Structural equation modelling in comparative and international education

The use of advanced quantitative research methods in the social sciences has flourished for decades. Data on social environments and human behaviour is complex. As human behavior is highly variable and unpredictable, it is difficult to capture and analyze. There are many factors that can influence behavior, such as individual differences, social and cultural norms, situational factors, and personal experiences. It is subjective and can be influenced by individual perspectives, emotions, and biases. This subjectivity can make it challenging to interpret and generalize findings from this data. Furthermore, it is multifaceted in that different facets such as psychological factors, social, cultural, and biological factors influence human behaviour. This complexity makes it challenging to identify the specific causes of this behavior and then to develop effective interventions. Finally, behavior is context-dependent, meaning that it can vary depending on the situation or environment. This makes it important to consider the context in which the behavior is occurring when collecting and analyzing data. This complexity makes this type of data challenging to accurately measure and understand. Nevertheless,¬¬ this underscores the importance of collecting and analyzing behavioral data to better understand human cognition, emotions, and decision-making processes. In order to account for this complexity, Structural Equation Modelling (SEM) serves as a method of analysis that captures these subtle nuances in such data. This chapter explores this method of data analysis and how it is and might be used in Comparative and International Education (CIE) research.