4. Problems Faced During School Closures
Problems Faced by Children and Households
Access to the internet, digital devices, and educational platforms were the primary barriers to children's retention in education during the COVID-19 pandemic in Turkey. By the end of the academic year in 2020, only 26% of students were able to access EBA for more than an hour a week. Evidence on the educational experiences of children and families has shown that children who had to partially or fully discontinue their education during the pandemic experienced problems with access to the internet or digital devices. A survey study by the Ministry of National Education has shown that approximately 13% of students participating in the study (N= 41,430) were not able to attend any classes at all during the pandemic. 1.5% of these students reported not having access to a TV or the internet, whereas 7% of these students reported not being able to attend classes due to a lack of internet access. Many informants underlined that access to EBA classes was not equal to engagement in learning. According to an interview with a member of the teachers’ union, an unpublished survey with 2038 teachers seems to confirm this. Almost all the teachers (97%) participating in this survey shared the opinion that their students regressed during the pandemic, and 93% of these teachers agreed that it was not possible to compensate for the learning losses during the reopening of the schools. While the opening of EBA support centres was useful, there might have been gaps in informing the public about them. According to a study conducted by four national NGOs (Başak Kültür Sanat Vakfı (BSV), Sulukule Gönüllüleri Derneği (SGD), Tarlabaşı Toplum Merkezi (TTM) ve Small Projects Istanbul) located in Istanbul, with 86 children and 71 caregivers during January-April 2021, almost none of the caregivers or children knew about EBA support centres.
A large proportion of households in Turkey were unprepared for online education. A recent survey by TURKSTAT underlines the important gaps in children's computer use and internet access through fixed broadband connection in households. According to the results of TURKSTAT’s Survey on Information and Communication Technology (ICT) Usage in Households and by Individuals, 2021, the proportion of households with internet access is at 92.0%, a slight increase from the rate in 2020, which was 90.7%. However, 61.9% of households used fixed broadband connection (ADSL, cable, optic fibre, etc.), while 88.5% of the households had mobile broadband connection to access the internet. TURKSTAT also conducted a special module along with this survey with children, to understand their usage of information and communication technology. According to the results of this survey, 82.7% of children aged 6-15 years old reported using the internet. 64.4% of children in this age group used mobile phone/smartphone while 55.6% of children used computers (desktop/laptop/tablet). These findings are in line with the devices used by students when accessing EBA. The user statistics published by the Ministry of National Education have shown that the majority of the students accessed EBA via mobile devices (60%), whereas the proportion of students using a computer to access the platform was only 31%. Interviews with stakeholders also revealed that families struggled with providing digital devices to their children. Limited financial resources of families and multiple school-aged children living in the same household were linked to problems with access to digital devices during the pandemic. An interviewee underlined that the digital device supplies provided by the government and other local organisations only reached a small portion of families in need. Other interviews also confirmed that the emergency responses to these issues were not enough to compensate for the needs of many disadvantaged families in Turkey. Another problem experienced by families was with navigating EBA. Informants underlined that parents’ digital illiteracy was a barrier to their children’s access to online education during the pandemic. According to NGO informant experiences with local families, many parents struggled to guide their children’s use of EBA during the pandemic. This finding was also seen in a study conducted by Derin Yoksulluk Ağı during July-September 2020, among 103 households that DYA supported. According to the report, there were problems with access to EBA TV, for which the parents did not know how to set in their TV.
Educational disadvantages experienced by children in rural and disadvantaged areas in Turkey were exacerbated during the pandemic. The local statistics of access to the internet at home show larger variations for the most underprivileged regions in Turkey. For instance, 75.5% of the households in Southeast Turkey did not own fixed broadband connection at the beginning of the pandemic (in 2020), while this rate was 49.2% for the country overall, while access to the internet via a mobile supplier was similar to the rest of the country (85.4% in Southeast Turkey vs 86.9% in Turkey, in 2020). These numbers also reflect on students' access to online education in different parts of Turkey. A survey study of 155 children from Diyarbakir has shown that 72% of children reported having difficulties in continuing their education during the pandemic due to a lack of digital devices. 16.1% of children participating in this study had to discontinue their education fully, and 19.4% of children were forced into labour during the pandemic. A local report from a province of Gaziantep has shown that the active use of EBA varied from 0% to 97% across the students enrolled in schools in the region. Many teachers and school principals from schools located in rural areas of the region referred to problems with their students' access to the internet and digital devices. A mixed-methods study involving 2,398 parents, teachers, and local authorities (2,009 of those are local authorities) on the educational experiences of families in rural Turkey reported that 45.5% of the villages in Turkey experienced problems with online education during the pandemic. The report shows that 26.5% of the villages participating in the survey reported having frequent power-cuts due to infrastructural problems exacerbated by weather conditions. More than a quarter of the local authorities (28.6%) described the pandemic as a difficult period based on health (38.4%) and education-related (31.7%) problems experienced by their village members. Infrastructure problems were not the only issue in children’s access to education in rural areas. A stakeholder mentioned that low educational aspirations of parents also had a negative effect on children’s continuity in education. In some extreme cases, teachers witnessed families using the printed learning materials as kindling at home.
School education during the pandemic was also severely disrupted for refugee children due to issues with access to the internet and digital devices, as well as other problems. Evidence from various resources has shown that most refugee children had difficulty accessing education during the pandemic. According to a survey of 1,020 refugee families, 21% of children in education had to discontinue their school education due to a lack of resources. Primary barriers to refugee children's access to education were identified as either having no access to the internet (22%) or TV (12%); unavailability of equipment for all children in a family (17%); language barriers experienced by parents and children (13%), and problems with using the various educational platforms. For instance, a study demonstrated that some refugee children did not have access to EBA TV due to not having a Turkish TV satellite at home. In a face-to-face interview study with 100 refugee families in Izmir, parents of children whose education was disrupted due to the pandemic (35%) referred to technical issues and language barriers in explaining the reasons for their children's school withdrawal. Another survey study including 1,133 refugee parents of 0-17-year-old children in Turkey has shown that a majority of children experienced problems with participating in online classes due to a lack of digital resources (69%). As a result, 23% of children fully discontinued their education, whereas only 44% partially participated in online classes. 90% of those who were able to continue their education accessed their classes via mobile devices. Another factor that negatively affected refugee children’s continuity in education was the exacerbation of discrimination during the pandemic, as well as their own perception of this. Informants explained that refugees were perceived as a threat to public health during the pandemic and were discriminated against in public spaces. These experiences may have deterred many refugee children from going to school and demotivated parents to support their children’s continuity in education during the reopening period.
Socioeconomic status of the families played an important role in their children's access to education during the pandemic. Poverty was a common denominator in the majority of access problems during the pandemic. According to a report published by Derin Yoksulluk Ağı, the pandemic pushed more families into extreme poverty in Istanbul and left many households with food insecurity. A majority of these families also had no means to support their children’s learning during the pandemic (See Figure 8). Debilitating levels of poverty across these households also led school-aged children into work, keeping them out of education during the pandemic. A report on child welfare during the pandemic, for instance, has shown that families living in extreme poverty had to prioritise basic human needs such as heating their home and feeding their family over education. The pathways into labour faced by refugee children were also intersectional and linked with poverty. For instance, a report has shown that 78% of refugee children from disadvantaged households were able to continue their education during the pandemic, whereas this number was reduced to 63% for children living in extreme poverty. Other reports on refugee children have also underlined that the financial resources of families led to educational barriers other than access to the internet or digital devices during the pandemic. According to these reports, some refugee children had to discontinue their education to financially support their families.  In one of the reports, including interviews with 100 refugee families in western Turkey, the number of children financially supporting their families increased from 23 to 43. Interviews with stakeholders revealed further information on the negative experiences of refugee families. In an interview with one of the leading non-governmental organisations working with refugee families, informants pinpointed the effects of the pandemic on single mothers, whose sole income depended on domestic work such as cleaning, child minding, and adult care. With the pandemic restrictions, many refugee mothers lost their means to care for their children. For these reasons, many school-aged children were pushed into paid jobs to support their families during the pandemic. According to the stakeholders, the effects of the pandemic on children also varied by gender. Male children, for instance, took paid jobs to compensate for the income losses of their families, whereas female children helped their parents with household chores and domestic or rural work. According to the stakeholders, remote education made it difficult for schools and teachers to monitor these children, who were already at risk of leaving school early.
Figure 8 A report published by Derin Yoksulluk Ağı Households portrayed the learning environment in households in extreme poverty
Source: Derin Yoksulluk Ağı. Pandemide Yoksullukla Mücadele (2020). Accessed from the following link: https://derinyoksullukagi.org/wp-content/uploads/2020/11/DYA-Pandemide-Derin-Yoksullukla-Mu%CC%88cadele.pdf
In addition to access problems, students also experienced issues with the features and the content of EBA. Some children experienced access problems as a result of the language barriers experienced when using the platform. Children whose home language is other than Turkish reported struggling with understanding the classes delivered on EBA and EBA TV. Another problem was children's adjustment to the online system. A survey study of 876 parents has shown that the majority of children had adaptation problems with taking online classes during the pandemic and struggled with learning. Another study on the learning experiences of students in K-12 education (N = 6342) echoed this evidence. Many children found the educational content tedious and experienced problems with staying focused during online classes. Only 29.6% of high school students and 26.2% of secondary school students participating in this research did not find it difficult to focus on online classes. The largest number of students who experienced attention problems during the classes were in primary school (84.3%). Stakeholders also underlined that many children needed their parents’ support in understanding the online classes delivered via EBA TV. Policy analysts emphasised that EBA lacked supporting features for providing students feedback and facilitating teacher-child communication, making learning difficult for students during the pandemic. Furthermore, the content and difficulty level of asynchronous classes on EBA did not respond to student skills, making it difficult for students to adapt. In addition to these problems raised during the interviews with stakeholders, other functional issues with EBA led to problems with online education during the pandemic. One of the problems experienced by many children was not knowing when new learning materials or homework were made available on the platform. This was also partly due to not knowing how to navigate the platform. To overcome this problem, many teachers communicated with parents on more accessible social communication platforms (e.g., WhatsApp), which added to their increased number of responsibilities during the pandemic.
