Tens of thousands of school leavers took part in a survey for participants of the External Independent Testing 2016 (further on – EIT-2016). For the first time this survey allows to evaluate the impact of socio-economic factors on educational attainments.
Predictably, a noticeable gap between urban and rural as well as between ordinary and “premium” schools can to a great extent (yet not fully) be attributed to the difference in social background of school leavers. In particular, parents’ education plays an important role. Among other factors influencing the results, there is parent’s career field and position, having parent(s) working abroad, availability of books at home, size of a class, need to go to school situated in another locality, possibility to use a private tutor while preparing for testing, gender, etc. The survey also takes into account individual and motivational factors, which are considered significant. As an unexpected result, the absence of relation between material well-being of a family and EIT points has been found. This study does not give all the answers. More research in this field, similar yet methodologically improved are welcomed every year in order to see the trends and to prove the significance of mentioned factors. Still, as the first step, such a research project is of utmost value for better understanding of the current situation with the access to high quality education in Ukraine and of the ways of transformation of education politics.
An attempt to decrease the impact of socio-economic background and environment of children on their educational attainments is one of the priorities of the politics of education of developed countries. This is what the concepts of equality of secondary education as well as equal access to education refer to. In the conditions of competitive access to higher education and meritocratic selection system, equality in secondary education means that every child, no matter what their social background and environment are, has equal chances to continue education and their education attainments depend only on their abilities, inclinations and diligence. This way secondary education can compensate socio-economic inequality and make modern societies fairer.
In order to increase equality of education system in Ukraine, it is essential, first, to determine how equal secondary education in Ukraine is now. It is essential to find out how educational attainments are distributed and whether there is relation between these attainments and socio-economic factors. It is possibly the first time when we are able to do such a research. This became possible owing to a survey for participants of the EIT-2016 organized by the Ukrainian center for evaluation of the quality of education using the questionnaire prepared by the researchers from the Institute of education analytics and CEDOS (the methodology of the present study is shown in the Appendix 1).
We have educational results of all the school leavers (11th grade) in Ukrainian language and literature based on the external independent testing (EIT) of knowledge. This allowed us to analyze these results and the relations they have with some social factors without being influenced by self-selection. In the previous years when only those who wanted to get higher education took the EIT such self-selection used to limit the possibility to make conclusions concerning education equality. The EIT results in other subjects, math and history of Ukraine, in particular, still need to be analyzed with limitations as not all the school leavers take these tests. Besides, it is crucial to remember that the EIT is not obligatory for the students who got full secondary education in professional-technical and higher education institutions. According to the State statistics service, almost 40% of school leavers after the 9 th grade choose not to continue education in the 10th grade (49% in the rural area).
In the present text, we are focusing on the points the students got in Ukrainian language and literature and in math, which is the most popular subject in non-humanities. Unfortunately, we only have answers from those participants of the survey who passed the test (scored the minimum amount of points). Therefore, the average score in the sampling is somewhat higher than among all the participants of the EIT this year (according to the data from the Ukrainian center for evaluation of the quality of education). It does not prevent us, however, from analyzing the relative impact of some factors on the final score.
It is worth noting that this is not the first analysis of a survey of participants of the EIT-2016: the report of the Institute of education analytics offers an extensive descriptive statistics that takes into account all the subjects in which the test was taken.
The role of locality and of school type
The type of locality and of school are among the most popular factors listed as influencing educational attainments of school leavers. These are also the most visible factors as one can find the information about them in the standard EIT data. From year to year, scores of students from urban area are significantly higher than those of the rural students, and students of gymnasiums, lyceums, and similar premium schools show better results than representatives of ordinary schools. If we compare only “similar” students, for example, only the school leavers from ordinary schools in urban and rural area excluding gymnasiums, the factor of urban area remains influential. The same applies to the “school type” factor.
