# Comprehensive Evaluation Method of Teaching Effect Based on Particle Swarm Optimization Neural Network Model

Authors: Heng Cao; Qianhui Gao
Journal: Discrete Dynamics in Nature and Society
 (2022)

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## Abstract

The important role of teaching evaluation system is embodied in: starting from the teaching goal and the vocational education teaching activities. This paper studies the optimization algorithm and optimization system, it not only makes the algorithm involve basic mathematical operations, and the computer support required for the data processing process is not high, but it also improves the evaluation of the degree of optimization. In view of these characteristics, this paper has conducted in-depth research to fully prove the feasibility and superiority of the content of this article. The specific summary is as follows: (1) Introduced the design concept of particle swarm optimization teaching evaluation system. (2) The use of object-oriented programming algorithms makes it easier for the algorithm to find an entry point, solve practical problems, and optimize the reusability of the algorithm method. (3) Particle swarm optimization based on quantum behavior, adjusting parameter values, the highest and the lowest, greatly reduces the difficulty of program parameter adjustment. (4) In terms of operation, it can quickly and efficiently complete the maintenance of teacher teaching information, evaluation relationship management of teacher teaching quality evaluation, evaluation content management, student evaluation, supervision evaluation, college leadership evaluation, evaluation performance management, and other operations. The interface is extremely humane. It adopts a web-style tour method. There are many types of functions, and the system includes common functions required for general teacher teaching information management and quality evaluation, and while providing various functions, it closely integrates the various actual needs of the college. The security performance is good. The system provides user name and password verification, which improves the security of the system. Database management is convenient and fast, providing a database-friendly management interface, and timely and accurate query. (5) This system adopts an object-oriented development method. During the development process, full consideration of the user’s needs enabled the system to have powerful functions and streamlined procedures. In the end, this application software basically completed the goals required by the requirements analysis.


