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In this article, I answer the questions from Witherington and Boom’s introduction to this special issue in the form of an imaginary interview, led by David Boom, equally imaginary editor of The Processual Inquirer, an obscure but interesting journal that appears in imaginary physical print only, and which, as a consequence, has so far left no traces on the Internet….

Within education, the importance of creativity is recognized as an essential 21st-century skill. Based on this premise, the first aim of this article is to provide a theoretical integration through the development of a framework based on the principles of complex dynamic systems theory, which describes and explains children's creativity. This model is used to explain differing views on the role of education in developing children's creativity. Our second aim is empirical integration. On the basis of a three-dimensional taxonomy, we performed a systematic review of the recent literature (2006-2017, 184 studies) on primary school students 'creativity. Our results show that creativity is most often measured as a static, aggregated construct. In line with our theoretical model, we suggest ways that future research can elaborate on the moment-to-moment interactions that form the basis of long-term creative development, as well as on the mechanisms that connect different levels of creativity.

Murayama and Jach rightfully aim to conceptualize motivation as an emergent property of a dynamic system of interacting elements. However, they do not embrace the ontological and paradigmatic constraints of the dynamic systems approach. They therefore miss the very process of emergence and how it can be formally modeled and tested by specific types of computer simulation.

In business and sports, teams often experience periods of positive and negative momentum while pursuing their goals. However, researchers have not yet been able to provide insights into how psychological and behavioral states actually change during positive and negative team momentum. In the current study we aimed to provide these insights by introducing an experimental dynamical research design. Rowing pairs had to compete against a virtual opponent on rowing ergometers, while a screen in front of the team broadcasted the ongoing race. The race was manipulated so that the team's rowing avatar gradually progressed (positive momentum) or regressed (negative momentum) in relation to the victory. The participants responded verbally to collective efficacy and task cohesion items appearing on the screen each minute. In addition, effort exertion and interpersonal coordination were continuously measured. Our results showed negative psychological changes (perceptions of collective efficacy and task cohesion) during negative team momentum, which were stronger than the positive changes during positive team momentum. Moreover, teams' exerted efforts rapidly decreased during negative momentum, whereas positive momentum accompanied a more variable and adaptive sequence of effort exertion. Finally, the interpersonal coordination was worse during negative momentum than during positive momentum. These results provide the first empirical insights into actual team momentum dynamics, and demonstrate how a dynamical research approach significantly contributes to current knowledge on psychological and behavioral processes.

Understanding the development of talent has been a major challenge across the arts, education, and particularly sports. Here, we show that a dynamic network model predicts typical individual developmental patterns, which for a few athletes result in exceptional achievements. We first validated the model on individual trajectories of famous athletes (Roger Federer, Serena Williams, Sidney Crosby, and Lionel Messi). Second, we fitted the model on athletic achievements across sports, geographical scale, and gender. We show that the model provides good predictions for the distributions of grand slam victories in tennis (male players, n=1528; female players, n=1274), major wins in golf (male players, n=1011; female players, n=1183), and goals scored in the NHL (ice hockey, n=6677) and in FC Barcelona (soccer, n=585). The dynamic network model offers a new avenue toward understanding talent development in sports and other achievement domains.

Using an extended definition of sexuality, this mixed-methods study builds on existing research into adolescents’ emergent sexual development by longitudinally examining adolescents’ sexual behavior trajectories (i.e., from less to more intimate sexual behavior). Over a 2-year period, 45 adolescents (M age = 15.9 years) reported on their sexual behavior using questionnaires and on their everyday expressions of sexuality in the form of semi-structured diaries. Cluster analysis using the questionnaire data identified three sexual behavior trajectories: a non-sexually active trajectory (meaning no or minor sexual behavior) ( n  = 29), a gradually sexually active trajectory (meaning step-by-step sexual behavior development) ( n  = 12), and a fast sexually active trajectory (meaning rapid sexual behavior development) ( n  = 4). Qualitative analysis using diaries revealed the following themes: romantic versus sex-related topics, desires, uncertainties, and references to the social context. In general, all adolescents reported more about romantic aspects of sexuality (than about sexual acts) in the diaries, regardless of their sexual behavior trajectory. Sexually active adolescents (i.e., gradual and fast) were more concerned with sexuality in their diaries, especially more with the physical aspects of sexuality, than non-active adolescents. Gradual adolescents experienced more desires about physical sexual contact and reported fewer references to their social network than non-active and fast adolescents. The findings suggest that sexual education that discusses the internal experiences of sexuality, such as feelings and thoughts, particularly the romantic aspects, may help adolescents process their preferences for different sexual and romantic acts and may contribute to healthy sexual development.

