In accordance with dynamic systems theory,we assume that variability is an important developmental phenomenon. However, the standard methodological toolkit of the developmental psychologist offers few instruments for the study of variability. In this article we will present several new methods that are especially useful for visualizing and describing intra-individual variability in individual time-serial data of repeated observations. In order to illustrate these methods, we apply them to data of early language development. After reviewing the common techniques and measures, we present new methods that show variability in developmental time-series data: the moving min-max graph, and the progmax-regmin graph. In addition, we demonstrate a technique that is able to detect sudden increases of variability: the critical frequency method. Also, we propose a technique that is based on a central assumption of the measurement-error-hypothesis: namely the symmetric distribution of error. Finally, as traditional statistical techniques have little to offer in testing variability hypotheses, we examine the possibilities that are provided by random sampling techniques. Our aim with the present discussion of variability and the demonstration of some simple yet illustrative techniques is to help researchers focus on rich additional sources of information that will lead to more interesting hypotheses and more powerful testing procedures, adapted to the unique nature of developmental data.

This article illustrates that studying intra‐individual variability in Second Language Development can provide insight into the developmental dynamics of second language (L2) learners. Adopting a Dynamic Systems Theory framework (Thelen & Smith, 1994; van Geert, 1994) and using insights from microgenetic variability studies in developmental psychology (Siegler, 2006), we focus on L2 systems during a time of rapid development, applying advanced visualization techniques. A reinterpretation of a longitudinal study by Cancino et al. (1978) on the use of negation shows nonlinear patterns and peaks of regression, and illustrates the relevance of regarding internal variability as a source of information in itself. A case study of an advanced learner reveals a general increase over time for the correlates included, but the development is nonlinear, showing moments of progress and regress. The case study also brings to light an interesting dynamic interaction of subsystems. In accordance with the assumption of a limitation of resources, the learner shows a variable development for some related measurements in the course of the trajectory.

Public significance statement: This review synthesizes 102 studies and 689 estimates of emotion dynamic patterns in 19.928 children and adolescents. Adolescents reported more variable positive emotions and more intense negative emotions. Youth with mental health problems reported more variable and less intense positive emotions and more intense anxiety.

Across different domains, from sports to science, some individuals accomplish excellent levels of performance. For over 150 years, researchers have debated the roles of specific nature and nurture components to develop excellence. In this article, we argue that the key to excellence does not reside in specific underlying components, but rather in the ongoing interactions among the components. We propose that excellence emerges out of dynamic networks consisting of idiosyncratic mixtures of interacting components such as genetic endowment, motivation, practice, and coaching. Using computer simulations we demonstrate that the dynamic network model accurately predicts typical properties of excellence reported in the literature, such as the idiosyncratic developmental trajectories leading to excellence and the highly skewed distributions of productivity present in virtually any achievement domain. Based on this novel theoretical perspective on excellent human performance, this article concludes by suggesting policy implications and directions for future research.

Current individual-based, process-oriented approaches (dynamic systems theory and the microgenetic perspective) have led to an increase of variability-centred studies in the literature. The aim of this article is to propose a technique that incorporates variability in the analysis of the shape of developmental change. This approach is illustrated by the analysis of time serial language data, in particular data on the development of preposition use, collected from four participants. Visual inspection suggests that the development of prepositions-in-contexts shows a characteristic pattern of two phases, corresponding with a discontinuity. Three criteria for testing such discontinuous phase-wise change in individual data are presented and applied to the data. These are: (1) the sub-pattern criterion, (2) the peak criterion and (3) the membership criterion. The analyses rely on bootstrap and resampling procedures based on various null hypotheses. The results show that there are some indications of discontinuity in all participants, although clear inter-individual differences have been found, depending on the criteria used. In the discussion we will address several fundamental issues concerning (dis)continuity and variability in individual-based, process-oriented data sets. Copyright # 2007 John Wiley & Sons, Ltd.Key words: intra-individual variability; early language development; continuity; discontinuity; random sampling techniques; dynamic systems theory; microgenetic One of the major achievements of individual-based, process-oriented approaches (dynamic systems theory and the microgenetic perspective) is the increase in the number of variability-centred studies that have appeared in the literature. The implication is that a growing number of researchers acknowledge the meaningfulness of intra-individual variability and show an interest in irregular aspects of