Cross-recurrence quantification analysis (CRQA) is a powerful nonlinear time-series method to study coordination and cooperation between people. This chapter concentrates on two methodological issues related to CRQA on categorical data streams, which are commonly encountered in the behavioral sciences. Firstly, we introduce a more general definition of recurrence as 'behavioral matching', which can be applied to several kinds of matches simultaneously, visualized by a color coding. We will refer to this as cross-matching, and to the resulting quantification procedure as Chromatic CRQA. Secondly, cross-recurrence plots of categorical data often prominently consists of rectangular structures. This calls for a differential analysis of vertical and horizontal lines, rather than of diagonal lines. We introduce a simple procedure for this, referred to as Anisotropic CRQA. Both procedures are demonstrated with empirical studies on children's problem-solving behavior and by means of a model simulation. The authors hope that the ideas presented here increase the power and applicability of CRQA in the behavioral sciences, and that this chapter serves as a stepping stone for their mathematical and methodological development.

Traditional analyses of reasoning and interactions often describe the building of knowledge by comparing general outcomes of group data (e.g., averages, frequencies and percentages) and as a result, often neglect the underlying individual processes. In this paper, we present a case study of two dyads of children (four to six years old) working on a problem-solving task and aim to capture the moment-to-moment changes in a time serial data set. Particularly, we present the changes in the types of interactions and scientific reasoning skills (SRS) during a single problem-solving task. The three descriptive techniques implemented in the data analysis are: (1) a time-series analysis to track the behaviours from moment to moment; (2) transition matrices to describe behaviour changes; and (3) a hierarchical agglomerative clustering (HAC) with a hybrid clustering technique used to detect dyadic patterns. Our results describe the intra-individual variability of the dyads, supporting the assumption of the non-ergodicity (i.e., neither homogeneous nor static) condition of psychological processes. We show that intra-individual trajectories in the children's behaviours are neither homogeneous nor stationary, but variable over time.

La mecánica cuántica representa un reto para la actual investigación en la enseñanzade la física, en gran medida, debido a que los fenómenos que ocurren a escala microscópica han reducido ideas fuertemente arraigadas a nuestra intuición, como es la idea del camino seguido por un cuerpo (trayectoria), la idea de ubicar un objeto en un lugar (localidad), o la idea de determinar con exactitud el resultado de una medición (determinismo). El investigador Lei Bao enfoca su estudio en varios tópicos que considera fundamentales para tener un buen entendimiento de la mecánica cuántica; uno de estos tópicos es la interpretación probabilística de la función de onda.En este artículo se lleva a cabo un análisis conceptual alrededor de la función de onda a través de un diagrama cognitivo denominado mentefacto conceptual; este ideograma ayuda a identificar y organizar nociones constitutivas y diferenciadoras implícitas en el concepto de función de onda, y se constituye en un aporte para la enseñanza-aprendizaje de este concepto.

Transfer is not static but a dynamic process of learning. In this article, the concept of transfer and the implications of its study are reconsidered from the theoretical basis of the complex dynamic system approach. We describe "transfer" as an emergent process that implies not a copy of knowledge applied to a new situation, but a new configuration of knowledge to solve new situations. Therefore, we discussed the concept of transfer based on the following dynamic principles: soft-assembly, multi causality, variability, self-organization, and iteration. To reconsider the concept of transfer, we provide empirical evidence, illustrating these principles by discussing two studies of transfer carried out with preschoolers. The participants were 34 children of 4 years old (M = 4,6), and 8 children of 4 to 6 years old (M = 5,2). Using repeated measure designs (3 weeks and 6 months, respectively), participants worked on sets of problem-solving situations in the domain of physics (i.e. Archimedes' principle and Air pressure). By using time-series graphs we identified the relevant elements of the tasks used by the children during the problem-solving process to analyze how this process ABOUT THE AUTHORS