@article {1092, title = {THE GENERATIVE MECHANISM OF SECONDARY SCHOOL STUDENTS{\textquoteright} OCCUPATIONAL EXPECTATIONS IN THE BALTIC COUNTRIES: INFLUENCE OF FAMILY, SCHOOL, AND INDIVIDUAL SCIENCE LEARNING ACHIEVEMENT}, journal = {Journal of Baltic Science Education}, volume = {20}, year = {2021}, month = {October/2021}, pages = {Continuous}, type = {Original article}, chapter = {759-774}, abstract = {Gender, learning achievements, parents{\textquoteright} occupational status, social-economic backgrounds, and a few traits of schools affect students{\textquoteright} occupational expectations. However, no research had integrated the above factors to investigate the generative mechanism of students{\textquoteright} occupational expectations. After combining student-level and school-level PISA 2018 datasets, two-level latent covariate modeling was used to find the generative mechanism of students{\textquoteright} occupational expectations in the Baltic countries. The mechanism had its primary concern to understand roles parents{\textquoteright} occupational status and individual science learning achievement played on students{\textquoteright} occupational expectations. The results indicate that the generative mechanism of students{\textquoteright} occupational expectations of Lithuania, Estonia, and Latvia are the power model, the maternal model, and the science learning achievement pattern, respectively. It suggests one parent having high occupational status is to mold children{\textquoteright}s high-skilled occupational expectations, and it would be better the mother is the higher occupational status parent. It highlights the importance of strengthening adult education, especially that aimed at families with both parents of low occupational status. It disapproves of a mother being a full-time housewife. It may impede her children from having ambitions for high-skilled jobs. }, keywords = {occupational expectation, PISA 2018 datasets, science learning achievement, two-level latent covariate model}, issn = {1648-3898}, doi = {https://doi.org/10.33225/jbse/21.20.759}, url = {http://oaji.net/articles/2021/987-1633680421.pdf}, author = {Tao Jiang and Chen, J.-G. and Wei Fang} }