Educational contexts serve as significant agents of socialization, contributing to the development of not only academic skills but also of a diverse range of socio-emotional competencies. Simultaneously, these environments function as arenas where instances of peer violence, discrimination based on ethnicity, gender, sexuality, and ability, among other biases, are prevalent. These challenges affect a considerable number of students, potentially leading to mental health issues and contributing to school absenteeism or dropout. PISA results demonstrated that 17 to 40% 15-year-olds are dissatisfied with school and that one in four adolescents have low feelings of belongingness (Willms, 2003).

School belonging is defined as “the extent to which students feel personally accepted, respected, included, and supported by others in the school social environment” (Goodenow & Grady, 1993, p. 80). School belonging is influenced by a variety of individual factors such as gender, ethnicity/ race and ethnic identification, self-esteem, personality, social skills, as well as external factors, such as school climate and teacher support (Ahmadi & Ahmadi, 2020; Allen et al., 2023; Slaten et al., 2016; Watson et al., 2020). More specifically, studies suggest that the meaning of belonging may be different for students of different ethnicities who experience differential levels of discrimination (Murphy & Zirkel, 2015), which consequently affects their sense of school belonging (Brown & Tam, 2019). Some studies that compared school belonging between immigrant and non-immigrant adolescents pointed to higher school belonging among immigrant students (e.g. Allen et al., 2021), while others showed the opposite (e.g. Bottiani et al., 2017). A person’s socioeconomic status (SES) is also associated with the school belonging (Allen et al., 2023). As for the gender differences, some studies reported no differences (e.g. Sanchez et al., 2005), while the others revealed that girls have a higher sense of belonging (e.g., Smerdon, 2002). Previous studies demonstrated that perceived safety, healthy norms concerning bullying, teacher social and academic support and teacher-student relationship are positively correlated with school belonging (Slaten et al., 2016).

School belonging is related to both academic success and students’ prosocial behaviour and wellbeing (Arslan, 2021; Prati & Cicognani, 2021; Slaten et al., 2016). Therefore, for scholars, educational policy makers, and practitioners it is of utmost importance to explore school belonging and determine ways in which it can be improved.

This study was conducted within the project “Narrativization of ethnic identities of adolescents from culturally dominant and minority backgrounds, and the role of the school context” (NIdEA), supported by the Science Fund of the Republic of Serbia (grant number 1518). It relied on the Bronfebrenner’s ecological model of human development, and its adaptation from Allen and associates (2016) who place the students at the center of the model and assert that their sense of belonging is either fostered or hindered by their experience with different layers. Microsystem entails teacher, peer and parent support, while the mesosystem includes school policy, practices and extracurricular activities. The exosystem includes influences from the neighbourhood and extended family, while the macrolevel refers to broader societal factors such as history, social climate and legislation (Allen et al., 2016). Our study aimed to determine if the individual’s sociodemographic variables and certain micro-, meso- and exo-system factors can predict secondary school students’ sense of school belonging. More specifically, we explored gender, SES and ethnic status in the society (majority or minority) as personal factors, and different aspects of school climate, bullying, and ethnicity-based discrimination as school- and community-related factors of school belonging.

Instruments. For this paper we used a single-item 5-point Likert type measure of school belonging (“I feel I belong to this school”). To assess school climate, we utilized the four-point Likert-type Delaware School Climate Scale (DSCS), version for students (Bear et al., 2011), consisting of 31 items and five subscales: (1) Teacher – Student Relations; (2) Student–Student Relations; (3) Clarity of Expectations; (4) Fairness of Rules, and (5) School Safety. In addition, the student version includes Student Engagement and Bullying subscale. The DSCS’ subscales demonstrated good reliability in our study, with Cronbach’s alpha ranging from .622 to .783. Relying on different models and scales measuring ethnicity-based discrimination, we designed a 16-item five-point Likert-type scale assessing discrimination by peers, teachers, the institution (school as a whole), and community. Cronbach’s alpha coefficients ranged from .719 to .791. Students reported their SES on a multiple-choice question (1 standing for „We barely cover expenses for food”, and 6 – „We have enough money for a luxurious life, including traveling to exotic destinations and investing”). Because there were not many participants involved, we merged the two lowest categories into one for further analyses, so the variable we used had five categories. We asked about participants' gender through a multiple-choice question with categories: Male, Female, and Other. For the sake of this paper, we only used the first two categories. For the purposes of this paper, we categorized participants into four ethnic categories, including ethnic majority (Serbian) and three most represented minorities in Serbia (Hungarian, Bosniak, and Roma). Procedure and participants. We selected 20 schools (six general and 14 vocational secondary schools) from multiethnic regions. All students were informed about the research and after providing informed consents they filled out the questionnaires in their native languages. Final sample consisted of 904 students, (Mage = 16.24, SD = 1.05, with 51.6% females). More than two thirds (69.9%) identified as Serbian (ethnic majority), 10.8% as Hungarian, 11.1% as Bosniak, and 8.2% as Roma. Data Analysis. After descriptive statistic, we applied a hierarchical multiple regression analysis with school belonging being a criterion variable and the predictor variables being: students’ gender, SES and ethnic status (Model 1), teacher-student relations, student-student relations, clarity of expectations, fairness of rules, school engagement, bullying, discrimination by teachers, discrimination by peers and school-wide discrimination (Model 2), and discrimination in the community (Model 3).

Students demonstrated a relatively high level of school belonging (M = 2.97, SD = .909) and positive perceptions of school climate (highest scores for Clarity of expectations M = 3.07, SD = .58). Ethnicity-based discrimination from teachers was assessed as the highest (M = 2.08, SD = .9), while the one from the community was the lowest (M = 1.58, SD = .86). The results showed that only the second model was significant (F(10, 677) = 17.895, p = .000, R2 = .217), with teacher-student relations (b = -.153 , t = -3.539, p = .000), clarity of expectations (b =.111, t = 2.644, p = .008), fairness of rules (b = .099, t = 2.054, p = .040), school safety (b = .090, t = 2.188, p = .029), student engagement (b = .229, t = 4.164, p = .000) and bullying (b = .139, t = 3.500, p = .000) being significant predictors. Neither gender, SES, ethnic status, nor discrimination in the community were significantly associated with school belonging. Our results support previous findings about lack of gender differences in school belonging (Sanchez et al., 2005) but contradict those which assert relevance of SES and ethnicity for school belonging (Allen et al., 2021; 2023). We assume that contextual factors (e.g., status of certain ethnic minority groups at the national and local community level, the level of socioeconomic development of the community and school) should be considered when studying the role of these variables. School factors, on the other hand, proved to be relevant, especially those related to bullying, teacher-student relationship, and students’ engagement. Bronfenbrenner’s model proved to be a useful framework for understanding the predictors of school belonging, but future studies should include more factors from the exosystem and preferably use a more comprehensive measure of school belonging.

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