The home environment played an important role in the effectiveness of online education during the pandemic. Children who experienced problems with learning online also came from crowded households. For instance, only 8.9% of children from smaller households reported not being able to benefit from online classes, whereas this number was higher for children from crowded households (17.8%). These problems were especially documented and underlined as a learning impediment for refugee children. In a qualitative study of 36 refugee children enrolled in primary schools in Turkey, many children reported having difficulties with learning due to household crowdedness and interruptions from family members. Some children also mentioned finding it hard to focus on schoolwork whilst having responsibilities for household chores. Children also mentioned struggling with their coursework as they were not able to receive help from their parents due to language barriers. Stakeholders also underlined these problems in the interviews and added further information. Some informants, for example, emphasized the importance of housing during the pandemic and highlighted the disadvantages experienced by children living in urban apartments. These children had problems with access to gardens or parks for recreational activities during the pandemic. Another factor affecting family well-being was the social support network available to families during the pandemic. Interviews suggested that living in a supportive neighbourhood or having other family members to help with childcare (e.g., grandparents) had a positive effect on the experiences of disadvantaged families with childrearing during the pandemic.
Child well-being was severely affected during the pandemic leading to an increased number of mental health problems. In a study of adolescent well-being involving responses from 2,754 secondary and high school students in Turkey, researchers found that 44% of students experienced pessimistic thoughts about the future during the pandemic. Almost a quarter of students (24%) reported losing hope in the future, whereas 20% of them reported having feelings of meaninglessness. A small group of children (10%) participating in this research also reported needing psychological support during the pandemic. A survey study of 1133 parents of refugee children has shown that 40% of children experienced at least one of the symptoms of anxiety and depression, 30% of children struggled with communicating with their family and friends, and 57% of children experienced anger, some leading to behavioural problems. These well-being problems also affected children's physical health. Reports of parents participating in the survey demonstrated that 49% of children experienced sleeping problems, whereas 55% of children had problems with their appetite or experienced issues around eating during the pandemic. In a report published by the national medical council in Turkey, doctors underlined that the issues experienced by children were risk factors for the neurodevelopmental and socioemotional well-being of children, especially those with disabilities or special needs. Stakeholders also emphasized these problems and added further information in the interviews. Many stakeholders stressed the importance of household cohesion for the well-being of children during the pandemic. An NGO stakeholder who works with disadvantaged families mentioned that many parents reported having more disputes at home due to financial problems exacerbated by the pandemic. These disputes led to domestic violence incidents in some households, exposing affected children to trauma. Parents also experienced not knowing what to do with their children at home. Children with no siblings or with working parents also struggled with having opportunities to socialise at home. As a solution, many parents left their children to watch TV or to play with digital devices for long periods of time. These problems also compounded the mental health problems experienced by parents and had a negative effect on family cohesion. Many stakeholders and academics explained that schools did not have sufficient numbers of counselling teachers to guide parents and their children through the pandemic regarding their issues with mental health and well-being.
The quality of education provided for underrepresented youth groups has presumably deteriorated during the pandemic, although the educational implications of the pandemic remain undocumented. According to an official letter published in March 2021, there are 345 accompanying children under the age of 6 living in correctional facilities in Turkey. A report documenting interviews with 14 convicted parents with accompanying children shows that detention centres are damaging for children's health and wellbeing as well as education. Some children in these centres are not given access to early childcare or quality education. Similar problems exist for young offenders. According to the official data made available by TUIK, during 2020 alone, 10,234 children between the ages of 12-17 were convicted in Turkey, a high majority of whom were male (96.7%). There is no information or research currently available on how the pandemic affected these children and their education. Another youth group at educational risk is children with addiction problems (e.g., drugs). The official statistics from TUIK demonstrate that the percentage of children with addiction problems is still high (34.1%). Educational intervention programmes for these children remain limited across the country, and medical professionals warn against the significant future implications of this welfare issue. Another underrepresented youth group is children in care. According to the official statistics, the number of children currently in care in Turkey is 13,524. The Ministry of Family, Labour, and Social Services pledged to actively track the educational progress of children in care and provide counselling services during the pandemic, but no follow-up information has been made available. The interviews with stakeholders also highlighted the lack of attention received by children with special educational needs and their families. Many informants mentioned that the negative effects of the pandemic were doubled for children with special educational needs, leaving them more vulnerable to health and well-being problems in the future.
Existing Disadvantages Related to Education for Children in Turkey
According to latest global learning assessments of PISA and TIMSS, even prior to the pandemic, important shares of children performed below the minimum proficiency thresholds in Turkey. According to PISA 2018 results, pre-pandemic, a considerable share of 15-year-old students was already performing below the minimum proficiency levels, and inequalities existed with respect to socioeconomic status in Turkey. In the latest round of PISA, 37%, 26% and 25% of students in Turkey performed below the minimum proficiency levels in math, reading and science, respectively. Pre-pandemic socioeconomic status of students was also already correlated with learning outcomes. Socioeconomic status of students explained around 11% of the variation in test scores in all subjects in Turkey, which is slightly lower than the OECD averages (14%, 12% and 13% respectively in math, reading and science). Between school inequalities also existed, with low and high performing students clustering in the same schools more often than the OECD average. Turkey’s test scores improved in 2018 compared to 2015 levels but were not statistically different than the 2009 and 2012 levels.
According to TIMSS 2019 results, there has been an improvement in learning outcomes of 4th and 8th-grade students in Turkey over the years, but learning resources at home created important differences in children’s learning outcomes. For the first time since 1999, Turkey’s average scores in math and science for 4th graders and for science for 8th graders have been higher than the median score of 500 in TIMSS 2019. Yet, important shares of children still score below the minimum proficiency level with 12% in math and 10% in science for 4th graders and 20% in math and 12% in science for 8th graders. Despite the improvements, inequalities that existed between children and learning resources at home was an important factor that is associated with differences in learning outcomes of children. A considerable share of children is living in households with very low learning resources. 26% of children in 4th grade had “very low” learning resources at home as opposed to 6% of children with “high” learning resources. These shares were 32% and 9%, respectively, for 8th graders. For 4th graders, a 175 point difference is found in math scores between the groups of children who have “high” and “very low” learning resources at home, and the difference was 166 points in math for 8th graders.
Home Learning Environment of Children in Turkey
The home learning environment is an important factor in predicting disparities in children's education outcomes. While the definition of home learning environment varies across studies, it generally involves (i) children's participation in learning activities, (ii) the quality of parent-child interactions, and (iii) the availability of learning materials.
The importance of the home learning environment was much more pronounced during the lockdowns. Turkey has implemented remote learning for about 15 months, March 2020-June 2021, through the EBA platform and EBA TV. However, not all children have had equal access to remote learning, or even if they could access the resources, they may not have been able to benefit from it as effectively due to not having an adequate studying environment, not having enough adult supervision available in the household or not having enough resources for all the children in the household when many children are living together.
In this respect, a multi-dimensional look at the home learning environment is crucial in understanding the possible deprivations of children in terms of learning and education with regards to the challenges presented by the COVID crisis. While access to infrastructure for remote learning is a necessary condition, it is not sufficient in itself for the child to continue learning at an effective rate. Hence the home learning environment should be assessed more holistically. While home learning environment indices generally include more specific questions related to the parents' time spent with children doing activities such as reading or playing as well as the availability of learning materials in the household, here we have a broader look taking into account the specific situation introduced by the COVID crisis and also taking into account data availability.
The home learning environment is generally studied in the literature for children in early childhood. The indices created to measure the HLE in a composite way are constructed largely using variables measuring the frequency of activities that the child participates in at home that can enhance his/her learning. Melhuish et al. (2008) create a home learning environment index for pre-schoolers using the frequency of activities that a child does at home, including activities such as being read to, playing with numbers, painting and drawing, being taught letters. The index is created by adding the Likert scaled frequency of the activities. Another approach in creating the index is z-standardising the indicators and then taking an average of them as used in Lehrl et al. (2019), in which the index is created using different sets of variables for the preschool age and for secondary school-age children as well. Lehrl et al. (2021) follow a similar method and take the average of the frequency of activities such as reading to the child, counting, playing with alphabet toys in creating an analogue HLE scale and looking at/playing with apps, going online, doing something with the computer in creating a digital HLE scale.
HLE is also assessed using The Home Observation for Measurement of the Environment (HOME) in a number of studies. HOME is a survey tool designed to measure the quality and quantity of stimulation and support available to a child in the home environment and consists of different instruments depending on the age of the child from infant/toddler to late adolescent age group. The raw score is calculated by a simple summation of responses. Kuger et al. (2018) and Todd and Wolpin (2007) are among the studies that use the HOME index.
In this part of the report, we make use of DHS 2018 to understand the pre-pandemic home learning environment of both Turkish and Syrian children aged 6-17 years old. DHS is preferred since it involves questions to reflect the home learning environment of children and also includes a sample for Syrians, which allowed us to look at the situation for both Turkish and Syrian children.
Turkey hosts the world’s largest refugee population and is home to 3.7 million Syrians under temporary protection as of February 2022 along with around 330,000 refugees and asylum seekers from other nationalities under international protection. Among the Syrians under temporary protection living in Turkey, 47.4% are in the 0-18 year old age group and making a total of 1.8 million children (the official statistics are given for age groups 0-4 year olds, 5-9 year olds, 10-14 year olds and 15-18 year olds, hence 18 year olds are also included in the number of total children). Given that Turkey’s population of 0-18 year olds is 24 million, Syrian children constitute a sizable group, that is around 7.4% of the Turkish population in the same age group. Hence in this report, through using DHS we also report statistics on the Syrian children when possible.