Long-term learning trajectories evolve through microdevelopmental sequences (i.e., short-term processes of change during learning tasks) and depend on variability during and across learning tasks. The aim of this study is to examine the coupling between short-term teacher-student dynamics and students’ long-term learning trajectories, thereby providing empirical support for the link between the short- and long-term time scale in cognitive development. For 31 students (ages 3–5 years) from regular and special education, five teacher-student interactions during science tasks were filmed and coded in real time with regard to the student’s level of understanding and the teacher’s support throughout the task. A hierarchical cluster analysis resulted in four different learning trajectories over the course of 1.5 years, labeled as a high-scoring, mid-scoring, fluctuating, and low-scoring group of students. When connecting these trajectories to microdevelopmental data, the interactions of the high-scoring students were characterized by more moment-to-moment variations in the teacher’s support and student’s level of understanding, while the low-scoring group had the least variability compared to the other groups. Students with emotional and behavioral disabilities were represented across all learning trajectories, despite frequent accounts in the literature on their significant academic delays.

The variability of self-esteem is an important characteristic of self-esteem. However, little is known about the mechanisms that underlie it. The goal of the current study was to empirically explore these underlying mechanisms. It is commonly assumed that state self-esteem (the fleeting experience of the self) is a response to the immediate social context. Drawing from a complex dynamic systems perspective, the self-organizing self-esteem model asserts that this responsivity is not passive or stimulus-response like, but that the impact of the social context on state self-esteem is intimately connected to the intrinsic dynamics of self-esteem. The model suggests that intrinsic dynamics are the result of higher-order self-esteem attractors that can constrain state self-esteem variability. The current study tests this model, and more specifically, the prediction that state self-esteem variability is less influenced by changes in the immediate context if relatively strong, as opposed to weak, self-esteem attractors underlie intrinsic dynamics of self-esteem. To test this, parent-adolescent dyads (N=13, Mage=13.6) were filmed during seminaturalistic discussions. Observable components of adolescent state self-esteem were coded in real time, as well as real-time parental autonomy-support and relatedness. Kohonen’s self-organizing maps were used to derive attractor-like patterns: repeated higher-order patterns of adolescents’ self-esteem components. State space grids were used to assess how much adolescents’ self-esteem attractors constrained their state self-esteem variability. We found varying levels of attractor strength in our sample. In accordance with our prediction, we found that state self-esteem was less sensitive to changes in parental support and relatedness for adolescents with stronger self-esteem attractors. Discussion revolves around the implications of our findings for the ontology of self-esteem.

The basic properties and concepts of dynamic systems theory are introduced by means of an imaginary, literary example, namely, Alice (from Wonderland) walking to the Queen in Through the Looking Glass (Carroll, 1871). The discussion encompasses notions such as time evolution, evolution term, attractor, self-organization, and timescales. These abstract notions are then applied to the study of first language (L1) and second language (L2) acquisition. The steps that should be taken toward the construction of dynamic systems models of L2 learning are described, including a discussion of the difficulties and the theoretical opportunities that accompany this model building. Finally, a concrete example of model building and of the study of variability as an indicator of developmental transitions in L1 acquisition is given. (Verlag).

Health-related quality of life (HRQOL) is a person-centered concept. The analysis of HRQOL is highly relevant in the aged population, which is generally suffering from health decline. Starting from a conceptual dynamic systems model that describes the development of HRQOL in individuals over time, this study aims to develop and test a quantitative dynamic systems model, in order to reveal the possible dynamic trends of HRQOL among older adults. The model is tested in different ways: first, with a calibration procedure to test whether the model produces theoretically plausible results, and second, with a preliminary validation procedure using empirical data of 194 older adults. This first validation tested the prediction that given a particular starting point (first empirical data point), the model will generate dynamic trajectories that lead to the observed endpoint (second empirical data point). The analyses reveal that the quantitative model produces theoretically plausible trajectories, thus providing support for the calibration procedure. Furthermore, the analyses of validation show a good fit between empirical and simulated data. In fact, no differences were found in the comparison between empirical and simulated final data for the same subgroup of participants, whereas the comparison between different subgroups of people resulted in significant differences. These data provide an initial basis of evidence for the dynamic nature of HRQOL during the aging process. Therefore, these data may give new theoretical and applied insights into the study of HRQOL and its development with time in the aging population.