Metacognitive scaffolding during collaborative learning: a promising combination

This article explores the effect of computerized scaffolding with different scaffolds (structuring vs. problematizing) on intra-group metacognitive interaction. In this study, we investigate 4 types of intra-group social metacognitive activities; namely ignored, accepted, shared and co-constructed metacognitive activities in 18 triads (6 control groups; no scaffolds and 12 experimental groups; 6 structuring scaffolds and 6 problematizing scaffolds).We found that groups receiving scaffolding showed significantly more intra-group interactions in which the group members co-construct social metacognitive activities. Groups receiving problematizing scaffolds showed significantly less ignored and more co-constructed social metacognitive interaction compared to groups receiving structuring scaffolds. These findings indicate that scaffolding positively influenced the group members’ intra-group social metacognitive interaction. We also found a significant relation between students’ participation in intra-group social metacognitive interaction and students’ metacognitive knowledge. Twelve percent of the variance in students’ metacognitive knowledge was explained by their participation in intra-group shared social metacognitive interaction. Therefore, future research should consider how to design scaffolds that elicit intra-group social metacognitive interaction among group members to enhance the development of students’ metacognitive knowledge

Mapping temporal dynamics in social interactions with unified structural equation modeling: A description and demonstration revealing time-dependent sex differences in play behavior

Developmental science is rich with observations of social interactions, but few available methodological and statistical approaches take full advantage of the information provided by these data. The authors propose implementation of the unified structural equation model (uSEM), a network analysis technique, for observational data coded repeatedly across time; uSEM captures the temporal dynamics underlying changes in behavior at the individual level by revealing the ways in which a single person influences – concurrently and in the future – other people. To demonstrate the utility of uSEM, the authors applied it to ratings of positive affect and vigor of activity during children’s unstructured laboratory play with unfamiliar, same-sex peers. Results revealed the time-dependent nature of sex differences in play behavior. For girls more than boys, positive affect was dependent upon peers’ prior positive affect. For boys more than girls, vigor of activity was dependent upon peers’ current vigor of activity.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/123050/1/Mapping temporal dynamics in social interactions with unified structural equation modeling_ A description and demonstration revealing time-dependent sex differences in play behavior.pd

The Individual Day-to-Day Process of Social Anxiety in Vulnerable College Students

Transitions requiring the creation of new social networks may be challenging for individuals vulnerable to social anxiety, which may hinder successful adjustment. Using person-specific methodology, this study examined social anxiety in vulnerable university freshman away from home during their first semester of college to understand how day-to-day processes of social anxiety influenced future social anxiety and social withdrawal. Participants completed daily measures of four components of social anxiety which were examined as a process during a single day, and as a process affecting social anxiety and social withdrawal the next day. For most individuals, same day fear of negative evaluation was associated with maladaptive cognitive processes (anticipatory processing and post-event rumination) and influenced social withdrawal behaviors. Across time relations were less robust and varied between participants suggesting the importance of situational factors and individual differences. These findings may have implications for the effectiveness of various intervention strategies

Person-Oriented and Subject-Specific Methodology: Some Additional Remarks

Objections that dynamic factor analysis, a prime subject-specific variable-oriented method, enables testing of all central person-oriented theoretical principles are answered in principled ways and a conjecture is presented regarding the relation between person- and variable-oriented methods

On the relation between person-oriented and subject-specific approaches

The necessity of using subject-specific data analysis of non-ergodic psychological processes is explained, emphasizing the difference between inter-individual and intra-individual variation. It is argued that subject-specific data analysis not only matches the principles underlying Developmental Systems Theory, but also enables testing of all principles of person-oriented theory. A new generalized perspective on measurement equivalence in subject-specific data analysis is introduced. The importance of computational optimal control of psychological processes within the context of subject-specific data analysis is emphasized. In closing, some broader aims of subject-specific data analysis are considered

State space modeling of time-varying contemporaneous and lagged relations in connectivity maps

