Application of Random Dynamic Grouping Simulation Algorithm in PE Teaching Evaluation

Abstract

The probability ranking conclusion is an extension of the absolute form evaluation conclusion. Firstly, the random simulation evaluation model is introduced; then, the general idea of converting the traditional evaluation method to the random simulation evaluation model is analyzed; on this basis, based on the rule of “further ensuring the stability of the ranking chain on the basis of increasing the possibility of the ranking chain,” two methods of solving the probability ranking conclusion are given. Based on the rule of “further guaranteeing the stability of the ranking chain on the basis of improving the likelihood of the ranking chain,” two methods are given to solve the likelihood conclusion. This paper argues that this absolute form of conclusion hinders the approximation of the theory to the essence of the actual problem and is an important reason for the problem of “non-consistency of multi-evaluation conclusions.” To address this problem, a stochastic simulation-based comprehensive evaluation solution algorithm based on the idea of “Monte Carlo simulation” is proposed, and the corresponding ranking method is investigated, which is characterized by generating evaluation conclusions with probability (reliability) information, and thus has more advantages than the absolute conclusion form in terms of problem interpretability. The method is characterized by the generation of evaluation conclusions with probabilistic (reliability) information and thus has more advantages than the absolute conclusion form in terms of problem interpretation. Because of the independence of the stochastic simulation solution method, it is applied to the “bottom-up” evaluation model as an example, and a novel autonomous evaluation method is constructed. Finally, the application of the stochastic simulation evaluation model is illustrated by an example and compared with the absolute form evaluation. The evaluation model is an extension of the traditional evaluation model, which can further broaden the practical application of comprehensive evaluation theory.

Research on Multiple Evaluation of English Teaching in Higher Vocational School-Enterprise Cooperation in the Era of Multimedia Informatization

“…It can effectively reduce the influence of human factors on the decisionmaking results, so it has a more scientific application prospect in teaching quality assessment. The neural network has a strong nonlinear processing ability, can solve nonlinear problems, and has shown good performance in practical applications [23][24][25].…”

Evaluation Method of Physical Education Teaching and Training Quality Based on Deep Learning

“…rough formula (11), the single-level weight of physical education teaching and training evaluation index is obtained, and then, the index weight is calculated. e product of the index weight and the upper-level index weight is obtained to obtain the relative weight of each layer of evaluation index in the hierarchy for the overall goal of physical education teaching and training, that is, the weight value of the index relative to the overall goal.…”

“…To reduce the pressure on all aspects of society, the school has to use the sword of examination-oriented education-examination and cancel the dangerous items in students' physical education class and the endurance items of long-distance running. However, teaching for the purpose of examination is obviously not the real education we pursue [ 9 – 11 ]. The development of the country depends on talents, and the cultivation of talents depends on education.…”