AN INVESTIGATION OF ONLINE LEARNING READINESS AMONG PHYSICAL EDUCATION STUDENTS IN VIETNAM

Cardiorespiratory fitness is the ability to maintain moderate or high-intensity efforts for In light of the global Covid pandemic, educational institutions worldwide have shifted to online modalities, presenting both opportunities and challenges. This study offers an in-depth examination of the online learning readiness among students at the Ho Chi Minh City University of Physical Education and Sports in Vietnam. Drawing from comprehensive data, we assess critical factors determining successful online learning experiences. These factors include the availability and adequacy of students' technological equipment, their personal internet access quality and reliability, the specific online learning intentions and motivations of the 14th intake students, and the hurdles they encountered when interfacing with the learning management system. Additionally, the research sheds light on potential pedagogical adjustments and infrastructural enhancements that can be made to streamline the transition. By discerning the precise state of online learning preparedness and the challenges faced, this research not only gauges the current state of affairs but also provides actionable insights aimed at optimizing the effectiveness of digital instruction at the Ho Chi Minh City University of Physical Education and Sports.  Article visualizations

MOBILE LEARNING FOR PHYSICAL EDUCATION STUDENTS IN VIETNAM: PROMISES AND CHALLENGES

The rise in mobile learning has seen an impressive increase as smartphones and tablets have increased in popularity in recent years. The cheap, easy access to these devices for students contributes to the need for use for educational and learning purposes. This trend is no exception for physical education. This study surveyed 125 physical education students in 4 badminton classes from 2018 to 2020 to evaluate their readiness for mobile learning in terms of hardware devices, technology skills, learning styles, and habits. Data coming from questionnaires in the courses and server logs of a mobile learning system show that the majority of physical education students in the study are ready for mobile learning despite some challenges regarding internet infrastructure and lack of formal online learning skills training. Article visualizations

BLENDED LEARNING IN BADMINTON TRAINING FOR PROFESSIONALS: STUDENTS’ PERCEPTIONS AND PERFORMANCE IMPACTS

As with other subject areas, badminton instruction for practitioners is experiencing a lot of changes under the impact of technology. Recently there has been the possibility of moving badminton training classes to the online platform but there is no consensus on its efficacy. This study is conducted to study the effects of blended learning activities on the perceptions and performance of students in physical education. Forty students in physical education are selected and divided into two groups: an experimental group, and a control group. All groups in face-to-face learning sessions have the same curriculum, course-book, equipment and teaching method. The questionnaire and interview data show that students in blended class sessions had positive perceptions of learning activities.  Article visualizations

M-LEARNING APPLICATION IN TEACHING BADMINTON FOR PHYSICAL EDUCATION STUDENTS IN VIETNAM

The article evaluates the efficacy of M-learning in instructing the Badminton course for K14 university students at the University of Sports and Physical Education in Ho Chi Minh City, Vietnam. Utilizing an experimental design, it contrasts the outcomes of two groups: the K13 students who were taught through conventional face-to-face methods and the K14 students who engaged in blended learning. Both groups were exposed to identical content and assessment procedures. The findings indicate that students in the blended learning approach outperformed their peers in the traditional setting. The study also delves into resource utilization and collects feedback from learners, underscoring the advantages of M-learning in Badminton instruction.  Article visualizations

A Bibliometric Analysis of Studies Concerning Policy Issues in Covid-19 Pandemic

This research analysed the studies of policy on issues related to COVID-19. The results show the most productive countries, the most frequently cited sources, the most co-occurred topics of studies concerning policy issues since the epidemic was a breakout at the beginning. The data in this research were collected from the Scopus database with two search terms, "COVID-19" and "policy" of the social science domain, and published from the first day of 2020 to the search time (September 10, 2020). The final dataset consists of 384 valid documents analysed by descriptive statistics, and co-occurrence analysis was applied in R. Among 46 countries, the United States, the United Kingdom, Australia, China, India, and Italy are the leading countries that published these studies. Almost all the funded scholars focused on Europe, the Americas, and Asia. The main topics of the articles are "working in COVID-19 period", "community health and social support," "using ICT in teaching and learning," "human rights." Within funded studies, four interesting topics are "social well-being," "ICT infrastructure," "agricultural policy," and "born-digital." This study presents the current situation of how studies concerning policy issues have been issued to respond to the COVID-19 pandemic

Joint Transaction Transmission and Channel Selection in Cognitive Radio Based Blockchain Networks: A Deep Reinforcement Learning Approach

To ensure that the data aggregation, data storage, and data processing are all performed in a decentralized but trusted manner, we propose to use the blockchain with the mining pool to support IoT services based on cognitive radio networks. As such, the secondary user can send its sensing data, i.e., transactions, to the mining pools. After being verified by miners, the transactions are added to the blocks. However, under the dynamics of the primary channel and the uncertainty of the mempool state of the mining pool, it is challenging for the secondary user to determine an optimal transaction transmission policy. In this paper, we propose to use the deep reinforcement learning algorithm to derive an optimal transaction transmission policy for the secondary user. Specifically, we adopt a Double Deep-Q Network (DDQN) that allows the secondary user to learn the optimal policy. The simulation results clearly show that the proposed deep reinforcement learning algorithm outperforms the conventional Q-learning scheme in terms of reward and learning speed

Speedup of Interval Type 2 Fuzzy Logic Systems Based on GPU for Robot Navigation

As the number of rules and sample rate for type 2 fuzzy logic systems (T2FLSs) increases, the speed of calculations becomes a problem. The T2FLS has a large membership value of inherent algorithmic parallelism that modern CPU architectures do not exploit. In the T2FLS, many rules and algorithms can be speedup on a graphics processing unit (GPU) as long as the majority of computation a various stages and components are not dependent on each other. This paper demonstrates how to install interval type 2 fuzzy logic systems (IT2-FLSs) on the GPU and experiments for obstacle avoidance behavior of robot navigation. GPU-based calculations are high-performance solution and free up the CPU. The experimental results show that the performance of the GPU is many times faster than CPU