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## Body

## 1. Introduction

At present, my country’s higher vocational and technical education is developing rapidly and its scale is constantly growing. Higher vocational and technical education has become an inseparable and important part of my country’s education system. The relationship between vocational and technical education and economy is the most direct and close. It has cultivated the “technical”, “practical,” and “applied” compound talents required by the production line. In recent years, China’s vocational and technical education has made faster growth in terms of school scale, professional orientation, enrollment, and geography. How to ensure the teaching quality of vocational and technical education and train “composite” high-quality to adapt to the development of my country’s social and economic construction has now been an important problem. The evaluation of teaching quality has become one of the main concerns. Although China’s higher vocational education started late, the scale of development is staggering [1–5].As in 2010, there have been more than 1500 vocational colleges of various types across the country, including those established by some undergraduate colleges. The total number of vocational colleges exceeds 1700, where the number of enrollment and the number of students at school accounted for 60% of ordinary colleges and universities. School teaching quality is the lifeline of school survival and development. The teaching quality evaluation system is an objective, fair, and comprehensive monitoring system that can help improve the quality of vocational schools [6–8].Classroom teaching quality is the fundamental way to the school’s educational goals. Implementing teacher’s classroom teaching quality on one hand helps the education department and school administrators understand the teaching progress. The capability of teachers to work directly affects the level of talent training. However, it is always a complicated and difficult process to evaluate the teaching ability level of a school. The establishment of classroom teaching quality evaluation systems for teachers in various vocational colleges has established many evaluation methods, but usually after collecting a large amount of evaluation data, data mining decision rules are adopted. Often in data processing, many problems will be faced [9–11].Evaluation of predictive models: If it is based on different indicators, after comparing and evaluating different prediction models, the comparison results may also be different, which just shows the inconsistency of different evaluation indicators. Therefore, the evaluation of the prediction performance of the prediction model must be based on certain evaluation indicators. Under normal circumstances, people often choose a more valuable evaluation system based on actual conditions. Modern financial econometrics is mainly based on mathematical statistical models and studies and describes the characteristics and laws of financial markets. Financial markets are more complex and nonlinear, so new methods and tools need to be introduced. The financial market is ever-changing, and the evaluation of forecasting methods or systems is also varied, and a certain forecasting method can only be better than other methods for a certain period of time or under certain conditions. Therefore, how to evaluate the quality of various forecasting methods is an important issue in financial forecasting analysis. It is necessary to optimize the time and control parameters too much, and it is always difficult to control during the optimization process. Therefore, it is necessary to seek a simpler and more efficient global optimization algorithm, which is a research hotspot in the field of evaluation systems [12–15].The particle swarm optimization (PSO) algorithm (as shown in Figure1) is a simple and effective random search swarm intelligent algorithm. It has the advantages of easy implementation and fewer control parameters. Therefore, it has become an intelligent optimization, evolutionary calculation, and new hotspot. Now, the algorithm has been applied to medical images, stocks, videos, and so on. This research is still in its infancy, but the existing research results show that it has great feasibility in optimization processing. It can be seen that the degree of combination of swarm intelligence algorithm and evaluation optimization is an inevitable trend in the field of theoretical research and applied research.Figure 1
