other countries, such as the United States, reported that the reduction in maternal employment during the pandemic resulted in a significant increase in school dropout rates, an unprecedented occurrence (Landivar et al., 2023). A similar trend was identified by Afridi et al. (2016), where the participation of working mothers in rural India positively influenced the likelihood of children attending school and had implications for their educational attainment. Furthermore, the support from Brauner-Otto et al. (2022) highlighted that working mothers in Nepal, particularly those in stable employment positions, motivate their children to pursue higher education and aspire for better job opportunities.

This study focuses on the role of the mother because several studies have stated that the preferences of mothers and fathers are different, with mothers being more likely to spend their income on their children. Thus, the effect of the mother’s income will be greater than that of other household incomes, similar to the greater health or nutrition benefits related to the effect of the mother’s income (Glick & Sahn, 2000). In line with this, Duraisamy (1992) found that the probability of a child being enrolled in school (as well as receiving treatment and care) is positively related to the mother’s ownership of assets. Similarly, Thomas (1990) found that the share of the household budget for education, health, and housing increases with the share of household income under the mother’s control. It would also be interesting to include the current pandemic factor as a comparison variable in cases where pandemic-related policies might affect working mothers.

Literature review

The determinants of children attending school in developing countries comprise an interesting topic. However, as there are differences in the positive and negative impact results, there is no definite conclusion. Moreover, this study aims to complement the existing knowledge in this regard. Studies in several countries have been carried out by researchers, including Banzragch et al. (2019), who stated that the higher the mother’s education is, the higher the education level of their children will be. A study by DeGraff and Bilsborrow (2013) in the Philippines also stated that the higher education of a mother has a similar effect on her children, not only because it reflects economic status but also because of the educational interests of her children. In addition, research conducted in China indicated that highly educated mothers have a positive impact on their children’s education, particularly amidst the pandemic during school closures and home-based learning (Lau et al., 2021). Similar findings were observed in Bangladesh (Sifat et al., 2022). This is supported by Datcher-Loury (1988) that highly educated mothers significantly enhance their children’s duration of schooling. This is mainly because parents from higher education backgrounds tend to have higher educational expectations for their children (Davis-Kean, 2005; Mello, 2009). However, Behrman and Rosenzweig (2002) found that increased maternal schooling led to decreased parenting time. Therefore, it can be said that an increase in the mother’s schooling does not benefit the child’s schooling effect, while such a benefit is possible for other increases.

The empirical analysis of working mothers’ and children’s education also faces differences of results. Among the related studies is research conducted by Landivar et al. (2023) in the United States, reported that reduced maternal employment during the pandemic has led to a decrease in the number of children continuing their education, with this decline being the most severe compared to previous years. Another study from Afridi et al. (2016), which aimed to identify shifts in rural women’s participation in the labour market and their impact on their children’s educational outcomes. Using an OLS regression, it was found that the participation of mothers in the workforce has a positive effect on the probability of their children attending school and the time their children are at school, which of course has implications for their children’s educational attainment. On the other hand, this study found evidence showing that the positive impact of maternal participation at work could be caused by an increase in the mother’s position in decision-making within the household. In line with this, a study conducted by Azizah and Salam (2022) mentioned that the mother’s decision-making in the family affects their opportunity to work.

The underlying mechanism emphasizing of the importance of the education of mothers and working mothers explained that the contribution of working mothers supports the view that finance has a significant impact on children’s educational attainment. Increasing the family’s fixed income through increasing parental education will also have a positive impact on children’s education, especially for girls (Chevalier et al., 2013).

Several studies regarding household mechanisms during an economic downturn are also related to this study. The encouragement of women to either join the workforce or become more actively involved in income-generating activities within the family is being investigated as a way of offsetting lost family income. This requires women to care for younger children while engaging in other household responsibilities, perhaps at the expense of their attendance at school. For example, Moser (1992) reported that women in Ecuador, are more likely to enter the workforce in response to economic downturns and if they have a higher number of daughters. These results suggest that girls’ school enrolment, or at least their ability to do schoolwork, is lower than that of boys. Additionally, in Ecuador, according to an interview conducted by Rodriguez (1994), female students fall victim to financial difficulties because when their mothers have to spend time at work, they are required to do more work at home.

