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针对信息化发展中在线试卷的组卷工作中存在的问题,诸如如何让考试的试题更好地检验学生的知识水平,怎样考察学生掌握和未掌握的知识等问题,探索提出了一种自适应的组卷方法,把学生个性化信息引入其中,采用期望的试卷难度、区分度作为约束条件,将从试题库选择的试题子集的难度和区分度值与期望的难度和区分度的差作为目标函数,从而提出一种个性化信息遗传组卷算法(Personalized Information Genetic Algorithm,PI-GA)。测验结果证明,在生成试卷的时候,PI-GA算法可以有效地为学生提供个性化试卷,对比几种常见的算法,执行时间最短,并且所组成的最终试卷中包含的学生未掌握试题数量具有灵活性。
In view of the problems existing in the process of composing the online test papers in the development of informationization, such as how to make the test questions better test students ’knowledge level and how to examine the students’ mastery and unscientific knowledge, this paper proposes an adaptive , The students’ personalization information is introduced into it. Using the difficulty and degree of examination paper as the constraints, the difference between the degree of difficulty and the degree of discrimination and the degree of difficulty and degree of discrimination that are selected from the test question bank are taken as Objective function, a personalized information genetic algorithm (PI-GA) is proposed. The test results show that the PI-GA algorithm can effectively provide students with personalized test papers when generating test papers. Compared with several common algorithms, the PI-GA algorithm has the shortest execution time, and the students in the final papers that are composed do not have the number of test papers flexibility.