The strategies of parental involvement in adolescents’ education and extracurricular activities
Different parental strategies in education are bound to produce various effects: not all of these strategies are equally productive in their application. At the same time, the impact of parental involvement in general education on their children's extracurricular activities has not been thoroughly studied. This article attempts to fill this gap by analyzing the relationship between strategies of parental involvement in education and adolescents' participation in extracurricular activities. The data source for this study were parents whose children attend general education institutions (N = 3,887; Mage of children = 12.4, SD = 3.1; 55.6% female). A latent class analysis identified three categories of parental participation in education: “Intrusive”, “Supervisory”, and “Detached”. Each category showed different patterns of involvement from primary to high school, distinguished by the type of extracurricular participation encouraged by parents. In primary school, children of “Intrusive” parents attended the highest number of extracurricular activities. In secondary school, they attended fewer activities compared to the children of “Supervisory” parents. Children of “Supervisory” parents often chose to participate in activities on their own, and continued to attend the selected activity, or change activity on their own initiative. The children of “Detached” parents were less involved in extracurricular activities in primary school. In some cases, they chose their own extracurricular activities as they grew older. The study demonstrates that parental involvement is related to adolescents’ participation in extracurricular activities. Parents’ strategies should be considered instrumental as they produce a variety of different outcomes, depending upon the adolescents’ age and type of activities. The identified strategies may serve as a basis for recommendations for development of parental competencies, consultations, and family education.
This article discusses ways to stimulate students' motivation to participate in extracurricular activities. The author points out the following forms of extra-curricular activities: administrative, informative and entertaining. The author proposes the scale of assessment of students for participation in extracurricular activities. These forms should be taken into account in the rating system of the student's academic achievement
ABSTRACT The aim of this study was to consider digit ratio (2D:4D: a putative marker of prenatal testosterone and estrogen levels) and aggression in a sample of 1,452 children and adolescents (mean age 13.6 years) from five regions of Russia. The 2D:4D was calculated from direct measurements of the fingers, and aggression scores were obtained from completed Buss and Perry (J Pers Soc Psychol 63 (1992) 452–459) aggression questionnaires. The 2D:4D demonstrated significant sexual dimorphism, with lower 2D:4D in boys in all regions. Physical aggression scores were highest in boys, but verbal aggression, anger and hostility were highest in girls. The highest right hand 2D:4D in boys was found in the most northerly population (Central Russia Region). Our data revealed small, but highly significant negative correlations between right 2D:4D, right–left 2D:4D (DR-L) and self-ratings on physical aggression in boys, but not in girls. These relationships remained after considering Russian ethnics only, and controlling for region. We suggest that the associations may be due to sex differences in prenatal androgen secretion. Am J Phys Anthropol 152:130-139, 2013. VC 2013 Wiley Periodicals, Inc.
Why do children learn in different ways: some are good students who show interest and zeal, while others are lazy and have to be taught against their will? Why do schools have over- and underachievers? Of course, there are a multitude of reasons. But almost 50 years ago it was shown using large data sets that families with high socioeconomic status are more likely to have children who are good students. Of course, there are many examples of successful students from poor families. However, they tend to be the exception to the rule. The certainty of success in school increases with rising socioeconomic status.
The distractive effects on attentional task performance in different paradigms are analyzed in this paper. I demonstrate how distractors may negatively affect (interference effect), positively (redundancy effect) or neutrally (null effect). Distractor effects described in literature are classified in accordance with their hypothetical source. The general rule of the theory is also introduced. It contains the formal prediction of the particular distractor effect, based on entropy and redundancy measures from the mathematical theory of communication (Shannon, 1948). Single- vs dual-process frameworks are considered for hypothetical mechanisms which underpin the distractor effects. Distractor profiles (DPs) are also introduced for the formalization and simple visualization of experimental data concerning the distractor effects. Typical shapes of DPs and their interpretations are discussed with examples from three frequently cited experiments. Finally, the paper introduces hierarchical hypothesis that states the level-fashion modulating interrelations between distractor effects of different classes.
We address the external effects on public sector efficiency measures acquired using Data Envelopment Analysis. We use the health care system in Russian regions in 2011 to evaluate modern approaches to accounting for external effects. We propose a promising method of correcting DEA efficiency measures. Despite the multiple advantages DEA offers, the usage of this approach carries with it a number of methodological difficulties. Accounting for multiple factors of efficiency calls for more complex methods, among which the most promising are DMU clustering and calculating local production possibility frontiers. Using regression models for estimate correction requires further study due to possible systematic errors during estimation. A mixture of data correction and DMU clustering together with multi-stage DEA seems most promising at the moment. Analyzing several stages of transforming society’s resources into social welfare will allow for picking out the weak points in a state agency’s work.