Bayesian Analysis of Academic Achievement: Turkish Immigrant Students in Western Europe

Research concerning the educational outcomes of immigrant students has gained significance in the social sciences; however, there are relatively few international studies due to the problem of small sample sizes. This research employs a Bayesian method to make estimates with small sample sizes and address this gap. Using the data from PISA 2018, this study examines the effects of language skills, educational aspirations, and socioeconomic variables on the academic achievement of Turkish immigrant students in five Western European countries, considering the influence of the destination countries. Findings indicate that speaking a language different from the test language at home has varying and negative effects on the academic achievement of Turkish immigrant students across different destination countries. Also, the study found that aspirations to complete vocational education negatively affect academic achievement while aspirations to complete higher education have a positive impact. The paper concluded that Turkish immigrant students' life satisfaction and their fathers' educational level adversely influenced academic performance in relation to negative selection. Furthermore, gender disparities among immigrant students were noted, with girls facing a significant disadvantage in mathematics and science relative to boys. These results indicate that the socioeconomic background characteristics, as well as the migration selection, education, and integration policies of destination countries, have different influences on the academic achievement of immigrant students from the same ethnic origin.