A Dynamic Network Model to Explain the Development of Excellent Human Performance

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

Attractor States in Teaching and Learning Processes:A Study of Out-of-School Science Education

In order for out-of-school science activities that take place during school hours but outside the school context to be successful, instructors must have sufficient pedagogical content knowledge (PCK) to guarantee high-quality teaching and learning. We argue that PCK is a quality of the instructor-pupil system that is constructed in real-time interaction. When PCK is evident in real-time interaction, we define it as Expressed Pedagogical Content Knowledge (EPCK). The aim of this study is to empirically explore whether EPCK shows a systematic pattern of variation, and if so whether the pattern occurs in recurrent and temporary stable attractor states as predicted in the complex dynamic systems theory. This study concerned nine out-of-school activities in which pupils of upper primary school classes participated. A multivariate coding scheme was used to capture EPCK in real time. A principal component analysis of the time series of all the variables reduced the number of dimensions. A cluster revealed general descriptions of the dimensions across all cases. Cluster analyses of individual cases divided the time series into sequences, revealing High-, Low- and Non-EPCK states. High-EPCK attractor states emerged at particular moments during activities, rather than being present all the time. Such High-EPCK attractor states were only found in a few cases, namely those where the pupils were prepared for the visit and the instructors were trained

Language use in kindergarten science lessons:Language production and academic language during a video feedback coaching intervention in kindergarten science lessons

This paper aims to gain insight into language production and academic language of 4- and 5-year-old students and their teachers in the course of a teacher intervention during kindergarten science education. The study is based on videotaped classroom observations, and specifically focuses on the academic language use of students (Nintervention = 18, Ncontrols = 26) and teachers (Nintervention = 5, Ncontrols = 5). The results suggest that this general teacher intervention yields interesting changes in language use and production. Patterns of change over time confirm the idiosyncratic and non-linear nature of these changes. Science lessons represent an appropriate context in which to acquaint students with academic language, which can be used as a basis to build upon more sophisticated language skills

A theory and dynamic model of dyadic interaction:Concerns, appraisals, and contagiousness in a developmental context

A theory of the dynamics of dyadic interaction is presented, based on the concepts of "concern" (i.e., intentions, goals, and interests), "appraisal" and "contagiousness". Differences between children who participate in a specific interaction are linked to differences in social competence and social power. An overview is given of the social psychological underpinnings of these concepts and of their developmental trajectories. The theory is transformed into a mathematical, dynamic systems model of dyadic interaction. The model describes the time evolution of an "involvement" variable, which is defined as "the number of actions of an individual that are explicitly aimed at the interaction partner". In order to illustrate the veracity and applicability of the mathematical model, an empirical study is described that applies the model to a dyadic play situation in children of different sociometric statuses. Most of the predictions generated by the model are verified. The conclusion addresses, among others, the use of dynamic systems models in the study of social development and a number of applied issues. A final point concerns the necessity of coupling models of short-term dynamics, such as the one presented in the current article, with models of long-term dynamics, i.e., of developmental change. (c) 2006 Elsevier Inc. All rights reserved

A Complexity Approach Toward Mind–Brain–Education (MBE); Challenges and Opportunities in Educational Intervention and Research

In the context of an educational or clinical intervention, we often ask questions such as “How does this intervention influence the task behavior of autistic children?” or “How does working memory influence inhibition of immediate responses?” What do we mean by the word influence here? In this article, we introduce the framework of complex dynamic systems (CDS) to disentangle the meaning of words such as influence, and to discuss the issue of education and intervention as something that takes place in the form of complex, real-time, situated processes. What are the applied implications of such a CDS framework? Can we use it to improve education? Five general principles—process laws—are introduced, which can be used to guide the way we formulate research questions and methods, and the way we use the results of such research. In addition, we briefly discuss a project in progress, in which we ourselves attempt to apply the process laws that govern educational activities. Finally, we report about a discussion about the usability of the process laws, both in educational research and in the classroom, as was held during our workshop at the Mind, Brain, and Education Conference, November 201

Corrigendum:Promoting creative autonomy support in school music education: an intervention study targeting interaction (Frontiers in Education, (2023), 7, (1102011), 10.3389/feduc.2022.1102011)

In the published article, there was an error in Figure 6 as published. The graph for teacher 3 appeared twice and the graph for teacher 6 was missing. The corrected Figure 6 and its caption appear below. Confidence intervals teachers 1–12 (experimental group) and teachers 13–18 (control group) for CASV over 8 lessons. Lesson numbers are next to CI's. The vertical rectangle depicts the baseline range (confidence intervals lessons 1 and 2). Note that for teacher 6 lesson 7 and 8, and for teacher 11 lesson 8 is missing. The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.</p