Other studies conducted in Latin America and elsewhere have found that women and girls spend more time on household chores than boys during periods of severe economic recession and that girls’ access to education may be restricted. Therefore, socioeconomic factors affect the level of school participation and children’s academics (Zhan & Sherraden, 2003; Bhat et al., 2016; Faraz & Noor, 2019; Ghaemi & Yazdanpanah, 2014; Gobena, 2018).

These differences, in turn, can make it difficult or impossible for girls to continue their studies. In principle, if parents value their daughter’s education highly, they can hire domestic help or turn to institutional childcare sources to allow their daughter to spend time in school. However, poor families are unlikely to be able to use these alternatives; furthermore, the reduction in their consumption of other goods and services will also be a choice; in general, these families do not have access to credit markets that would allow them to make investments in schools without sacrificing their current consumption. Therefore, as emphasized in the introduction section, for most households, with regard to the mother’s education, decisions about the mother’s employment, childcare, and schooling are closely related; these results ultimately have the potential to generate debate, as previous research has been done.

Research method

The data used in this study are sourced from the National Socioeconomic Survey (SUSENAS), which was conducted in March 2021 and compiled by the Central Board of Statistics (BPS). In addition, the 2018 SUSENAS is used as a comparison as it provides data collected prior to the pandemic (the normal condition). The SUSENAS in practice presents individual and household information collected throughout Indonesia, which contains sociodemographic, educational, employment, health, technology utilization and other social characteristics of more than 240,000 individuals. SUSENAS, covering households across 34 provinces in Indonesia. This survey, is a large scale nationally representative data survey that allows one to draw inferences with confidence about household and individual behavioural. SUSENAS is a microdata set specifically designed to provide an accurate representation of the demographic composition of the entire Indonesian population. The utilization of extensive sample sizes in SUSENAS enhances the level of representativeness, ensuring a more robust depiction of the population. The sampling technique used by SUSENAS is the Stratified Random Sampling based on census blocks in each district/city in Indonesia. From more than 700,000 census blocks, 40% of the census blocks were taken using a probability proportional to size (PPS) method using the size of the number of households resulting from the 2010 Population Census in each stratum at district levels (Amelia et al., 2022). Relating with this study objectives, the sample in this study included boys and daughters in Indonesia who still lived with their birth mothers or mothers who were aged 7–18 years (primary school until senior high school aged) at the time of the survey.

The logit regression was used to examine whether the education of mothers and working mothers played a role in their children’s education during the COVID-19 pandemic in Indonesia. The choice of logit regression is based on several advantages of the model, including the non-linear relationship between the probability values and X, the absence of normality assumptions, and the ability to incorporate as many independent variables as necessary according to the theory being tested in this research (Gujarati, 2013). Compared to other method such as probit regression, it basically provides similar result, while using Linear Probability Model (LPM) which uses the Ordinary Least Square concept will result in the emergence of abnormal error distribution problems and heteroscedasticity violations.

The dependent variable then was binary, namely, if children were either attending school (school-age children who are at school during the survey) or not attending school (school-age children who were no longer continuing their studies during the survey). The logit regression is estimated in three different models separately, namely, (1) children at the primary education (7–12 years old), (2) junior secondary education (13–15 years old) and (3) senior secondary education levels (16–18 years old), expecting that the results might be different across different levels of education.

There were two main independent variables used in the analysis as follows:

• mother’s education, which was divided into 4 categories of dummy variables (mothers have a university education, a senior high school education, a junior high school education, or a primary school education); and

• working mothers as a dummy variable, namely, either a working mother or a non-working mother.

The control variables included several individual and household characteristics as follows:

• personal characteristics of the mother, including age (and age squared) and marital status;

• personal characteristics of children, including the sex of the child (girls or boys); and

• household characteristics, including area of residence (urban/rural), total spending per capita, total assets, area of island of residence (Sumatra, Java, Kalimantan, Bali), and official status level of the COVID-19 pandemic of the provinces from the Indonesian government on March 2021 (high level or low level) based on using epidemiological indicators, public health surveillance, and health services.