Even though the type of locality and of school mark the difference in educational attainments, they cannot explain it. The popular assumptions concerning the causes of this inequality are lower qualification of rural teachers and material conditions of schools, on the one hand, and better teachers practicing effective teaching methods with the better school equipment in the urban area, in gymnasiums and lyceums particularly, - on the other. Less often one can hear that specialized schools, gymnasiums, and lyceums have different study plans. According to these study plans children have more academic hours to grasp major subjects. What is even more important, the Ukrainian system of education allows the parents to choose educational institutions (schools). It also allows specialized schools, gymnasiums and lyceums to select the best students from the other schools. Considering the fact that the children studying in these “premium” institutions already had the best educational attainments it is difficult to say whether it is due to higher quality of education or simply due to preselection, their EIT results are so high. It is also necessary to explain the academic attainments of the children, since apart from skills and inclinations the environment has certain impact upon them. One should ask whether the parents have invested their time and resources in children’s development during the first years of their life, whether the children had access to pre-school education, what the quality of this education was, whether the children could adopt from their parents skills needed for further studies such as concentration of attention, self-discipline, interest in surrounding world. The answers to these questions depend on social and economic capital a family possesses. Parents’ education, occupation, size of incomes, access to learning support materials, and leisure are related to educational attainments of children practically in all the countries.
Until now in Ukraine there was no possibility to study the relations between social and economic situation of children and their educational attainments. This is why the survey of EIT participants 2016 has such a great significance.
Without taking in consideration any other factors, studying in an urban school increases an average score of an EIT participant by 11 points in Ukrainian language (151 against 162) and by 14 points in math (138 against 152). Studying in a premium school adds to the average score 13 for the test in Ukrainian language (156 against 169) and 14 in math (144 against 158). Adding two factors allows to see even greater gaps: an urban premium school leaver has 18-point advantage in Ukrainian language and 21 points more in math compared to an ordinary rural school leaver.
Such a comparison of average scores does not take into account numerous factors. We can use many of those thank to the survey results by using them as variables in multiple regression analysis. Linear regression allows seeing individual impact of each variable (i.e. of each factor) independent from other variables upon the result (in this case – score in Ukrainian language or math). In other words, regression analysis shows how many points each variable “adds” or “deducts” provided the other conditions are equal. Such analysis does not allow making definite conclusions with regard to the scale of impact of different variables, because there is no survey that would clarify all the important variables without an exception. Nevertheless, regression analysis is a step forward compared to a simple statistic comparison (“an average urban school score compared to an average rural school score” and so forth). In the present text, we demonstrate general context received from descriptive statistics as well as regression analysis results (for the full list of variables used for analysis and their coefficients see Appendix 2). The regression results are marked bold in the text in order to better see the difference between descriptive and regression analysis.
Using larger amount of variables in regression analysis causes decrease of importance of the city and school type for the final score. In the Ukrainian language test an urban school gives 1.9 and a premium school 6 point advantage. In the math test these factors are more important: an urban school adds 3.8 points, premium – 7.3 points more. We could only take into account for analysis the variables available due to the survey, therefore, it is possible that adding new factors will allow in future to show that it is even less influential whether it is a premium and urban school or not.
Which exactly additional variables, or socio-economic and motivation factors, explain the gap between rural and urban, premium and ordinary schools? We will try to identify some most important ones.
Individual and motivation factors
Beyond any doubt, personal diligence and motivation of each student plays a large role in the definition of their grades. Social factors cannot fully account for EIT results, as there are rural school leavers with the excellent grades and students from urban gymnasiums who fail the exams. Some questions from the survey show the contribution of individual and motivation factors to the results of an EIT participant. In particular, the students were asked where they plan to continue their education after the test and whether they had prepared for the EIT in advance.
This year EIT in Ukrainian language was obligatory for all the 11 th grade school leavers independent from their plans for the future. Naturally, vast majority of those who passed the test and got the chance to participate in this survey were going to enter the university, some – to a foreign one. Somewhat more than 12% only answered that they were planning to get vocational education or not to continue studies at all. Not surprisingly, these 12% had, on average, much lower results: the gap is almost 30 points in Ukrainian language and 23 points in math. Regression analysis shows that, all other conditions being equal, the intention to enter a university adds 11.8 points to Ukrainian language and 6.5 points to math results. This is, therefore, the most important motivation variable in the survey: the school leavers have much more serious attitude toward the test when their result has impact on the possibility to enter the higher education institution they have chosen.
There is correlation, naturally, between this variable and social factors. Among rural students 21% answered that they are not planning to enter a university compared to 9% of the students in the cities. Similar numbers for ordinary and premium schools: 15% in ordinary schools do not plan higher education while it is only 5% for premium schools. The probability of university plans grows together with the parents’ level of education increase: 95% of those who have both parents with higher education plan to go for higher education against 76% of those whose parents have only secondary education diplomas. Availability of a personal computer (not shared with other family members) and a smartphone (the indicators of family’s relative material well-being) increases probability of higher education plans, not that dramatically, though. As it will be seen further, the education of the parents has less impact on children’s education attainments than their income.