Pre-pandemic, in 2018, both Turkish and Syrian children had certain disadvantages in terms of having a supportive home learning environment. First, there were existing gaps in terms of the necessary infrastructure to access remote learning (See Figure 9). A considerable share of children lacked an internet connection, a computer or a satellite TV or paid TV services. 43.3% of Turkish children and 40.5% of Syrian children had an internet connection in the household, while 39.9% of Turkish children and only 4.5% of Syrian children had a computer. Having a satellite TV or paid TV services was much more common for Turkish children. 85.3% of Turkish children and 55.4% of Syrian children lived in households with satellite TV or paid TV services.
Figure 9 Turkish and Syrian children lack certain dimensions to have a supportive home learning environment
% of Turkish and Syrian children that has the dimension in the household, for children aged 6-17 years old
Source data: DHS 2018.
Space availability is another important dimension in having a supportive home learning environment. In terms of space availability, almost all Syrian children were living in a household with limited space availability, hence in an overcrowded household as well as a considerable share of Turkish children. 95.8% of Syrian children and 59.7% of Turkish children lived in overcrowded households.
When we look at the quality of adult interaction, as another major dimension of having a supportive home learning environment, not having a parent with a higher education degree stands out for Turkish children while mother not knowing Turkish and having no one in the household to support with homework are among other major disadvantages for Syrian children. Living with both parents in the household or other adult relatives could provide support for children in their home learning activities. For the majority of Turkish and Syrian children (91.7% for Turkish children and 84.2% for Syrian children), both parents are living in the household. In terms of having other adult relatives in the household, 45.9% of Turkish children and 51.2% of Syrian children have other adult relatives in the household. Apart from having parents or adults in the household, the quality of adult interaction could be determined through other indicators such as Turkish knowledge of the mother, the level of education of adults in the household, and if there is anyone in the household spending time with the children. In terms of Turkish knowledge of the mother, Syrian children are quite disadvantaged. Only 21.1% of Syrian children’s mother knows Turkish, while this rate is 95.6% for Turkish children. Having an adult with a higher education degree in the household is an indicator in which both Turkish and Syrian children are disadvantaged. Only 11.8% of Syrian children and 27.5% of Turkish children live with an adult in the household with a higher education degree. Perhaps related to not knowing Turkish, having someone in the household helping with the homework of children is low for Syrian children with 40.5%, while this rate is 72.8% for Turkish children. Having someone at home playing games or reading books to children, or spending time with the children outside the house is similar for both Turkish and Syrian children. 76.3% of Syrian children and 77.0% of Turkish children live in a household where it is reported that someone in the household spends time with the children playing or reading to them. And 71.6% of Turkish children and 70.8% of Syrian children live in a household where it is reported that there is someone in the household spending time with them outside the household.
Turning these indicators into a composite index shows that Turkish children but especially Syrian children entered the crisis with disadvantages in terms of their home learning environment quality (See Annex 1.2 for the detailed methodology). A child would have an HLEQI of 100 if he/she had all these indicators in the household. The average HLEQI is calculated as 61.7 (out of 100) for Turkish children, while it is 36.5 for Syrian children (See Figure 10). Looking at the distribution of HLEQI for Turkish and Syrian children, it can also be seen that majority of Syrian children aged 6-17 years old (94.3%) have an HLEQI lower than the Turkish average. Overall, 26.9% of Turkish children aged 6-17 years old and 77.2% of Syrian children in the same age group have an HLEQI less than 50 (out of 100). When we look at the distribution of HLEQI further by school attendance status of children, the discrepancies between children attending school and not attending school is seen. Especially for Turkish children, the divide is clearly visible, where the average HLEQI is 43.8 for children not attending school while it is 63.1 for children attending school. For the Syrian children, these averages are 30.6 and 39.8, respectively. Hence overall, children not attending school also are further disadvantaged in terms of having a home learning environment that is not supportive.
Figure 10 Turkish children but especially Syrian children entered the pandemic with disadvantages in terms of their home learning environment quality
Distribution of the Household Learning Environment Quality Index (HLEQI)
a. Turkish and Syrian children aged 6-17 b. Turkish and Syrian children aged 6-17, by school attendance status
Source data: DHS 2018.
Among Turkish children, HLEQI is higher for children attending school, living in wealthier households and households with more educated adults and in households where the number of children is lower (See Figure 11). In other words, children have a more supportive home learning environment in households with these characteristics. Looking at various subgroups of children, HLEQI is highest with 84.7 (out of 100) for children in the 5th wealth quintile (wealthiest 20% of the population, according to household assets). In comparison, children in the 1st quintile (poorest 20% of the population) have an HLLEQI of 43.1 on average. Mother tongue of the mother and region of the household are also factors of inequality in terms of a supportive home learning environment. On average, children living in the East have an average HLEQI of 51.1 as opposed to 67.4 for children living in the west. Living in households with more children is also associated with having a lower HLEQI.
Among Syrian children, HLEQI is higher for some groups as well, yet, for none of the sub-groups, HLEQI is higher than the average HLEQI for Turkish children (See Figure 11). For all child subgroups, even the children living in the wealthiest 20% of the Syrian population, the average HLEQI is lower with 48.1, than the Turkish average of 61.7. Regional inequality in HLEQI observed in the case of Turkish children also cannot be observed for Syrian children. On average, Syrian children living in different regions have similar HLEQI levels. Overall, the differences between subgroups with respect to HLEQI is smaller in the Syrian sample compared to the Turkish sample. For instance, the difference between the poorest and richest quintile is 41.6 for the Turkish children while it is 25.1 for Syrian children.
Hence, our findings using DHS 2018 show that Syrian children overall, and Turkish children especially those living in the East and who are in the bottom 20% of the population in terms of household wealth, have entered the pandemic with larger gaps in terms of having a supportive home learning environment that would be instrumental during remote learning.
Figure 11 Pre-pandemic variations can be observed in the average HLEQI by individual and household characteristics of children
Average HLEQI of children aged 6-17 years old, by their characteristics
Source data: DHS 2018.
Estimated Learning Losses During the Lockdown
Several studies estimate the possible learning losses that would occur due to the COVID crisis in other country contexts. Using learning gains from studying one more grade, Azevedo et al. (2020) estimate that children's learning losses in terms of PISA scores could range between 7-25 points for upper-middle-income countries. Other studies using absenteeism and summer learning losses literature estimate lower achievement levels for children, especially for mathematics compared to reading, for the U.S. Apart from simulations, collection of assessment data also point out to learning losses. Evidence from countries including Mexico, Russia, Pakistan and South Africa show important learning losses for children in different grades. Assessment data from the Netherlands during COVID-19 suggest that an 8-week school closure led to learning losses in children. The impact was higher on children with less-educated parents. A study from Ghana suggests that the availability of home learning support and home learning resources are important indicators in explaining learning loss gaps.
As children are living in households with different environments to support home learning, during the lockdowns, this might have had an impact on their learning outcomes. Making use of the variation in home learning environment quality of children, we estimated possible learning outcomes of the children in Turkey after the end of remote learning using PISA 2018, which is a global learning assessment for 15-year-olds. Our model assumes that children, on average, will stay where they have been at the beginning of the pandemic, not making the progress that they could have made while instead significant inequalities would occur in between children based on their home learning environment quality (See Annex 1.3 for the methodology).
Assuming PISA 2018 as the starting point, the possible progress that could be achieved is predicted not to take place in Turkey in all three subject areas due to the remote learning process and the variation in the home learning environment of students. The added value of studying another grade is first estimated for Turkey using PISA 2018 for different subjects (math, science, reading) and found as 27.3, 19.2 and 20.4 points, respectively (See Annex 1.3 for the regression results). Due to the variation in students’ home learning environment, the students’ after shock learning scores are predicted to stall, and it is assumed that no progress will be made on average. Hence after shock, scores of students are on average lower than the counterfactual (or what would have been without the pandemic). For math, the average score is 5.6% lower, while it is 3.9% and 4.2% lower, respectively, for reading and science, compared to the counterfactual. While the distribution of the students’ scores was expected to shift to the right, instead, the scores in the upper end of the distribution became better while the scores in the lower end of the distribution are estimated to have gotten worse (See Figure 12).
Compared to their counterfactual scores, after shock, none of the groups of children can make the possible progress that they could have made and hence are behind the counterfactual learning scores on average (See Figure 13). Some student subgroups experience higher learning losses compared to the counterfactual. These groups are students living in the poorest households, students with no internet or those with parents with low levels of education, students speaking languages other than Turkish, living in villages or small towns. These groups are also the subgroups experiencing learning losses when compared to the baseline scores.
Internet connection in the household and households’ socioeconomic status measured through household wealth and parental education are important factors in creating a supportive learning environment to prevent learning losses. Students without an internet connection at home, experience a learning loss of 14.0% in math, 10.0% in reading and 10.4% in science, compared to the counterfactual outcome. Students living in the lowest wealth quintile (in terms of asset ownership), are also quite disadvantaged. On average, students in the lowest wealth quintile experience learning losses at the rate of 13.8%, 9.7% and 10.1%, respectively, in math, reading and science compared to their counterfactual scores. In terms of parental education, students experience learning losses compared to the counterfactual on average for all sub groups but students whose parents at most have an educational attainment level of high school or less are predicted to experience learning losses between 4.4-7.2 times higher than the learning losses experienced by those who have at least one of the parents with a university degree.
Mostly spoken language at home is also important in creating a supportive learning environment for children, and the results show that when mostly spoken language at home is not Turkish, larger learning losses occur. In fact, the group with the highest learning losses on average are those for whom the mostly spoken language at home is not Turkish. This group of students, on average, are estimated to have an after shock score that is 15.0% lower for math, 10.9% lower for reading and 11.3% lower for science, compared to the counterfactual scores.
