Lu Peng, Cong Xiao, Zhou Dongdai
Department of Media Technology and Communication, Northeast Dianli University, Jilin, Jilin 132012, China.
College of Science, Northeast Dianli University, Jilin, Jilin 132012, China.
ScientificWorldJournal. 2014;2014:167124. doi: 10.1155/2014/167124. Epub 2014 May 14.
The computerized evaluation is now one of the most important methods to diagnose learning; with the application of artificial intelligence techniques in the field of evaluation, the computerized adaptive testing gradually becomes one of the most important evaluation methods. In this test, the computer dynamic updates the learner's ability level and selects tailored items from the item pool. In order to meet the needs of the test it requires that the system has a relatively high efficiency of the implementation. To solve this problem, we proposed a novel method of web-based testing environment based on simulated annealing algorithm. In the development of the system, through a series of experiments, we compared the simulated annealing method and other methods of the efficiency and efficacy. The experimental results show that this method ensures choosing nearly optimal items from the item bank for learners, meeting a variety of assessment needs, being reliable, and having valid judgment in the ability of learners. In addition, using simulated annealing algorithm to solve the computing complexity of the system greatly improves the efficiency of select items from system and near-optimal solutions.
计算机化评估如今是诊断学习情况的最重要方法之一；随着人工智能技术在评估领域的应用，计算机自适应测试逐渐成为最重要的评估方法之一。在这种测试中，计算机动态更新学习者的能力水平，并从题库中选择量身定制的题目。为满足测试需求，要求系统具有较高的执行效率。为解决这一问题，我们提出了一种基于模拟退火算法的新型网络测试环境方法。在系统开发过程中，通过一系列实验，我们比较了模拟退火方法与其他方法的效率和效果。实验结果表明，该方法能确保为学习者从题库中选择近乎最优的题目，满足各种评估需求，具有可靠性，且对学习者的能力有有效的判断。此外，使用模拟退火算法解决系统的计算复杂性，极大地提高了从系统中选择题目的效率和获得近乎最优解的能力。