Table 1 presents summary statistics for the main variables of children’s education

Table 1. Summary statistics.

		2021			(2018)
Variable	Type/Description	Obs.	Mean	Std. Dev	Obs.	Mean	Std. Dev
Dependent Variables
Children at Senior Secondary School (16–18)	dummy (1: attend the school)	75,470	0.577	0.494	68,662	0.593	0.491
Children at Junior Secondary School (13–15)	dummy (1: attend the school)	61,540	0.757	0.428	61,767	0.809	0.392
Child at Primary School (7–12)	dummy (1: attend the school)	104,277	0.921	0.268	120,734	0.905	0.306
Independent Variables
Mother has University Education	dummy (1: graduated from university)	264,765	0.094	0.291	297,916	0.080	0.271
Mother has Senor Secondary Education	dummy (1: graduated from Senior Secondary Sch,)	264,765	0.254	0.435	297,916	0.221	0.415
Mother has Junor Secondary Education	dummy (1: graduated from Junior Secondary Sch.)	264,765	0.197	0.397	297,916	0.198	0.398
Mother has Primary Education	dummy (1: graduated from Primary School)	264,765	0.421	0.494	297,916	0.435	0.495
Working Mother	dummy (1: working)	264,765	0.454	0.498	297,916	0.443	0.496
Mother’s Characteristics
Mother’s Marital Status	dummy (1: married)	264,765	0.919	0.273	297,916	0.931	0.253
Mother’s Ages	Continuous	264,765	43.128	7.690	297,938	41.610	7.922
Mother’s Age Squared	Continuous	264,765	1.919.209	6.865.737	297,938	1.794.225	6.858.609
Children’s Characteristics
Girl	dummy (1: girl)	264,765	0.471	0.499	297,938	0.467	0.498
Household Characteristics
Urban/Rural	dummy (1: urban)	264,765	0.420	0.494	297,938	0.416	0.493
Per Capita Expenditure	log per capita consumption expenditure	264,765	1.110.687	957.628	297,938	979.948	838.199
Log of Assets	Continuous	264,765	3.200	1.909	297,938	3.001	1.997
Sumatra	dummy (1: live in Sumatra)	264,765	0.332	0.471	297,938	0.316	0.465
Java	dummy (1: live in Java)	264,765	0.262	0.439	297,938	0.239	0.426
Kalimantan	dummy (1: live in Kalimantan)	264,765	0.102	0.303	297,938	0.099	0.299
Bali	dummy (1: live in Bali)	264,765	0.018	0.136	297,938	0.017	0.128
Covid-19 Level	dummy (1: high level)	264,765	0.117	0.321

Main results

The results of the logit regression are presented in Table 2. Based on the results, the mother’s education shows a positive effect on children’s education, particularly for primary school education. There is a significant ranking of children’s education, reflected by an increase in the coefficient, from 0.002 for mothers with primary school education to 0.035 for mothers with university education in 2021, while in 2018, the coefficient increases from 0.003 for mothers with primary school education to 0.056 for mothers with university education. This finding is based on the fact that mothers who have a university education want their children to have an education that is also at least as high as theirs, indicated by positive effects in all children’s education for mothers who have a university education. Therefore, in other words, we can say that the opportunity for children to obtain higher education will be greater when the mother’s education is also high.

Table 2. Logit regression results.