Particle swarm algorithm.The advantage of Hepner’s fetish group: Since the particle swarm algorithm has been proposed, due to the fast algorithm calculation and easy implementation, it has attracted the attention of the international community and many scholars in the research field. Their research can be divided into: algorithm, algorithm analysis, improvement, and algorithm application [16–18].First, Kennedy and Eberhart first proposed an improved binary PSO algorithm in 1997, which provides a structural optimization method for neural networks for the performance comparison of PSO algorithm and genetic algorithm, as shown in Figure2. Second, in order to improve the convergence performance of the algorithm, Shi and Eberhart introduced the inertia weight to the speed term of the PSO algorithm in 1998 and proposed to dynamically adjust the inertia weight during the evolution process to balance the globality of convergence and the speed of convergence. Related scholars call it the standard PSO algorithm (StandardPSO, SPSO). Relevant scholars have carried out a detailed algorithm analysis on this through algebraic methods and have given guiding suggestions for parameter selection [19–21].Figure 2
Neural network.Angeline borrowed computational evolutionary algorithms in 1998 and 1999, chose the concept of hybrid power, and introduced the PSO algorithm. Eliminate the difference between particles, there will be a higher amount of particles copied by the particles, and by comparing the value of each particle, the convergence of the algorithm is improved. Lovbjerg uses the further evolution of the computer system in the PSO algorithm, such as replication, the concrete form of the crossover algorithm, and the effectiveness of the simulation algorithm through the typical test function [22, 23].To ensure the diversity of the group, Kennedy introduces the concept of neighborhood topology to adjust the dynamic selection of neighborhoods and at the same time, introduces social beliefs to combine the spatial neighborhood with the ring topology in the neighborhood topology to increase the information exchange between neighborhoods and improve the group diversity. Lovbjerg et al. introduced the concept of subpopulation in genetic algorithm into PSO algorithm in 2001 and at the same time, introduced a propagation operator to exchange information among subpopulations. From the perspective of probability and statistics in 2004, J. Kennedy adopted a normal distribution of random perturbations in the movement of particles and adopted a neighborhood ring topology to improve the performance of the PSO algorithm. In the same year, R. A. Krohling changed the acceleration factor changes in the evolution equation from the original uniform distribution to the normal distribution and achieved certain results [24–29].Teaching evaluation is an ancient and young subject. Countries such as the United States, Britain, and Germany started earlier. They began to use it as an independent branch subject at the end of the 19th century and gradually developed in a scientific direction. Teaching evaluation is produced with the emergence of education and develops with the development of education. The development of teaching assessment can be divided into three stages. The first stage was from the 1930s to the 1950s. The characteristics of this stage are as follows: teaching evaluation theories and methods have been further enriched and developed, but teaching evaluation activities have not yet been popularized. The second stage was from the 1950s to the 1980s. During this period, teaching evaluation changed from a topic of concern to educators to a topic of concern to governments and the general public. The third stage is from the 1980s to the present. It is characterized by the evaluation methods and the introduction of new scientific methods. In the process of evaluation, people gradually began to use systematic scientific methodology to carry out educational evaluation, coupled with the use of fuzzy mathematics, data mining technology, neural network, and other technologies. There are many methods of teaching quality evaluation, among which the most common evaluation method consists of comprehensive judgment method, rating method, comment method, realistic method, and comprehensive scoring method.In order to improve the global convergence of the PSO algorithm, ensuring the diversity of particles is the key. In order to ensure the diversity of the particles in the population during the evolution process, Suganthan introduced the concept of the space domain in the standard PSO algorithm. The particles in the same space domain were formed into a subparticle group for evolution, and the selection threshold was dynamically changed with the evolution.


