This introductory chapter provides an overview of the report and key educational system features in Eastern Partnership (EaP) countries and economies. It explains the purpose and structure of the report, which includes five chapters and focuses on three substantive topics: student outcomes, equity and learning environment within and outside of schools. The report draws on data from the OECD Programme for International Student Assessment (PISA) as its main sources of evidence. This chapter briefly describes the features of PISA and the methodology used to assess student performance and gather contextual information. It also provides an overview of the key features of EaP countries/economies and their education systems, focusing on the economic context and investment in education, the social and cultural context, and the educational landscape.
Education in the Eastern Partnership: Findings from PISA
Abstract
The Eastern Partnership (EaP) is a joint initiative of the European Union (EU), its member states and five countries in Eastern Europe and the South Caucasus – Armenia, Azerbaijan, Georgia, the Republic of Moldova (hereafter Moldova) and Ukraine.1 It was launched in 2009 and has developed through consultations, summits and agreements. The EaP aims to strengthen and deepen the political and economic relations between EU member states and partner countries, and support sustainable reform processes in EaP countries. The policy agenda adopted for the EaP in 2020 identified five priority goals, with resilience at its core: economy and connectivity, good governance and the rule of law, environmental and climate resilience, support for digital transformation, and fair and inclusive societies (EC, 2020[1]).
While the EaP countries are different in many respects (e.g. population size, language, path to EU membership), they are also similar in important ways (e.g. they transitioned to market economies after the fall of the Soviet Union and currently face challenges of economic growth, diversification and poverty reduction). Education is a central building block of regional and national reform efforts, particularly in strengthening human capital to address the region’s largest development challenges. The role of education in supporting green and digital transitions is especially critical as EaP countries look to equip their populations with the skills necessary for these emerging sectors. While there are signs of improvements in educational participation and learning outcomes over the last decades, educational progress has not been equitable across all population groups and many students still struggle to master basic competencies. Addressing these challenges will be crucial to the region’s economic development, social prosperity and integration into Europe.
This report aims to identify strengths, challenges and effective practices to improve student learning, equity and well-being in selected EaP countries/economies, drawing on data from the OECD Programme for International Student Assessment (PISA).2 The EaP countries/economies forming part of the report are Baku in Azerbaijan, Georgia, Moldova and 18 of the 27 regions in Ukraine. The development of their participation in PISA is described further below. Armenia has not yet participated in PISA, although participation is underway for PISA 2025. Throughout the report, any reference to EaP countries and economies, as well as the EaP average, therefore specifically pertains to Baku, Georgia, Moldova and Ukrainian regions.
Large-scale assessments such as PISA provide a rich evidence base to drive necessary changes and improvements in education systems. The insights in this report are particularly relevant for secondary school as PISA primarily collects data at this level of education. It seeks to generate policy ideas for the region and individual education systems by comparing the performance of EaP countries/economies against selected international benchmarks. These benchmarks are chosen based on indicators of relevance and aspiration. For example, for the analysis of student outcomes in Chapter 2, Estonia and Singapore are used as aspirational benchmarks in addition to the OECD average, while for Chapter 3 on equity, Finland and Japan are used as benchmarks. The average for EU countries is typically similar to the OECD average on a number of indicators. For selected indicators, the report also highlights countries that have seen the greatest improvements or declines over time and identifies countries with performance levels similar to those of EaP countries/economies to help position their results.
The analysis focuses on three substantive topics as follows:
Chapter 2 focuses on student outcomes, including learning outcomes, students’ feelings of safety and belonging at school, and expectations for education and work.
Chapter 3 examines equity in students’ educational opportunities, exploring how these vary by student background and access to educational resources.
Chapter 4 investigates the learning environment within and outside of schools, including aspects such as learning during school closures, teacher support, disciplinary climate, truancy, digital device usage and parental involvement.
Chapter 5 synthesises the key conclusions from these chapters in a way that is intended to inform policy discussions in EaP countries/economies (Figure 1.1).
The report focuses on data that are relevant to all systems. Therefore, the analysis does not cover data that do not meet this criterion or significantly influence the overall educational performance in EaP countries/economies. This includes differences between students in public and private schools, between students in general and vocational tracks, and students from a non-immigrant and immigrant background:
Students in private schools: Fewer than 2% of 15-year-old students attend private school in Baku, Moldova and Ukrainian regions. This is higher only in Georgia, where 9% of students attend private school, but still only half of the OECD average of 18%.
