# Design of College Students’ Sports Assessment System Based on Data Mining

Authors: Gang Wang
Journal: Scientific Programming
 (2022)

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## Abstract

In order to improve the quality of modern physical education (PE) and let PE teachers get rid of the busy data management, this article puts forward the design of an assessment system about sports performance based on data mining and introduces the scheme of the system in detail. Based on NET three-tier architecture, the demand of users is analyzed, combined with web technology, SQL database platform, and the theory of data mining. The technical architecture of the system and the design of the database are discussed, and the realization of the functional module of sports achievement management is implemented. The system is tested so that the accuracy is verified in use. At the same time, the system runs well after testing and application. Through this system, PE teachers can realize the management and statistics of sports performance, reduce the intensity of teachers, and enable PE teachers to devote themselves to improving the quality of PE teaching.


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## Body

## 1. Introduction

In the process of China’s social and economic progress, China’s education system is undergoing continuous reform, and the requirements for comprehensive physical fitness and high-quality talents are getting higher than before. In modern society, students not only need good grades but also have a demand for physical fitness so that they can make advances in future work [1]. This also meant that physical education is the foundation of other disciplines, students’ sports test also began to count their total scores, and the view that sports is not so important has been gradually changed [2]. As for the calculation of sports achievement, it is mainly through the test of students’ PE class, such as high jump, long jump, and 300-meter dash, which are converted into specific scores according to the relevant regulations of the school. Because of the diverse content of PE courses, much achievement data are produced in the implementation of testing. Teachers have to implement the data conversion and input them into the school educational administration system. The results are made by hand movement under heavy workload so that the work efficiency cant be improved, which restricts the sustainable development of physical education [3, 4]. To solve these problems, we need a data statistics and analysis system that can make PE teachers get rid of heavy tasks, effectively solve these problems, and optimize inner work so as to give full play to the guiding role of teachers in PE teaching.With the rapid development of computer technology, data mining is constantly improving, and more and more companies and enterprises are beginning to use data mining technology to improve their own management system [5], which constantly promotes the prosperity of their companies. For data mining technology, it is widely used in major companies. However, the application in colleges is relatively less because colleges pay more attention to theoretical knowledge, and data mining technology is less used in the management system of colleges [6–8]. But in fact, this is a loss to the management system of colleges. Due to the lack of application, the related management of students is rather heavy, which results in lower working efficiency. The data mining technology has the advantages of good performance, simple operation, and easy employment. Due to these advantages, the rapid development of this technology is constantly promoted [9]. In view of the problems in modern PE teaching, this article utilizes information mining innovation to understand the programmed handling and analysis of data on sports achievement, which is convenient for students to inquire about their scores and teachers’ statistics so as to continuously improve the efficiency and teaching quality of the college.


## 2. Introduction to Related Technical

### 2.1. ASP.NET Technology

ASP.NET is developed by integrating ASP and NET technologies [10, 11]. ASP.NET is applicable to a wide range of each field, such as the dynamic process of website design. Compared with other technologies, ASP.NET has its own unique advantages. It mainly includes the following points: (1) ASP.NET is a newly developed technology, which is popular among people, and it integrates the advantages of both ASP and NET technologies; (2) ASP.NET has a wide range of database resources, and it can translate many languages, which is convenient for people to use; (3) ASP.NET has been developed on the basis of various technologies, which has many functional advantages and is easier to operate than others [12, 13].It can be seen from Figure1 that ASP.NET is mainly composed of three parts, which are mainly divided into the user layer, business logic layer, and data access layer.(1)
The user layer, also known as the presentation layer, is a layer directly facing customers, and all interaction between users is the responsibility of this layer. Therefore, in the application of this layer, It is necessary to build a concise appearance to facilitate users’ operation [14].(2)
Business logic layer located in the middle layer is mainly used to calculate and process business-related logic. This layer plays a connecting role and is the core layer of the three layers [15].(3)
Data access layer, which mainly represents various operations on the database, provides various data services for the previous layer and feeds back the processing results.Figure 1
Three-layer structure based on ASP.NET.These three layers are related and interlocking. Reasonable adjustment of these layers can not only improve the operating efficiency of the company but also improve the economic benefits of the enterprise. Moreover, these components have their own unique advantages, and at the same time, the operation and use are relatively simple and practical.


### 2.2. Database of SQL Server

SQL is a structured language for querying, and SQL Server is a database management system. The database management system is used for storing all kinds of data used in the system, and at the same time, various operations of data, including query, modification, and deletion, are realized by transferring SQL statements. This kind of database management system is mostly used to develop a distributed system, which is convenient to operate. Moreover, it is powerful, can realize various functions of accessing and operating data, and provides a concise user interface to learn [16, 17].The database system of the sports assessment system is SQL Server 2005, which was chosen because of its unique advantages, as follows: (1) the application of distributed view greatly improves the speed of accessing the database and the work efficiency, while the distributed view can quickly locate the data [18]; (2) it supports multiple development languages, including XML and other languages; (3) it has better performance and higher reliability; (4) it encapsulates a variety of technologies that are commonly used to realize data integration; (5) SQL Server 2005 provides users with a virtual network of the interface system.


