We aim to demonstrate that the understanding of behavior and development requires a better fit between methods to gather and analyze data and the dynamic nature of psychological phenomena. We argue that there are limits to the application of static designs of data collection in correlation design and to focusing on measures of central tendency when inferring on the complex processes of change in human behavior and development. We describe possible ways to correct the errors we make and to overcome the difficulties that we face when measuring change. We conclude that there is a need to identify a comprehensive model of gathering and analyzing data that takes into account the observation period of the phenomena (short- and long-term research), the complexity of the studied form of activity (elementary and complex) and the situation/context of the measurement (well-defined situation and situation “at large”).
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