Session Information
09 SES 16 B, Student Contexts, Mobility, Tutoring and Participation
Paper Session
Contribution
Mathematical and reading comprehension skills are extremely important for success in everyday life, which is why it is important to assess them during school age (Grimm 2008). In Hungary, student competence results are examined lot of studies based on various criteria, which may cover the entire population or a specific group (Guld and Csanádi 2020, Ambrusné Magony 2020, Szemerszki 2020). The Hungarian competency assessment is based on the PISA study, which also examines several areas based on several background variables (Hegedűs 2024a). Lot of studies have examined the impact of family background on performance (Borgen et al. 2025), and family involvement in learning and providing the necessary conditions for learning leads to better competency results (Wilder 2014). The language patterns used at home also have an impact on students' school performance, as people from different family backgrounds use different language codes, so disadvantaged children often do not know the common language used in education (Daniele 2021). In addition to family background, there are also gender differences, with girls performing better in reading comprehension and boys in mathematics (Granocchio 2023).
The school maintainer also has a significant impact on children's performance (Kyriakides et al. 2024). In Hungary, children perform better in church-run schools, which is due to the fact that these institutions use entrance exams and select students, often based on their family background (Hegedűs 2024b). There are significant differences between institutions in terms of the extra opportunities they offer children (e.g., extracurricular activities), as well as in the availability and quality of teachers (Rowe 2020). Every of these factors determine how well children perform on tests, as well as the conditions under which disadvantaged children learn. The aim of the education system should be to reduce social differences, but this is not the case in Hungary (Hegedűs 2024b).
Lot of foreign (Jakubowski et al. 2025) and national (Hermann and Molnár 2022) studies have examined student performance and education during the COVID period, with results showing that student performance declined and differences based on social background have increased even more because disadvantaged student groups did not have access to the appropriate information and communication equipment for home learning. Home learning is also influenced by parents' educational attainment, as parents with lower levels of education are less able to help their children (Silinskas & Kikas 2022). Disadvantaged families generally have more children, which makes learning more difficult. Even if information and communication technology equipment is available, they cannot log in to multiple classes at the same time (Mönkediek et al. 2020).
The aim of our current research is to examine the reading comprehension and mathematics results of students in the 2019 sixth-grade student database and the 2022 sixth-grade student database, as well as the differences between the two years. We use trend analysis in our research because we examine the differences between student groups based on the same age group. In our research, we examine how different background variables (e.g., family background, gender, school operator) influence students' reading comprehension and mathematics performance.
Research questions:
What differences are there in reading comprehension and math performance between the two years based on school maintainer?
What differences are there in reading comprehension and math performance between the two years based on family background?
What differences are there in reading comprehension and math performance between the two years based on gender?
Method
The research database containing the results of the Hungarian National Competence Assessment can be obtained much later after enrolment and through a complicated procedure based on the GDPR protocol. In this study, we analyzed the results of the tests recorded by the Education Office and the answers to the related background questionnaire. The competency assessment is conducted every May among all 6th, 8th, and 10th grade students (no assessment was conducted during COVID). In 2019, the assessment focused on reading comprehension and mathematics, while in 2022 it was supplemented with natural sciences and foreign languages. In this study, we analyzed the 6th grade database because COVID has a greater impact on the acquisition of writing, reading, and arithmetic skills at a younger age. The 2019 database contains data from 99,615 students, while the 2022 database contains data from 88,725 students. In our study, we focus on differences based on maintainers, family background, and gender. We analyzed the data using SPSS statistical software. We created a maintainer variable in the database: state (1), church (2), foundation and other (3). Our other focus is on family background, for which we used the family background index created by the Education Office. The family background index was developed based on several variables, such as parents' educational attainment, computer access, own desk, etc. Based on the family background index, we classified the students into three categories: low, average, and high family background, and examined the students' reading comprehension and mathematics results on this basis. We made a comparison between the two years based on the variables mentioned above. For the study, we performed a multidimensional ANOVA analysis to compare the means and used Pearson's correlation between continuous variables after testing for normality.
