Through the lens of science capital, this research aims to detect the key factors and their main effects in identifying students with science-related career expectations. A machine learning approach (i.e., random forest) was employed to analyze a dataset of 519,334 15-year-old students from the Programme for International Student Assessment (PISA)…

Previous research has demonstrated the potential of examining log-file data from computer-based assessments to understand student interactions with complex inquiry tasks. Rather than solely providing information about what has been achieved or the accuracy of student responses ("product data"), students' log files offer additional…