Students in vocational education: Except for Ukrainian regions, where 19% of students are enrolled in a vocational programme, only 6% of students in Moldova and no students in Baku and Georgia attend such a programme. Across OECD countries, 13% of all 15-year-old students in the PISA sample are in a vocational programme.
Students with an immigrant background: While students with an immigrant background represent 13% of the sample across OECD countries, they constitute only 1% in Georgia and Ukrainian regions, 2% in Moldova and 4% in Baku.
What is PISA? How have EaP countries and economies participated?
What is PISA?
PISA is an international survey that tests 15-year-old students3 worldwide in the competencies essential for participating fully in society and the economy. With its focus on this age group, PISA offers a comprehensive picture of students’ cumulative learning experiences from early childhood up to the age of 15. These experiences encompass all aspects of a student’s life, including schooling, home education and other external influences. This survey forms the basis of this report.
First implemented in 2000, PISA has been conducted every three years. The eighth iteration of the assessment, initially scheduled for 2021, was postponed to 2022 in response to the disruptions caused by the COVID-19 pandemic. The pandemic posed significant challenges to educational systems globally, affecting the implementation of the PISA 2022 assessment. Some countries and economies struggled to meet PISA technical standards for student sampling during this period. These specific countries and economies are marked with an asterisk throughout this report. Further details regarding these sampling issues are provided in Box 1.1.
PISA 2022 collected data from 81 countries and economies. The test was originally planned to take place in 2021 but was delayed by one year due to the COVID-19 pandemic. The exceptional circumstances throughout this period, including lockdowns and school closures, led to occasional data collection difficulties. While the vast majority of countries and economies met PISA’s technical standards,1 a small number did not.
In prior PISA rounds, countries and economies that failed to comply with the standards could face exclusion from the main part of reporting. However, given the unprecedented situation of undertaking a survey during a pandemic, PISA 2022 results include data from all participating education systems, including those for which sampling issues were identified.
Thirteen adjudicated entities (i.e. countries, economies and regions within countries) did not meet one or more PISA sampling standards. Canada, Ireland, New Zealand, the United Kingdom (excluding Scotland) and Scotland (United Kingdom) submitted technically strong analyses, indicating that estimates may have significant bias due to low response rates (below PISA standards). Australia, Denmark, Hong Kong (China), Jamaica, Latvia, the Netherlands, Panama and the United States did not meet one or more PISA sampling standards and it is uncertain if there is more than minimal bias based on available data at the time. Caution is necessary when interpreting the estimates for these entities, some of which are used as benchmarks in this report.
Source: OECD (2023[2]), PISA 2022 Results (Volume I): The State of Learning and Equity in Education, https://doi.org/10.1787/53f23881-en.
How have EaP countries/economies participated in PISA?
Since its inception, global participation in PISA has expanded considerably. From 43 countries/economies in the first assessment in 2000, participation grew to 81 by 2022.4 Among these, EaP countries/economies have progressively increased their engagement, as shown in Table 1.1.
Georgia and Moldova began their participation in 2009 and have participated in four assessments since, except for the 2012 cycle. Azerbaijan joined PISA for the first time in 2006 but has only participated with its capital city, Baku, since PISA 2018. Ukraine was the last EaP country/economy to join, starting in 2018. However, following Russia’s full-scale invasion of Ukraine, only 18 of the country’s 27 regions were able to participate in the 2022 assessment.5 Box 1.2 provides detailed information on Ukraine’s participation.
Ukraine participated in PISA for the first time in 2018. For PISA 2022, there were significant changes in the survey implementation, most notably reduced participation following the start of the full-scale war. The 2022 survey was meant to include Ukraine’s entire educational system. However, because of the war, only 18 out of the 27 jurisdictions were able to participate.
PISA technical standards permit countries/economies to exclude up to 5% of the target population – 15-year-old students enrolled in Grade 7 or higher – either by excluding schools or students within schools. In 2022, 16 countries and economies did not meet this standard.
In Ukraine, the exclusion rate was very high, at 36.1%, when computed with respect to the original sampling frame, covering the entire country.1 However, the high exclusion rate was primarily due to the inability to complete survey operations successfully in regions severely affected by the war. Results from the 18 regions that participated in PISA 2022 can be deemed reliable for reporting. However, comparisons with previous data should be made with caution and with due consideration of the differences in target populations. The exclusion rate in Ukrainian regions was 14.9%.
The 18 regions that participated include Cherkasy, Kirovohrad, Poltava, Vinnytsia, Chernihiv, Kyiv, Sumy, the city of Kyiv, Zhytomyr, Odesa, Chernivtsi, Ivano-Frankivsk, Khmelnytskyi, Lviv, Rivne, Ternopil, Volyn and Zakarpattia oblasts.
