From missteps to insights: Reflecting on failed secondary analyses

Secondary analysis of existing data provides unique opportunities for researchers to conduct large-scale studies with enhanced efficiency of resources and time, a concept increasingly utilized in educational research. This study aimed to provide crucial insights into the alignment between original and secondary theoretical frameworks, the creation and interpretation of variables, and the careful handling of data structures. This study explored the specific challenges and opportunities of using secondary analysis through two illustrative cases involving the Trends in International Mathematics and Science Study (TIMSS) and the Seoul Educational Longitudinal Study (SELS). The case with the TIMSS data highlighted the complexities of applying theoretical frameworks and interpreting newly generated variables when the original data lacked certain measurements needed for current research questions. A significant challenge identified in the SELS data was the non-uniformity of ID structures over years, which complicates the understanding of longitudinal trends and demands meticulous attention to detail. Our cases underscored the necessity for rigorous theoretical alignment, precise operational definitions, and nuanced statistical interpretations when conducting secondary analysis and international comparison. These are essential to unlock the full potential of large-scale public datasets in educational research, ensuring that findings are both scientifically robust and practically relevant.