Figure 12 The shock leads to inequalities in the distribution of learning outcomes where the scores in the upper end of the distribution became better while the scores in the lower end of the distribution are estimated to have gotten worse
Kernel density of the math, reading and science scores of students, before shock, counterfactual and after shock
Source data: PISA 2018. Scores are reported as 10 plausible values. To come up with Kernel densities we draw kernel densities for each plausible score separately and then take the average of the density values and then depict the averages.
Figure 13 Compared to their counterfactual scores, after shock, all student groups experience learning losses on average
Average scores of students, before shock, counterfactual and after shock and % change in scores after shock compared to the counterfactual (secondary y-axis)
Source data: PISA 2018.
Students studying in certain school types, locations and school funding types are also predicted to experience larger learning losses. The students that are going to school in large cities are predicted to have smaller learning losses on average, compared to the counterfactual while students going to schools in towns, cities and especially in villages and small towns are predicted to experience larger learning losses. In fact, compared to the students studying in large cities, students studying in villages or small towns experience learning losses that are twice as high in all subject areas. Students that are studying in multi-programme high schools, imam and preacher high schools, and vocational and technical high schools are also predicted to have larger learning losses in general as a result of the pandemic. For instance, the counterfactual learning losses are at 2.2% in math for students studying in science high schools while it is at 10.5% for students studying at multi-programme high schools. Students studying in public schools are also on average predicted to have larger learning losses, while students studying in private schools are predicted to have smaller learning losses. The counterfactual learning losses are twice as high in all subject areas for students studying in public schools compared to those studying in private schools.
The inequality between student scores is expected to rise since students who initially had lower scores are predicted to have larger learning losses on average, while those with higher scores initially are expected to have much smaller learning losses compared to the counterfactual (See Figure 14). Students who had lower scores in the baseline are predicted to obtain worse outcomes. This is due to the fact that students who have low learning scores are more likely to also have a low HLEQI, and hence they are already living in households with weak support for learning at home. Students with proficiency levels of 0, 1 and 2 in the baseline are predicted to experience much larger learning losses compared to the counterfactual, ranging between 10.9% and 6.1% in math, 9.8% and 4.4% in reading and 9.4% and 4.8% in science. On the other hand, students in the highest proficiency level in the baseline are predicted to have learning losses of only at 0.8%, 0.1% and 0.8% in the same subjects, compared to the counterfactual. Yet, it must also be noted that even the group with the highest proficiency level cannot achieve the counterfactual gains on average.
Figure 14 The inequality between student scores is expected to rise since students who initially had lower scores are predicted to have larger learning losses on average compared to those with higher scores in the baseline Average learning scores of students, before shock, counterfactual and after shock and % change in scores after shock compared to the counterfactual (secondary axis)
Source data: PISA 2018. Thresholds for proficiency levels are taken from the PISA 2018 Technical Report, Chapter 15: Proficiency Scale Construction. (https://www.oecd.org/pisa/data/pisa2018technicalreport/PISA2018%20TecReport-Ch-15-Proficiency-Scales.pdf)
Other Risks during the Pandemic
Different household and individual characteristics of children made them vulnerable to more extreme risks during the pandemic. In this section, using DHS 2018, we delve into the household and individual characteristics of children and try to understand and profile the children at risk of school dropout and child labour during the crisis, taking into account their background characteristics that might make them more vulnerable.
Risk of Dropping Out of School
The net enrolment rate in education during the pandemic decreased the most in early childhood education, and there were slight increases or decreases for older age groups. The share of children who were not enrolled in education during the pandemic was highest for the category of 3-5-year-olds. According to official statistics, 94.4% of 3-year-old children were not enrolled to an Early Childhood Education and Care (ECEC) institution during the academic year of 2020-2021. This number was 83.6% for 4-year-olds and 41.5% for 5-year-olds. In the previous academic year, these rates were considerably lower with 86.7%, 66.6% and 24.9% for 3, 4 and 5-year-olds, respectively. For older age groups, enrolment rates increased for children aged 14-17 years old (1.6 percentage points) and decreased minimally for children aged 6-9 years old (0.7 percentage points) and 10-13 years old (0.09 percentage points).
Using enrolment data from the Ministry of National Education, and controlling for cohort effects, ERI (2021) points out that there are decreases in the net enrolment rate for 14-17 year olds when the same group of children is followed through in between 2019-2020 and 2020-2021 academic years (See Table 1). For the children aged 13 years old in 2019-2020 academic year net enrolment rate was 98.5% while net enrolment rate for the children with the same birth year a year after, hence when they turned 14 years old is 96.3%, meaning a 2.2 percentage points drop. The decrease is highest for the children turning 16 years old in the 2020-2021 academic year, with a decrease of 3.8 percentage points.
Table 1 Decreases in the net enrolment rate for 14-17 year olds can be seen when the same group of children is followed through in the academic years 2019-2020 and 2020-2021
Source: ERG. (2021). Eğitim İzleme Raporu 2021, Öğrenciler ve Eğitime Erişim.
Using household level data, it is possible to describe the profiles of the children who are most likely to have dropped out in this process. Focusing on the information from DHS 2018, before the pandemic (in 2018), the majority of Turkish children attended school while the attendance rate was considerably lower for Syrian children. 91.9% of Turkish children aged 6-17 years old attended school, while this rate was 63.2% for Syrian children. As the age group increases, the school attendance rate decreases for both groups, and the decrease for Syrian children is greater. Among Turkish children, 96.3% of children aged 6-9 years old and 96.9% of children aged 10-13 years old were attending school as opposed to 79.5% and 73.6% of Syrian children in the same age groups, respectively. For the children in 14-17 years old age group, while 82.8% of Turkish children aged 14-17 years old attended school, this rate dropped down to only 27.6% for Syrian children.
Children with certain household characteristics had a higher probability of dropout already prior to the pandemic. For both Turkish and Syrian children, the dropout rate is higher for children living in poorer households and households with less-educated adults and in households where the number of children is higher. For Turkish children, 17.4% of children are not attending school among those that are in the bottom 20% according to the asset index of their household, while this rate drops down to 1.9% for Turkish children in the top 20%. A similar divide can be seen among Syrian children, but with higher rates. For Syrian children, those that are in the bottom 20% of the Syrian population, have a drop out rate of 42.1% while for those that are in the top 20% have a drop rate of 28.7%. Hence even in the comparatively well-off group of Syrians, the drop out rate among children is much higher than the Turkish average and even higher than the subgroup for whom the drop out rates are highest for the Turkish children that is the children in the bottom 20%.
Controlling for several individual and household characteristics at the same time in a regression model, factors like age, household wealth and education level of adults in the households stand out for both groups of children (See Annex 1.4 for the methodology and regression results). For Turkish children, being in the age group 14-17 years old, and the number of working age adults in the household are statistically significantly and negatively associated with school attendance while having at least one adult in the household with a higher education degree, living in a richer household and living in certain regions are statistically significantly and positively associated with school attendance. The share of adults working in a paid job among the adults in the household is positively and significantly associated with school attendance, but when household wealth is controlled for in the regression, the statistical significance disappears, and the size of the coefficient gets smaller.
Figure 15 The children at risk of drop out are only in the 14-17 age group in the Turkish sample, while the children at risk are in all age groups in the Syrian sample
% of children at risk of school dropout
Source data: DHS 2018. Turkish Overall Sample includes 7,792 children, and Syrian Migrant Sample includes 3,326 children. Children at risk are those who attend school, and whose predicted score for school attendance is below 0.6 prior to the pandemic.
For the Syrian children, being in any of the older age groups, compared to being in the age group 6-9 years old, the number of working age adults and number of children living in the household are statistically significantly and negatively associated with school attendance while being a female child, having adults in the household with higher education degrees, living in richer households are statistically significantly and positively associated with school attendance. The share of adults working in a paid job among the adults in the household is not significantly associated with school attendance.
Figure 16 For the Turkish sample, the 14-17 year old children at risk of school dropout are only at the poorest households and households with much less-educated adults, while for the Syrian children at risk, such a clear distinction does not occur and children coming from all kinds of backgrounds could be at risk
Percentage of Turkish and Syrian children at risk of drop out, aged 6-17 years old, by their characteristics
Source data: DHS 2018. Turkish Overall Sample includes 7,792 children, and Syrian Migrant Sample includes 3,326 children.
Using predicted school attendance scores of children coming from the same regressions, we further predicted the group of children who are attending school but at risk of dropping out of school given their individual and household characteristics, hence the children who are more vulnerable to shocks (See Annex 1.4 for the methodology). This rate is 1.3% for Turkish children and 11.3% for Syrian children (See Figure 15). In other words, of Turkish children aged 6-17 years old 1.3% are attending school but are at risk of drop out and 11.3% are attending school but at risk of drop-out.
While the children at risk of drop-out are only in the 14-17 age group in the Turkish sample, the children at risk are in all age groups in the Syrian sample, and the older the children get, the percentage of children at risk also increases. In fact, for the Syrian children, almost all of the children aged 14-17 years old and attending school are at risk of drop out. This is not the case for younger children. For the 6-9 year old Syrian children, 4.2% are attending school but at risk of drop-out while this rate rises to 7.2% for the 10-13 year olds.
For the Turkish sample, the 14-17 year old children at risk of school dropout are only at the poorest households and households with much less-educated adults, while for the Syrian children at risk, such a clear distinction does not occur and children coming from all kinds of backgrounds could be at risk (Figure 16). While this is the case, the percentage of being at risk for Syrian children is still higher in poorer households and in households with less educated adults and more children.
Risk of Child Labour
Before the pandemic (in 2018), according to DHS, a comparatively lower share of Turkish children and a higher share of Syrian children worked in a paid job. 4.4% of Turkish children aged 12-17 years old worked in a paid job, while this rate is 20.3% for Syrian children in the same age group. Another source of child labour statistics is TURKSTAT’s Child Labour Force Statistics 2019 (CLFS), and it gives a similar share of children working. According to CLFS, 4.4% of Turkish children aged 6-17 years old are engaged in employment, and 2.8% of these children work as a regular or casual employee.