The nine jurisdictions that could not participate were Dnipropetrovsk, Donetsk, Kharkiv, Luhansk, Zaporizhzhia, Kherson, Mykolaiv oblasts, the Autonomous Republic of Crimea, and the city of Sevastopol.
1. Detailed data on PISA target population and samples is available at: https://www.oecd-ilibrary.org/sites/53f23881-en/1/4/2/index.html?itemId=/content/publication/53f23881-en&_csp_=de697f9ada06fe758fbc0d6d8d2c70fa&itemIGO=oecd&itemContentType=book#tablegrp-d1e14601-fbbb2a911b.
Participation of EaP countries/economies in PISA cycles
Note: Azerbaijan as a whole country participated in PISA 2006 and 2009; only Baku participated in PISA 2018 and 2022. Georgia and Moldova conducted the PISA 2009 assessment in 2010 as part of PISA 2009+. In Ukraine, almost the entire country participated in PISA 2018; only 18 of the country’s 27 regions participated in PISA 2022.
How does PISA measure student performance?
What does PISA assess?
PISA assesses the extent to which students have acquired the knowledge and skills in reading, mathematics and science required to succeed in life. Each PISA cycle prioritises one of these domains, dedicating nearly half of the total testing time to it. In the 2022 cycle, mathematics was the core area of focus.
PISA assesses what students know and examines how well students can extrapolate from what they have learned and apply their knowledge in real-life settings. To establish clear expectations for what it means to be proficient in each subject, PISA develops subject-specific assessment frameworks (OECD, 2023[2]). Annex 1.A provides a detailed overview of the 2022 assessment for mathematics. This information can help readers understand what it means to be proficient in mathematics in PISA. When interpreting PISA scores, readers can keep in mind that a 20-point difference is approximately equivalent to the typical annual learning gain of a 15-year-old, representing the average pace of learning for students of that age across participating countries (Avvisati and Givord, 2023[3]).
How does PISA assess?
PISA has transitioned from a paper-based to a computer-based assessment format in almost all participating countries/economies, including all EaP countries and economies (Table 1.2). Moldova and Ukraine adopted the computer-based mode of administration for the first time in 2022. Although efforts are made to make results from the two modes comparable, interpreting trends requires caution. Factors such as students’ motivation levels can influence performance trends.
The assessment lasts a total of two hours for each student. In this time, they tackle a mix of multiple-choice and open-ended questions. Taking advantage of the flexibility of computer-based assessment, the mathematics and reading sections apply a multi-stage adaptive approach. This method adjusts the difficulty of test items based on a student’s performance in preceding sections. Test items are grouped around passages that set out real-life scenarios. The full battery of test items is over 15 hours of content across the different domains, though each student only encounters a portion of these test items.
Notes: Georgia took the PISA 2022 creative thinking questionnaire but not the creative thinking assessment. All other EaP countries/economies took both the creative thinking assessment and questionnaire.
The PISA 2022 assessment was administered on computers in 77 out of 81 countries/economies. The creative thinking assessment was conducted in 74 countries (10 of them only took the questionnaires but did not conduct the assessment) and the financial literacy assessment was conducted in 20. The information and communication technology (ICT) questionnaire was implemented in 52 countries/economies, the parent questionnaire in 17, the teacher questionnaire in 18 and the well-being questionnaire in 15 countries/economies.
What additional information does PISA gather?
In addition to information about students’ knowledge and competencies, PISA collects extensive information about students’ educational context, including the learning environment and student attitudes, dispositions and experiences at home and school. These additional data help to better understand educational outcomes, learning quality and equity. All participating countries and economies, including EaP systems, distribute school and student questionnaires to collect these data.
Optionally, countries and economies can collect data on teaching practices through the teacher questionnaire and parental involvement via the parent questionnaire. In the EaP region, Baku and Georgia implemented the teacher questionnaire, with Georgia also opting to distribute the parent questionnaire.
In the context of the COVID-19 pandemic, the PISA 2022 cycle included a Global Crises Module in the school and student questionnaires. This addition aimed to capture insights into how education was managed during school closures. The findings from this module are discussed in Chapter 4 of the report. Readers should keep in mind, however, that many students did not respond to questions about COVID-19 school closures (i.e. high non-response rates) placed at the end of the student questionnaire, limiting these data’s representative nature.