Dependent Variable : Education Children (1: Attend School, 0: Not Attend School)	2021			(2018)
	Children in Primary School (7–12 years)	Children in Junior Secondary School (13–15 years)	Children in Senior Secondary School (16–18 years)	Children in Primary School (7–12 years)	Children in Junior Secondary School (13–15 years)	Children in Senior Secondary School (16–18 years)
Mother_University	0.035***	0.165***	0.174***	0.056***	0.140***	0.241***
Mother_Senior High School	0.033***	0.119***	−0.001	0.051***	0.130***	0.043***
Mother_Junior High School	0.023***	0.046***	−0.074***	0.038***	0.048***	−0.041***
Mother_Primary School	0.002*	−0.017**	−0.075***	0.003**	−0.013***	−0.058***
Working Mother	0.006***	0.022***	0.039***	0.005***	0.010***	0.032***
Mother’s Marital Status	0.019***	0.067***	0.049***	0.026***	0.045***	0.064***
Mother’s Ages	−0.008***	−0.036***	−0.065***	−0.013***	−0.027***	−0.072***
Mother’s Age Squared	0.000***	0.000***	0.001***	0.000***	0.001***	0.000***
Girl	0.023***	0.088***	0.085***	0.026***	0.056***	0.068***
Urban	0.008***	0.030***	−0.003	−0.003***	0.013***	−0.029***
Per Capita Expenditure	0.003***	0.019***	0.018***	0.004***	0.009***	0.021***
Assets	0.004***	0.015***	0.012***	0.003***	0.013***	0.009***
Sumatra	0.004***	−0.004	−0.064***	0.006***	−0.036***	−0.016***
Java	0.003***	−0.075***	−0.125***	0.004***	−0.099***	−0.050***
Kalimantan	−0.008***	−0.032***	−0.085***	−0.013***	−0.060***	−0.022**
Bali	0.012***	−0.071***	−0.023	0.008***	−0.011	−0.029*
Covid-19 Level	−0.006***	−0.018***	−0.037***	-	-	-
Constant	0.971***	0.803***	0.605***	0.955***	0.871***	0.605***
No. Observation	104,277	61,540	75,470	120,727	61,763	68,655

***p<0.01, **p<0.05, *p<0.1.

This result is supported by previous evidence for Indonesia showing a significant correlation between parents’ educational background and their children’s educational attainment (Hertz & Jayasundera, 2007; Mare & Maralani, 2006). Banzragch et al. (2019) conducted research in several other countries and stated that the higher the mother’s education is, the higher the education level of their children will be. A study by DeGraff and Bilsborrow (2013) conducted in the Philippines also stated that the higher education of a mother has a similar effect on her children. According to Chen et al. (2020), during the pandemic, a mother’s higher education resulted in a 53% increase in their children’s education being continued at the next level.

In the pre-pandemic period (2018), all of the coefficients for mother’s education are greater than the pandemic period (2021). This outcome generally shows a decline in the probability to achieve higher education during the pandemic. For example, mothers with a senior high school education level showed positive results supporting their children to achieve the same senior high school level of education during the pre-pandemic, but these results were not significant during the pandemic.

Mothers with an education at the junior high school level showed positive results regarding their children’s school participation at the primary and junior high levels, but these effects are negative for children at the senior high school level. This means that mothers with a junior high school education level are not generally able to increase their child’s chances of continuing their education at the next level. During the pandemic, the possibility of children dropping out of school at the high school level was even greater (−0.074 vs 0.041). These results indicate that children whose mothers have a low level of education level are more likely to have children whose education level is also low. This is also in accordance with the statement made by Nielsen et al. (2006) that there are genetic factors in children’s education that are rooted from the mother’s educational background.

Mothers who have a primary school education level showed that they were not able to improve the chances of their children’s education continuing at the next level. The effect of this negative coefficient is also greater than that of mothers who graduated from junior high school. This means that it is increasingly difficult for children to continue their education in high school if their mother only has a primary school education (the lowest level of education). Therefore, it is necessary to have other supporting factors, both external and internal, that can help these children to be able to continue their education to a higher level. Such support should be expanded, similar to the program offered by the government, namely, 9 years of compulsory education.

This is consistent with the finding of the previous analysis, namely, parents with a primary school education level (lowest educational level) usually have lowest incomes or lowest economic status. Therefore, children from poor families may find it more beneficial to go to work than to school. Baxter (2002) also stated that mothers with a primary school education level tend to have difficulty sending their children to a higher level of education.

Although this study has not compared the effect between mother and father, several authors have found that the influence of mothers’ education on a child’s schooling is stronger than that of the fathers’ education (such as (Idris et al., 2020; M. A. Khan et al., 2021; Lau & Ng, 2019). Mothers spend more time with their children than fathers, which means that the mother’s education is more important; thus, the mother’s education has a stronger effect than the father’s education. The independent effects of a mother’s education are generally related to the mother’s upbringing at home.