Another variable illustrating seriousness of one’s intentions to enter university is whether the EIT participants had prepared for the text beforehand (separate question was asked for each subject). For the test in Ukrainian language prepared 81% of the students and only 43% for the math. Those who had prepared beforehand received 19 points more in Ukrainian language and 8 points more in math. In regression analysis, preparation added 9.4 points to Ukrainian language and 8.6 points to math. Similar to the intentions to enter university, the preparation for EIT beforehand correlates positively with the parents’ education, availability of personal books, in other words, with so-called cultural capital of a family.
Among specific preparation for the test activities the best results come from the preparation with a private tutor (also when this was a teacher from the same school). A tutor adds 5.1 points to Ukrainian language and only 0.9 points to math, according to regression analysis. Other preparation activities have insignificant positive and negative impact, while sometimes without consistency (for example, preparation courses for the higher education institutions have negative impact for Ukrainian language and positive for math). Such kind of variables’ behavior does not allow making definite conclusions about their role. Instead, the answer “prepared with parents or relatives” has large negative effect both for Ukrainian language, and for math, which shows rather the lack of preparation. Yet only 3% of the participants specified this option.
Girls pass the EIR better than boys do. In the sampling from the survey, the girls got on average 11 points more in Ukrainian language and 0.3 points more in math. Taking into account other social factors in regression analysis cut the gap in Ukrainian to 7 points, while in math all other conditions being equal the boys have 3.1-point advantage.
Low results in Ukrainian language can be explained by the fact that only 75% of the boys who took part in the survey answered that they prepared to the exam compared to 86% of the girls. In math, on the contrary, the boys prepared more often: 50% against 36%. Another factor important for good results, especially in Ukrainian language, is availability of personal books, apart from textbooks. This also gives advantage to the girls: 77% of the girls in the survey answered they had personal books compared to 62% of the boys. Also somewhat less boys (85% against 89%) mentioned they were going to enter universities after the EIT.
Other factors depending on the family and the locality, of course, are not very different for men and women. We also did not find confirmation for hypothesis that much before school leaving girls are doing better than boys and have higher chances to study in a premium institutions. In fact, same 24% of both boys and girls studied in premium schools.
It is interesting that there are only 47% among the participants of the survey. This does not mean that there are much more girls in Ukrainian schools: the bigger part of boys do not continue studies to full secondary education. According to the State statistics service, boys compose 51% of the 5-9th grades students and only 48% of the 10-11th grade students. It also indicates lower, overall, educational achievements and motivations of the boys. There is no doubt that if the tests were conducted among all 16- and 17-year old youngsters (both those pursuing full secondary degree and not), the gap between girls and boy would be even bigger.
Education of the family
As we discovered, one of the most influential among the social factors is the level of parents’ education. Of course, education of the family has indirect impact on children’s educational attainments. Educated parents understand the value of education better, they can suggest more and help their children more in learning process, they spend their free time not only watching TV but also teach their kids to enjoy reading. Education also correlates positively with family’s well-being, however, in Ukraine, at least so far, this relation is not that strong and many children for not that rich yet very educated families show better results than their schoolmates whose families are better off.
For analysis we divided all the participants in five groups according to the education of their parents: 1. both parents have higher education; 2. only one of the parents has higher education; 3. both parents have vocational or secondary vocational education; 4. one of the parents has vocational or secondary vocational education and the other has secondary education; 5. both parents have secondary education maximum.
On average, a school leaver from the 1st group gets 169 points in Ukrainian language compared to a school leaver from the 5th group. The gap in math is similar – 158 points against 135 points. Taking into account additional variables allows to see how each next educational level of the parents increases children’s results. The 4 th group has 4.7- and 3.8-point advantage over the 5 th group in Ukrainian and math correspondingly; the 3 rd group has over the 5 th group already 7.2- and 5.5.-point advantage; the 1 st group – 10.4 and 11.9 points correspondingly.
