Construction of University Sports Flipped Classroom Based on Sports Skills Learning and Mobile Edge Computing-Driven Neural Network

Abstract

In order to make students more interested in PE learning in PE teaching, it is necessary for PE educators to change the traditional way of thinking, take students as the main body of PE learning, be guided by teachers themselves, and use mobile edge computing and neural network technology as technologies. It enables students to carry out intelligent physical education independently. Whether the teaching is effective does not mean whether the teacher has completed the teaching content seriously, but whether the students have learned something, or whether the students have learned well. Based on the actual teaching practice of flipped sports classroom, this paper takes the “effectiveness” of sports classroom teaching as the breakthrough point, mainly adopts the research methods of comparative analysis, mobile edge computing, and neural network, and combines relevant domestic and foreign research results on the teaching of sports flipped classroom at home and abroad. An in-depth and comprehensive analysis of the effectiveness was carried out. The research results show that it is reliable to build a university sports flipped classroom with a neural network driven by motor skill learning and mobile edge computing as the carrier.

Method for Evaluating the Effectiveness of Physical Education Classes Utilizing offline and Online Mobile Edge Computing

“…(Wang and Xu, 2021) [6] Stated that many technological devices that help with this kind of interactions are collectively referred to as "knowledge transfer tools," and they help people learn by increasing their capacity to take in information, processing information into skills, and encouraging their own cognitive processes. According to (Sodhro et al, 2019) [7], incorporating multimedia technology into classrooms is essential if education is to remain contemporary in the 21st century. Many teachers see the development of multimedia as a catalyst for change and growth in educational settings.…”

“…They also claimed that the assessment system for Chinese universities' physical education instructors was badly flawed and called for reform. According to (Guo and Yang, 2022) [4], the main issues that need to be fixed during the execution of sports educational evaluations include unclear evaluation targets, biased substances, a single assessment topic, conventional evaluation procedures, and a lack of assessment feedback. It was proposed that, in order to address the problem of establishing a system of ratings for activities instruction, attention be paid to an integrated assessment goal of "understanding ability accomplishment," evaluation of subject matter of "emotional advancement psychology," integration of the varied assessment participants of "the instructor-student companion," and the practice of "timely objective positive."…”

Design of intelligent assistive system for physical education: based on personalized training plan

“…The methodologies of a response variable, stochastic tree, back-propagation Bayesian network, and deep learning models are mainly in comparison. [11] highlights the shortcomings of the evaluation and review of conventional physical education technical skill course work and suggests a procedure that utilizes convolutional neural networks and limited sample-acquiring knowledge. It is analyzed based on the undertone and qualities of machine learning.…”

Retracted: Construction of University Sports Flipped Classroom Based on Sports Skills Learning and Mobile Edge Computing-Driven Neural Network

“…This article has been retracted by Hindawi following an investigation undertaken by the publisher [1]. This investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process:…”