Analyses of EaP countries/economies
In partnership with the European Commission and the United Nations Children's Fund (UNICEF), the OECD has analysed education systems in EaP countries/economies through both quantitative data analyses and more qualitative methods in recent years. Insights from this other work inform this report and help contextualise data analysis findings. Additionally, secondary research and data, such as from the United Nations Educational, Scientific and Cultural Organization (UNESCO), the World Bank and non‑governmental organisations, are used to add perspective.
The OECD and UNICEF have analysed PISA 2018 data for all four EaP countries/economies reviewed in this report as part of a broader report for Eastern Europe and Central Asia. The latter also covered six additional countries such as Belarus, Kazakhstan and Türkiye and analysed aspects that are not the focus of this report, such as student sorting across different programmes, learning time and teacher qualifications (OECD/UNICEF, 2021[4]). A separate report – developed by the OECD, the European Commission and UNICEF – analysed education in the Western Balkans (OECD, 2020[5]).
Besides PISA, EaP countries/economies participate in other OECD surveys. Georgia participated in the 2018 Teaching and Learning International Survey (TALIS). Ukrainian regions participated in the 2023 Survey on Social and Emotional Skills.
Together with UNICEF, the OECD has gathered more qualitative insights into the EaP education systems through dedicated studies, namely for Georgia in a Review of Evaluation and Assessment in Education (Li et al., 2019[6]), for Moldova through EU-funded policy perspectives on staff professional development and curriculum resources (OECD, 2023[7]) and the evaluation of vocational education and training (OECD, 2023[8]) and for Ukraine through an integrity assessment (OECD, 2017[9]). For Ukraine, the OECD has also published a number of policy briefs in response to the war, specifically with a focus on supporting Ukrainian refugee students.6
In each participating country, PISA assesses a representative sample of students aged between 15 years 3 months and 16 years 2 months at the time of the assessment and having completed at least 6 years of formal schooling. PISA only assesses young people attending an educational institution. The learning outcomes of 15-year-olds who are out of school are not captured in PISA.
Notes: Data cells are coloured when they contain information that makes it possible to calculate a statistical test for differences between countries (i.e. this is not the case in the first three rows of the table).
Percentage or value or difference in indicator is significantly above other EaP countries/economies.
Percentage or value or difference in indicator is significantly below other EaP countries/economies.
1. Weighted number of participating students, i.e. the number of students in the nationally defined target population the PISA sample represents.
2. The PISA Coverage Index 3 informs how well the PISA sample covers the 15-year-old-population. Low values in this index may be attributed to 15-year-olds who are no longer enrolled in school or who were held back in primary school. Coverage Index 3 may also be lower due to student exclusions from the PISA test and dropouts during the school year.
Socio-economically disadvantaged students among the 25% of students with the lowest values on the ESCS index in their country or economy.
3. Socio-economically advantaged students among the 25% of students with the highest values on the ESCS index in their country or economy.
Source: OECD (2022[10]), PISA 2022 Database, https://www.oecd.org/en/data/datasets/pisa-2022-database.html.
A two-stage sampling procedure is used within countries to select a sample of at least 150 schools and roughly 42 students within each of those schools. EaP countries/economies assessed a similar number of students, ranging from more than 6 000 in Moldova to almost 8 000 in Baku. Ukrainian regions had the lowest number of participating students with fewer than 4 000 (in 2018, when Ukrainian regions participated in PISA, except those under Russian occupation or controlled by the two self-declared break-away republics in the east of the country, the number of participating students in Ukraine was 5 998). These students represent about 165 000 fifteen-year-olds enrolled in school in Ukrainian regions, 40 000 in Georgia and 30 000 in Baku and Moldova (Table 1.3).
The national context of each country participating in PISA greatly affects the students sampled to participate in the survey. This section discusses some of the key contextual features of EaP countries/economies and how these are reflected in their PISA 2022 student samples (Table 1.3). Readers should keep these contextual factors in mind to interpret the analysis throughout this report. The association between these different contextual factors and students’ learning and well-being are discussed in depth in Chapter 3 (e.g. differences between rural and urban students).
Economic context and investment in education
Wealth and education outcomes
While there is some variation in per capita gross domestic product (GDP) between EaP countries/ economies, EaP countries/economies are less affluent than most OECD countries. EaP countries/ economies had an average GDP per capita of USD 15 620 purchasing power parity (PPP) in 2022, compared to the OECD average of USD 48 388 (Figure 1.2).
Economic development levels should be considered when interpreting results from PISA. Across participating countries and economies, 62% of performance differences in mean mathematics scores between countries in PISA 2022 can be accounted for by national per capita income.