Most connectivity mapping techniques for neuroimaging data assume stationarity (i.e., network parameters are constant across time), but this assumption does not always hold true. The authors provide a description of a new approach for simultaneously detecting time-varying (or dynamic) contemporaneous and lagged relations in brain connectivity maps. Specifically, they use a novel raw data likelihood estimation technique (involving a second-order extended Kalman filter/smoother embedded in a nonlinear optimizer) to determine the variances of the random walks associated with state space model parameters and their autoregressive components. The authors illustrate their approach with simulated and blood oxygen level-dependent functional magnetic resonance imaging data from 30 daily cigarette smokers performing a verbal working memory task, focusing on seven regions of interest (ROIs). Twelve participants had dynamic directed functional connectivity maps: Eleven had one or more time-varying contemporaneous ROI state loadings, and one had a time-varying autoregressive parameter. Compared to smokers without dynamic maps, smokers with dynamic maps performed the task with greater accuracy. Thus, accurate detection of dynamic brain processes is meaningfully related to behavior in a clinical sample

Phenotypic Selection in Ornamental Breeding: It's Better to Have the BLUPs Than to Have the BLUEs

Plant breeders always face the challenge to select the best individuals. Selection methods are required that maximize selection gain based on available data. When several crosses have been made, the BLUP procedure achieves this by combining phenotypic data with information on pedigree relationships via an index, known as family-index selection. The index, estimated based on the intra-class correlation coefficient, exploits the relationship among individuals within a family relative to other families in the population. An intra-class correlation coefficient of one indicates that the individual performance can be fully explained based on the family background, whereas an intra-class correlation coefficient of zero indicates the performance of individuals is independent of the family background. In the case the intra-class correlation coefficient is one, family-index selection is considered. In the case the intra-class correlation coefficient is zero, individual selection is considered. The main difference between individual and family-index selection lies in the adjustment in estimating the individual's effect depending on the intra-class correlation coefficient afforded by the latter. Two examples serve to illustrate the application of the BLUP method. The efficiency of individual and family-index selection was evaluated in terms of the heritability obtained from linear mixed models implementing the selection methods by suitably defining the treatment factor as the sum of individual and family effect. Family-index selection was found to be at least as efficient as individual selection in Dianthus caryophyllus L., except for flower size in standard carnation and vase life in mini carnation for which traits family-index selection outperformed individual selection. Family-index selection was superior to individual selection in Pelargonium zonale in cases when the heritability was low. Hence, the pedigree-based BLUP procedure can enhance selection efficiency in production-related traits in P. zonale or shelf-life related in D. caryophyllus L

Revisiting measurement invariance in intelligence testing in aging research: Evidence for almost complete metric invariance across age groups.

Background / Objectives: Invariance of intelligence across age is often assumed but infrequently explicitly tested. Horn and McArdle (1992) tested measurement invariance of intelligence, providing adequate model fit but might not consider all relevant aspects like subtest differences. The goal of the current paper is to explore age-related invariance of the WAIS-R using an alternative model that allows direct tests of age on WAIS-R subtests. Methods: Cross-sectional data on 940 participants aged 16-75 from the WAIS-R normative values were used. Subtests examined were information, comprehension, similarities, vocabulary, picture completion, block design, picture arrange-ment, and object assembly. The two intelligence factors considered were fluid and crystallized intelligence. Self-reported ages were divided into young (16-22, n = 300), adult (29-39, n = 275), middle (40-60, n = 205), and older (61-75, n = 160) adult groups. Results: Partial metric invariance holds in the WAIS-R. Although most subtests reflected fluid and crystalized intelligence similarly across different ages, invariance did not hold for block design on fluid intelligence and picture arrangement on crystallized intelligence for older adults. Additionally, there was evidence of a correlated residual between information and vocabulary for the young adults only. This partial metric invariance model yielded acceptable model fit compared to previously-proposed invariance models of Horn and McArdle (1992). Conclusion: Almost complete metric invariance holds for a two-factor model of intelligence. Most subtests were invariant across age groups, suggesting little evidence for age-related bias in the WAIS-R. However, we did find unique relationships between two subtests and intelligence. Future studies should examine age-related differences in subtests when testing measurement invariance in intelligence