Looking at DHS 2018, as age increases, participation in employment increases for both Syrian and Turkish children. For Turkish children, 1.4% of children aged 12-14 years old have been working in a paid job, while this rate increases to 7.6% for 15-17 year olds. For Syrian children, the rates are higher with 12.0% and 31.5% for the same age groups. Overall, 4.9% of Turkish children and 24.0% of Syrian children aged 6-17 years old live in a household where at least one child aged 12 years old or older work in paid labour.
Focusing on children living in a household with child labour, children living in households with certain characteristics are more likely to be living in a household with child labour. As in the case of school dropout, for both Turkish and Syrian children living in a household with child labour is higher for children living in households with less-educated adults and in households where the number of children is higher. However, with respect to household assets, there seems to be a difference between Turkish and Syrian samples. Turkish children living in wealthier households are less likely to be living in a household with child labour. 10.4% of children in the first quintile are living in a household with child labour, while this rate is only 1.1% for children in the fifth quintile. For Syrian children, on the other hand, the rates are very similar for the children in the bottom 20% and the wealthiest 20% with 19.8% and 21.9% of the children in these groups respectively living in a household with child labour.
Controlling for several individual and household characteristics at the same time in a regression model, factors like age, education level of adults in the households and number of children in the household stand out for both groups of children, Turkish and Syrian (See Annex 1.4 for the methodology and regression results). For the Turkish and Syrian samples, being in the older age groups and the number of children in the household are statistically significantly and positively associated with living in a household with child labour while having an adult in the household with higher education is statistically significantly and negatively associated with living in a household with child labour.
Figure 17 As in the case of being at risk of school dropout, the children at risk are only in the 14-17 year old age group in the Turkish sample, while the children at risk are in all age groups in the Syrian sample, and as the age group increases, the percentage of children at risk also increases
% of children at risk of child labour
Source data: DHS 2018. Turkish Overall Sample includes 7,792 children, and Syrian Migrant Sample includes 3,326 children. Children at risk are those who do not live in a HH with child labour and whose predicted score for living in a HH with child labour is above 0.4.
While for the Turkish sample share of adults working in a paid job among the adults in the household is not statistically significantly associated with living in a household with child labour, this is not the case for the Syrian sample. Syrian children living in households where more of the adults are working are more likely to be living in a household with child labour as well. When someone in the household is working, it might be the case it is easier to find a job for the children in the same place. The relationship between household wealth and child labour is also different for Turkish and Syrian samples. The likelihood of living in a household with child labour decreases for Turkish children with increasing levels of wealth, while this relationship is not statistically significant for Syrian children.
Using the same regression models, we also predicted the children at risk of being in child labour (through living in a household with child labour). The percentage of children who are at risk of child labour (through living in a household with child labour) is very low for Turkish children at only 0.02% and relatively much higher for Syrian children at 7.1% (See Figure 17). As in the case of being at risk of school dropout, the children at risk are only in the 14-17 year old age group in the Turkish sample, while the children at risk are in all age groups in the Syrian sample, and as the age group increases, the percentage of children at risk also increases.
For the Turkish sample, since the risk of participating in child labour is already very low, children at risk are only in the poorest households, in households with the lowest education level of adults, and in households with more than 5 children (See Figure 18). On the other hand, Syrian children at risk, once again, are in all different characteristics, and the percentage of Syrian children at risk is higher for boys and households with less educated adults and more children.
Figure 18 For the Turkish sample, children at risk are only in the poorest households, in households with the lowest education level of adults, and in households with more than 5 children, while the Syrian children at risk, once again, are in all different characteristics
Percentage of Turkish and Syrian children at risk of child labour, aged 6-17 years old, by their characteristics
Source data: DHS 2018. Turkish Overall Sample includes 7,792 children, and Syrian Migrant Sample includes 3,326 children.
Children in Turkey faced multiple overlapping risks prior to the pandemic. Lastly, we combined these risks together and looked first at the share of children (i) who already dropped out of school, (ii) who are living in a household with child labour and (iii) living in a household with a low HLEQI (i.e. lower than the Turkish average) and next added on the children who are at risk of dropping out and who are at risk of living in a household with child labour.
Prior to pandemic, while 46.5% of Turkish children were not exposed to any disadvantage (i.e. having already dropped out of school, living in a household with child labour or having low HLEQI), this rate was only 4.6% for Syrian children (See Figure 19 Panel A). In terms of exposure to all three disadvantages, the rate was 13.9% for Syrian children, which is much higher than for Turkish children (1.4%). Considering the children who are further at risk due to their household or individual characteristics during the pandemic, the risk groups get larger (See Figure 19 Panel B). Syrian children were more at risk during the pandemic compared to Turkish children, when we define the risk this time as being already in the disadvantaged group (i.e. being already dropped out of school) or having a high calculated dropout or household child labour risk. In terms of being at risk of exposure to all three dimensions, the rate increases from 13.9% at the current situation to 21.5% for Syrian children, while this increase is only from 1.4% to 1.5% for Turkish children.
Figure 19 Syrian children were more at risk prior to the pandemic and during the pandemic compared to Turkish children, when we define the risk as being already in the disadvantaged group (i.e. being already dropped out of school) or having a high calculated dropout or household child labour risk
A. Percentage of Turkish and Syrian children aged 6-17 years old who have exposure to multiple risks - prior to the pandemic
Turkish children Syrian children
B. Percentage of Turkish and Syrian children aged 6-17 years old who have exposure to multiple risks- during the pandemic
Turkish children Syrian children
Source data: DHS 2018.
Problems Faced by Schools and Teachers During School Closures
After discussing the issues faced at the household level by children, in this section we focus on the problems faced by schools and teachers during the school closures.
Digital barriers to education negatively affected school and teacher effectiveness during the pandemic as teachers were for the most part, unprepared for teaching online and struggled to adapt to online education. One of the main barriers to online education during the pandemic was teachers' lack of digital literacy. A survey of 1071 teachers across the country identified some of the demographic factors related to teachers' IT skills. According to this research, female teachers and older teachers (+41) in particular experienced more problems using digital platforms during the remote education period. The digital illiteracy of teachers has also previously been identified as a problem. Researchers have underlined that the majority of teachers in Turkey did not have any professional training in online teaching platforms prior to the launch of EBA. These problems led to difficulties in navigating the online education platform and negatively affected teacher effectiveness during the pandemic.  The digital skills of teachers were also identified as a protective factor for children’s online learning in interviews with stakeholders. Research with teachers has also documented that many teachers were caught unprepared for online education and had never practised teaching online before.  This problem was also raised during interviews conducted with stakeholders. According to an interview with UNICEF Turkey, the training programme, which was launched by the Ministry of National Education to improve the digital skills of teachers during the pandemic, reached approximately 300,000 teachers from a pool of more than 1,000,000 teachers in the country due to access issues. In response to these issues, the Ministry of National Education announced forthcoming future projects to improve teachers' digital literacy and support their access to online education platforms as part of their Horizon 2023 Education plans.
Many teachers lacked digital resources to teach or had students with no access to digital devices. A majority of schools in rural areas do not have the infrastructure to support teachers or students in using online learning platforms (Tosun et al., 2021). During the pandemic, internet access problems and limited availability of digital devices required teachers' initiative to create solutions in reaching students and delivering classes. A commentary report published by the teacher's union in Turkey underlined that transferring to online education left teachers with an undocumented responsibility to support students in need. Many teachers had to provide their own devices to continue teaching online, use other available platforms to deliver classes, and produce digital materials to aid their teaching. An interview study with 3743 teachers in K-12 education, for example, revealed that a majority of teachers in Turkey (59%) had to purchase a computer/tablet and exceed their internet use. The expenses spent on digital devices and the internet during the pandemic had a negative effect on teachers’ financial assets. Interviewing stakeholders, this issue was also emphasised as a barrier to teaching during the pandemic. According to the interviews, many teachers lacked digital devices or preparedness to continue their teaching or their device quality led to problems during online classes, which interfered with their teaching. Teachers also had to monitor their students who did not have access to digital devices and support their learning with after-school classes or via mobile communication apps. One interviewee, whose work focuses on education in rural areas, has shown that many teachers had to prepare physical teaching materials for children with no internet access, and in some cases, they also had to travel across the area to deliver these materials to children. Other interviews also supported this finding. According to the informants, many teachers took initiatives to hold classes in person (e.g., visiting student homes, meeting in parks or other open spaces) to ensure that children with no internet access or digital devices continued learning during the school closures.
A majority of teachers found teaching materials inapplicable to online classes and experienced problems with teaching during the pandemic. A report published by a research and development organization in Turkey portrayed the experiences of teachers drawing on a large-scale survey with 638 teachers in 12 representative cities across the country. According to the report, teachers found curriculum resources not suitable for online classes (81%) and experienced problems with teaching online due to a lack of digitised learning and teaching materials (80%). Research on the use of online platforms in education shows that teachers' ability to navigate online platforms plays a major role in their teaching effectiveness. Given the technological barriers experienced by many teachers and the lack of digitised educational materials, the evidence suggests that the learning experiences of the most disadvantaged children heavily depended on their teachers and their ability to compensate for the lack of digital resources during the pandemic. In most of the interviews with stakeholders, this finding also appeared as a recurring theme. Informants underlined that the technical issues experienced during the pandemic were frequently solved by teachers’ initiatives, including preparing physical learning materials, reaching out to students via phone calls/text messages or via using more accessible platforms, and meeting students in person at their homes or open public spaces when possible.
Infrastructure was not ready in many schools to allow for a safe reopening across the country. Interviews with key informants have underlined that the problems with infrastructure in most schools were an important barrier to the implementation of safety measures for re-opening. The informants, whose work involved collaborating with teachers in resource-constrained areas in the country, have highlighted that social distancing was not possible in the majority of the classrooms with more than 35 children. According to this interview, high pupil-teacher ratios across classrooms in the country also made it difficult to monitor the safety measures in schools. Early childhood educators also experienced problems with implementing safety measures in their classes. According to an academic interview, the safety measures were initially found difficult to apply to young children by many teachers. Following this, the removal of toys and play objects for health and safety measures in preschools reduced the quality of ECE and its role in early motor development.
