Journal of the Association for Information Systems


Evolved information processing traits are defined as mental traits that have been evolved by our species in response to evolutionary pressures and that are associated with the processing of information. Evolutionary psychologists and human evolution researchers have long realized that theorizing about evolved mental traits is very difficult to do in ways that lead to valid testable predictions. Quite often that theorizing leads to what are known as Panglossian (or naïve) explanations, which may at first glance be seen as valid evolutionary explanations of observable traits, but end up proving to be wrong and misleading. We propose four meta-theoretical principles to guide future research on evolved information processing traits and their effects on technology-mediated task performance, and help researchers avoid Panglossian explanations. We argue that this type of research holds the promise of bringing fresh insights into the study of human behavior toward information and communication technologies, and thus, helping advance the field of information systems through a promising path that has rarely been taken before. We derive the four principles from mathematical formulations developed based on two of the most fundamental conceptual tools employed in population genetics and mathematical modeling of evolutionary processes: Fisher’s Fundamental Theorem of Natural Selection and the Price Equation. We provide an illustration of the application of the principles through an empirical study of a technology-mediated learning task. The analysis was conducted using WarpPLS 1.0. The study provides support for a puzzling phenomenon, known as flashbulb memorization, the context of web-mediated learning.





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