College Physical Education and Training in Big Data: A Big Data Mining and Analysis System

Area of Science:

• Sports Science
• Data Science
• Educational Technology

Background:

• Big data analytics are increasingly vital in research, prediction, and evaluation.
• College students' engagement in physical education is rising, driven by internet and smartphone accessibility.
• Existing technical limitations hinder effective collection and utilization of sports data generated during physical education.

Purpose of the Study:

• To design an intelligent big data system tailored for college physical education training.
• To address key challenges including data decentralization, talent shortages, technical support, and venue utilization.
• To improve the collection, storage, and analysis of sports data.

Main Methods:

• Development of an intelligent big data system for college physical education.
• Focus on decentralized data collection strategies.
• Implementation of a high-performance response framework for storing analytical data.
• Prioritization of ease of data collection in system design.

Main Results:

• The designed system facilitates effective data collection and management in physical education.
• Addresses critical issues such as data decentralization and talent gaps.
• Provides a robust framework for storing and analyzing sports-related data.
• Demonstrates potential for optimizing venue utilization.

Conclusions:

• The intelligent big data system offers a significant advancement for college physical education training.
• Effective data management and analysis are crucial for optimizing sports programs.
• The system design contributes to the improvement and optimization of current physical education practices.