Education in Europe should be inclusive and fair. Inclusive for giving all students a chance to receive a good quality education and fair – it should not be influenced by students’ socio-economic background (European Commission/EACEA/Eurydice, 2020; Frønes et al., 2020).

OECD PISA results show that, with variations, students’ achievements are related to socio-economic status (SES) (OECD, 2019). In Latvia, the SES level of a school has a greater influence on students’ achievement than  SES of students’ family (Geske et al., 2015), therefore students should have equal opportunities to access schools with high SES, regardless of their socio-economic background.

In 2021 a new Law on Administrative Territories and Populated Areas came into force in the Republic of Latvia. To reduce fragmentation, the number of municipalities and State cities was reduced from 119 to 43. Regional reform as a regional development issue might help students from families with lower SES get closer to schools with higher SES. To assure that more schools have high SES in municipalities, it is necessary to reorganize and optimize the school network and student achievement analysis can be used to make evidence-based decisions. As the majority of schools in Latvia are municipal schools, municipalities share the responsibility for assuring the quality and equity of education within the schools of their governance.

Over the last few years, Latvia has taken part in many international large-scale assessment (ILSA) programs e.g. IEA (International Association for the Evaluation of Educational Achievement), ICCS (International Civic and Citizenship Education Study), PIRLS (Progress in International Reading Literacy Study) and TIMSS (Trends in International Mathematics and Science Study), as well as in OECD PISA (Programme for International Student Assessment). ILSA data has a crucial advantage in comparison with national assessments: it’s free from any local influence so the results are independent and comparable regardless of the changes that take place in the current country. It provides data for research on a variety of issues as well as has strong methodological foundations, which allows secondary analysis for a better understanding of trends in education (Hernández-Torrano & Courtney, 2021).

The main differences in approaches between IEA studies and OECD’s PISA are that IEA studies focus on curriculum based knowledge and skills, as well as samples students according to their grade, while OECD focuses on competencies that will be necessary for student’s adulthood and samples regarding the age (Rocher & Hastedt, 2020).  However, IEA and OECD studies can be merged (Strietholt & Scherer,  2018). Merging data files helps to increase the number of variables and therefore gives a wider range of information as well as gives the possibility to obtain new results (Sarwar et al., 2013). 

Although international data allows the comparison across different education systems and shares the techniques, organizational structures, and policies that can help to improve the existing education system (Cresswell et al., 2015) national assessments are irreplaceable for national education quality and performance analysis within a particular education system, therefore in this particular study, there were used data from both national examinations and ILSA.

Research questions are:

-        How to use ILSA data to evaluate students’ achievement in municipalities?

-        What is the level of education quality in municipalities of Latvia?

Research objectives are:

- to identify how ILSA data can be used for evaluating students’ achievement in municipalities;

- to investigate the quality and equity of education in different municipalities of Latvia.

Achievement data of each ILSA (PIRLS 2016, ICCS 2016, PISA 2018, and TIMSS 2019) study and three centralized ISCED level 3 maturity exams (in Mathematics, Latvian, and English in 2018, 2019, and 2020) were recalculated for every student so that the means are 500 and standard deviations - 100. The overall result for each municipality was obtained by calculating the average value. A similar procedure was implemented for calculating students’ SES in all ILSA studies for each municipality.

The results show a positive and relatively high correlation (R=0.79) between students’ SES and their academic achievement in ILSA at the municipality level. In addition, the study showed a positive correlation between ILSA (ISCED level 1 and ISCED level 2) and centralized maturity exams of ISCED level 3. That proves the validity of the used method. The combined and separate analysis of students’ achievement of ILSA and state maturity exams provides extensive information on differences in the quality of education. Results also show a positive, relatively high correlation (R=0.76) between student achievement and the economic activity of municipalities. The study proved that it is legitimate to combine ILSA and results of state examinations to obtain the assessment of education quality in municipalities.

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