一种分阶求解回溯组卷算法

Hierarchical solving paper-generating algorithm based on backtracking search

针对在线测评的广泛应用及现有组卷算法组卷效率低、过程繁琐、无法确保质量等问题,对人工组卷、随机函数选取法、回溯试探法及遗传算法进行了研究,并在回溯试探法的基础上提出一种分阶求解回溯组卷算法。首先依据分阶求解剪枝的思想,建立算法模型,再以提高效率和质量为目标,建立算法分析模型,按照题型、章节等指标将题库分阶求解,提高组卷效率及组卷质量。试验验证的结果表明,随着题库题目数量的增加,分阶求解回溯组卷算法在组卷效率、组卷质量(重复率、覆盖率)、试卷质量(区分度、信度)等方面都有显著提高。

In view of the problems that the online judge is widely used and the existing paper-generating algorithm is low in efficiency,process complexity,and the quality of the paper-generating is not high.Study the artificial paper-generating,random function selection method,backtracking search method and genetic algorithm,and proposes a Hierarchical Solving paper-generating algorithm based on backtracking search.First,establish an algorithm model according to the idea of hierarchical solving pruning,and then the algorithm analysis model is set up with the goal is to improve efficiency and quality of the paper-generating,according to the type of questions,chapters and other indicators,the question bank is hierarchical solved to improve the efficiency of the paper-generating and the quality of the paper-generating.The experimental results show that with the increase of the amount of data,the hierarchical solving paper-generating algorithm based on backtracking search has obviously improved in the efficiency of paper-generating(repetition rate,coverage rate),the quality of paper-generating and the quality of paper(discrimination,reliability).