Students’ STEM career expectations: effects of science and mathematics abilities and attitudes relative to language abilities and attitudes

In response to growing concerns about low participation in science, technology, engineering, and mathematics (STEM) careers, there is a need for more understanding of the underlying cognitive and motivational mechanisms affecting students’ STEM career expectations. This study examined whether relative strengths of abilities and attitudes in science, mathematics, and Chinese language could predict STEM career expectations among junior secondary school students. Data were from the Hong Kong PISA 2022 sample. Data were analysed using person-centred approaches and structural equation modelling (SEM). Results revealed six distinct attitude classes (Passionate, Prefer Chinese, Prefer Science/Math, Prefer Chinese/Math, Persistent, and Uncommitted) and four ability profiles (High-achieving, Above-average, Below-average, and Low-achieving). Students in the Prefer Science/Math class with a clear science/mathematics preference over the Chinese language were the most likely to select STEM careers, whereas the other groups (e.g. Passionate, Prefer Chinese, Persistent, and Uncommitted) were less likely to pursue them. Additionally, the Prefer Science/Math class positively mediated the relationships between student ability profiles and career expectations, whereas the Prefer Chinese/Math class negatively mediated these relationships. Overall, this study underscores the importance of attitudes toward science and mathematics relative to other subjects (e.g. language) in shaping adolescents’ career expectations and future STEM participation.