The Application of Genetic Algorithm and an Evaluation Algorithm in Online Examination System

Yang Zhao
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Abstract

Online examination system plays a significant role in education. However, there are varieties of disadvantages in non-optimized systems, such as randomly selecting questions that make the exam paper has an imbalance difficulty, the unanticipated weight of knowledge points, and so on. A genetic algorithm is an efficient and achievable way to improve the ability to generate exam paper. Besides, a massive amount of data are generated when the system is running. Nevertheless, some of the systems only store the data, in another word, they do not make full use of the generated data. An evaluation algorithm is put forward in this essay to give objective and scientific evaluations on students’ learning and teachers’ teaching via using the data that are generated in examinations, which is based on the degree of difficulty. To make this algorithm working well, the degree of difficulty of questions stored in the database is supposed to be updated dynamically when the samples of questions’ answers become large enough.
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遗传算法与评价算法在在线考试系统中的应用
在线考试系统在教育中发挥着重要的作用。然而,非优化系统也存在各种弊端,比如随机选择题目,使得试卷难度不平衡,知识点的权重超出预期等等。遗传算法是提高试卷生成能力的一种有效可行的方法。此外,系统在运行过程中会产生大量的数据。然而,有些系统只是存储数据,换句话说,它们没有充分利用生成的数据。本文提出了一种基于难易程度的评价算法,利用考试中产生的数据对学生的学习和教师的教学进行客观、科学的评价。为了使该算法能够很好地工作,需要在问题答案样本足够大时,动态更新数据库中存储的问题的难易程度。
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