## 2. Particle Swarm Optimization Model

Genetic algorithm, as shown in Figure3, is an evolutionary algorithm used to solve the optimal search. The evolutionary algorithm was originally developed by borrowing gene mutation, elimination selection and hybrid evolution. PSO is an evolutionary computing technology, Eberhart and Kennedy invented from the predation behavior of birds. The PSO algorithm is similar to the genetic algorithm and is also an iterative optimization tool. A set of random solutions are generated when the system is initialized, and the optimal value is searched through iteration, but there is no mutation of genetic algorithm crossover and mutation, and only the particles in the solution space are searched according to the optimal particles.Figure 3
Block diagram of the genetic algorithm optimization program.Using evolutionary calculation to optimize the evaluation degree of the teaching evaluation system, compared with the existing methods such as fuzzy comprehensive processing, neural network processing, weighted average processing, analytic hierarchy process, and grey relational evaluation theory evaluation, the accuracy and speed are greatly improved.In 1995, Kennedy and Eberhart published an article regarding to particle swarm algorithm. The difference is that particle swarm algorithm, unlike other evolutionary algorithms for personal use, but the search space of each particle can be expressed by the size and weight of a certain speed. The flight speed can be adjusted according to the flight experience and flight dynamics of individuals and groups. The algorithm regards each individual as a particle in anN-dimensional search space, and adopts a velocity-position search model (N is the number of independent variables in the actual problem solving). The position of each particle is(1)xi=xi1,xi2,Λ,υiN.In the formula:i = 1, 2, Λ, m is the population size.Formula (1) is a latent solution. Its speed is(2)υi=υxi1,υi2,Λ,υiN.The aforementioned formula determines the displacement of the particle in the unit iteration number of the search space. PSO randomly initializes the position and velocity ofm particles (m is the population size). In each iteration, the particle updates its velocity and position by dynamically tracking the two extreme values. The first is the optimal solution generated by the particle search from the initial to the current iteration number: individual extreme value:(3)Pi=Pi1,Pi2,Λ,PiN,where P is the power.The second is the current optimal solution of the particle population: the global extremum:(4)Pg=Pg1,Pg2,Λ,PgN.The corresponding formula is as follows:(5)υidk+1=wυidk+ρ1r1Pid−xidk+ρ2r2Pgd−xidk,xidk+1=xidk+υidk+1,where d = 1, 2, Λ, N is the dimensionality; υidk is the d-dimensional component of the flight velocity in the kth iteration of the ith particle, and the particle velocity νi is limited by a maximum velocity; ρ1, ρ2 are learning factors, which are nonnegative constants. This parameter is used to adjust the role of the particle’s own experience and social experience in the movement, which means that each particle is pushed toward Pi. Pg is the weight of the statistical acceleration term at the position; w is the weighting coefficient, with a value between 0.4 and 0.9. w is determined by the following formula:(6)w=wmax−wmax−wminNummax×Num,where wmax and wmin are the maximum and minimum values of w, respectively, and Nummax and Num are the maximum number of iterations and the current number of iterations, respectively.It represents the process of particles learning the experience of other particles and represents the sharing of information and social collaboration between particles. The model without the second part is called the model with only the social part. The model converges fast, but it is easy to fall into the local optimum for complex problems. Without the third part, there is no connection between individuals, and the probability of finding the optimum is low. The error is shown in Figure4.Figure 4
Error.For convenience, this article expresses the form of the classic particle swarm algorithm as follows:(7)Vit+1=Vit+c1r1Pit−xit+c2r2Pgt−xit,xit+1=xit+Vit+1.Particle swarm optimization based on quantum behavior (QPSO algorithm) is a classic PSO algorithm, which is formed on the basis of improvement. It mainly combines the ideas of quantum physics to modify the “evolution” method (that is, update the particles in the PSO position method), the main consideration is to update the position of the particles, the specific calculation process is as follows:The QPSO particle has the following three formulas:(8)mbestt+1=1M∑i=1MPit,PPijt+1=fijt+1Pijt+1−fijt+1Pgjt,xijt+1=PPijt+1+Randt+1at+1mbestjt+1−xijtln1uijt+1.At the same time, this method also has some shortcomings. However, as a kind of bionic random algorithm, evolutionary calculation itself has many shortcomings. For example, the most adequate genetic algorithm in research. Although it can be used to solve complex problems, it has been difficult to overcome the shortcomings of premature convergence; genetic manipulation and evolution at the same time.