As it was already mentioned, parents’ education influences positively the intentions to continue the higher education after testing. There are much more educated parents in the cities than in the rural area : only 16% of students from rural schools have two parents with higher education compared to 37% in the cities. The numbers are the same for ordinary and premium schools – 24% and 47% correspondingly (we compared only those students who live with both parents).
Question to EIT participants about possessing certain material values: own room, own PC, smartphone, etc. also show positive correlation between the education and family’s well-being. For example, 61% of students from the families with secondary education have smartphone or tablet compared to 81% in families with high education level. The things, which could be rather attributed to cultural capital and not necessarily material well-being, such as home library or personal books a school leaver possesses are even more related to the education of the parents.
Parents’ occupation is another factor related to education that can also be considered a part of social or cultural capital of a family. In this case not only a particular profession but also the status and sphere of occupation are important.
With regard to occupation status, on average those participants have the highest EIT results whose parents have stable jobs. The students whose both parents have constant occupation have on average 7 points more in Ukrainian language and 8 points more in math than those whose both parents do not work or are retired (we compared only those who either have both parents or persons acting as parents). Yet, in regression analysis, the occupation status factor fully loses significant influence upon EIT results: these 7-8 points are fully explained with other variables.
Parents’ education has to be particularly important, as the higher their education level is, the higher is probability that both parents work: among the parents with the high education level, in 74% of the cases both have stable occupation compared to 49% in the case of parents with secondary education. There is also a notable difference between urban and rural school leavers (related, most probably, with the difficulties in finding a stable job in rural area).
The sphere of parents’ occupation of the participants of EIT also has an impact upon educational attainments but mostly through education: those, whose parents work in more complex and intellectual fields – public service, transport and communications, financial service, culture and health care – have higher scores.
The lowest scores have those whose parents work in agriculture, industry and construction. The children whose parents work in the area of education (probably, mostly teachers) and in informational technologies area (IT) stand apart. The students whose mother works in education have 167 points in Ukrainian language on average (compared to average 160 points within the sample). Those, whose father works in programming have, on average, 164 in math (compared to 149 within the sample).
The students were also asked which exactly position do their parents occupy with the answer options such as “manager,” “entrepreneur,” “worker,” etc. The best results again are associated with the higher level of education. These are the students, who chose options “specialist” (engineer, lawyer, doctor, teacher, accountant, agronomist, etc.). In regression analysis, we introduced a separate variable for parents-specialists and variable for parents-education employees (in the case of Ukrainian language) and parents from IT field (for the test in math). Our hypothesis was that mentioned fields of parents’ occupation positively influence the results independently from parents’ education variable among the others in analysis. This proved to be true: parents-specialists add 3.6 points to Ukrainian language and 2.8 to math. Educational workers have additional responsibility for 4.4 points in Ukrainian and parents in IT sphere – for 5.2 math points.
To summarize, even though occupational status of parents does not have an independent impact upon the results, particular place of work of a father or a mother can have certain effect on educational attainments of a child. Surely, parents’ employment status is related to education, almost all the education or IT employees have higher education. However, the effect of parents’ occupation seems to be independent on their education level effect.
Completeness of a family
“Family” means different things for different test participants. The most of them mentioned a father and a mother describing their families. 17.3% more live with their mothers and only small part – only with fathers or other relatives. Incomplete family (when one or both parents are absent) negatively influences the results. Moreover, those who live only with the father have 10-point lower score in Ukrainian than participants with both parents (living with a mother only “takes away” 3 points only). Completeness of a family influences also material well-being and attention that parents can give to their children. It is not surprising, therefore, that it also plays role and correlates with such indicators as studying in a premium school and so forth.
However, completeness of a family itself does not have statistically significant impact or all this impact is transferred through other, related factors. Still there is an effect related to the absence of one of parents due to work abroad. Such families are, in general, better off (apparently thank to money transfers) but the results of EIT participants from such families are substantially worse. Only around 5% of participants have parents who work abroad but they are unevenly distributed across the regions: in Zakarpats’ka oblast, 20% of school leavers have parents abroad, in Ivano-Frankivs’ka – 15%, in Ternopil’ska – 11.5%. Parents working abroad is an phenomenon more spread in rural area and in smaller cities.