Teachers struggled with adapting children to the changes in the school environment and rules during the school reopening period. Another problem experienced by teachers during the school reopening was behavioural problems experienced by children in adjusting to the existing and novel school rules. In interviews with stakeholders, many informants underlined that children who spent their preschool education at home during the pandemic were not ready to adapt to the rule-bound environment of the school. Children also struggled with maintaining their focus during classes and performing simple tasks (e.g., using writing skills) based on competencies acquired during the first two years of primary school. This problem left many primary school teachers with an undocumented responsibility of re-orienting young children with the classroom environment and school behaviours.
The effects of school closures on parent-teacher partnerships varied according to contextual and socioeconomic factors. The interviews with stakeholders showed that the pandemic affected the parent-teacher partnership during the school closures in different ways. Some of the stakeholders mentioned that the relationship between teachers and parents weakened due to school closures, whereas others noted that connections between teachers and parents were strengthened during the pandemic, with parent-teacher interactions improving through online communication tools. A stakeholder also underlined that a strong connection between parents and teachers played a protective role in education and contributed to children’s learning during the pandemic. The changing nature of interactions between parents and teachers also led to negative experiences for some teachers. A few stakeholders mentioned that some teachers were interrupted by parents during their online classes, or had to navigate online requests and questions from parents outside their teaching hours. Although research in Turkey has not documented the effects of the pandemic on parent-teacher communications or partnerships specifically, evidence from other countries suggests that both teachers and parents were left with novel responsibilities, which had some positive effects on their relationship with one another with more frequent communication as well as frustration and confusion.
Teachers faced a double disadvantage with mounting responsibilities during the pandemic. An in-depth interview study with 17 teachers in K-12 education has shown that the stress and anxiety experienced by teachers during the pandemic have intensified due to the increased workload.  Helping students to engage in learning during remote education was a challenge for many teachers. Another survey study with 3743 teachers in K-12 education has also shown that a majority of teachers struggled to stay motivated and experienced low student engagement during their online classes.  Similar themes arose during the interviews with stakeholders. According to the interviews, many teachers were at risk of developing mental health problems during the pandemic. Informants underlined that excessive workloads and anxiety experienced by many teachers during the pandemic affected their well-being as well as their teaching quality. Household chores and childcare at home made teaching during the day difficult, especially for female teachers. As a result, some teachers had to change their teaching schedules and hold their classes in the evenings. Although some teachers were able to stay motivated and continue to support their students during school closures, many teachers mentally struggled with witnessing the academic regression of their students. Similarly, teachers also found it difficult to reach their students when their families lacked interest or did not value school education. These experiences led to feelings of inadequacy and loneliness for many. The informant also underlined that local programmes responding to the needs of teachers generated encouraging outcomes, leading to positive effects on teachers’ self-belief and efficacy. Another problem experienced by teachers that was repeatedly highlighted in the interviews was the lack of prioritization of teachers in the vaccination programme. A representative from one teachers’ union in Turkey, for example, mentioned that schools were open before the vaccination programme reached all the teachers in the country, putting some of their lives at an increased risk.
The centralised education system in the country made it difficult for headteachers and teachers to implement needs-based measures in schools. Evidence from interviews suggests that the centralised nature of the education system in Turkey prevented schools from responding to the local needs of children and families in a timely manner. Many stakeholders mentioned that the educational needs of children in rural areas were not met due to the restrictions that should not apply to some of the more underpopulated villages in Turkey. Stakeholders argued that monitoring for the virus in schools had been relatively easy in some locations, which would have allowed the education to continue as usual, especially when most children did not have access to the internet or digital devices. The location-sensitive measures, however, came into effect in the later stages of the pandemic in March 2021. The period of location-specific measures only lasted for 6 weeks ending with a combination of distance and face-to-face education measures depending on school level. According to the stakeholders, changes to the school regulations during the pandemic caught school administrators and teachers unprepared to respond expeditiously. The uncertainty caused by these changes also put a strain on teachers’ well-being.
The staff and educational needs of ECE institutions were not attended to sufficiently by the policy response during the pandemic, leaving many teachers and schools feeling alone. In a study conducted with 24 ECEC teachers, in addition to technological problems, many teachers identified parents' lack of interest and prejudices to online classes as the main barriers to ECEC attendance during the pandemic. Stakeholders ascribed the low enrolment rate in preschools to the lack of unconditional free access to early childhood education in Turkey.
Early childhood educators struggled to apply their teaching online due to the nature of teaching for this age group. According to the interviews with the stakeholders, conducting learning activities and playing online was largely not possible in preschool classes as the majority of activities required physical interactions and joint engagement with children. Similarly, the absence of an online learning platform tailored for early childhood education made teaching more difficult during school closures. This problem is also reflected in parents’ experiences with their young children. An informant underlined that many parents had problems with maintaining their children’s attention during online classes and struggled to find activities to support their children’s learning. Furthermore, younger children may have been more affected by the changing nature of education during the pandemic. Interviews undertaken show that many families prioritised the education of their older children in the household. Not having a sufficient number of digital devices at home was one of the leading reasons that explained this behaviour, although informants also mentioned witnessing an absence of understanding of the importance of ECE among parents. In these cases, teacher effectiveness and creative initiative played an important role. Stakeholders, for example, mentioned that many early childhood educators took the initiative to meet children in small groups in open public spaces and parks to continue their teaching.
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Press release on Survey on Information and Communication Technology Usage by Children, 2021. Accessed through: https://data.tuik.gov.tr/Bulten/Index?p=Survey-on-Information-and-Communication-Technology-Usage-by-Children-2021-41132&dil=2  MEB. (2021). Sayılarla Uzaktan Eğitim [Infographic]. MEB. https://yegitek.meb.gov.tr/www/sayilarla-uzaktan-egitim/icerik/3225  KII3, KII12  KII5, KII11  Göçmen, E., Kalender, G., Foggo, H., Yüksel, S., Şener, Ş., & Duman, Ş. (2020). Pandemi Döneminde Derin Yoksulluk ve Haklara Erişim Araştırması. İstanbul: Turkey  TUIK (2021). İstatistiki Bölge Birimleri Sınıflaması 1.Düzey'e göre evden genişbant bağlantı ile İnternet erişimi olan hanelerin oranı, 2011-2021. Accessed from: https://data.tuik.gov.tr/Bulten/Index?p=Hanehalki-Bilisim-Teknolojileri-(BT)-Kullanim-Arastirmasi-2021-37437#:~:text=Geni%C5%9Fbant%20ile%20%C4%B0nternete%20eri%C5%9Fim%20sa%C4%9Flayan%20hanelerin%20oran%C4%B1%202021%20y%C4%B1l%C4%B1nda%20%92,ba%C4%9Flant%C4%B1%20ile%20%C4%B0nternete%20eri%C5%9Fim%20sa%C4%9Flad%C4%B1.  Yalçın, A. ve Korkmaz, N. (2021). ‘‘Çalışmalıyım, çünkü para lazım’’ pandemide artan çocuk işçiliği araştırma raporu Diyarbakır örneği. Rengarenk Umutlar Derneği.  MEB. (2020). Covid-19 Pandemisi ile Mücadele Süreci Milli Eğitim Müdürlüğü Raporu. MEB. Gaziantep: Turkey  Ibid.  KODA. (2021). Köy Halkının Gözünden Pandemide Köylerin Ve Köy Okullarinin Durumu. Istanbul: KODA  Ibid.  Ibid.  