基于改进的遗传算法的智能组卷算法研究

随着人工智能技术在高校信息化过程的不断推广,智能在线考试模式已成为高校教学改革的一种新手段。目前现有的在线考试系统由于一些现实约束,还存在很多不足。文中针对现有的考试系统存在智能组卷后的试卷难度不均衡、题库试题难度系数确定不合理的现象,提出一种基于改进的遗传算法自动组卷策略。利用伯努利大数定律和机器自适应学习方式,确定题库中试题合理的难度系数。在试题的难度系数确定后,试卷的难度系数就是参入组卷的试题的平均难度系数,组卷中,只需指定试卷的平均难度系数和各类题型的数量即可。

Research on Intelligent Test Paper Generating Algorithm Based on Improved Genetic Algorithm

With the continuous promotion of university informatization process of artificial intelligence technology,intelligent online examination mode has become a newway of teaching reform in colleges and universities. At present,the online examination system,because of some realistic constraints,has many deficiencies. In this paper,in viewof the phenomenon that the intelligent examination system after the examination is not balanced,and exam difficulty coefficient is unreasonable,put forward a strategy of automatic generating test paper based on improved genetic algorithm. Use the Bernoulli lawof large numbers and machine learning methods to determine the reasonable difficulty coefficient of test question database,after determining the difficulty coefficient,the test paper difficulty coefficient is average difficulty coefficient of incorporation test paper,only the designated test average difficulty coefficient and various types of quantity can be.