Effectiveness of quality physical education in improving students' manipulative skill competency

Purpose： This study aimed to examine the extent to which the quality physical education teaching （QPET） practices contributed to improving 4th- and 5th-grade students＇ manipulative skill competency. Methods： Participants were 9 elementary physical education （PE） teachers and their 4th- and 5th-grade students （n = 2709 3420）. The students＇ skill competency was assessed with 3 manipulative skills using PE metrics assessment rubrics. The PE teachers＇ levels of QPET were assessed by coding 63 videotaped lessons using the assessing quality teaching rubrics （AQTR）, which consisted of 4 essential dimensions including task design, task presentation, class management, and instructional guidance. Codes were confirmed through inter-rater reliability （82.4%, 84.5%, and 94%）. Data were analyzed through descriptive statistics, multiple R2 regression models, and independent sample t tests. Results： This study indicated that the 4 essential dimensions of QPET were all significant contributors to students＇ manipulative skill competency. These predictors were significantly higher for boys than for girls in soccer and striking skills, while they were significantly higher for girls than for boys in throwing skill competency. Of the 4 essential dimensions of QPET, task presentation played the most significant role in contributing to all 3 skill competencies for both boys and girls. Further, students who experienced high QPET were significantly more skillfully competent than those students who did not have this experience. Conclusion： It was concluded that the QPET practices played a significantly critical role in contributing to students＇ manipulative skill competency.

Manipulative skill competency and health-related physical fitnes in elementary school students

Background：Improving motor skill competency and enhancing health-related physical fitnes are desired learning outcomes for school-aged children.Achieving motor skill competency and a healthy level of physical fitnes lay a foundation for being a physically active person across a lifetime.The purpose of this study was to investigate relationships between levels of manipulative skill competency and physical fitnes for elementary school boys and girls.Methods：In this study,565 fourth-grade students and their 9 physical education teachers were voluntary participants.The students were assessed in 4 basic specialized manipulative skills and 4 fitnes components during regular physical education lessons.Data were analyzed with descriptive statistics,univariate analyses,and multiple R2 liner regression methods.Results：Boys were more proficien at the manipulative skills than girls,while girls had significan higher percentages for meeting the healthy fitnes zone for the fitnes tests than boys.Four manipulative skills significant y predicted progressive aerobic cardiovascular endurance run（PACER）,push-up,and trunk lifts tests at p〈0.05 level,but not curl-up test for both boys and girls.Boys and girls in the skill-competent group significant y outperformed their counterparts in the skill-incompetent group on PACER,push-up,and trunk lifts tests at p〈0.05 level,with an exception of curl-up test.Conclusion：The more competent in manipulative skills,the higher healthy level in cardiovascular endurance,upper-body muscular strength and endurance,and fl xibility the students demonstrated.Demonstrating manipulative skill competence and maintaining a healthy level of physical fitnes are 2 major desired learning outcomes for elementary school students to be able to achieve.

A Novel Heterogeneous Actor-critic Algorithm with Recent Emphasizing Replay Memory

Reinforcement learning(RL) algorithms have been demonstrated to solve a variety of continuous control tasks. However,the training efficiency and performance of such methods limit further applications. In this paper, we propose an off-policy heterogeneous actor-critic(HAC) algorithm, which contains soft Q-function and ordinary Q-function. The soft Q-function encourages the exploration of a Gaussian policy, and the ordinary Q-function optimizes the mean of the Gaussian policy to improve the training efficiency. Experience replay memory is another vital component of off-policy RL methods. We propose a new sampling technique that emphasizes recently experienced transitions to boost the policy training. Besides, we integrate HAC with hindsight experience replay(HER) to deal with sparse reward tasks, which are common in the robotic manipulation domain. Finally, we evaluate our methods on a series of continuous control benchmark tasks and robotic manipulation tasks. The experimental results show that our method outperforms prior state-of-the-art methods in terms of training efficiency and performance, which validates the effectiveness of our method.