O efeito posterior duradouro de treinamento (EPDT) das cargas concentradas de força : investigação a partir de ensaio com equipe infanto juvenil e juvenil de voleibol

Universidade Estadual de Campinas. Faculdade de Educação Física

A motivação de alunos no contexto da progressão continuada

This study investigated the intrinsic and extrinsic motivacional orientations of students in the context of the educational continuous progression. The sample was composed of 160 subjects of second, fourth, sixth and eighth grades of the elementary school. Data was collected by means of the presentation of histories involving the intrinsic, extrinsic motivation and the educational continuous progression system. Subjects were interviewed individually. Their answers were transcribed verbatim and submitted to content analysis. Results indicated that a expressive percentage of students did not know the educational system of continuous progression. Students revealed a predominantly intrinsic motivation orientation with advances in age and in school grade level, even though knowing that they will not repeat any school grade. This study pointed out the importance of deepening our knowledge concerning the impact of the educational continuous progression in students' motivation to learn.

Augmented Mixed Models For Clustered Proportion Data.

Often in biomedical research, we deal with continuous (clustered) proportion responses ranging between zero and one quantifying the disease status of the cluster units. Interestingly, the study population might also consist of relatively disease-free as well as highly diseased subjects, contributing to proportion values in the interval [0, 1]. Regression on a variety of parametric densities with support lying in (0, 1), such as beta regression, can assess important covariate effects. However, they are deemed inappropriate due to the presence of zeros and/or ones. To evade this, we introduce a class of general proportion density, and further augment the probabilities of zero and one to this general proportion density, controlling for the clustering. Our approach is Bayesian and presents a computationally convenient framework amenable to available freeware. Bayesian case-deletion influence diagnostics based on q-divergence measures are automatic from the Markov chain Monte Carlo output. The methodology is illustrated using both simulation studies and application to a real dataset from a clinical periodontology study.