KII1  KII1  Inter-Agency Protection Coordination Turkey. (2020). Protection Sector Needs Assessment. Ankara: Turkey  Tokyay, M. (2020, April 17). Uzaktan eğitim dijital uçurumu derinleştiriyor mu? İnterneti olmayan öğrenci nasıl eğitim alacak? Euronews. Retrived from: https://tr.euronews.com/2020/04/17/uzaktan-egitim-dijital-ucurumu-derinlestiriyor-mu-interneti-olmayan-ogrenci-nas-l-egitim-a  Deri Tekstil ve Kundura İşçileri Derneği. (2021). Pandemi'de Mülteci Çocuk İşçiliği Raporu. Izmir: Turkey  ASAM. (2021). COVID-19 Pandemisinin Türkiye’deki Uluslararası ve Geçici Koruma Altındaki Çocuklar Üzerinde Etkileri. Ankara: Turkey  KII8  KII8  Gökçen, C. (2020). Pandemi’de Derin Yoksullukla Mücadele. Derin Yoksulluk Ağı. İstanbul: Turkey  Ibid  Ibid  Başak Kültür ve Sanat Vakfı (BSV), Small Projects Istanbul (2020), Sulukule Gönüllüleri Derneği (SGD), Tarlabaşı Toplum Merkezi (TTM) (2021) Covid-19 sürecinde İstanbul’un Farklı Yerlerinde Çocukların HAklarına Erişimi- Eğitim Hakkı, Yetişkinler için Final Raporu. Retrieved from: http://covid19cocukhaklariizleme.org/uploads/pdf/821cf3d3992f479ad85fde101a31e67f.pdf  Inter-Agency Protection Coordination Turkey. (2020). Protection Sector Needs Assessment. Ankara: Turkey  ASAM. (2021). COVID-19 Pandemisinin Türkiye’deki Uluslararası ve Geçici Koruma Altındaki Çocuklar Üzerinde Etkileri. Ankara: Turkey  Deri Tekstil ve Kundura İşçileri Derneği. (2021). Pandemi'de Mülteci Çocuk İşçiliği Raporu. Izmir: Deri Tekstil ve Kundura İşçileri Derneği  Ibid  KII8  KII8  KII8, KII1, KII10  KII1, KII8, KII7, KII10, KII11  KII10, KII7  ERG. (2020). Öğrenciler ve Eğitime Erişim Eğitim İzleme Raporu 2020. Istanbul: Turkey  Çelik, S. & Kardaş İşler, N. (2020). Göç Mağduru Çocukların Covid-19 Salgını Sürecindeki Öğrenme Deneyimleri . Milli Eğitim Dergisi , Salgın Sürecinde Türkiye'de Ve Dünyada Eğitim , 783-800 . DOI: 10.37669/milliegitim.783048 Aydın, O. (2021). Covid 19 Salgın Sürecinin Çocuklar Üzerindeki Etkileri. Temel Eğitim Araştırmaları Dergisi, 2021; 1 (2): 163-195 (e-ISSN 2791-6391); DOI: 10.29228/tead.11  Orhan, F., Yilmaz, B. M., Zeren, G., Sensoy, O. & Atakisi, B. (2020). COVID-19 Sürecinde Uzaktan Öğretme Süreci İle İlgili İlk ve Ortaöğretim Öğrencilerinin Algıları ve Duygularına Yönelik Bir Analiz, TUBITAK, Program Kodu: 1001 Proje No: 120K193  Ibid  Ibid  KII11, KII6  TEDMEM. (2021). COVID-19 Sürecinde Eğitim: Uzaktan Öğrenme, Sorunlar ve Çözüm Önerileri. Ankara: Turkey  Ibid  KII5  KII5, KII6  KII13, KII4, KII1  Orhan, F., Yilmaz, B. M., Zeren, G., Sensoy, O. & Atakisi, B. (2020). COVID-19 Sürecinde Uzaktan Öğretme Süreci İle İlgili İlk ve Ortaöğretim Öğrencilerinin Algıları ve Duygularına Yönelik Bir Analiz, TUBITAK, Program Kodu: 1001 Proje No: 120K193  Çelik, S. & Kardaş İşler, N. (2020). Göç Mağduru Çocukların Covid-19 Salgını Sürecindeki Öğrenme Deneyimleri . Milli Eğitim Dergisi , Salgın Sürecinde Türkiye'de Ve Dünyada Eğitim , 783-800 . DOI: 10.37669/milliegitim.783048  Ibid  Ibid  KII9, KII4  KII9, KII8  Yalova Rehberik ve Araştırma Merkezı. (2021). Öğrenclern Covd-19 Pandemsnden Etklenme Düzeyler Araştırması. [Infographic]. Yalova Rehberik ve Araştırma Merkezı. https://yalovaram.meb.k12.tr/meb_iys_dosyalar/77/01/363601/dosyalar/2021_06/04142335_OYrencilerin_SalgYndan_Etkilenme.pdf  ibid  ASAM. (2021). COVID-19 Pandemisinin Türkiye’deki Uluslararası ve Geçici Koruma Altındaki Çocuklar Üzerinde Etkileri. Ankara: Turkey  Ibid  Türk Tabipleri Birliği. (2020). Pandemide Okul Sağlığına İlişkin Uzman Görüşleri. Ankara: Türk Tabipleri Birliği  KII9, KII3, KII6  KII9  KII3  KII9, KII4  KII5  KII9  KII9  KII3, KII6, KII12  MEB. (2021). Bazı Basın Yayın Organlarında ''3 Bin Çocuk Anneleriyle Cezaevinde" Şeklinde Yayınlanan ve Gerçekleri Yansıtmayan Haberlerle İlgili Basın Açıklaması. MEB. Retrieved from: https://cte.adalet.gov.tr/Home/SayfaDetay/basin-aciklamasi09032021045708  Yaşam Hakları Derneği. (2021). Anneleriyle Birlikte Mahpus Olan Çocuklar. Istanbul: Yaşam Hakları Derneği  Ibid  TUIK. (2020).Ceza İnfaz Kurumu İstatistikleri, 2019. Accessed from: https://data.tuik.gov.tr/Bulten/Index?p=Prison-Statistics-2019-33625  Turkey iHealth.. Why Are Turkish Teenagers Victim Of Drug Addiction?. Turkey iHealth. Retrieved from: https://turkeymedicals.com/teenagers-addiction  TUIK (2021). İstatistiklerle Çocuk, 2020. Accessed from: https://data.tuik.gov.tr/Bulten/Index?p=Istatistiklerle-Cocuk-2020-37228  Bir Gün. (2020, September 15). Koruma altındaki çocuklara takip. Bir Gün. etrieved from: https://www.birgun.net/haber/koruma-altindaki-cocuklara-takip-315628  KII5, KII13, KII3, KII12  OECD (2019). Results from PISA 2018 Turkey Country Note. Paris: OECD. Retrieved from: https://www.oecd.org/pisa/publications/PISA2018_CN_TUR.pdf  OECD (2019). Results from PISA 2018 Turkey Country Note. Paris: OECD. Retrieved from: https://www.oecd.org/pisa/publications/PISA2018_CN_TUR.pdf MEB (2019). PISA 2018 Türkiye Ön Raporu. Ankara: Turkey. Retrieved from: https://www.meb.gov.tr/meb_iys_dosyalar/2019_12/03105347_PISA_2018_Turkiye_On_Raporu.pdf  OECD (2019). Results from PISA 2018 Turkey Country Note. Paris: OECD. Retrieved from: https://www.oecd.org/pisa/publications/PISA2018_CN_TUR.pdf  Ibid.  TEDMEM. (2021). Türkiye’nin TIMSS 2019 performansı üzerine değerlendirme ve öneriler (TEDMEM Analiz Dizisi 8). Ankara: TEDMEM  4th grade children with “high” learning resources are those that have more than 100 books at home, who have their own room and internet connection at home, whose parents report that children have more than 25 books and that at least one of the parents have a university degree and at least one has works as a professional employee. 4th grade children with “very low” learning resources are those that have less than 25 books at home, who do not have their own room or internet connection at home, whose parents report that children have 10 books or less and that none of the parents have a university degree and none works as a professional employee or owns a small business.  8th grade children with “high” learning resources are those that have more than 100 books at home, who have a supportive learning environment at home, and whose parents report that at least one of the parents have a university degree. 8th grade children with “very low” learning resources are those that less than 25 books at home, who do not have a supportive learning environment at home, and whose parents report that none of the parents have a university degree.  Simone Lehrl, Maria Evangelou & Pam Sammons (2020) The home learning environment and its role in shaping children’s educational development, School Effectiveness and School Improvement, 31:1, 1-6, DOI: 10.1080/09243453.2020.1693487  Lehrl, S., Evangelou, M., Sammons, P. (2020). The home learning environment and its role in shaping children’s educational development. School Effectiveness and School Improvement 31(1), 1-6. doi:10.1080/09243453.2020.1693487  The Scottish Government. (2010). Impact of the Home Learning Environment on Child Cognitive Development: Secondary Analysis of Data from ‘Growing Up in Scotland’. Aminipour, S., Asgari, A., Hejazi, E., & Roßbach, H. G. (2018). Home Learning Environments: A Cross-Cultural Study Between Germany and Iran. Journal of Psychoeducational Assessment, 38. doi:10.1177/0734282918778465  Melhuish, E.C., Sylva, K., Sammons, P., Siraj-Blatchford, I., Taggart, B., & Phan, M. (2008) Effects of the Home Learning Environment and preschool center experience upon literacy and numeracy development in early primary school. Journal of Social Issues, 64, 157-188.  Lehrl, S., Ebert, S., Blaurock, S., Rossbach, H.-G., & Weinert, S. (2019). Long-term and domain-specific relations between the early years home learning environment and students’ academic outcomes in secondary school. School Effectiveness and School Improvement, 1–23. doi:10.1080/09243453.2019.1618346  Lehrl, S., Linberg, A., Niklas, F., & Kuger, S. (2021). The Home Learning Environment in the Digital Age—Associations Between Self-Reported “Analog” and “Digital” Home Learning Environment and Children’s Socio-Emotional and Academic Outcomes. Frontiers in Psychology, 12.  Caldwell, B. M., & Bradley, R. H. (2016). Home Observation for Measurement of the Environment: Administration Manual. Tempe, AZ: Family & Human Dynamics Research Institute, Arizona State University.  Todd, P. E., & Wolpin, K. I. (2007). The Production of Cognitive Achievement in Children: Home, School, and Racial Test Score Gaps. Journal of Human Capital, 1(1), 91–136. doi:10.1086/526401  Kuger, S., Marcus, J., & Spiess, C. K. (2019). Day care quality and changes in the home learning environment of children. Education Economics, 27(3), 265-286. Todd, P. E., & Wolpin, K. I. (2007). The Production of Cognitive Achievement in Children: Home, School, and Racial Test Score Gaps. Journal of Human Capital, 1(1), 91–136. doi:10.1086/526401  Ministry Interior of Turkey Presidency of Migration Management (2022). Temporary Protection Statistics. Accessed through https://en.goc.gov.tr/temporary-protection27 UNHCR (2021). Turkey Fact Sheet September 2021. Accessed through: https://www.unhcr.org/tr/wp-content/uploads/sites/14/2021/10/Bi-annual-fact-sheet-2021-09-Turkey-1.pdf  TUIK. (2022). Press release on Address Based Population Registration System Results, 2021. Accessed through: https://data.tuik.gov.tr/Bulten/Index?p=Adrese-Dayali-Nufus-Kayit-Sistemi-Sonuclari-2021-45500 Note that the population size in the official statistics reported here does not include Syrians under temporary protection.  