More often it is a father who works abroad, somewhat less frequently – mother, and even more rare is when both parents are absents. Out of these three hypothetical cases, the worst results come with a mother working abroad. School leavers whose mothers work abroad have 8 points less in Ukrainian language and 8 points less in math than school leavers from families where no one works abroad. Taking in consideration additional variables, mother’s absence due to working abroad has statistically significant effect, taking away 2.3. points in Ukrainian language (there is no effect for math).
One of the questions in the questionnaires was related to specifically prosperity of an EIT participant’s family. They either had to evaluate their families' material well-being using a 5-option scale, starting from “we barely make both ends meet” to “we can afford buying whatever we want.” As a result, 8.5% of respondents placed themselves into the “wealthiest” category, 5% - to the poorest one, and the most of participants - 37% - chose the medium answer. There was no significant correlation, though, between family’s wealth and student’s study results. Without taking into consideration other variables, “middle” students showed even better results. In regression analysis the family wealth indicator does not have any statistically significant effect.
This is one of the least obvious conclusions of the present research, which needs to be clarified. It is highly probable, that the question about one’s family’s well-being was framed not good enough in order to avoid subjective answers. Having parents who work abroad also may have certain effect - these families are often well-off,yet the children there do not pay enough attention to studies due to lack of attention from the parents. Finally, the chances are high that Ukraine (yet) just does not have strong stable correlation between financial and educational or cultural status, to which Western sociologies often refer to. A large group of parents who in the post-Soviet society are educated and care about education of their children - often these are teachers, health care staff, academics - do not have high incomes in Ukraine. Those having high incomes are often successful entrepreneurs who achieved success in our transitional economy often not thank to their education. For example, among the wealthiest EIT participants the most popular occupation of the father is an entrepreneur in big or medium business. In the meantime, their children have EIT results that are almost not different from the average score across the country and are significantly lower than those of the children of “specialists” (i.e. teachers, doctors, etc.).
There were also other questions directly or indirectly related to material well-being of a family. The participants of the survey were asked to answer whether they have such things as a personal desk, personal computer (or computer shared with other family members), own room (or a shared room), smartphone and tablet. The same block contained questions about having a home library and personal books (apart from the text books), but those are less related to the material condition.
Regression analysis showed that having a personal desk and smartphone (or tablet) has insignificant positive influence upon the test results, while having own room, shared room and own computer - insignificant negative influence. These are not obvious and somewhat not obvious results. They can be a consequence of mistakes made in the survey: almost 10% of participants answered that they have own room and, at the same time, shared room with a sibling. This is also the part of the sample that got relatively lower EIT results.
Books and home work
At the same time, having books at home definitely has positive effect. Taking into account additional variables, home library improves EIT result by 2.6 points in Ukrainian language and by 2.6 points in math. Personal books (apart from textbooks) add 5.4 to Ukrainian and 3.4 to math.
Both indicators have positive correlation with the education level of parents of EIT participants. Yet at the same time both show independent effect in regression analysis. Having books at home additionally to parents’ education may indicate serious interest of parents for literature, science, and so on, while, considering that in Ukraine, starting from the 90s, it has been getting easier and easier to receive higher education, just having a higher education diploma does not always mean anything. Buying books for children indicates parents’ desire to invest into children’s intellectual development. Finally, personal books is partially an individual and not a social factor that shows own motivation of a school leaver.
Buying books is a sign of parents’ caring about children’s education showing they pay certain attention to that. There were also some other questions related to parents’ attention, however, they, paradoxically, show somewhat different effect. The participants could answer the question “evaluate how often your parents checked if you made your homework” choosing options from “every day” to “practically never.” And the less often parents control homework, the better children’s results are: even taking into account additional variables, absence of control adds 13 points in Ukrainian as well as in math compared to participants whose parents used to с heck their homework all the time.
It does not necessarily mean, though, that there is a mistake or a paradox. If a student regularly has good grades, there is no need to check her homework. Besides, such an approach tends to increase independence and responsibility level of a student compared to those teenagers who are used to parents’ help or need to be controlled. Therefore, in this particular case parents’ “lack of attention” to children’s education indicates positive educational attainments and not the contrary. It is interesting that not checking homework does not even have significant correlation with parents’ education. It tells us more rather about individual characteristics of a student (she does not need being controlled), than about some distinctive approach educated parents may have.
One more question about attention: “evaluate how often your parents or other relatives asked you what you have learned at school” – does not have statistically significant effect.
