Evaluation of the Quality of Football Teaching in Colleges and Universities Based on Artificial Neural Networks

Abstract

Every country is developing under the concept of artificial intelligence. Many countries are already working on student monitoring systems that allow them to control the student’s mentality and analyze each student’s behavior with the help of a wireless headband. There is certain high-tech education within the country in a maximum number of schools, which can be considered robotic monetization. With the help of tiny robots inside the classrooms, each student’s activeness and engagement level in the classes are captured and submitted to the teacher. All these practical applications help us imagine that there will be a massive response to artificial intelligence in the future of this world. On the other hand, sports management is a critical issue to consider for the country’s growth. This research evaluates the quality of football teaching by implementing an Artificial Neural Network model for online mode of education. The proposed model functions with the implementation of Association Rule Mining (ARM) in the intelligent system to monitor the activities of the player by training with the Artificial Neural Network (ANN). The proposed model is compared with the existing K-Mean algorithm, and it is observed that the proposed model has achieved an accurate evaluation of 99.6%.