### 2.3. Data Mining

In brief, data mining is to extract or “explore” knowledge from data in quantity [19, 20]. Many people regard data mining as another term data that is commonly used.It is synonymous with knowledge discovery in database (KDD) in mining database, while others just regard data mining as a link of KDD, which is a process of extracting useful patterns from data automatically and efficiently using specific algorithms of data mining. KDD is a cyclic process including data mining and data preparation.At present, there is no exact definition of “data mining.” A relatively accepted definition is put forward by W.J. Frawley, G. Piatetsky-Shapiro, and others: that is, data mining is an extraordinary process to obtain patterns that are correct, novel, potentially applicable, and finally understandable from data [21].Information mining is a multistage process and can, for the most part, be isolated into three principal stages: information readiness, information mining, and result articulation and translation. KDD is an iterative process of the three stages. The specific process can be described in Figure2 [22].Figure 2
Process knowledge discovery in database.


#### 2.3.1. Stage of Data Preparation

Data preparation represents the biggest extent in the entire course of information mining, which as a rule, comes to around 60%. This stage can be additionally separated into three substeps: information choice, information preprocessing, and information change [23–25]. Information determination basically alludes to separating pertinent information from the current dataset or information distribution center to frame information focused on. Information preprocessing processes the extricated information to meet the necessities of information mining. Its main job is to check spelling mistakes, remove duplicates, and make up incomplete records. Data transformation is mainly to normalize data. For example, continuous data is converted into discrete data to facilitate symbol induction; likewise, the discrete data can be converted into continuous data in order to unify the dimension (or dimensionless) so that all index data can be uniformly processed in various algorithms.


#### 2.3.2. Stage of Data Mining

At this stage, the task of mining, such as data classification, clustering, discovery of association rule, or sequential pattern, should be determined first [26]. After determining the mining task, it is necessary to decide which mining algorithm to use. The choice of algorithm is the most important factor in the data mining stage and the key factor related to the effectiveness of acquired knowledge, which directly affects the quality of mining patterns. The algorithm should be selected according to the characteristics of data and the actual requirements of users [27]. After finishing the arrangements above, you can run the calculation of information mining. This stage is the most concerned by data mining investigators and specialists in related fields, which can be called data mining in the genuine sense.


#### 2.3.3. Expression and Explanation of Results

Knowledge discovery mode in the stage of data mining can analyze and evaluate the extracted information according to the purpose of the end user’s decision [28], while can also distinguish the valuable information and eliminate patterns that are redundant or irrelevant. For the mode that cannot meet the user’s requirements, it is necessary to return to the previous stage, such as reselecting data and adopting methods of new data transition. Set new parameter values, or even change a mining algorithm.


## 2.1. ASP.NET Technology

ASP.NET is developed by integrating ASP and NET technologies [10, 11]. ASP.NET is applicable to a wide range of each field, such as the dynamic process of website design. Compared with other technologies, ASP.NET has its own unique advantages. It mainly includes the following points: (1) ASP.NET is a newly developed technology, which is popular among people, and it integrates the advantages of both ASP and NET technologies; (2) ASP.NET has a wide range of database resources, and it can translate many languages, which is convenient for people to use; (3) ASP.NET has been developed on the basis of various technologies, which has many functional advantages and is easier to operate than others [12, 13].It can be seen from Figure1 that ASP.NET is mainly composed of three parts, which are mainly divided into the user layer, business logic layer, and data access layer.(1)
The user layer, also known as the presentation layer, is a layer directly facing customers, and all interaction between users is the responsibility of this layer. Therefore, in the application of this layer, It is necessary to build a concise appearance to facilitate users’ operation [14].(2)
Business logic layer located in the middle layer is mainly used to calculate and process business-related logic. This layer plays a connecting role and is the core layer of the three layers [15].(3)
Data access layer, which mainly represents various operations on the database, provides various data services for the previous layer and feeds back the processing results.Figure 1
Three-layer structure based on ASP.NET.These three layers are related and interlocking. Reasonable adjustment of these layers can not only improve the operating efficiency of the company but also improve the economic benefits of the enterprise. Moreover, these components have their own unique advantages, and at the same time, the operation and use are relatively simple and practical.


## 2.2. Database of SQL Server

SQL is a structured language for querying, and SQL Server is a database management system. The database management system is used for storing all kinds of data used in the system, and at the same time, various operations of data, including query, modification, and deletion, are realized by transferring SQL statements. This kind of database management system is mostly used to develop a distributed system, which is convenient to operate. Moreover, it is powerful, can realize various functions of accessing and operating data, and provides a concise user interface to learn [16, 17].The database system of the sports assessment system is SQL Server 2005, which was chosen because of its unique advantages, as follows: (1) the application of distributed view greatly improves the speed of accessing the database and the work efficiency, while the distributed view can quickly locate the data [18]; (2) it supports multiple development languages, including XML and other languages; (3) it has better performance and higher reliability; (4) it encapsulates a variety of technologies that are commonly used to realize data integration; (5) SQL Server 2005 provides users with a virtual network of the interface system.


