Enhancing Cognitive Strategies in Sports Training: Insights from Second Language Acquisition Using Swarm Optimization Algorithms and Neural Networks

Abstract

The psychological, sociological, and linguistic frameworks of second language acquisition offer valuable insights into natural language learning processes, which can be parallel in sports psychology to enhance training methodologies. In the realm of sports, just as in language learning, there exists the challenge of creating optimal learning environments. This study draws analogies between English learning strategies in Chinese universities and sports training techniques, leveraging theories from second language acquisition to inform coaching practices in sports. With the advent of the Internet era, sports training, like university English teaching, encounters both new opportunities and challenges, with an increasing emphasis on specialization and informatization. Artificial intelligence technologies, like those applied in educational settings, can be adapted to sports to enhance training efficiency, contextual understanding, and emotional engagement. This paper proposes a novel approach using a swarm optimization algorithm and neural network model to analyze and enhance coaching quality. The model employs an encoder and decoder to extract semantic features from athletic performance data and optimizes training strategies using swarm techniques. This method not only supports coaches in tailoring training based on athletes' specific needs but also integrates advanced technological tools to refine and elevate athletes' performance and application abilities in competitive contexts.