## 3. Detailed Design of Teaching Evaluation System

Comprehensively considering the rapid development of education and the various situations that occurred in the development of school informatization, combined with the reality of Wuxi Transportation Higher Vocational and Technical School, after the implementation of the teacher teaching information management and quality evaluation system, the following goals should be achieved:(1)
Teachers’ teaching information management is informatized, and teachers’ teaching information can be grasped at any time(2)
The evaluation of teachers’ teaching quality is standardized and institutionalized, and all teachers are evaluated using uniform standards(3)
Teachers’ teaching quality evaluation factors are targeted and detailed, and the content of the evaluation is different according to the identity of the evaluator (student, supervisor, and college leader)(4)
Provide fast, accurate, and detailed latest information on teacher evaluation results(5)
The interface is friendly and beautiful, the operation is simple and easy, and the query is flexible and convenient(6)
Through the implementation of the system, the management level of teacher information can be improved(7)
The system is easy to maintain, reliable, and safe to meet the requirements of practicability and advancementFeasibility analysis is essential to carry out a major compression to simplify the system analysis and design process. Its purpose is to determine whether the problem can be solved in the shortest possible time with the least cost. Generally speaking, the feasibility of the system can be analyzed in terms of economic feasibility, technical feasibility, and operational feasibility.Evaluate the consequences of the operation of the new system. At the same time, considering the existing personnel management issues, it is analyzed whether the development of the new system can be completed within a given time. The economic feasibility study report carried out a cost-benefit analysis, estimated the operation and maintenance cost of the new system and the future system, and the development cost. It is estimated that the new system can greatly improve management efficiency and benefits.Measure whether the required technology is available according to the goals of the system and consider or analyze it from the performance requirements of hardware and software, environmental conditions, and operational levels. Considering the feasibility of system implementation, the software design adopts ASP.NET 2.0 and uses SQL Server 2000 database as the storage data management platform. In terms of hardware, there is a lot of room for choice, as long as it is a Pentium III series, computer memory is 128 MB or more, and the hard disk is about 300 MB, it can meet the development requirements of the system! Obviously, the higher the hardware configuration, the smoother the system will run. Considering the current overall configuration level of computer hardware, this system is feasible. In terms of software, as ASP.NET 2.0 and SQL SERVER 2000 are two very mature development tools, there is no doubt in terms of security, availability, and reliability, so the software is feasible.In today’s society, with highly developed information technology and computer technology, more and more schools realize that informatization is an indispensable step to improve management efficiency. The teachers in the school are all people who have received higher management education, and they know the importance of modern management methods to the college. For the teachers’ teaching information management and quality evaluation system that will replace the manual management of teachers’ information and teaching evaluation, it is even more indispensable to be equipped with modern management ideas. Therefore, on the basis of giving sufficient development funds to the system, the leaders of the college integrated modern management ideas into it, making it a management system with modern management methods.The hardware system is a computer with Windows XP operating system. This application system is established on the basis of network system and database system, and the background of development and operation is B/S network computing mode.Evaluate the consequences of the operation of the new system. At the same time, considering the existing personnel management issues, it is analyzed whether the development of the new system can be completed within a given time. ASP.NET2.0 is currently one of the most popular Web development tools. It provides users with a complete visual development environment and can use numerous server controls to quickly develop Web applications. In other words, ASP.NET is a server-side dynamic Web development technology. At present, there are many dynamic Web development technologies. ASP.NET’s predecessor, ASP (Active Server Pages), has achieved success in the field of dynamic Web technologies with its simple syntax and embedded html method. Based on ASP, Microsoft released ASP.NET in November 2000 and officially released ASP.NET 2.0, which is more powerful and easier to use in 2005. In ASP.NET 2.0, many classes have been redesigned and implemented. In order to achieve higher development efficiency, some new controls have been added. For Web application designers and developers, ASP.NET 2.0 is an important milestone in the history of Web development.By default, three languages can be used as scripting languages in ASP.NET applications, namely, VB.NET, JScript.NET, and C#. Among them, VB.NET is an upgrade to the VB language, JScript.Net is an upgrade to the JScript language, and C# is the native language of .NET, a brand new object-oriented programming language released with the release of .NET. Therefore, C# is the best language for programming using .NET.SQL server is the best partner of ASP.NET. It is simple to use, powerful, and meets the performance requirements of enterprise-level data management. SQL Server 2000 uses T-SQL language and is a relational database management system according to C/S mode. The teacher’s teaching quality evaluation of this system uses the quantized method. The deviation comparison is shown in Figure5.Figure 5
Error comparison.A university widely adopts a student online evaluation system, a teaching quality management committee expert listening system and a teacher mutual listening scoring system. How to evaluate teachers in a fair and reasonable manner. Promoting teachers is a problem that the college has been committed to solving. Using neural network to process and analyze the data can better solve this problem. The system uses the data obtained by students scoring 16 indicators of the instructor as input values. The 16 indicators are: work enthusiasm and full of energy; classroom organization; degree of seriousness of lectures; timely and patient after-class tutoring and answering questions; teaching content is correct‚ appropriate capacity and speed; the teaching content focuses on science, logic, and system; able to clarify the key points and difficulties and handle properly; integrate theory with actual conditions; inspire innovative thinking; assignments and corrections; use different methods according to teaching needs; use of multimedia teaching methods; standard and vivid teaching language; clear and reasonable writing on the blackboard; able to combine teaching content and classroom discipline to educate students; teachers’ compliance with discipline; and overall impression of the instructor. The output index, that is, the evaluation of classroom teaching quality uses the evaluation value of multiple experts from the teaching quality management committee after the teacher has listened to the class. The significance of using such sample data to train the neural network is that although the various indicators evaluated by the teacher are typed out by the students, the final evaluation results can reflect the evaluation ideas of the experts. According to the neural network model optimized by the aforementioned design PSO, 16 input neurons, representing 16 indicators, 8 hidden layer neurons, and 1 output layer neuron are determined. After the development of requirements analysis, design, and coding stages, the source code begins to enter the software testing stage. However, there may be some errors and defects in the software product at different stages before the test. These errors and defects need to be found and corrected in time to recover huge economic losses. Prove the correctness of the program.