## 2.3. Data Mining

In brief, data mining is to extract or “explore” knowledge from data in quantity [19, 20]. Many people regard data mining as another term data that is commonly used.It is synonymous with knowledge discovery in database (KDD) in mining database, while others just regard data mining as a link of KDD, which is a process of extracting useful patterns from data automatically and efficiently using specific algorithms of data mining. KDD is a cyclic process including data mining and data preparation.At present, there is no exact definition of “data mining.” A relatively accepted definition is put forward by W.J. Frawley, G. Piatetsky-Shapiro, and others: that is, data mining is an extraordinary process to obtain patterns that are correct, novel, potentially applicable, and finally understandable from data [21].Information mining is a multistage process and can, for the most part, be isolated into three principal stages: information readiness, information mining, and result articulation and translation. KDD is an iterative process of the three stages. The specific process can be described in Figure2 [22].Figure 2
Process knowledge discovery in database.


### 2.3.1. Stage of Data Preparation

Data preparation represents the biggest extent in the entire course of information mining, which as a rule, comes to around 60%. This stage can be additionally separated into three substeps: information choice, information preprocessing, and information change [23–25]. Information determination basically alludes to separating pertinent information from the current dataset or information distribution center to frame information focused on. Information preprocessing processes the extricated information to meet the necessities of information mining. Its main job is to check spelling mistakes, remove duplicates, and make up incomplete records. Data transformation is mainly to normalize data. For example, continuous data is converted into discrete data to facilitate symbol induction; likewise, the discrete data can be converted into continuous data in order to unify the dimension (or dimensionless) so that all index data can be uniformly processed in various algorithms.


### 2.3.2. Stage of Data Mining

At this stage, the task of mining, such as data classification, clustering, discovery of association rule, or sequential pattern, should be determined first [26]. After determining the mining task, it is necessary to decide which mining algorithm to use. The choice of algorithm is the most important factor in the data mining stage and the key factor related to the effectiveness of acquired knowledge, which directly affects the quality of mining patterns. The algorithm should be selected according to the characteristics of data and the actual requirements of users [27]. After finishing the arrangements above, you can run the calculation of information mining. This stage is the most concerned by data mining investigators and specialists in related fields, which can be called data mining in the genuine sense.


### 2.3.3. Expression and Explanation of Results

Knowledge discovery mode in the stage of data mining can analyze and evaluate the extracted information according to the purpose of the end user’s decision [28], while can also distinguish the valuable information and eliminate patterns that are redundant or irrelevant. For the mode that cannot meet the user’s requirements, it is necessary to return to the previous stage, such as reselecting data and adopting methods of new data transition. Set new parameter values, or even change a mining algorithm.


## 2.3.1. Stage of Data Preparation

Data preparation represents the biggest extent in the entire course of information mining, which as a rule, comes to around 60%. This stage can be additionally separated into three substeps: information choice, information preprocessing, and information change [23–25]. Information determination basically alludes to separating pertinent information from the current dataset or information distribution center to frame information focused on. Information preprocessing processes the extricated information to meet the necessities of information mining. Its main job is to check spelling mistakes, remove duplicates, and make up incomplete records. Data transformation is mainly to normalize data. For example, continuous data is converted into discrete data to facilitate symbol induction; likewise, the discrete data can be converted into continuous data in order to unify the dimension (or dimensionless) so that all index data can be uniformly processed in various algorithms.


## 2.3.2. Stage of Data Mining

At this stage, the task of mining, such as data classification, clustering, discovery of association rule, or sequential pattern, should be determined first [26]. After determining the mining task, it is necessary to decide which mining algorithm to use. The choice of algorithm is the most important factor in the data mining stage and the key factor related to the effectiveness of acquired knowledge, which directly affects the quality of mining patterns. The algorithm should be selected according to the characteristics of data and the actual requirements of users [27]. After finishing the arrangements above, you can run the calculation of information mining. This stage is the most concerned by data mining investigators and specialists in related fields, which can be called data mining in the genuine sense.


## 2.3.3. Expression and Explanation of Results

Knowledge discovery mode in the stage of data mining can analyze and evaluate the extracted information according to the purpose of the end user’s decision [28], while can also distinguish the valuable information and eliminate patterns that are redundant or irrelevant. For the mode that cannot meet the user’s requirements, it is necessary to return to the previous stage, such as reselecting data and adopting methods of new data transition. Set new parameter values, or even change a mining algorithm.


## 3. Overall Design of System

### 3.1. Demand Analysis

In terms of physical education, teachers have to face the realistic problem of a huge workload at the stage of examination. With the increasing attention paid by the state to students’ corporeity, how to establish a perfect performance assessment system and carry out more targeted teaching through the statistics and management of students’ PE achievements over the years is an important issue for physical education. The users of the system are administrators, teachers, and students, while different roles correspond to different operation permissions and users need to log in with their personal account and password. The system provides users with different permissions according to personal account information and then completes the operation of corresponding permissions. There are many categories of sports test items, and the test methods, scores, and scoring methods are different. Therefore, it is necessary to set different scoring forms according to different items when calculating scores, and the total score of each item is 100 points. The addition, modification, and deletion of these test item categories need to be achieved by the system.


