Event-distributions inform scientists about the variability and dispersion of repeated measurements. This dispersion can be understood from a complex systems perspective, and quantified in terms of fractal geometry. The key premise is that a distribution's shape reveals information about the governing dynamics of the system that gave rise to the distribution. Two categories of characteristic dynamics are distinguished: additive systems governed by component-dominant dynamics and multiplicative or interdependent systems governed by interaction-dominant dynamics. A logic by which systems governed by interaction-dominant dynamics are expected to yield mixtures of lognormal and inverse power-law samples is discussed. These mixtures are described by a so-called cocktail model of response times derived from human cognitive performances. The overarching goals of this article are twofold: First, to offer readers an introduction to this theoretical perspective and second, to offer an overview of the related statistical methods.

Research on background factors in adult language learners’ success has largely focused on first-time learners of a second language. In this study, we utilize a well-established second language learner model (the Socioeducational Model; Gardner, 1985a) to compare heritage language and second language learners in a first-semester college Spanish class. Participants (31 heritage language learners; 80 second language learners) completed a survey at the end of the semester assessing their ethnic identity, language backgrounds, attitudes and motivation toward learning Spanish. Course grades were collected as a measure of language learning success. Results indicate that heritage language learners and second language learners are similar on most background factors, but that the background factors predicting each group’s language learning success are quite different. Implications for our understanding of language learners and future research directions are discussed.

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