Notes: Data on GDP per capita for Baku refer to the whole country of Azerbaijan and, for Ukrainian regions (18 of 27), refer to the whole country of Ukraine. EaP countries/economies are coloured in red.
* Caution is required when interpreting estimates because one or more PISA sampling standards were not met (see Box 1.1 in this chapter).
Source: OECD (2022[10]), PISA 2022 Database, https://www.oecd.org/en/data/datasets/pisa-2022-database.html.
Figure 1.2 shows the performance of education systems relative to their per capita GDP. The EaP school systems perform around what would be expected from their levels of economic development. Some EaP systems perform better than other countries with similar or higher income levels. For example, Moldova surpasses Colombia and Costa Rica in mathematics despite having a lower GDP. Meanwhile, Mongolia, with an even lower GDP, still does better than Baku, Moldova and Georgia in the same subject. This indicates the potential for policy to help overcome resource limitations.
Spending and education outcomes
Overall educational spending per student in all EaP countries/economies is considerably lower than on average across OECD countries.7 Spending among EaP systems is highest in Ukraine (USD 37 798) and Moldova (USD 35 686) and lowest in Azerbaijan (USD 16 237) and Georgia (USD 14 950).
EaP countries/economies also perform roughly what would be expected based on their spending on education per student. Nevertheless, Baku and Georgia perform slightly higher than might be expected from their expenditure levels.
Total education expenditure on educational institutions per student and mathematics performance
Note: Educational spending refers to countries’ cumulative spending per student from the age of 6 up to 15 after accounting for PPP. Data on educational expenditure for Baku refer to the whole country of Azerbaijan and, for Ukrainian regions (18 of 27), refer to the whole country of Ukraine. EaP countries/economies are coloured in red. Only countries and economies with available data are shown.
* Caution is required when interpreting estimates because one or more PISA sampling standards were not met (see Box 1.1 in this chapter)
Source: OECD (2022[10]), PISA 2022 Database, https://www.oecd.org/en/data/datasets/pisa-2022-database.html.
As the PISA data suggest, educational spending makes a difference in student learning up to a certain point (Figure 1.3). That is, one can observe a relationship between spending and student achievement, but as spending levels increase, how funds are used plays an even more important role in shaping how well students learn (OECD, 2017[11]; OECD, 2023[12]). EaP countries/economies are among those where increased spending could make a difference. However, this does not imply that the limited available resources should not be used efficiently.
Social and cultural context
Students’ economic, social and cultural status (ESCS)
An important concern for all countries is how students from disadvantaged backgrounds perform compared to their advantaged peers. This indicates the extent to which the school system provides equal opportunity to students regardless of socio-economic circumstances.
In EaP countries/economies, the average student typically has a lower socio-economic status than students in OECD countries (Table 1.3). PISA measures this through an ESCS index, which considers factors such as home possessions (indicative of family wealth), parents’ education level and their employment. The ESCS index is standardised so that the OECD average is zero with a standard deviation of one. A lower ESCS value indicates lower average socio-economic status, while a higher value indicates higher socio-economic status.
Across EaP systems, the average socio-economic status of students is broadly similar in Baku, Georgia and Moldova. While slightly higher in Ukrainian regions, it is still well below the OECD average.
One can also consider how the most socio-economically advantaged and disadvantaged students in each EaP country compare socio-economically with their counterparts in other countries. Across EaP systems, the most advantaged students8 are found in Georgia and Ukrainian regions. On average, the most advantaged students in EaP countries/economies are less advantaged than the most advantaged students in OECD countries (Table 1.3).
Conversely, across EaP systems, the most disadvantaged students9 are in Moldova. Compared to the most disadvantaged students across OECD countries, the most disadvantaged students in EaP countries/economies experience greater socio-economic disadvantage.
Inequality in students’ socio-economic status can be measured by the difference in socio-economic status between advantaged and disadvantaged students. Socio-economic inequality is higher (by a small but statistically significant margin) in EaP countries/economies than on average across OECD countries, except for Ukrainian regions. Here, socio-economic inequality is lower than the OECD average and lower than in other EaP countries/economies (Table 1.3).
Socio-economic inequality among 15-year-old students, however, does not necessarily mirror patterns of income inequality at the country level. This is partly because Baku and Ukrainian regions in PISA 2022 are not measures of the entire country. Among EaP countries, according to the Gini index10 for 2020, income inequality is the highest in Georgia (Gini index = 40.21), followed by Moldova (30.17) and Ukraine (29.64). The lowest income inequality is measured in Azerbaijan (19.21). For comparison, the Gini index for high-income countries was 38.01 in 2020 (UNU-WIDER, 2022[13]).
