结合影子题库的选题策略
New Item Selection Method Combining with Shadow Bank

高效安全的选题策略是计算机化自适应测验追求的目标.最大Fisher信息量选题测验效率高、能力估计准确,但项目调用不均匀,影响考试的安全;而增设影子题库能较好地平衡项目调用的均匀性.根据上述2种选题策略的优缺点,在0-1评分模型下,结合影子题库得到一种新的选题策略,并在按a分层、按最大信息量分层中引入了新的选题方法.计算机模拟实验显示:新的选题方法效果比较理想.
Computerized Adaptive Testing(CAT)has been in pursuit of the goal is to develop both efficient and safe item selection strategies.It is well known that there is a typical selection strategy called Maximum Fisher Information(MFI).However,this strategy has its advantages together with its downsides.On the one hand,MFI method can obtain high efficiency and accurate estimation of ability; on the other hand,its uneven item selection may lead to the insecurity of examination.Meanwhile,though shadow bank can be a good method of the item called evenly,it may result in the inefficiency of the test.Taking the advantages and disadvantages of the two selection strategies in the 0-1 scored CAT into consideration,a new item selection strategy is proposed in this paper,and pull this new method in a-Stratification(a-STR)and Maximum Information Stratification(MIS).The computer simulation shows that the new method works ideally