scholarly journals Singapore's Physical Education in the Era of Artificial Intelligence: Supports and Strategies

2021 ◽  
Vol 10 (6) ◽  
pp. 645-654
Author(s):  
Ho Jin Chung
Keyword(s):  
Artificial Intelligence ◽  
Physical Education

Reform and innovation of artificial intelligence technology for information service in university physical education

2020 ◽  
pp. 1-11
Author(s):  
Jianye Zhang
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Physical Education ◽  
Information Service ◽  
Management Decision ◽  
Negative Effects ◽  
Education Management ◽  
Depth Analysis ◽  
Artificial Intelligence Technology ◽  
The Difference

This article analyzes the reform of information services in university physical education based on artificial intelligence technology and conducts in-depth and innovative research on it. In-depth analysis of the relationship between big data and the development and application of information technology such as the Internet, Internet of Things, cloud computing, to clarify the difference and connection between big data, informatization and intelligence. Artificial intelligence will bring opportunities for changes in data collection, management decision-making, governance models, education and teaching, scientific research services, evaluation and evaluation of physical education in our university. At the same time, big data education management in colleges and universities faces many challenges such as the balance of privacy and freedom, data hegemony, data junk, data standards, and data security, and they have many negative effects. In accordance with the requirements of educational modernization, centering on the goal of intelligent and humanized education management, it aims existing issues in college physical education management.

An AI based design of student performance prediction and evaluation system in college physical education

2020 ◽  
pp. 1-9
Author(s):  
Zhang Yangsheng
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Physical Education ◽  
Student Performance ◽  
Internal Structure ◽  
Process Evaluation ◽  
Performance Prediction ◽  
Evaluation System ◽  
Evaluation Model ◽  
Good Effect

College physical education is too one-sided, which makes the teaching process evaluation meaningless. Based on this, based on neural network technology, this article combines artificial intelligence teaching system to build an artificial intelligence sports teaching evaluation model based on neural network. The artificial intelligence model starts from the process evaluation and the final evaluation. Moreover, it uses a recurrent neural network for data training and analysis, and introduces a new decoder to perform data processing, and introduces a simplified gated neural network internal structure diagram to build the internal structure of the model.In addition, this study designs a control experiment to evaluate the performance of the model constructed in this study. The research results show that the artificial intelligence model constructed in this paper has a good effect in the performance prediction and evaluation of college sports students.

The effectiveness of physical education teaching in college based on Artificial intelligence methods

2020 ◽  
pp. 1-11
Author(s):  
Zihao Li ◽  
Hejin Wang
Keyword(s):  
Artificial Intelligence ◽  
Physical Education ◽  
Rapid Development ◽  
Participation Rate ◽  
Colleges And Universities ◽  
The Body ◽  
Current Status ◽  
Innovative Teaching ◽  
Artificial Intelligence Technology ◽  
Low Activity

Traditional physical education in colleges and universities is difficult to arouse students’ interest in sports, resulting in low activity participation rate and inability to exercise the body. How to effectively improve the effectiveness of physical education in colleges and universities has become one of the hot topics of most concern from all walks of life. In physical education, innovative teaching concepts and methods, teaching methods and processes, and teaching evaluation methods are all conducive to improving the classroom atmosphere of physical education and successfully improve the effectiveness of physical education. This article focuses on analyzing the current status of physical education in colleges and universities. Based on the rapid development of artificial intelligence technology, how to improve the effectiveness of physical education is studied, and an experimental method is used to compare and analyze physical education in a college. The analysis results show that artificial intelligence-based physical education can obviously improve students’ strength quality, speed quality, endurance quality, and agility quality, which provides a more important reference and reference for improving the effectiveness of college physical education.

Artificial intelligence based on effectiveness of inverted classroom teaching of college sports

2020 ◽  
pp. 1-11
Author(s):  
Jianqin Cheng ◽  
Xiaomeng Wang
Keyword(s):  
Artificial Intelligence ◽  
Physical Education ◽  
Real Time ◽  
Visual Analysis ◽  
Analytical Framework ◽  
Colleges And Universities ◽  
Classroom Teaching ◽  
Teaching Behaviors ◽  
Inverted Classroom ◽  
Artificial Intelligence Technology

This study takes the effectiveness analysis of inverted classroom teaching in colleges and universities as a breakthrough point, and combines artificial intelligence technology with the analysis method of inverted classroom teaching in colleges and universities to enrich the existing methods for analyzing, the behavior of inverted classroom teaching in colleges and universities to realize the effectiveness of inverted classroom teaching in colleges and universities analysis. This research first constructs an analytical framework for the teaching behaviors of college physical education inverted classrooms based on artificial intelligence technology, which consists of observation dimension and the evaluation dimension. In order to further test the scientifically and operability of the analytical framework, taking emotion recognition as an example, practical operations are combined with specific examples to obtain visual analysis results. This study expands the dimension and depth of analysis of the behavior of inverted sport in classroom teaching in sport inversion colleges and universities, and has obvious advantages in saving manpower and real-time visual display. Through the analysis of the effectiveness of physical education inverted classroom teaching in sports inversion colleges and universities through artificial intelligence technology, the use of technology to participate in the analysis of physical education inverted classroom teaching behaviors in sports inverted colleges and universities, shorten the evaluation time, expand the evaluation dimension, improve the evaluation efficiency, achieve real-time feedback, real-time attention to classroom effects. Effectively regulating the inverted classroom teaching behavior of college physical education can promote the cultivation of teachers’ professional abilities, scientifically and accurately improve and correct teaching problems, and improve the quality of education and teaching. Eventually, students will achieve comprehensive self-evaluation of students, and promote personalized and standardized growth of students.

An artificial intelligence fuzzy system for improvement of physical education teaching method

2020 ◽  
pp. 1-10
Author(s):  
Gaobin ◽  
Cao Huan Nan ◽  
Liu Zhen Zhong
Keyword(s):  
Artificial Intelligence ◽  
Physical Education ◽  
Teaching Methods ◽  
Evaluation System ◽  
Teaching Method ◽  
Motion Vector ◽  
System Structure ◽  
Functional Requirements ◽  
Experimental Teaching ◽  
Vector Decomposition

There are certain disadvantages in the traditional physical education teaching model. In order to improve the advanced nature of physical education teaching methods, this paper builds a physical education evaluation system based on artificial intelligence fuzzy algorithm. The system uses fuzzy control instructions as the basis to combine human language and mechanical language, so that the machine can recognize human working language habits and execute commands according to the instructions. Moreover, in this study, the trapezoid function is selected as the membership function, and the improved particle optimization algorithm is used to capture the student’s motion process and the motion vector decomposition, and the system structure model is constructed based on the functional requirements analysis. In addition, this study conducts system performance analysis through experimental teaching methods. The research results show that this system can effectively promote the reform of teaching methods in physical education and has a certain practical effect.

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