Regarding the working status, the results show that working mothers have a positive effect on children’s chances of going to school in Indonesia. These results show that the chances of children going to school when mothers work are greater than the chances of children going to school when mothers do not work. The coefficient is higher, as is the increase in the level of education of children. This outcome reflects the increased efforts of working mothers to increase the level of investment for their families, which is related to better children’s educational outcomes. This study is also supported by the findings of Sofa (2019) and Wertheimer et al. (2008) regarding the low risk of working mothers and the associated high benefits related to their children’s education. The same finding was made evident in Indonesia by Dervisevic et al. (2021), which the authors stated is because mothers’ work does not seem to have a negative impact on child development processes (Del Boca et al., 2016). The study also found that the relationship between working mothers and children’s education becomes even greater when children are teenagers. This finding is reinforced by the research of Azizah and Salam (2022), which states that working mothers have a positive effect on children’s education, both in the short and long term.

Even though the results for both during and before the pandemic had no difference in sign, the coefficient found for during the pandemic was larger than that found for before. This means that the effect of working mothers during a pandemic on increasing their children’s participation in school is greater than that before the pandemic in all educational levels. This is potentially related to the family’s economic conditions, which more like to be decline during the pandemic.

Other discussions

The marital status of the mother was found to have a positive impact on children’s chances of going to school at the primary, junior high and senior high school levels both during the pandemic and before the pandemic. This indicates that the presence of intact parents in the family can increase significantly their children’s educational participation. A study by from Cid (2012) also found that married parents can reduce the dropout rate in their children’s education. Children from single-mother households or mothers with the head-of-family status have lower probability to attend school.

The results of the variable for mother’s age showed that the influence of mother’s age has a negative effect on children’s educational participation. This is based on the fact that older mothers are no longer productive enough to work and meet their children’s education costs. In addition, it is based on the roles and responsibilities that children of older parents must take over to provide for their families (DeGraff & Bilsborrow, 2003; Ketterlinus et al., 1991).

Meanwhile, the variable for mother’s age squared showed positive and significant results at all educational levels. This is potentially because as mothers get older, the attention she gives to her children decreases. Therefore, older mothers tend to give full responsibility to their children; they are considered adults and have freedom for themselves. Therefore, they can make school decisions themselves; thus, their chances of going to school will be greater.

Female children were found to have a greater chance of participating in school than boys. The existence of a learning policy from home during the pandemic enabling women to remain present in the learning process, while boys are more likely to find work outside the home and therefore leave school. As shown in the study of Grewenig et al. (2021), during the COVID-19 pandemic, especially in Germany, girls showed a greater percentage of attending school than boys. Recently, Psaki et al. (2018) examined low- and middle-income countries and found that girls’ education is more advanced than that of boys. Who examined Bolivia, and Tansel (2002), who examined Turkey, found evidence that mothers’ education is more important for girls than for boys.

For the ‘city’ variable, the results show that there are differences at each level of education. At the primary school level, during the pandemic, positive results are shown for children’s chances of going to school. In accordance with the research of Saha (2013), Wieser et al. (2020), and M. A. Khan et al. (2021), living in urban areas was shown to have a positive correlation with children’s educational participation. However, for senior high school students during the pandemic, the results show no significant effect. This indicates that during the pandemic, children who attend school at the senior high school level have the same opportunities, access, and barriers to attending school, regardless of whether they live in urban or rural areas. The per capita expenditure variable shows a positive influence on opportunities for children’s education participation. This result is supported by the findings of M. A. Khan et al. (2021), who stated that higher per capita household costs will increase children’s school participation particularly in primary schools. This argument is further strengthened by Nurrika et al. (2020), who stated that if the level of household consumption is higher, then the education of the children tends to be higher. Furthermore, ownership of assets shows a positive effect on children’s opportunities. The results of a study from Cid (2012) suggest that asset ownership has a positive influence on children’s educational outcomes.