### 3.2. System Design

The design of the target system is based on data mining through detailed exchanges and discussions with related PE teachers in colleges. Aiming at various problems in the management of sports achievements, the design and development scheme of the sports assessment system is put forward to solve the problems faced in the current management of sports through the application of the target system, which frees the PE teacher from the busy work in the past and realizes the automation and informatization of the management of sports achievements. Figure3 shows the overall diagram of sports achievement management.Figure 3
General use case diagram system.From the figure above, it is known that there are three types of users that the target system faces, namely, PE teachers, students, and system administrators. The three types of users can perform different system operations. The system administrator has the greatest authority and can perform any function in the system. PE teachers can perform other functions except for system management. In contrast, students have the least corresponding permissions and can only perform functional operations about performance management.The development of the system is based on the. NET three-layer structure divides the whole application into three layers, namely, presentation layer, business logic layers, and data access layers [29]. The presentation layer is a user-oriented application layer, which is responsible for completing the interaction with users. This layer usually uses the interface to complete the interaction by designing some controls on the interface [30]. It is only responsible for receiving access requests sent by users and feeding back the final results to users, and it does not need to be careful about the specific method to realize users’ requests. The business layer is located between the presentation layer and the data access layer, which is the core link of the logic processing of the whole system, and is responsible for the logical calculation and processing of the user’s request while receiving the data from the data access layer at the same time. The data layer works for gaining data and executing programs and feeding the processing results back to users. Figure 4 shows the architecture of the system.Figure 4
Overall technical architecture of the system.


## 3.1. Demand Analysis

In terms of physical education, teachers have to face the realistic problem of a huge workload at the stage of examination. With the increasing attention paid by the state to students’ corporeity, how to establish a perfect performance assessment system and carry out more targeted teaching through the statistics and management of students’ PE achievements over the years is an important issue for physical education. The users of the system are administrators, teachers, and students, while different roles correspond to different operation permissions and users need to log in with their personal account and password. The system provides users with different permissions according to personal account information and then completes the operation of corresponding permissions. There are many categories of sports test items, and the test methods, scores, and scoring methods are different. Therefore, it is necessary to set different scoring forms according to different items when calculating scores, and the total score of each item is 100 points. The addition, modification, and deletion of these test item categories need to be achieved by the system.


## 3.2. System Design

The design of the target system is based on data mining through detailed exchanges and discussions with related PE teachers in colleges. Aiming at various problems in the management of sports achievements, the design and development scheme of the sports assessment system is put forward to solve the problems faced in the current management of sports through the application of the target system, which frees the PE teacher from the busy work in the past and realizes the automation and informatization of the management of sports achievements. Figure3 shows the overall diagram of sports achievement management.Figure 3
General use case diagram system.From the figure above, it is known that there are three types of users that the target system faces, namely, PE teachers, students, and system administrators. The three types of users can perform different system operations. The system administrator has the greatest authority and can perform any function in the system. PE teachers can perform other functions except for system management. In contrast, students have the least corresponding permissions and can only perform functional operations about performance management.The development of the system is based on the. NET three-layer structure divides the whole application into three layers, namely, presentation layer, business logic layers, and data access layers [29]. The presentation layer is a user-oriented application layer, which is responsible for completing the interaction with users. This layer usually uses the interface to complete the interaction by designing some controls on the interface [30]. It is only responsible for receiving access requests sent by users and feeding back the final results to users, and it does not need to be careful about the specific method to realize users’ requests. The business layer is located between the presentation layer and the data access layer, which is the core link of the logic processing of the whole system, and is responsible for the logical calculation and processing of the user’s request while receiving the data from the data access layer at the same time. The data layer works for gaining data and executing programs and feeding the processing results back to users. Figure 4 shows the architecture of the system.Figure 4
Overall technical architecture of the system.


## 4. Function Module Design of the System

The overall functional structure diagram of the system is shown in Figure5.Figure 5
Overall functional structure of the system.It can be seen from the figure that the system consists of five functional modules, namely, test type management, test project management, score management, score analysis, and system management.


### 4.1. Management Test Type

Test type refers to items related to sports test, which is stipulated by the syllabus. Test type management includes operations related to test types, including adding test types, modifying test types, deleting test types, and setting weights. Figure6 shows the functional block diagram of test type management.(1)
Increase test type: it means adding a new test type. During the process of adding, the system will verify the content added by the user, including whether it is blank or legal.(2)
Test type modification means to modify the existing sports test types and save the user’s modified results to the corresponding type database.(3)
Test type deletion: delete the original test type in the database. In the process of deletion, the deletion object selected by the user will be judged whether there are test items under the test type. If there are any, the user will be prompted that the test type cannot be deleted, and the type can only be deleted if it is determined that there are no test items.(4)
Score weight setting: it refers to setting the relevant proportion of the score weight under each test type.Figure 6
Functional structure diagram of test type management.