Expected Outcomes
COVID had a varying impact on school performance based on family background. There is a significant difference between the three groups formed based on family background. The lowest performance was among children from low-income families, and this group also saw the greatest decline in performance between the two years studied. Children from high family backgrounds had the highest performance and the smallest difference between the two years. The reason for this is that children in the high category based on family background had access to extra services online, and their parents were better able to help their children with their studies at home. There are also significant differences based on the type of institution, as institutions with different types of funding faced different challenges in teaching children during the COVID period, depending on the composition of their students. Public institutions have the highest proportion of disadvantaged students, which is why their performance is the lowest and their results were significantly lower between the two years examined. The best results were in the foundation and other categories, where reading comprehension and mathematics results also increased significantly. There is a significant difference between boys and girls. There was a smaller decline in reading comprehension among girls between the two years examined, while among boys this was the case in mathematics. The impact of COVID was much more noticeable in reading comprehension than in mathematics. The results show that COVID increased the differences between social groups and schools. Access to education was limited during COVID, which increased social inequalities. The practical significance of the results is that these gaps will have a long-term impact and may pose challenges for teachers. Based on the results, it is necessary to provide extra support to ensure that children can progress appropriately in the education system.
References
Ambrusné Magony, B. (2020). A szövegértés szerepe a matematikai szöveges feladatok megoldásában. Módszertani Közlemények, 60(2), 16–29. Borgen, N. T., Kirkebøen, L. J., Kotsadam, A., & Raaum, O. (2025). Do funds for more teachers improve student outcomes? Journal of Human Resources. Advance online publication. Daniele, V. (2021). Socioeconomic inequality and regional disparities in educational achievement: The role of relative poverty. Intelligence, 84, Article 101515. Grimm, K. J. (2008). Longitudinal associations between reading and mathematics achievement. Developmental Neuropsychology, 33(3), 410–426. Granocchio, E., De Salvatore, M., Bonanomi, E., & Sarti, D. (2023). Sex-related differences in reading achievement. Journal of Neuroscience Research, 101(5), 668–678. Guld, A. M., & Csanádi, K. (2020). Országos kompetenciamérés eredményeinek statisztikai feldolgozása a szövegértés és az idegen nyelv kedveltségének összefüggésében. Psychologia Hungarica Caroliensis, 8(4), 180–239. Hegedűs, R. (2024a). Student performance of different types of children with learning disabilities in Hungary. In L. Gómez Chova, C. González Martínez, & J. Lees (Eds.), ICERI2024 Proceedings: 17th International Conference of Education, Research and Innovation (pp. 1278–1286). IATED Academy. Hegedűs, R. (2024b). Tanulási zavarok és iskolai teljesítmény. Belvedere Meridionale Kiadó. Hermann, Z., & Molnár, Gy. (2022). A koronavírus-járvány okozta rendkívüli oktatási helyzet hatása a tanulói teljesítményekre. In Horn, D. (Szerk.), Fehér könyv a COVID-19-járvány társadalmi-gazdasági hatásairól (pp. 130–136). HUN-REN Közgazdaság- és Regionális Tudományi Kutatóközpont. Jakubowski, M., Gajderowicz, T., & Patrinos, H. A. (2025). COVID-19, school closures, and student learning outcomes: New global evidence from PISA. npj Science of Learning, 10(1), Article 5. Kyriakides, L., Charalambous, E., Christoforidou, M., Antoniou, P., & Ioannou, I. (2024). Searching for differential effects of the dynamic approach to teacher professional development: A study on promoting formative assessment. European Journal of Teacher Education. Mönkediek, B., Schulz, W., Eichhorn, H., & Diewald, M. (2020). Is there something special about twin families? A comparison of parenting styles in twin and non-twin families. Social Science Research, 90, Article 102441. Rowe, E. (2020). Counting national school enrolment shares in Australia: The political arithmetic of declining public school enrolment. The Australian Educational Researcher, 47(4), 517–535. Silinskas, G., & Kikas, E. (2022). Parental involvement in math homework at elementary school: Quality of involvement and student-perceived help. Learning and Instruction, 77, Article 101538. Szemerszki, M. (2020). Különórák az iskolában és iskolán kívül. Educatio, 29(2), 205–221. Wilder, S. (2014). Effects of parental involvement on academic achievement: A meta-synthesis. Educational Review, 66(3), 377–397.
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