To compare each region of Indonesia, this study also tries to include dummy variables for the islands of Sumatra, Java, Kalimantan and Bali. The results show that households being located on the islands of Sumatra, Java and Bali has a greater influence on increasing enrolment in primary school for their children. This is because these three islands already have advanced economic growth and development.

The COVID-19 level variable (COVID-19) shows a negative result, which indicates that in areas greatly affected by COVID-19, children experienced reduced chances of going to school. This is in line with research by Aiano et al. (2021), who stated that the COVID-19 pandemic had an impact on reducing children’s participation in school. This is also consisted with the information provided by UNICEF Indonesia, which has stated that the COVID-19 pandemic is the main factor causing children to drop out of school. The increase in the number of children who are no longer in school or dropping out of school has been triggered by a decrease or even loss of family income due to the impact of the pandemic (UNICEF, 2021).

Conclusions

Low levels and low participation of education are still crucial problems in developing countries, and Indonesia is no exception. In particular, the COVID-19 pandemic has increasingly impacted the educational situation. This study tries to determine the effect of mothers’ education and working mothers on children’s education during the COVID-19 pandemic. The results conclude that the education provided during a pandemic tends to be worse for children’s educational participation in school. This is due to the economic crisis caused by the pandemic, which causes many mothers with a below (or even a high) school education to not be able to sufficiently meet the needs of their families; this means that their children potentially have to leave school and join the job market. Specifically, the results showed that mothers’ education, in general, positively affected children’s educational opportunities. The higher the mother’s education is, the greater the opportunity for their children to continue their education at a higher level is. However, when the mother’s education is low, the chances of the child being able to continue on the path to higher education are also lower. The variable of working mother is found to have a positive and significant effect on all children’s education levels. The higher the child’s education level is, the greater the influence of working mothers on their children’s education participation level is. During the pandemic, the effect of working mothers on their children’s education level showed greater outcomes. This means that mothers who worked during the pandemic had an increasing influence on increasing their children’s school participation at a higher level of education. Hence, the augmentation of family income through the employment of mothers will yield favourable consequences for the educational continuity of their children.

The findings of this study have significant implication for policy-makers with regard to Indonesia’s 9-year compulsory education program. The findings demonstrate that there are still obstacles to the educational process; i.e. children of mothers with a primary school education level still have limited opportunities. In the meantime, the results of the 12-year compulsory education program demonstrate that particularly during the pandemic, it has become increasingly challenging for children to continue their education. Therefore, it is necessary to enhance the program to facilitate children’s access to post primary education. The need for mothers to have easy access to education, including informal education, might not only help mothers understand the value of education more fully but also provide easy access for them to enter the labour market. Anticipating the consequences of investments in women’s schooling thus requires attention to the role that schooling plays in the marriage market as well as to opportunities in the labour market for women.

However, there are some limitations of this research. This study only examines how the education of the mother influenced the education of her children, as well as how the status of a working mothers influenced the education of her children during the COVID-19 pandemic in Indonesia. The question of whether working mothers’ sector of activities (such as formal or informal sectors) influences their children’s education is not specifically discussed in this study. The specific relationship between the sector activities, the earnings received by working mothers and the education of their children can be the focus of future studies.

Disclosure statement

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

Additional information

Funding

This study was in part funded by Direktorat Jenderal Pendidikan Tinggi, Riset, dan Teknologi through Pendidikan Magister Menuju Doktor Untuk Sarjana Unggul (NKB 0267/E5/AK.04/2022).

Notes on contributors

Dien Amalina Nur Asrofi

Dien Amalina Nur Asrofi is doctoral candidate and researcher in the Department of Economics, Brawijaya University-Indonesia. Her research interest in labor economics, and economics development. Focusing on female labour, female entrepreneur, and children education.

Devanto Shasta Pratomo

Devanto Shasta Pratomo is a professor in labour economics at Brawijaya University-Indonesia. His research focuses on labour economics, education and migration.

Farah Wulandari Pangestuty

Farah Wulandari Pangestuty is a lecturer in Department of Economics at Brawijaya University, Indonesia. Her expertise are Economic Development, Nutrition and Food Economics, Food Security, and Rural Development.