Effects of model-centered instruction on effectiveness, efficiency, and engagement with ill-structured problem solving

The goals of this study were to investigate the timing and the mechanism by which two types of model-centered instruction (MCI)—expert modeling (EM) and self-guided modeling (SGM)—might be made increasingly effective, efficient, and engaging for learners with different levels of expertise. The 62 pre-service and in-service evaluators who participated in the study were randomly assigned to one of these two types of MCI. The participants in the EM group were provided with the conceptual models used by experts to solve ethical conflicts within program evaluation. The participants in SGM group received no guidance in developing their own mental models. Regarding instructional effectiveness measures, there were no significant differences between the two types of MCI. However, inexperienced learners in the EM group invested less instructional effort and time than did those in the SGM group. In addition, inexperienced learners in the EM group also exhibited more engagement than did those in the SGM group. Therefore, EM is likely to be the more appropriate instructional design for inexperienced learners. Expert modeling required experienced learners to invest more mental effort, because if the conceptual model of the expert was redundant, it required them to integrate the previous schema with resulting overload of their working memory. Regardless of the types of MCI employed, the inexperienced participants showed significantly higher levels of attention and satisfaction than did the experienced participants.     

Fathers’ roles in the process of talent development

In the process of children’s talent development, fathers have been largely ignored compared to mothers who are mostly identified as the initial and primary influence for their children. Though modern fathers are becoming more engaged in childrearing and interacting more with their children and changes in family systems lead to new challenges and demands for defining parental roles today, fathers are still predominately portrayed as the principal breadwinners of families. Literature including both empirical and anecdotal data has documented positive and promising outcomes of paternal involvement for children’s talent development though fathers’ roles are not always differentiated from mothers’ roles and little research studied fathers and gifted children, exclusively. This paper includes a comprehensive review of fathers’ contributions to children’s talent development and discussion about issues and suggestions for research involving fathers and talent development.     

Modeling Self-Regulation as a Process Usinga Multiple Time-Scale Multiphase Latent Basis Growth Model

Measurement burst designs, wherein individuals are measured intensively during multiple periods (i.e., bursts), have created new opportunities for studying change at multiple time scales. This article develops a model that might be useful in situations where the functional form of short-term change is unknown, might consist of multiple phases, and might change over the long term. Specifically, we combine measurement of intraindividual entropy, a latent basis growth model, a multiphase growth model, and a growth model with covariates into a unified framework that could help accommodate the complexity of patterns that emerge in multiple time-scale categorical data streams. Empirical data from a longitudinal study of young children’s behavior during laboratory tasks designed to induce frustration are used to illustrate the utility of the proposed model for simultaneously describing intratask (short-term) change in self-regulation and developmental (long-term) shifts in intratask change.     

The etiology of giftedness

Many theories of giftedness either explicitly or implicitly acknowledge the role of genetic influences; yet, empirical work has not been able to establish the impact that genes have specifically on gifted behavior. In contrast, a great deal of research has been targeted at understanding the etiology of individual differences in general and specific cognitive abilities across the entire range of ability and to a lesser extent, high cognitive ability. This paper attempts to outline what we know and what we don't know about the etiology of giftedness as operationally defined as high g. We review studies selected to represent a variety of approaches that each address a different question about genetics and giftedness. These studies include quantitative genetic research which estimate heritability, shared and nonshared family environment – at the high and low ends of intelligence – as well as the heritability of group differences for general cognitive ability and specific cognitive abilities. We discuss the molecular genetic methods and mechanisms contributing to cognitive ability and suggest how epigenetic factors may operate. Quantitative and molecular genetic studies that include endophenotypes representing intelligence at a level closer to the genotype, are also included. This last group of studies represent a relatively new area of work that builds on and extends the extensive groundwork established by classic quantitative genetic studies of behavior.     

The effect of trust on teacher empowerment: the mediation of teacher efficacy

This study explores the impact of teachers’ perception of trust in colleagues on their sense of empowerment in Mainland China, with a particular focus on the mediating role of teacher efficacy. The results of a survey of 1646 teachers indicate that although teachers scored positively on trust in colleagues, efficacy and empowerment, they had relatively lower scores on general teaching efficacy (GTE) and participation in decision-making. Trust in colleagues was a significant predictor of teacher empowerment. In addition, personal teaching efficacy had a significant mediation effect on the relationship between trust in colleagues and teacher empowerment, while GTE had not. These findings lead to some implications for understanding the nature of GTE and the relationship between trust and teacher empowerment.     

Electrowetting on dielectric driven droplet resonance and mixing enhancement in parallel-plate configuration

This study experimentally verifies that the mixing process in a droplet can be enhanced by driving the droplet at resonant frequencies and at alternating driving frequencies using a parallel-plate electrowetting on dielectric device. The mixing time, which is defined as the time required for reaching the well-mixed state, in a resonant droplet is found to be significantly shorter than that in a non-resonant droplet. Besides, it is also found that a higher driving potential leads to a better mixing effect, especially at resonant frequencies. Furthermore, when a droplet is driven by alternating two driving frequencies, especially two resonant frequencies, the mixing efficiency is found to be significantly enhanced for a specific alternating duration of these two frequencies.     

Resistive pulse sensing of magnetic beads and supraparticle structures using tunable pores

Tunable pores (TPs) have been used for resistive pulse sensing of 1 μm superparamagnetic beads, both dispersed and within a magnetic field. Upon application of this field, magnetic supraparticle structures (SPSs) were observed. Onset of aggregation was most effectively indicated by an increase in the mean event magnitude, with data collected using an automated thresholding method. Simulations enabled discrimination between resistive pulses caused by dimers and individual particles. Distinct but time-correlated peaks were often observed, suggesting that SPSs became separated in pressure-driven flow focused at the pore constriction. The distinct properties of magnetophoretic and pressure-driven transport mechanisms can explain variations in the event rate when particles move through an asymmetric pore in either direction, with or without a magnetic field applied. Use of TPs for resistive pulse sensing holds potential for efficient, versatile analysis and measurement of nano- and microparticles, while magnetic beads and particle aggregation play important roles in many prospective biosensing applications.