In the studies on education, there is no unanimous opinion about influence that class size may have upon the students’ education results. Some researchers argue that small classes are more appropriate for effective learning process as teachers have more time for each student. On the other hand, larger scale research shows correlation between large number of students in a class and good grades. It is not clear whether there is a causal relation in this correlation. Understandably, larger classes are more common for big cities where more parents that are educated live and it is easier to find better teachers. In Ukraine, due to the delay with school network optimization, only 11 students on average study in a class of a rural school compared to 24 in big cities (CEDOS analytics).
There was a question in our survey about the class size. However, it covered only the last for the school leavers, 11th grade and did not cover, therefore, the smallest rural schools where 10-11th grades simply do not exist. In spite of this, there is a big difference between rural and urban classes: 84% of rural students studied in classes with less than 20 students. In the cities, this number is 36%, in big cities – 23%. At the same time 16% of school leavers from big cities had classes with more than 30 students which is practically impossible in rural area.
The education results in the meantime correspond to this correlation. School leavers from the smallest classes where there were less than 10 students have average score in Ukrainian language 150.4 and 137.4 in math. School leavers from the classes with 31-35 students have 164.4 in Ukrainian and 153.5 in math. It is interesting that small category of the EIT participants who studied in classes with more than 35 students (less than 1% of the sample) have on average somewhat smaller score than participants from the previous category (31-35). They are too few, though, to make conclusions, yet these results may indicate negative influence of too large classes even in the cities.
Even though the main source of this variance is obvious – the difference between urban and rural schools and, first of all, between urban and rural parents – small classes have somewhat worse test results even when the analysis is limited to big cities. It is possible that better schools are more popular, therefore, their classes are more crowded. Regression analysis confirms the influence of the class size: school leavers from classes with more than 20 students provided all other conditions are equal have on average 1.5 points more in Ukrainian language and 2.1 point more in math.
It is possible that this influence is caused by variables that we could not take into account in the analysis and class size itself does not influence education results. Still if the influence exists, this is one more argument supporting the need to speed up school network optimization and enlargement of rural schools so that the students do not have to study in half-empty classes lacking good teachers.
Distance to the school
One more indicator showing difference between rural and urban students is the distance they have to cover to get to the school. More and more rural students have to use a bus to get to a school located in neighboring, larger locality. It refers in particular to the 10th and 11th grades as often even quite big village do not have those. Apart from school buses the students use public transport, some take a bicycle, and some are driven to school by their parents who have own cars. The survey participants, who answered “yes” to the question if they studied not in the locality where they lived, also had to specify how they get there.
The survey results do not favor going to school from another locality: the final scores difference is 4.5 points in Ukrainian language and 3.5 points in math giving advantage to the “locals.” However, this difference is for the greater part explained by mostly rural origin of the students. If the schools of the survey participants are grouped according to the size of localities, there is almost no difference in the limits of villages, urban-type settlements, and small cities between “locals” and “non-locals,” because both groups have similar socio-economic status. At the same time, as well as in big cities, the difference between local students and those who have to get to the school every day from smaller localities is more noticeable.
In general, the necessity to commute to a school situated in another locality emerges more often in rural area due to the lack of schools of the I-III degree: more than 20% of all the rural school leavers in the survey studied not in the locality where they lived. For the medium size cities, the number is lower, 8-10%, and then increases again in the big cities. Apparently, the students go to the schools in the big cities not because they do not have schools of higher degree in their localities, but due to the higher quality of schools (in the cities 43% of “non-locals” study in premium schools, compared to 34% of locals).
Among the students who have to commute to the school, the worst results have those who had to use school bus: on average, only 150 points in Ukrainian language and 138.7 in math. Those who used public transport have 158.8 and 149.2 correspondingly, and the school leavers whose parents used own cars had the best results – 162 and 151.7 correspondingly. The difference is substantial, yet the family that have private cars, obviously, have socio-economic status that allows them giving a child better education. In the meantime, the school buses are more common for the smallest villages where the text scores are the worst in principle due to low parents’ education and related factors.
Does the distance to the school and the way of commuting influence in the end the results, considering socio-economic status and other factors? Regression analysis shows that those students who had to travel to another locality to study in the 11 th grade, got in total 1.4 points less in Ukrainian and 0.9 less in math. However, it is not improbable that this difference is caused by rural origin of many of those students, who studied in urban schools (with all the consequences of living in a rural area). We could not take into account this probability, as we only have information about place of studies and not about place of residence of a student.