### 4.2. Test Project Management

Test projects refer to specific projects involved in sports tests, such as high jump, long jump, and basketball. Test projects management refers to the management of business related to test projects. Figure7 shows the functional structure diagram of test project management.(1)
Increase test projects: it means adding new test projects. During the process of adding, the system will verify the contents added by users, including whether they are blank and legal.(2)
Test projects modification means relevant modification operations are carried out on the existing sports test projects, and the user’s modified results are saved in the corresponding type database.(3)
Delete test projects: delete the original test projects in the database.(4)
Point weight setting: it refers to setting the relevant proportion of the score weight under each test project.Figure 7
Functional structure diagram of test project management.


### 4.3. Performance Management

Performance management refers to the related management of students’ sports performance, including the entry of performance, the modification of performance, the deletion of performance, the inquiry of performance, the export of performance, and the conversion of scoring system. Figure8 shows the functional structure diagram of performance management.(1)
Input: it means that students’ sports scores are entered into the score database of the system. In the process of score entry, the data entered by the user will be verified, including whether it is blank or legal. Only after confirming that both of them are satisfied will a new piece of information be inserted into the database to complete the entry.(2)
Modification: modify the original scores in the system and save the modified results into the score database of the system.(3)
Deletion: delete the original scores in the system and save the deleted results.(4)
Inquiry: by querying students’ performance by entering specific query conditions, these conditions can include the student’s student number, and the student’s name or score range.(5)
Export: export the data related to students’ sports achievements to Excel tables, which is convenient for statistics and decision-making.(6)
Conversion: it is converted into the corresponding points system according to students’ scores.Figure 8
Functional structure diagram of performance management.


### 4.4. Statistical Analysis of Achievements

Statistical analysis is to count the students’ sports performance and analyze the statistical results using the algorithm of data mining. This is the core function of the target system. The functional structure diagram of the score analysis is given as shown in Figure9.(1)
Score statistics: It means that students’ sports performance is quantized to obtain the total score or average score. It also supports showing these statistical results in the form of charts or words, which is convenient for users to consult.(2)
Score analysis: It is the core part of the score analysis module, which refers to the analysis of students’ scores using the algorithm of data mining.Figure 9
Functional structure diagram of score analysis.


### 4.5. System Management

System management refers to the management and maintenance of all the basic information of the target system. The main work includes the functions of user addition, user modification, user deletion, permission allocation, database backup, and database restoration. System management is the essential basic function module of every software. The following is the functional structure diagram of system management, as shown in Figure10.(1)
User addition: it means adding users who enter the target system. The types of users targeted by the system include students, PE teachers, and system administrators.(2)
User modification: it refers to the modification of basic information of users, including modification of users’ password and modification of personal information of users.(3)
User deletion: it refers to the logout operation for information-related users who have entered the system.(4)
Permission assignment: it allocates relevant permissions for users entering the system.(5)
Database backup: it is used to back up the database of the system.(6)
Database: it restores the database of the system.Figure 10
Function structure diagram of system management.


## 4.1. Management Test Type

Test type refers to items related to sports test, which is stipulated by the syllabus. Test type management includes operations related to test types, including adding test types, modifying test types, deleting test types, and setting weights. Figure6 shows the functional block diagram of test type management.(1)
Increase test type: it means adding a new test type. During the process of adding, the system will verify the content added by the user, including whether it is blank or legal.(2)
Test type modification means to modify the existing sports test types and save the user’s modified results to the corresponding type database.(3)
Test type deletion: delete the original test type in the database. In the process of deletion, the deletion object selected by the user will be judged whether there are test items under the test type. If there are any, the user will be prompted that the test type cannot be deleted, and the type can only be deleted if it is determined that there are no test items.(4)
Score weight setting: it refers to setting the relevant proportion of the score weight under each test type.Figure 6
Functional structure diagram of test type management.


## 4.2. Test Project Management

Test projects refer to specific projects involved in sports tests, such as high jump, long jump, and basketball. Test projects management refers to the management of business related to test projects. Figure7 shows the functional structure diagram of test project management.(1)
Increase test projects: it means adding new test projects. During the process of adding, the system will verify the contents added by users, including whether they are blank and legal.(2)
Test projects modification means relevant modification operations are carried out on the existing sports test projects, and the user’s modified results are saved in the corresponding type database.(3)
Delete test projects: delete the original test projects in the database.(4)
Point weight setting: it refers to setting the relevant proportion of the score weight under each test project.Figure 7
Functional structure diagram of test project management.


## 4.3. Performance Management

Performance management refers to the related management of students’ sports performance, including the entry of performance, the modification of performance, the deletion of performance, the inquiry of performance, the export of performance, and the conversion of scoring system. Figure8 shows the functional structure diagram of performance management.(1)
Input: it means that students’ sports scores are entered into the score database of the system. In the process of score entry, the data entered by the user will be verified, including whether it is blank or legal. Only after confirming that both of them are satisfied will a new piece of information be inserted into the database to complete the entry.(2)
Modification: modify the original scores in the system and save the modified results into the score database of the system.(3)
Deletion: delete the original scores in the system and save the deleted results.(4)
Inquiry: by querying students’ performance by entering specific query conditions, these conditions can include the student’s student number, and the student’s name or score range.(5)
Export: export the data related to students’ sports achievements to Excel tables, which is convenient for statistics and decision-making.(6)
Conversion: it is converted into the corresponding points system according to students’ scores.Figure 8
Functional structure diagram of performance management.


