Self-Regulated Learning of a Motor Skill Through Emulation and Self-Control Levels in a Physical Education Setting

This study examined the effectiveness of the second and third level of Zimmerman's (2000) model of self-regulated learning development. Participants were 72 (28 boys and 44 girls) fifth- and sixth-grade students who practiced the novel task of dart-throwing. Results showed that sixth-grade Greek students who proceeded sequentially from the emulation to the self-control level improved their dart-throwing performance more than students who missed one or both of these levels, but fifth-grade students benefited equally either from the sequential practice at the emulation and the self-control level or from the experience at one of these self-regulatory levels. No differences were found in self-efficacy, although sixth-grade students who practiced at the emulation level reported higher satisfaction, and sixth-grade students who practiced at the self-control level reported higher intrinsic motivation compared to control group students. These results attest to the effectiveness of learning at the emulation and self-control levels and are discussed with reference to the social cognitive model of self-regulation development.     

Multimodal interactions in typically and atypically developing children: natural versus artificial environments

This review addresses the central role played by multimodal interactions in neurocognitive development. We first analyzed our studies of multimodal verbal and nonverbal cognition and emotional interactions within neuronal, that is, natural environments in typically developing children. We then tried to relate them to the topic of creating artificial environments using mobile toy robots to neurorehabilitate severely autistic children. By doing so, both neural/natural and artificial environments are considered as the basis of neuronal organization and reorganization. The common thread underlying the thinking behind this approach revolves around the brain’s intrinsic properties: neuroplasticity and the fact that the brain is neurodynamic. In our approach, neural organization and reorganization using natural or artificial environments aspires to bring computational perspectives into cognitive developmental neuroscience.     

Pairwise Likelihood Ratio Tests and Model Selection Criteria for Structural Equation Models with Ordinal Variables

Correlated multivariate ordinal data can be analysed with structural equation models. Parameter estimation has been tackled in the literature using limited-information methods including three-stage least squares and pseudo-likelihood estimation methods such as pairwise maximum likelihood estimation. In this paper, two likelihood ratio test statistics and their asymptotic distributions are derived for testing overall goodness-of-fit and nested models, respectively, under the estimation framework of pairwise maximum likelihood estimation. Simulation results show a satisfactory performance of type I error and power for the proposed test statistics and also suggest that the performance of the proposed test statistics is similar to that of the test statistics derived under the three-stage diagonally weighted and unweighted least squares. Furthermore, the corresponding, under the pairwise framework, model selection criteria, AIC and BIC, show satisfactory results in selecting the right model in our simulation examples. The derivation of the likelihood ratio test statistics and model selection criteria under the pairwise framework together with pairwise estimation provide a flexible framework for fitting and testing structural equation models for ordinal as well as for other types of data. The test statistics derived and the model selection criteria are used on data on ‘trust in the police’ selected from the 2010 European Social Survey. The proposed test statistics and the model selection criteria have been implemented in the R package lavaan.     

Self-regulated learning in physical education: Examining the effects of emulative and self-control practice

Objective

This study examined the effectiveness of sequential practice from the emulation to the self-control level of the social cognitive model of self-regulated learning development. The model proposes that students who practice with social feedback at the emulation level first and then set goals and self-record their performance at the self-control level master sport skills effectively.

Design

The design included one between-subjects factor, the group with five levels and one within-subjects factor, time (pre-test, post-test).

Method

One hundred fifth and sixth grade students (40 boys and 60 girls) were assigned to four experimental and one control group and practiced the basketball dribble.

Results

The results showed that students of all experimental groups improved their dribbling performance from pre- to post-test. Students who received social feedback and observed repeated demonstrations at the emulation level and then set process or performance goals and self-recorded their performance at the self-control level improved their dribbling performance more than students who missed emulative practice. No improvement was found for control group students.

Conclusions

These results supported the effectiveness of the social cognitive model of self-regulated learning development, showing that this model can be used as an instructional approach for teaching sport skills in physical education.     

Detecting Outliers in Factor Analysis Using the Forward Search Algorithm

Dynamic factor analysis summarizes changes in scores on a battery of manifest variables over repeated measurements in terms of a time series in a substantially smaller number of latent factors. Algebraic formulae for standard errors of parameter estimates are more difficult to obtain than in the usual intersubject factor analysis because of the interdependence of successive observations. Bootstrap methods can fill this need, however. The standard bootstrap of individual timepoints is not appropriate because it destroys their order in time and consequently gives incorrect standard error estimates. Two bootstrap procedures that are appropriate for dynamic factor analysis are described. The moving block bootstrap breaks down the original time series into blocks and draws samples of blocks instead of individual timepoints. A parametric bootstrap is essentially a Monte Carlo study in which the population parameters are taken to be estimates obtained from the available sample. These bootstrap procedures are demonstrated using 103 days of affective mood self-ratings from a pregnant woman, 90 days of personality self-ratings from a psychology freshman, and a simulation study.     

Preliminary investigation of relations between young students' self-regulatory strategies and their metacognitive experiences

The present study investigated second-graders' self-regulative behav ior during task engagement and its relations to performance and to students' on-line metacognitive experiences. Participants were 25 individually examined Greek second graders (13 boys and 12 girls; M age: 7.6 yr., SD = 0.2). Students' use of cognitive, metacognitive, and motivational regulatory strategies while performing a cognitive task were directly observed and recorded by two independent observers. Students' task-specific performance was also evaluated. Finally, students' feeling of satisfaction with the solution produced, their estimate of effort expenditure, and estimate of the solution's correctness were assessed. Analysis showed these second grade students' use of self-regulatory strategies and feeling of satisfaction were significantly associated with their performance. However, metacognitive experiences reported after the solution were only slightly related to the students' actual self-regulative behavior during the task, implying that the relations of students' regulatory efforts with their metacognitive processes are still developing at such a young age.     

Excess of mixed-footedness among professional soccer players

This study concerns the distribution of footedness among professional soccer players (n=415) and nonsporting university students (n=430). Chi-squared showed that there were statistically significant differences between the proportion of mixed-footedness in the two groups (p<.0001). It appears that mixed-footedness or the ability to use both feet with an almost equal consistency is an important factor in the potential of individuals to reach high skill in soccer play. The mixed-footedness of these professional soccer players can be understood best in terms of both the nature of the game and genetic predisposition. This result is of direct interest in the context of those activities in which structural and functional biases in the lower extremities are important variables in acquisition and performance of motor skill.     

Approximated Penalized Maximum Likelihood for Exploratory Factor Analysis: An Orthogonal Case

The problem of penalized maximum likelihood (PML) for an exploratory factor analysis (EFA) model is studied in this paper. An EFA model is typically estimated using maximum likelihood and then the estimated loading matrix is rotated to obtain a sparse representation. Penalized maximum likelihood simultaneously fits the EFA model and produces a sparse loading matrix. To overcome some of the computational drawbacks of PML, an approximation to PML is proposed in this paper. It is further applied to an empirical dataset for illustration. A simulation study shows that the approximation naturally produces a sparse loading matrix and more accurately estimates the factor loadings and the covariance matrix, in the sense of having a lower mean squared error than factor rotations, under various conditions.     

Single- and Multiple-Group Penalized Factor Analysis: A Trust-Region Algorithm Approach with Integrated Automatic Multiple Tuning Parameter Selection

Psychometrika - Penalized factor analysis is an efficient technique that produces a factor loading matrix with many zero elements thanks to the introduction of sparsity-inducing penalties within...