Socio-Emotional Concern Dynamics in a Model of Real-Time Dyadic Interaction: Parent-Child Play in Autism

We used a validated agent-based model—Socio-Emotional CONcern DynamicS (SECONDS)—to model real-time playful interaction between a child diagnosed with Autism Spectrum Disorders (ASD) and its parent. SECONDS provides a real-time (second-by-second) virtual environment that could be used for clinical trials and testingprocess-orientedexplanationsofASDsymptomatology.Weconductednumerical experiments with SECONDS (1) for internal model validation comparing two parental behavioral strategies for stimulating social development in ASD (play-centered vs. initiative-centered) and (2) for empirical case-based model validation. We compared 2,000 simulated play sessions of two particular dyads with (second-by-second) time-series observations within 29 play sessions of a real parent-child dyad with ASD on six variables related to maintaining and initiating play. Overall, both simulated dyads provided a better fit to the observed dyad than reference null distributions. Given the idiosyncratic behaviors expected in ASD, the observed correspondence is non-trivial. Our results demonstrate the applicability of SECONDS to parent-child dyads in ASD. In the future, SECONDS could help design interventions for parental care in AS

Assessing Situated Knowledge

Subconsciously, experienced teachers make use of situated knowledge: knowledge that is connected to, and arises from, the interactions between the physical environment where the action takes place and a material body acting in that environment. Since situated knowledge is important in day-to-day teaching to solve incidents, it should be taught in teacher training courses. Consequently, in the test at the end of such a course, these learning objectives should be tested. By using cases and by setting higher learning objectives that explicitly address the situated nature of this knowledge, situated knowledge can be assessed. In this study, the main question is: Do teacher trainers use cases that are aimed at acquiring situated knowledge? An empirical study, carried out in eleven secondary teacher-training programs in the Netherlands, revealed that just a single program did indeed assess situated knowledge. Considering its importance, however, it is essential that it is included in all secondary teacher-training programs. To assist teacher training programs to achieve this goal, this article offers recommendations for implementing tests with cases to assess situated knowledge

Understanding mind, brain, and education as a complex, dynamic developing system: Measurement, modeling, and research

Overview Human development and education can benefit from a framework that analyzes behavior and brain change as involving dynamic systems processes. Dynamic systems researchers build specific models focusing on processes of change in learning and teaching, beginning with individual growth patterns and including in mathematical models multiple layers and scales of casual interaction. These models shift the focus of research and assessment to individual behavior, fluctuations in time, and the combination of gradual change with periodic abrupt changes in performance and brain patterns. Dynamic systems models explain and predict important properties of learning and teaching such as non-linear change and self-organization (spontaneous increase of order and information). They readily combine apparently opposite processes in the same theory and model, such as gene versus environment or individual versus context/culture, a characteristic called superposition. Measurements should involve the kind of assessment that teachers and schools do every day in the classroom – repeated measures of individual behavior. The models then provide ways of analyzing common educational phenomena, such as variability in performance, ambiguity of behavior, and context specificity. A dynamic approach promises to provide useful tools for understanding the complex individual changes that occur during education and child development. The Editors Human development constitutes a complex system. Rocha (1999) defines a complex system as “… any system featuring a large number of interacting components (agents, processes, etc.) … whose aggregate activity is nonlinear (not derivable from the summations of the activity of individual components) … and typically exhibits … self-organization …”

Assessment of preschooler’s scientific reasoning in adult–child interactions: What is the optimal context?

In educational settings, continuous assessment of the child's level of understanding is necessary to effectively utilize the principles of scaffolding and to create contexts that can advance the scientific reasoning of the child. In this article, we argue that a child's performance is a dynamic notion that is created by all elements in an interaction, including the task. Therefore, we studied preschoolers' levels of scientific reasoning varying different properties of the assessment context. Young children were interviewed about four scientific tasks using one out of four different protocols (varying in the degree of flexibility and adaptiveness) by an adult. In the first study, different task contents resulted in different performance levels. The second study indicated that the most structured protocol elicited the highest maximum level of reasoning in children and the highest percentage of correct predictions. The third study showed differences between the protocols in the adult's verbal behavior. Adaptation in verbal behavior to different children by the adult did not result in higher scientific understanding by the children, whereas a higher degree of task structure did. Combined, the studies emphasize the importance of context, which has implications for assessment and teaching situations