## 4.4. Statistical Analysis of Achievements

Statistical analysis is to count the students’ sports performance and analyze the statistical results using the algorithm of data mining. This is the core function of the target system. The functional structure diagram of the score analysis is given as shown in Figure9.(1)
Score statistics: It means that students’ sports performance is quantized to obtain the total score or average score. It also supports showing these statistical results in the form of charts or words, which is convenient for users to consult.(2)
Score analysis: It is the core part of the score analysis module, which refers to the analysis of students’ scores using the algorithm of data mining.Figure 9
Functional structure diagram of score analysis.


## 4.5. System Management

System management refers to the management and maintenance of all the basic information of the target system. The main work includes the functions of user addition, user modification, user deletion, permission allocation, database backup, and database restoration. System management is the essential basic function module of every software. The following is the functional structure diagram of system management, as shown in Figure10.(1)
User addition: it means adding users who enter the target system. The types of users targeted by the system include students, PE teachers, and system administrators.(2)
User modification: it refers to the modification of basic information of users, including modification of users’ password and modification of personal information of users.(3)
User deletion: it refers to the logout operation for information-related users who have entered the system.(4)
Permission assignment: it allocates relevant permissions for users entering the system.(5)
Database backup: it is used to back up the database of the system.(6)
Database: it restores the database of the system.Figure 10
Function structure diagram of system management.


## 5. Design of System Database

### 5.1. Design of Database System

According to the detailed analysis of the target system, the data table is designed here combined with the conceptual design and logical design of the system’s database.Table1 shows the information table of users, which is mainly applied to store information related to the system, including ID, name, login Miyun, and type of users.Table 1
Information table of user.
Field nameData type (length)Primary keyNullDescribeYong Hu IDIntYesNoUser IDYong Hu Mingvarchar(20)NoNoUsernameMi Mavarchar(20)NoYesLogin passwordLei XingBitNoNoUser typeTable2 shows the information table of students, which is mainly applied to store various information related to students, including name, ID, and login password of students.Table 2
Information table of students.
Field nameData type (length)Primary keyNullDescribeXue Sheng IDIntYesNoIDXue Sheng XMvarchar(20)NoNoStudent nameXue Haovarchar(11)NoNoStudent IDMi Mavarchar(20)NoNoLogin passwordTable3 shows the table of test type, which is used to store various information related to test types, including test type name, type description, and weight.Table 3
Test type table.
Field nameData type (length)Primary keyNullDescribeCe Shi Lei Xing IDIntYesNoTest type IDLei Xing Ming Chengvarchar(20)NoNoTest type nameLei Xing Miao ShuTextNoYesTest type descriptionLei Xing Quan ZhongIntNoNoTest type weightTable4 shows the table of test projects, which is mainly used to store various information related to test projects, including ID, name, type, description, and score weight of test projects.Table 4
Test item table.
Field nameData type (length)Primary keyNullDescribeCe Shi Xiang Mu IDIntYesNoTest project IDXiang Mu Ming Chengvarchar(20)NoNoTest item nameCe Shi Lei Xing IDIntNoNoBelonging to the test typeXiang Mu Miao ShuTextNoYesTest item descriptionXiang Mu Quan ZhongIntNoNoTest item weightTable5 shows the table of test score, which is mainly applied to store the basic information related to students’ test scores, including the test score number, test projects, student ID, and score.Table 5
Test score table.
Field nameData type (length)Primary keyNullDescribeDe Fen IDIntYesNoScore numberCe Shi Xiang Mu IDIntNoNoTest itemsXue Haovarchar(11)NoNoStudent IDFen ZhiIntNoNoPointsTable6 shows the table of students’ achievement, which is used to store the basic information related to students’ achievements, including grade ID, student ID, and total score.Table 6
Student achievement sheet.
Field nameData type (length)Primary keyNullDescribeCheng Ji IDIntYesNoGrade IDXue Haovarchar(11)NoNoStudent IDZong Fen ZhiFloatNoNoTotal scoreTable7 shows the conversion table of the points system, which is used to store the basic information needed for the conversion of the points system, including score ID, maximum score, minimum scores, and conversion name.Table 7
Conversion table of the points system.
Field nameData type (length)Primary keyNullDescribeFen Zhi IDIntYesNoPoint system IDFen Zhi Zui Xiao ZhiIntNoNoMinimum scoreFen Zhi Zui Da ZhiIntNoNoMaximum scoreMing Chengvarchar(10)NoNoname


### 5.2. Application of ID3 Learning Algorithm

Data entropy, called normal data in the principle of data, is a normal worth used to quantify the communicated data. The data communicated in the source incorporates a set number of totally unrelated and together complete occasions, all of which appear with a certain probability, which is expressed by the mathematical formula: a group of eventsx1, X1,…, Xr, which appear with a given probability p(X1), p(Xr), the mean value H(X) is the information entropy, and it is equal to the mathematical expectation of the (self) information amount I(X) of each event, namely,(1)HX=−∑r=1rpXiIXi=−∑r=1rpXilogpXi.ID3 algorithm achieves the best classification in the algorithm according to the attribute of maximum information entropy and the principle conducive to the classification. The gain of information of an attribute will reduce the information entropy of the system, and the key operation of the ID3 algorithm is to calculate and compare the information of each attribute. It is needed to take a representative training sample as an example to introduce the decision tree node, which determines whether the samples are in the same category. By selecting the best classification attribute of the sample as the node attribute and dividing the samples, according to this node attribute, the maximum standard value is obtained. If samples are lacking in a branch, the sample types of the training cluster need to be compared.


