Match or Mismatch: Data Mining to Approach Insights of Academic Socialization Pathways of Science PhD Students
摘要
This study aims to uncover the pathways of academic socialization for PhD students using a data mining approach. It analyzed data from nearly 3,000 PhD students at UCAS across four scientific disciplines, yielding consistent conclusions on academic socialization pathways. The indicators of PhD training activities align well with the theoretical framework of academic socialization, revealing distinct pathways within this process. High-achieving students are able to transition smoothly across critical thresholds, actively engaging in research and social practices, and achieving exceptional research outcomes. In contrast, merely-qualified students often struggle to define their research direction and realize their research ideas, relying on research collaboration to compensate for these challenges. These pathways of academic socialization and developmental approaches may lead to career mismatches after PhD graduation. The implications for study support and university policy innovations were discussed accordingly.