Geographic location
Research has shown that providing quality learning environments in rural environments can be more challenging. Rural schools may struggle to offer diverse and rich educational experiences because of limited resources and isolation from peer institutions (Echazarra and Radinger, 2019[14]; OECD, 2018[15]).
In EaP countries/economies, with the exception of Baku, a relatively high proportion of students attend schools in rural areas, as defined by PISA (populations of 3 000 people or fewer). Moldova has one of the highest percentages of students attending rural schools among the countries/economies participating in PISA 2022 – 39% – and the highest among EaP countries/economies.
The low number of rural students in Baku reflects the fact that only Baku, the main metropolitan area of the country, took part in PISA 2022; in PISA 2009, when students from all of Azerbaijan took the test, the share of students attending a school in rural areas was 32% (OECD, 2010[16]).
Again, data at the country level help further contextualise levels of rurality in EaP countries. Similar to OECD countries, the share of the rural population of the total population has been declining in EaP countries/economies since the 1960s. The decline has been steepest in Ukraine. However, the rural population’s importance remains much larger in all EaP countries/economies than in OECD countries, with 30% in Ukraine, 39% in Georgia and 42% in Azerbaijan, compared to 18% in OECD countries. Levels of rurality in Azerbaijan and Georgia are similar to those in OECD countries like Poland and Slovenia (40% and 44% respectively). In Moldova, the share of the rural population has changed little since the 1990s: more than half of Moldovans lived in rural areas in 2023 (57%) (World Bank, 2023[17]).
Source: World Bank (2018[18]), Rural Population (% of Total Population) - Azerbaijan, Georgia, Ukraine, Moldova, OECD Members, Poland, Türkiye, https://data.worldbank.org/indicator/SP.RUR.TOTL.ZS?locations=AZ-GE-UA-MD-OE-PL-TR&skipRedirection=true.
Linguistic diversity
Linguistic diversity is an important factor in EaP education systems and is more prevalent than diversity based on immigrant background. The percentage of students who speak a different language at home compared to the one in which they sat their PISA assessment is highest in Baku and Ukrainian regions (in both economies, it is higher than on average across OECD countries) and lowest in Georgia and Moldova (in both countries, it is lower than on average across OECD countries). The share of students with an immigrant background is less than 5% in all EaP countries/economies whereas, on average, across OECD countries, it is 13%. Box 1.3 provides details on the languages spoken in EaP countries.
In PISA, linguistic diversity can be captured through two different indicators. On the one hand, the PISA student questionnaire that each student responds to after taking the PISA test included asking students what language they usually spoke at home. Based on this information, the percentage of students who speak at home a language that is different from the language in which they took the PISA assessment is derived. On the other hand, PISA has information on the language in which each student took the PISA test. The latter is used in this box.
Official and minority languages and language of assessment in PISA 2022
In Azerbaijan, Azeri is the official language, Russian is widely spoken as a second language and minority languages include Avar, Georgian, Kurdish, Lezgin and Talysh. In PISA 2022, eight out of ten students in Baku took the PISA test in Azeri, while the rest took it in Russian.
In Georgia, Georgian is the official language, Russian is widely spoken, and minority languages include Armenian, Azeri, Mingrelian and Svan. In PISA 2022, 93% of students took the PISA test in Georgian, 5% in Azeri, while the rest took it in Russian.
In Moldova, Romanian is the official language, Russian is widely spoken, and minority languages include Gagauz, Russian and Ukrainian. In PISA 2022, 82% of students took the PISA test in Romanian, while the rest took it in Russian.
In Ukraine, Ukrainian is the official language, Russian is widely spoken, and minority languages include Belarusian, Bulgarian, Crimean Tatar, Gagauz, Hungarian, Romanian, Russian and others. There is evidence that language preferences have changed in the context of war in Ukraine, but all these languages remain current in the country. In PISA 2022, 99% of students in Ukrainian regions took the PISA test in Ukrainian, while the rest took it in Russian.
Source: Minority Rights Group (n.d.[19]), Homepage, https://minorityrights.org/.
Educational landscape
Coverage rates (percentage of 15-year-olds enrolled in school)
The coverage of an education system, that is, the share of the school-age population enrolled in schools, can be considered an important metric of educational inclusion. Inclusion refers to the objective of ensuring that all students, particularly those from disadvantaged backgrounds or traditionally marginalised groups, have access to high-quality education and attain at least a baseline level of skills. High coverage rates are important as students who leave formal schooling before age 15 tend to perform less well on cognitive tests than those who remain at school (OECD, 2023[20]).