## 4. Testing of Teaching Evaluation System

Evaluation of predictive models: if it is based on different indicators, after comparing and evaluating different prediction models, the comparison results may also be different, which just shows the inconsistency of different evaluation indicators. Therefore, the evaluation of the prediction performance of the prediction model must be based on certain evaluation indicators. Under normal circumstances, people often choose a more valuable evaluation system based on actual conditions. Modern financial econometrics is mainly based on mathematical statistical models and studies and describes the characteristics and laws of financial markets. Financial markets are more complex and nonlinear, so new methods and tools need to be introduced. The financial market is ever-changing, and the evaluation of forecasting methods or systems is also varied, and a certain forecasting method can only be better than other methods for a certain period of time or under certain conditions. Therefore, how to evaluate the quality of various forecasting methods is an important issue in financial forecasting analysis.Low-quality software products will inevitably lead to an increase in maintenance costs and may also lead to other liability risks and loss of user credibility. At present, the correctness of the program has not been fundamentally resolved. Software testing is still the main means to find errors and defects, as shown in Figure6 based on MATLAB.Figure 6
Value in different zones.The key to testing is the design of test cases. The white box is installed in a transparent white box, and the test fully understands the structure and process of the scheme. It designs and tests to check whether the logic path of the program works normally according to the predetermined requirements. The black box is installed in an opaque black box, and the test does not understand the structure and process of the solution. It designs and tests to check whether the logic path of the program works normally according to the predetermined requirements. The predicted results are shown in Figures7 and 8. The rapid development of information technology has led to more and more extensive applications of software products, and the quality of software products has attracted more and more attention from people. Software developers, in order to avoid being eliminated in the fierce competition and occupying the market, must always regard product quality as an important goal of the enterprise.Figure 7
Deviation.Figure 8
Value versus data.As can be summarized from analyzes, the specific summary is as follows:(1)
Introduced the design concept of particle swarm optimization teaching evaluation system.(2)
The use of object-oriented programming algorithms makes it easier for the algorithm to find an entry point, solve practical problems, and optimize the reusability of the algorithm method.(3)
Particle swarm optimization based on quantum behavior, adjusting parameter values, the highest and the lowest, greatly reduces the difficulty of program parameter adjustment.(4)
In terms of operation, it can quickly and efficiently complete the maintenance of teacher teaching information, evaluation relationship management of teacher teaching quality evaluation, evaluation content management, student evaluation, supervision evaluation, college leadership evaluation, evaluation performance management, and other operations. The interface is extremely humane. It adopts a Web-style tour method. There are many types of functions, and the system includes common functions required for general teacher teaching information management and quality evaluation, and while providing various functions, it closely integrates the various actual needs of the college. The security performance is good. The system provides user name and password verification, which improves the security of the system. Database management is convenient and fast, providing a database-friendly management interface, and timely and accurate query.(5)
This system adopts an object-oriented development method. During the development process, full consideration of the user’s needs enabled the system to have powerful functions and streamlined procedures. In the end, this application software basically completed the goals required by the requirements analysis.


## 5. Conclusion

The paper swarm optimization algorithm and optimization system not only make the algorithm only involve basic mathematical operations, and the computer support required for the data processing process is not high, but it also improves the evaluation of the degree of optimization. The specific summary is as follows:(1)
Introduced the design concept of particle swarm optimization teaching evaluation system.(2)
The use of object-oriented programming algorithms makes it easier for the algorithm to find an entry point, solve practical problems, and optimize the reusability of the algorithm method.(3)
Particle swarm optimization based on quantum behavior, adjusting parameter values, the highest and the lowest, greatly reduces the difficulty of program parameter adjustment.(4)
In terms of operation, it can quickly and efficiently complete the maintenance of teacher teaching information, evaluation relationship management of teacher teaching quality evaluation, evaluation content management, student evaluation, supervision evaluation, college leadership evaluation, evaluation performance management, and other operations.(5)
This system adopts an object-oriented development method. During the development process, full consideration of the user’s needs enabled the system to have powerful functions and streamlined procedures. In the end, this application software basically completed the goals required by the requirements analysis.



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*Source: 8525531-2022-02-21.xml*