Design and Implementation of an Automatic Test Paper Generation System Based on ant colony optimization

Abstract

The paper proposed a model of automatic test paper generation system since the traditional test was time-consuming, labor-intensive and unstable. Based on the demand of the automatic test paper generation system the model explored the setting of the initial value information of the ant colony optimization and updated the rules so that the test results could he feed backed to the system. This model not only effectively solved the problem of the auto-generating test-paper but also improved the autonomous learning ability of the system, which was more intelligent to improve the performance. The practical test proves that the system has achieved the expected goal with high quality and high efficiency. The practical test shows that the system has advantages like fast generation of test papers, low repetition of the selected papers and effective colony algorithm. Examinations designed based on this system an achieve the expected testing goals