认知诊断计算机化自适应测验按模式分层选题策略
p-STR Item Selection Strategy of Computerized Adaptive Testing for Cognitive Diagnosis

提出一种题库按属性模式分层,并结合项目曝光度控制的新方法.蒙特卡洛模拟研究显示:该方法在题库使用均匀程度上表现优异,并保有较高测量精度.
Partition of an item pool into some sub-pools according to the attribute pattern(briefly,p-STR)in items is made and a new item selection strategy is proposed.The four types of the attribute hierarchies of linear,convergent,divergent and unstructured structure are considered and each type corresponds to an item pool and tests are fixed-length.The results of Monte Carlo simulations indicate that compared to other methods,the new strategy is effective in improvement of the security of item pool,meanwhile with high measurement accuracy