In DHS the question is “Does the household have internet connection?” The question does not emphasize or distinguish between mobile connection or fixed connection.  For the dimension “mother knows Turkish”, for children whose mother is interviewed her knowledge of Turkish is taken into account, for children whose mother is not interviewed, the variable takes 1 if any of the interviewed adult females knows Turkish. For the last three dimensions, again if the mother of the child is interviewed her answer is taken into account, if not, and there are other interviewed adult females, mode of their answers is taken into account.  Note that in all of the analysis in this section DHS 2018 Turkish and Syrian samples are used and for children with a constructed HLEQI. DHS 2018 Turkish sample includes 7,792 children, and the sample used in this analysis is reduced to 6,569 children due to having missing dimensions of home learning environment. The Syrian sample is also reduced from 3,326 to 3,084 due to the same reason.  According to the EUROSTAT’s definition a person is considered as living in an overcrowded household if the household does not have at its disposal a minimum number of rooms equal to: one room for the household; one room per couple in the household; one room for each single person aged 18 or more; one room per pair of single people of the same gender between 12 and 17 years of age; one room for each single person between 12 and 17 years of age and not included in the previous category; one room per pair of children under 12 years of age. The definition can be reached via the following link: https://ec.europa.eu/eurostat/en/web/products-datasets/-/TESSI175  These three questions are asked in the “Women’s status module” in the Women Questionnaire, to gather information about who is doing the household chores in the women’s households and are not asked specifically for each child.  Asset index and asset quintiles are constructed separately for the Turkish and Syrian samples, using the information on ownership of various assets. Hence bottom 20% of the Syrian sample is based on the asset index for the Syrian sample only. The asset index is constructed using the information on availability of the following items: LED/LCD TV, computer, deep freezer, gas/electric oven, microwave oven, dishwasher, garbage dispenser, washing machine, drying machine, iron, vacuum cleaner, home theatre, tea/coffee machine, kettle, generator, blender, paid TV services, satellite TV, internet, air conditioner, commercial vehicle, tractor, car/truck.  Kuhfeld, Megan and Beth Tarasawa. (2020). The COVID-19 slide: What summer learning loss can tell us about the potential impact of school closures on student academic achievement April 2020. Available online at https://www.nwea.org/content/uploads/2020/05/Collaborative-Brief_Covid19-Slide-APR20.pdf Kuhfeld, Megan, James Soland, Beth Tarasawa, Angela Johnson, Erik Ruzek and Jing Liu. (2020). Projecting the potential impacts of COVID-19 school closures on academic achievement. EdWorkingPaper No. 20-226.  The World Bank, UNESCO and UNICEF (2021). The State of the Global Education Crisis: A Path to Recovery. Washington D.C., Paris, New York: The World Bank, UNESCO, and UNICEF.  Engzell, P., Frey, A., & Verhagen, M. D. (2020). Learning inequality during the COVID-19 pandemic.  Sabates, R., Carter, E., & Stern, J. M. (2021). Using educational transitions to estimate learning loss due to COVID-19 school closures: The case of Complementary Basic Education in Ghana. International Journal of Educational Development, 82, 102377.  Wealth index (WEALTH) that was already constructed and included in PISA 2018 data file is used in these calculations.  MEB. (2021). Statistical Yearbook 2020/21. Ankara: Turkey  ERG. (2021). Eğitim İzleme Raporu 2021, Öğrenciler ve Eğitime Erişim. Istanbul: Turkey  TUIK. (2020). Press release on Survey Child Labour Force Statistics, 2019. Retrieved from: https://data.tuik.gov.tr/Bulten/Index?p=Child-Labour-Force-Survey-2019-33807  Turkish sample includes 7,792 children, and the sample used in this analysis is reduced to 6,569 children due to having missing dimensions of the home learning environment. The Syrian sample is also reduced from 3,326 to 3,084 due to the same reason. Hence the samples are composed of children with a constructed HLEQI. In Panel A, the school drop out circle includes children who already dropped out, the child labour circle includes children who already live in a household with child labour and low HLEQI circle includes children whose HLEQI values are below the mean HLEQI value of the children aged 6-17 in the Turkish sample which is 61.7 (out of 100). In Panel B, the school drop out circle includes children who already dropped out and also children at risk of school dropout (i.e. children who are attending school but whose predicted score for school attendance is below 0.6). The child labour circle includes children who already live in a household with child labour and also children at risk of child labour (i.e. children who are those not living in a HH with child labour but whose predicted score for living in a HH with child labour is above 0.4). low HLEQI circle includes children whose HLEQI values are below the mean HLEQI value of the children aged 6-17 in the Turkish sample which is 61.7 (out of 100).  Tosun, N., Mihci, C., & Bayzan, Ş. (2021). Challenges Encountered by In-Service K12 Teachers at The Beginning of The Covid-19 Pandemic Period: The Case Of Turkey. Participatory Educational Research, 8(4), 359-384.  Ibid.  İra, N., Yıldız, M., Yıldız, G., Yalçınkaya-Önder, E., & Aksu, A. (2021). Access to information technology of households and secondary school students in Turkey. Information Development, 02666669211008949.  Tosun, N., Mihci, C., & Bayzan, Ş. (2021). Challenges Encountered by In-Service K12 Teachers at The Beginning of The Covid-19 Pandemic Period: The Case Of Turkey. Participatory Educational Research, 8(4), 359-384.  Aral, N., & Kadan, G. (2021). Pandemi Sürecinde Okul Öncesi Öğretmenlerinin Yaşadiklari Problemlerin İncelenmesi. Kırşehir Ahi Evran Üniversitesi Sağlık Bilimleri Dergisi, 1(2), 99-114.  KII12, KII13, KII3  Aytaç, T. (2021). The Problems Faced by Teachers in Turkey during the COVID-19 Pandemic and Their Opinions. International Journal of Progressive Education, 17(1), 404-420.  Yüksel, E. A. (2021). Sinif Öğretmenlerinin Covid-19 Salgini Sürecinde Çevrim İçi Ders-Uzaktan Eğitim Deneyimlerinin İncelenmesi. Ulakbilge Sosyal Bilimler Dergisi, 9(57), 291-303.  KII 12  MEB. (2020, October 13). Türk Eğitim Tarihinin En Büyük Öğretmen Eğitimi Çalişmasini Yapiyoruz. MEB. Retrieved from: https://www.meb.gov.tr/turk-egitim-tarihinin-en-buyuk-ogretmen-egitimi-calismasini-yapiyoruz/haber/21795/tr  MEB. (2020, April 09). Öğretmenler İçin de "Uzaktan Eğitim" Başladi. MEB. Retrieved from: http://www.meb.gov.tr/ogretmenler-icin-de-uzaktan-egitim-basladi/haber/20667/tr MEB. (2020, November 05). Öğretmenlerin Ara Tatildeki Mesleki Gelişim Eğitimi, Uzaktan Yapilacak. MEB. Retrieved from: https://www.meb.gov.tr/ogretmenlerin-ara-tatildeki-mesleki-gelisim-egitimi-uzaktan-yapilacak/haber/24483/tr  Karabay, B. (2021). Pandemi süreci eğitimin öğretmen gözüyle bir yıllık değerlendirmesi. Eğitim-İş. Ankara: Turkey  Eğitim Sen. (2021). 2020-2021 Eğitim-Öğretim Yılında Eğitimin Durumu. Ankara: Turkey.  Karabay, B. (2021). Pandemi süreci eğitimin öğretmen gözüyle bir yıllık değerlendirmesi. Eğitim-İş. Ankara: Turkey  Eğitim Sen. (2021). Eğitim-Sen Uzaktan Eğitime Yakından Bakıyor. Ankara: Turkey.  Ibid  KII3, KII12, KII4  Aral, N., & Kadan, G. (2021). Pandemi Sürecinde Okul Öncesi Öğretmenlerinin Yaşadiklari Problemlerin İncelenmesi. Kırşehir Ahi Evran Üniversitesi Sağlık Bilimleri Dergisi, 1(2), 99-114.  KII1  KII10, KII6  Karabay, B. (2021). Pandemi süreci eğitimin öğretmen gözüyle bir yıllık değerlendirmesi. Eğitim-İş. Ankara: Turkey  Ibid  OECD. (2021). The State of Global Education. Paris: OECD  KII1, KII5, KII6, KII13  KII3  KII5  KII5  KII5, KII3, KII1  KII3 & KII9  KII5  KII5, KII6, KII1  KII8, KII4, KII13  KII11  KII3, KII5  Stelmach, B. (2020). It Takes a Virus: What Can Be Learned About Parent-Teacher Relations from Pandemic Realities?. University of Alberta  ERG. (2021). Eğitim İzleme Raporu 2021: Öğretmenler. Istanbul: ERG  Ibid.  Eğitim Sen. (2021). Eğitim-Sen Uzaktan Eğitime Yakından Bakıyor. Ankara: Turkey.  KII5, KII1  KII3, KII5  KII3  KII1  KII1  KII1  KII1  KII3  KII1, KII6, KII10  KII11, KII1  Gündoğmuş, Y., Kasap, S., Erdoğan, M., N. (2021, February 28). Bakan Ziya Selçuk: Liselerde yüz yüze sınavlarda illerin durumuna göre karar verilecek. Anadolu Ajans. Retrieved from: https://www.aa.com.tr/tr/egitim/bakan-ziya-selcuk-liselerde-yuz-yuze-sinavlarda-illerin-durumuna-gore-karar-verilecek/2159955  TEDMEM. (2022). 2021 eğitim değerlendirme raporu (TEDMEM Değerlendirme Dizisi 8). Ankara: Türk Eğitim Derneği.  KII4, KII10, KII11, KII3, KII6  KII10, KII11  Aral, N., & Kadan, G. (2021). Pandemi Sürecinde Okul Öncesi Öğretmenlerinin Yaşadiklari Problemlerin İncelenmesi. Kırşehir Ahi Evran Üniversitesi Sağlık Bilimleri Dergisi, 1(2), 99-114.  Aral, N., & Kadan, G. (2021). Pandemi Sürecinde Okul Öncesi Öğretmenlerinin Yaşadiklari Problemlerin İncelenmesi. Kırşehir Ahi Evran Üniversitesi Sağlık Bilimleri Dergisi, 1(2), 99-114.  KII5, KII4  KII9