Test Paper Composition Research Articles

Design and Implementation of Online Japanese Examination System Based on Genetic Algorithm

In order to solve the problem of online inspection of students’ theoretical knowledge of Japanese, this paper further optimizes and adjusts the design of the online Japanese examination system and presents an online Japanese examination system based on genetic algorithm. Taking the Japanese test as the research object, on the basis of comprehensively analyzing the problems of slow test paper composition, low success rate, and low quality of traditional online test systems, an intelligent test composition model based on genetic algorithm is proposed, and the implementation process of genetic algorithm and the key steps are described in detail. The results show that the online Japanese examination system based on genetic algorithm can meet the needs of test paper generation in more complex situations. After a long time of operation and continuous improvement, the online Japanese examination system has obtained the adaptability of the best solution. The value of the fitness is 99.666667; when the fitness is at this value, the error of the question type score of the test paper is 0, the average difficulty error on the test paper is 0, and the error of the section test point distribution is 0.666667. This fully illustrates the stability and effectiveness of the Japanese online examination system, which can meet the needs of daily Japanese majors and improve the efficiency of Japanese teaching.

Research on the Fusion of Hybrid Fuzzy Clustering Algorithm and Computer Automatic Test Paper Composition Algorithm

In order to improve the effect of intelligent automatic test paper composition, this paper combines the hybrid fuzzy clustering algorithm to study the computer automatic test paper composition algorithm. In this paper, a computer automatic test paper composition system based on hybrid fuzzy clustering algorithm is constructed. Moreover, the hybrid fuzzy clustering method used in this paper is used as the basic algorithm of the system, and the algorithm is improved according to the actual needs of intelligent paper composition. In addition, this paper uses an intelligent algorithm to input the relevant constraint parameters and combines the original parameters to select the most suitable test questions from the database and combine them into test papers. Finally, this paper constructs the system structure based on the requirements of intelligent test paper composition. The experimental research shows that the computer automatic test paper composition system based on the hybrid fuzzy clustering algorithm proposed in this paper has a good test paper composition function, which can effectively promote the progress of the intelligent examination mode in colleges and universities.

Computer Intelligent Test Paper System Based on Genetic Algorithm

The rapid development of the Internet has brought tremendous changes to people’s lives. Through the network function, the online examination is gradually accepted by various educational and teaching institutions. Currently, online exams have become the main method of teaching evaluation. In order to solve the problem of intelligent test paper more effectively, this paper proposes a mufti-threaded intelligent test paper strategy based on genetic algorithm, and designs the computer system structure in the standard test question bank. Convergence simulation and experimental results show that the algorithm is better than simple particle swarm optimization algorithm, simple genetic algorithm and its improved algorithm. Established a mathematical model and objective function for test paper composition, and proposed an intelligent test paper composition strategy based on genetic algorithm. The investigator used overall coding, crossover and mutation operations to improve the global optimization capability and convergence speed. It overcomes the phenomenon of premature and improves the accuracy and speed of convergence. It has the advantages of strong optimization ability and good stability.

Research on Random Algorithm of English Test Paper Composition

English, as one of the most important information carriers, has become the most widely used language worldwide, and its importance is increasingly prominent in each field of our society. Examinations are an important means of evaluating the level of English language learning and teaching outcomes. For the problems existed in traditional English exam, this paper research English online examination system intelligent test paper based on random algorithm. First, the design test paper constraints, including the question amount constraint, questions type constraints, knowledge point constraints, difficulty constraints, answer time constraints and so on; Then, using the linear congruence generator study of a random number generation, list recursive formula and describe parameters; Finally, using flow diagram to study random test paper process, for each step describing in detail. Advantages of random algorithm are easy to use, the disadvantage is not retrospective, applies to the number of exam papers and extraction requirements are relatively few cases.

Test Paper Composition Design on College English Examination Based on Genetic Algorithm

College English examination is an important part of university English education, for the difficult problems in the process of examination organization and management, in this paper, the intelligent test paper composition research based on genetic algorithm. First, basic research, including the basic idea of genetic algorithm, algorithm flow and perform operations on groups; then, studies test paper composition model, the test paper problem described as question number, question types, difficulty, discrimination, score, answer time, using the frequency property and other attributes, constituted seven dimensional vector. Finally, test paper composition design, to generate the initial population, fitness function design, operation operator design, algorithm terminates and others, four key steps were designed. The content of this paper to meet the quality and speed requirements of university English test paper composition, and has the advantages of randomness, scientificalness and so on.

Strategy for Test Paper Composition Based on Genetic Algorithm

Recently, with rapid development of computer/network technology and algorithms for composing test paper, cyber-based online examination system is a practically valuable hot research concern. In the paper, the mathematical model is created for solving problems with the online test paper composition system. Through comparative analysis of merits and shortcomings of various coding schemes, and to overcome the shortcoming that traditional genetic algorithms easily fall into premature convergence, it utilizes the adaptive adjustment method of dynamic parameters and elitist strategy to improve to develop the online test paper forming scheme based on adaptive genetic algorithm. For the selection of each parameter, simulation test is conducted to obtain the solution approximate to the best one.

Database Design on Intelligent Test Paper Composing System of College English Online Examination

College English is students public courses who dont major in English. The traditional examination mode has many defects, so online examination is the future, intelligent test paper composition is an important part of online examination, in this paper, according to the characteristics of College English test, design database on intelligent test system. Firstly, make t requirement analysis about the test, user, and algorithm; then, use entity relationship model to design the concept based on the analysis; finally, make the logical structure design, following the design principles for the logical structure of the meter, and the result is the table structure 10. The content of this paper has important application value for the construction of College English online examination management system, promoting the scientific and standardization of teaching management.

A Research on Genetic Algorithms Based on Test Paper Composition of Item Response Theory

Along with the computer technology in the examination of the application, the examination has become a hot topic. However, test paper is an important part of the adaptive test. According to the test generation of the objectives and requirements, this paper introduces a method based on item response theory ( IRT ) thought of genetic algorithm in the test application, thereby effectively solving the problem of intelligent test paper.

The Research of Automatic Test Paper Composition Based on Ant Colony Algorithm

The Research of Automatic Test Paper Composition Based on Ant Colony Algorithm