In PISA, the coverage of an education system is measured by the proportion of the national population of 15-year-olds (enrolled and not enrolled in school) represented by the PISA sample (referred to as Coverage Index 3). PISA only assesses students who are enrolled in Grade 7 or above in an educational institution, be this full- or part-time, public or private, academic or vocational. A low Coverage Index 3 can be related to issues such as a high rate of early school leaving, grade repetition or exclusion from the PISA test (e.g. due to special needs or limited assessment-language proficiency).
Among EaP countries/economies, the coverage of the education system is virtually universal in Moldova, high in Georgia and relatively low in Baku (Table 1.3). In Moldova, coverage is similar to that of countries such as Finland, Singapore and the United Kingdom (95% and higher). It is noticeable that Moldova has such a high coverage among 15-year-olds despite having compulsory education end at age 16; this is earlier than most other EaP countries. In Georgia, coverage is similar to that of countries such as Kosovo (86%) and Mongolia (87%). In Baku, coverage is similar to that of Türkiye (74%) and Romania (76%).
In Ukrainian regions, education system coverage measured by PISA was very low in 2022 (64%). However, this should be interpreted with caution in light of the administration of PISA in the context of war, as highlighted in Box 1.2. Also, students had to move due to the war, which made the population statistics outdated. In PISA 2018, the education system coverage in Ukraine was 87%.
Student grade level and compulsory education
To ensure comparability of the PISA target population across countries, PISA assesses students at a specific age rather than grade level. This approach is used because the grade level is linked to the structure of school systems, which varies significantly from country to country. The 15-year-olds in PISA may be distributed across different grade levels in different countries/economies. In some systems, students may be in lower secondary education, while in others, they may be in upper secondary education. In addition, 15-year-olds may move between these two levels and thus, students in the PISA sample may be from lower secondary and upper secondary.
In Georgia and Ukrainian regions, significantly more students are in upper secondary education when they take PISA – 93% and 97% – compared to the OECD average of 60%. In Baku, 66% of students were in upper secondary education during testing (Table 1.3). In Azerbaijan, Georgia and Ukraine, 15-year-old students who have not repeated a grade are expected to be enrolled in Grade 10, which marks the beginning of upper secondary education in these countries (Figure 1.4). The high percentage of 15-year-olds below the typical grade level may stem from issues in student progression, like grade repetition or delayed entry into primary school. In Baku’s case, the primary reason is often a delayed start to primary education. Over 30% of students reported starting school at age 7 or later, despite compulsory schooling beginning at age 5. Grade repetition rates are low, with only 3.8% of 15-year-olds repeating a grade during their schooling (compared to the OECD average of 8.9%).
By contrast, in Moldova, most of the students who took PISA are enrolled in lower secondary education (Table 1.3). In Moldova, 15-year-olds who have not repeated a grade are expected to be enrolled in Grade 9, the last year of lower secondary school (Figure 1.5). Students in Moldova are typically one grade level “behind” 15-year-old students in other EaP countries/economies because primary school starts one year later: in Moldova, children enter primary school at age 7, whereas in other EaP countries/ economies, the age of entry into primary school is 6 (this is also the most typical in OECD and non-OECD countries participating in PISA).
The above means that by the age of 15, students in Moldova have been exposed to a school curriculum for a shorter period than students of the same age in other countries. However, Moldova’s education system compensates for this apparent weakness by having children enter pre-primary education earlier. This level is compulsory in Moldova starting at age 2, whereas in other EaP countries/economies, no year of pre-primary education is compulsory. In addition, pre-primary education lasts longer in Moldova (four years) than in other EaP countries/economies and typical OECD and non-OECD countries. This is reflected in higher enrolment rates: according to student reports for PISA, 81% of 15-year-olds in Moldova had attended pre-primary education for more than 3 years, whereas in other EaP countries/economies, the corresponding shares are much lower.
Theoretical starting age and theoretical duration of pre-primary, primary and secondary education for students in general programmes
Notes: Theoretical starting age is when students are expected to enter an education level according to national law or regulation. The theoretical duration is the number of years of schooling a student is expected to complete before graduating from an education level according to law or regulation.
Countries and economies are shown in descending order of the number of compulsory years of schooling.
1. Typical is based on modal values across countries and economies.
Source: OECD (2022[10]), PISA 2022 Database, https://www.oecd.org/en/data/datasets/pisa-2022-database.html.
