Abstract In the computer age, data is the most valuable resource. Based on big data analysis technology, we have developed an intelligent physical training model for college students to control their training pace better. Simulation technology was also utilized to study and evaluate the operability of this technology, with the goal of developing more effective training programs for college students. The research found that... In the computer age, data is the most valuable resource. Based on big data analysis technology, we have developed an intelligent physical training model for college students to control their training pace better. Simulation technology was also utilized to study and evaluate the operability of this technology, with the goal of developing more effective training programs for college students. The research found that in the field of big data analysis, it is essential to utilize intelligent training methods to manage and adjust the competition time and intensity among college students. This method not only helps us to formulate and implement competition plans more swiftly but also aids in better understanding and handling a large amount of information, thereby improving the efficiency and quality of competitions. Hence, this method is worth our effort and promotion. Read More Read Less

Abstract The integration of traditional advantages, such as promoting Marxist theory and educational courses, with information technology is necessary for academic development. Achieving true “teaching based on individual differences” requires the scientific application of educational big data. This paper utilizes association rule mining technology to address the demand for student task point learning management in the current personalized learning platform system. It analyzes the current... The integration of traditional advantages, such as promoting Marxist theory and educational courses, with information technology is necessary for academic development. Achieving true “teaching based on individual differences” requires the scientific application of educational big data. This paper utilizes association rule mining technology to address the demand for student task point learning management in the current personalized learning platform system. It analyzes the current status and research trends of personalized learning and association rules. Then, it discusses the principles, advantages, and disadvantages of the classic Apriori algorithm and proposes an improved algorithm. Finally, the feasibility and actual effects of the algorithm are verified through simulations on the learning platform system, providing certain assistance for future research on Marxist theory and educational courses. Read More Read Less

Abstract In today’s society, the moral development of college students is crucial for maintaining social stability and growth, making it an urgent issue to address. To provide more practical information on moral development, we utilize K-Means clustering technology to group users based on their preferences, enabling the provision of more precise and valuable information. Firstly, the data is classified through a collaborative filtering algorithm to... In today’s society, the moral development of college students is crucial for maintaining social stability and growth, making it an urgent issue to address. To provide more practical information on moral development, we utilize K-Means clustering technology to group users based on their preferences, enabling the provision of more precise and valuable information. Firstly, the data is classified through a collaborative filtering algorithm to ensure data comparability and determine user preferences. Based on this, an effective model for recommending educational resources is created. Subsequently, the K-Means clustering algorithm is employed to develop a targeted recommendation process based on the specified objective function, yielding an effective recommendation of educational resources. Through experiments, we have found that this approach not only aligns well with the content of moral courses but also ensures that students are more engaged and achieve good results in reality. Read More Read Less