## 5.1. Design of Database System

According to the detailed analysis of the target system, the data table is designed here combined with the conceptual design and logical design of the system’s database.Table1 shows the information table of users, which is mainly applied to store information related to the system, including ID, name, login Miyun, and type of users.Table 1
Information table of user.
Field nameData type (length)Primary keyNullDescribeYong Hu IDIntYesNoUser IDYong Hu Mingvarchar(20)NoNoUsernameMi Mavarchar(20)NoYesLogin passwordLei XingBitNoNoUser typeTable2 shows the information table of students, which is mainly applied to store various information related to students, including name, ID, and login password of students.Table 2
Information table of students.
Field nameData type (length)Primary keyNullDescribeXue Sheng IDIntYesNoIDXue Sheng XMvarchar(20)NoNoStudent nameXue Haovarchar(11)NoNoStudent IDMi Mavarchar(20)NoNoLogin passwordTable3 shows the table of test type, which is used to store various information related to test types, including test type name, type description, and weight.Table 3
Test type table.
Field nameData type (length)Primary keyNullDescribeCe Shi Lei Xing IDIntYesNoTest type IDLei Xing Ming Chengvarchar(20)NoNoTest type nameLei Xing Miao ShuTextNoYesTest type descriptionLei Xing Quan ZhongIntNoNoTest type weightTable4 shows the table of test projects, which is mainly used to store various information related to test projects, including ID, name, type, description, and score weight of test projects.Table 4
Test item table.
Field nameData type (length)Primary keyNullDescribeCe Shi Xiang Mu IDIntYesNoTest project IDXiang Mu Ming Chengvarchar(20)NoNoTest item nameCe Shi Lei Xing IDIntNoNoBelonging to the test typeXiang Mu Miao ShuTextNoYesTest item descriptionXiang Mu Quan ZhongIntNoNoTest item weightTable5 shows the table of test score, which is mainly applied to store the basic information related to students’ test scores, including the test score number, test projects, student ID, and score.Table 5
Test score table.
Field nameData type (length)Primary keyNullDescribeDe Fen IDIntYesNoScore numberCe Shi Xiang Mu IDIntNoNoTest itemsXue Haovarchar(11)NoNoStudent IDFen ZhiIntNoNoPointsTable6 shows the table of students’ achievement, which is used to store the basic information related to students’ achievements, including grade ID, student ID, and total score.Table 6
Student achievement sheet.
Field nameData type (length)Primary keyNullDescribeCheng Ji IDIntYesNoGrade IDXue Haovarchar(11)NoNoStudent IDZong Fen ZhiFloatNoNoTotal scoreTable7 shows the conversion table of the points system, which is used to store the basic information needed for the conversion of the points system, including score ID, maximum score, minimum scores, and conversion name.Table 7
Conversion table of the points system.
Field nameData type (length)Primary keyNullDescribeFen Zhi IDIntYesNoPoint system IDFen Zhi Zui Xiao ZhiIntNoNoMinimum scoreFen Zhi Zui Da ZhiIntNoNoMaximum scoreMing Chengvarchar(10)NoNoname


## 5.2. Application of ID3 Learning Algorithm

Data entropy, called normal data in the principle of data, is a normal worth used to quantify the communicated data. The data communicated in the source incorporates a set number of totally unrelated and together complete occasions, all of which appear with a certain probability, which is expressed by the mathematical formula: a group of eventsx1, X1,…, Xr, which appear with a given probability p(X1), p(Xr), the mean value H(X) is the information entropy, and it is equal to the mathematical expectation of the (self) information amount I(X) of each event, namely,(1)HX=−∑r=1rpXiIXi=−∑r=1rpXilogpXi.ID3 algorithm achieves the best classification in the algorithm according to the attribute of maximum information entropy and the principle conducive to the classification. The gain of information of an attribute will reduce the information entropy of the system, and the key operation of the ID3 algorithm is to calculate and compare the information of each attribute. It is needed to take a representative training sample as an example to introduce the decision tree node, which determines whether the samples are in the same category. By selecting the best classification attribute of the sample as the node attribute and dividing the samples, according to this node attribute, the maximum standard value is obtained. If samples are lacking in a branch, the sample types of the training cluster need to be compared.