PISA develops subject-specific frameworks that define what it means to be proficient in mathematics, reading and science. These frameworks organise the subject according to key processes, contents and contexts that are measured in the assessment. The mathematics framework was updated for PISA 2022.
The PISA 2022 mathematics framework considers that being mathematically proficient is less about reproducing routine procedures and more about using mathematical reasoning, which requires a clear understanding of foundational mathematical concepts. Mathematics competency is defined as students’ capacity to reason mathematically and formulate, employ and interpret mathematics to solve problems in various real-world contexts. It includes concepts, procedures, facts and tools to describe, explain and predict phenomena.
Students at all levels of mathematics proficiency can demonstrate mathematical reasoning. At high levels of proficiency, students understand that a problem is quantitative in nature and can formulate complex mathematical models to solve it. At lower proficiency levels, mathematical reasoning is displayed by students who may not know much about formal mathematics but can intuitively spot a problem and solve it in informal ways using elementary mathematics.
To develop students’ ability to reason mathematically, schools and education systems need to go beyond teaching and evaluating routine mathematical procedures: students need to be ready to address unfamiliar real-world problems and apply the mathematical tools they have in new ways.
In addition to the overall mathematics scale, PISA 2022 developed mathematics subscales for specific mathematical processes and mathematical contents.
Mathematical processes
PISA 2022 considers four distinct mathematical processes. For each of these, a distinct mathematics subscale is developed. Each PISA mathematics test item is then designed to capture one of the processes. Students are not necessarily expected to use all four to respond to each test item.
The four process subscales include the following:
Mathematical reasoning.
Formulating situations mathematically.
Employing mathematical concepts, facts and procedures.
Interpreting, applying and evaluating mathematical outcomes.
Mathematical content
PISA 2022 also captures competencies in mathematics in four content domains and has again developed a subscale for each of these domains.
Quantity: Number sense and estimation; quantification of attributes, objects, relationships, situations and entities in the world; understanding various representations of those quantifications and judging interpretations and arguments based on quantity.
Uncertainty and data: Recognising the place of variation in the real world, including having a sense of the quantification of that variation and acknowledging its uncertainty and error in related inferences. It also includes forming, interpreting and evaluating conclusions drawn in situations of uncertainty. The presentation and interpretation of data are also included in this category, as well as basic topics in probability.
Change and relationships: Understanding fundamental types of change and recognising when they occur in order to use suitable mathematical models to describe and predict change. Includes appropriate functions and equations/inequalities as well as creating, interpreting and translating among symbolic and graphical representations of relationships.
Space and shape: Patterns; properties of objects; spatial visualisations; positions and orientations; representations of objects; decoding and encoding of visual information; navigation and dynamic interaction with real shapes as well as representations, movement, displacement and the ability to anticipate actions in space (OECD, 2023[2]).
References
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← 1. In line with the European Council Conclusions of 12 October 2020 and in light of Belarus’ involvement in the launch of Russia’s full-scale invasion of Ukraine, recognised in the European Council Conclusions of February 2022, the European Union has stopped engaging with representatives of Belarus public bodies and state-owned enterprises.
← 2. The report uses the terms “countries and economies” or “countries/economies” to account for the fact that in PISA 2022, only certain jurisdictions within Azerbaijan and Ukraine participated in the assessment.
← 3. In PISA reports, “15-year-old students” is used as a shorthand. However, in practice, the PISA target population is based on an age window: PISA assessed students who were at least 15 years and 3 complete months old and who were at most 16 years and 2 complete months old at the beginning of the assessment period, with a tolerance of 1 month on each side of this age window.
← 4. This includes 37 out of the 38 OECD countries, with Luxembourg being the exception, and 44 partner countries and economies.
← 5. Statement of the OECD Council on the Russian aggression against Ukraine, 24 February 2022, https://www.oecd.org/en/about/news/press-releases/2022/02/statement-of-oecd-council-on-the-russian-aggression-against-ukraine-.html
← 6. For more information, see the OECD Ukraine hub at https://www.oecd.org/ukraine-hub/en/.
← 7. Educational spending refers to countries’ cumulative spending per student from the age of 6 up to 15 after accounting for PPP.
← 8. Socio-economically advantaged students are those among the 25% of students with the highest values on the ESCS index in their country or economy.
← 9. Socio-economically disadvantaged students are those among the 25% of students with the lowest values on the ESCS index in their country or economy.
← 10. Gini index measures the extent to which the distribution of income (or, in some cases, consumption expenditure) among individuals or households within an economy deviates from a perfectly equal distribution. A Gini index of 0 represents perfect equality, while an index of 100 implies perfect inequality.