At the same time specific means of transport, including school bus, does not have statistically significant influence at all. Substantial disadvantage of school leavers that used school buses is fully explained by other factors – rural origin, parents‘ education, and so forth.
Having said that, the distance to school, probably, is important and, when possible, it is necessary to assure a presence of a good school not far from each student. However, the distance effect, in general, is insignificant and does not give additional negative effect itself. This is an important finding as there is an existing fear of possible consequences of the increase of the part of rural students who will use school buses. Although one survey, naturally, is not enough and there should be further research in order to clarify the importance of this factor.
To summarize, in spite of the big role of individual and motivation factors, particularly socio-economic circumstances, which cannot be practically influenced by a student, have a substantial impact on studies results. In other words, in Ukraine there is no assured equality of opportunities in secondary education and, correspondingly, access to higher education is not equal either. The situation when privileged children have higher chance for secondary education of good quality and to higher education will potentially lead only to reproduction and increase of such inequality.
Naturally, nowhere in the world perfect equality of opportunities to access education exists. Family, its material well-being, availability of good schools in the neighborhood and other factors will always play certain role. According to the international research PISA report, socio-economic background explains, on average, 13% of variation in participants’ results. On Ukrainian survey data, socio-economic variables explain around 11% when using similar methodology (method of principle components analysis. However, the set of variables varies; therefore, we still cannot fully compare the results). Alternatively, socio-economic background accounts for 20% in Ukrainian language and 17.5% for math using when using regression analysis (taking into account only “socio-economic” variables).
In other words influence of social factors in Ukraine, probably, is the same or even larger than on average in other countries-participants of PISA. The analysis presented in this text shows what exactly is more or less influential on education attainments. In particular, the material status of a family itself has insignificant or statistically insignificant impact. At the same time parents’ education and their occupational status is much more important. In addition, the place of residence of students plays quite some role: it seems that the schools in rural area tend to be worse, on average, than in the cities. Premium schools, like gymnasiums, play an important role, yet it is not improbable that all their advantage relies on selection of the most talented students at the different stages of studies.
Of course, the students who had prepared additionally for the EIT had much better results. Moreover, the impact of preparations with private tutor is especially important. Which means that the families with better material situation have some advantages. Both serious preparation for the EIT, and intentions to continue studies in a university are two important “individual” factors in our classification. The two factor are also not fully independent on students’ environment. Social expectations – from family, relatives, acquaintances- are different for students in different environment (it depends, in particular, on place of residence and social class). Therefore, even individual factors are, at the same time, social, even though we could not control for relations of individual and social in our research.
We emphasize social factors that much, as these are the things that could be changed with the help of state policies. It is clear that there is no education system capable of making all the children talented or at least diligent to the same extent. Still providing equal opportunities for high-quality secondary education, which would prepare students for higher education or for work in modern technological fields of economy, is the task that state education policy can and has to set. To clarify what exactly the factors influencing educational attainments are and what are the factors behind them is the first step to solve the problems within the system of education.
Appendix 1: Methodology of EIT participants survey
The questionnaire was posted on the web-page of Ukrainian center for evaluation of the quality of education (UCEQE) on the personal pages of participants of the EIT-2016, school leavers of general secondary schools in 2016. Every school leaver after they passed tests in Ukrainian and math was asked to answer the questions from the list.
The questionnaire had five question blocks that were linked to each other by logical connectors and transitions.
А. Completeness of a class. Ways of preparation for the EIT. Plans of a school leaver to continue education.
B. Place of residence and place of studies. How does a school leaver get to the school and how long does it take?
C. Family relations, educations of parents or of persons taking care of a school leaver.
D. Material well-being and relations in a family
E. General information about the participant.
The statistical data collected by the UCEQE after the survey had been completed was transferred to the Institute of education analytics for further analysis.
To process the data logical control of coherence of the answers to questionnaire’s questions and technology of restoring missed answers were used. Apart from that, in order to keep the general aggregate structure, among the participants of the survey the system of weight coefficients was used. The coefficient were calculated according to several groups: region, gender, type of locality, type of an institution.
50 919 school leavers of 2016 took part in the survey. After the results of the EIT in Ukrainian and math were published, the students who did not pass the test did not take the part in survey.