## 6. Implementation of System

### 6.1. Types of Sports Test

Management of sports test types includes various functional modules: addition of test types, modification of test types, deletion of test types, and setting of weights. The database tables involved in these module tests mainly include test type tables, and the corresponding database program statements are Insert, Modify, and Delete. Among them, the program of test type deletion is shown in Figure11.Figure 11
Program of test type deletion.


### 6.2. Projects of Sports Test

The executives of sports test projects allude to the administration of data connected with sports test and its practical modules chiefly include the following: expansion of sports test projects, setting of weight, alteration, and cancellation of sports test projects. The tables of dataset engaged with the execution basically incorporate the data table of test projects. Some key codes of realization of functions are given as follows. First, the program gets the information entered by the user on the page. Among them, the procedure of added test projects is shown in Figure12.Figure 12
Procedure of added test projects.


### 6.3. Management of Performance

Management of performance refers to the management of information related to students’ sports scores, which includes main functional modules: entry, modification, deletion, inquiry, export of scores, and conversion of point. In these modules, the core part is the entry and calculation of scores. In the process of entry, the tables of the database involved are information tables of scores, and the database tables indicated by calculation are information tables of scores and information tables of performance. Among them, the procedure of score entry is shown in Figure13.Figure 13
Procedure of score entry.


### 6.4. Problems and Solutions in the Process of System Testing

The problems and solutions in the process of testing the sports assessment system are as follows:(1)
After the system is installed, statistics of sports scores are made, but their download cannot be completed, and the system will not give a prompt of error. Solution: most of these problems are caused by the fact that office-related software is not installed in the system, which can be implemented after restarting according to the server. If it still cannot work, the permissions of components need to be modified.(2)
An error results in the termination of installation when IIS is registered and the database is coded. Solution: this situation usually occurs because the environment of NET is not installed, or the installed version does not match the version developed by the project; in addition, there is an error in the SQL. The current problems can be solved by improving these two aspects.


### 6.5. Evaluation of Teachers

After half a year’s systematic maintenance, the PE evaluation management system based on data mining technology has been put into use, and it has been well received by PE teachers. Through this system, the workload of PE teachers is greatly reduced, and they are freed from the complicated work of processing data, which effectively improves efficiency, truly replaces manual labor with machines, and promotes the normalization of teaching management through the application of sports management system based on data mining technology.


## 6.1. Types of Sports Test

Management of sports test types includes various functional modules: addition of test types, modification of test types, deletion of test types, and setting of weights. The database tables involved in these module tests mainly include test type tables, and the corresponding database program statements are Insert, Modify, and Delete. Among them, the program of test type deletion is shown in Figure11.Figure 11
Program of test type deletion.


## 6.2. Projects of Sports Test

The executives of sports test projects allude to the administration of data connected with sports test and its practical modules chiefly include the following: expansion of sports test projects, setting of weight, alteration, and cancellation of sports test projects. The tables of dataset engaged with the execution basically incorporate the data table of test projects. Some key codes of realization of functions are given as follows. First, the program gets the information entered by the user on the page. Among them, the procedure of added test projects is shown in Figure12.Figure 12
Procedure of added test projects.


## 6.3. Management of Performance

Management of performance refers to the management of information related to students’ sports scores, which includes main functional modules: entry, modification, deletion, inquiry, export of scores, and conversion of point. In these modules, the core part is the entry and calculation of scores. In the process of entry, the tables of the database involved are information tables of scores, and the database tables indicated by calculation are information tables of scores and information tables of performance. Among them, the procedure of score entry is shown in Figure13.Figure 13
Procedure of score entry.


## 6.4. Problems and Solutions in the Process of System Testing

The problems and solutions in the process of testing the sports assessment system are as follows:(1)
After the system is installed, statistics of sports scores are made, but their download cannot be completed, and the system will not give a prompt of error. Solution: most of these problems are caused by the fact that office-related software is not installed in the system, which can be implemented after restarting according to the server. If it still cannot work, the permissions of components need to be modified.(2)
An error results in the termination of installation when IIS is registered and the database is coded. Solution: this situation usually occurs because the environment of NET is not installed, or the installed version does not match the version developed by the project; in addition, there is an error in the SQL. The current problems can be solved by improving these two aspects.


## 6.5. Evaluation of Teachers

After half a year’s systematic maintenance, the PE evaluation management system based on data mining technology has been put into use, and it has been well received by PE teachers. Through this system, the workload of PE teachers is greatly reduced, and they are freed from the complicated work of processing data, which effectively improves efficiency, truly replaces manual labor with machines, and promotes the normalization of teaching management through the application of sports management system based on data mining technology.


## 7. Conclusion

Advances in computer and network technology provide technical support for the information construction of colleges. On the basis of data mining, this article constructs a three-tier sports assessment system, completes the introduction of the system’s functional modules and the design of the database, uses the ID3 algorithm to complete the data mining of the system, and finally completes the operation of each functional module. The results of the test show that the system runs stably, and the daily statistics and management of PE teachers’ sports scores can be completed more easily through this system, which improves teachers’ work efficiency, enables them to devote more energy to the improvement of PE teaching quality, and further enhances the level of automation and information management of physical education scores.



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*Source: 1337048-2022-04-18.xml*