In an inclusive school, the parents are involved, in both the SEN and non-SEN students (Paseka & Schwab, 2020). Several empirical studies have examined the relationship between parental involvement (PI) and academic achievement (Domina, 2005; Driessen et al., 2005; Sheldon and Epstein 2005; Erdem and Kaya 2020; Naite 2020), however, neither the PI itself nor the relationship between the two factors is shared equally by the researchers in the studies (Boonk et al. 2018, Nyitrai et al. 2019). In families with low socioeconomic backgrounds, the PI volume is lower than in high SES families. Students with special educational needs are more likely to be impacted by the PI because of its relevance to them. We have a great deal of cross-sectional studies, which look at the school-family collaboration in families with low socioeconomic status and in the case of families with special needs students, but we have very little information about the longitudinal changes of the PI and its influence over time.

This study aimed to examine the association beetween the PI and the school sucess in inclusive classrooms using a longitudinal database. We aim to analyze how the PI has changed over time as the school years progress. In our analysis highlighted the low SES SEN students, whose parent’s are fare from the schoollife.

All students in the 6th, 8th, and 10th grades in Hungary take part in a process called the National Assessment of Basic Competencies (NABC), which is a kind of census. From the years 2015-2019, we have merged the three based databases based on Student IDs and built a longitudinal database that covers the 6th through the 10th grade. During the four years of the school's existence, we want to analyse and understand how to change the PI and the variables that describe the success of the school for low SES and SEN students during the four years.

We found that students from low SES and those with special needs are at high risk of dropping out, but the amount of involvement they receive at school can help counterbalance this risk. When compared to the average population, the volume of the PI is higher in the case of the SEN students, but in the case of the low SES families with SEN students, the correlation is not valid.  As a result, one of the main conclusions from the study is that access to the hard-to-reach parents is very important for the schools in order to improve the educational opportunities students have in their schools.

In this study, we built an longitudinal database. The database used for the research was created by merging data at the student level. Our baseline year was the 2015 NABC measurement in Year 6, with Year 6 students as the base. We first merged the student and institution databases, and then repeated this step for the 2017 grade 8 and 2019 grade 10 databases. We then compiled a database based on the individual identifiers of Year 6 students, which can track students' achievements and backgrounds over four years in the case of an unbroken learning pathway. Our initial database contains 91956 students, the final merged database of data from three different years contains 104110 rows, i.e. the number of students with measurement IDs. The discrepancy between the two numbers indicates the problem that our response gap will be very high for many questions. The construction of the database is based on the fact that students who appear in one of the three years with their individual identifiers are included, i.e. they may have dropped out, repeated a class and thus dropped out or entered our database. A special attention was paid to students who could not be identified in the subsequent databases and therefore could have dropped out. The low SES and SEN student cathegory is recorded administratively in the central database. We used descriptive statistics and 2-level Hierarchical Linear Modeling (student nested in school). Since both academic achievement (Beta=0.34) and parental involvement (Beta=0.13) are strongly correlated with social background, we used the residuals of the regression for the descriptive statistics.

Our expected outcomes are at different levels. Our results show that the percentage of SEN pupils in the total population in Grade 6 is 5.9%. If we calculate the percentage by social background, it is distributed in a ratio of 1:2, i.e. the proportion of SEN pupils in the cumulatively deprived group is twice as high as in the non-deprived group. At higher grades, however, the proportion of non-deprived SEN pupils does not decrease to the same extent, i.e. it is more likely that pupils from the deprived groups crumble and disappear from the database. The proportion of SEN pupils who are not severely disadvantaged is 4.2%, while the same figure for the severely low SES group is 11%. In general, parents of SEN children are more involved and parents in low SES families are less involved. Less involvement is also typical for parents of SEN children if the family is disadvantaged. However, when we look at students who have an unbroken learning path, i.e. who have not dropped out but have fulfilled the requirements of the school system up to the age of 16, we see a different correlation. For successful (not dropped out) students, parents of disadvantaged SEN students show increasing levels of involvement. As a result, one of the main conclusions from the study is that access to hard-to-reach parents is very important for schools to improve the educational opportunities students have in their schools.

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