中文摘要：

研究比较了多级评分题计算机化自适应测验五种选题策略的优劣。应用的IRT模型是Samejima的等级反应模型。参加比较的选题策略有难度均值与能力匹配法、难度中值与能力匹配法、信息量最大法和两种A分层法。比较指标采用了能力估计值返回真值偏差、能力估计标准差、人均用题数和试题调用次数标准差四个。研究采用蒙特卡罗模拟法，结果显示每种方法各有优劣，在分层得当情况下，A分层法（中）的综合效果最佳。

英文摘要：

The initial purpose of comparing item selection strategies for CAT was to increase the efficiency of tests. As studies continued, however, it was found that increasing the efficiency of item bank using was also an important goal of comparing item selection strategies. These two goals often conflicted. The key solution was to find a strategy with which both goals could be accomplished. The item selection strategies for graded response model in this study included：the average of the difficulty orders matching with the ability ; the medium of the difficulty orders matching with the ability ; maximum information ; A stratified （average） ; and A stratified （medium）. The evaluation indexes used for comparison included： the bias of ability estimates for the true ; the standard error of ability estimates ; the average items which the examinees have administered ; the standard deviation of the frequency of items selected;and sum of the indices weighted. Using the Monte Carlo simulation method, we obtained some data and computer iterated the data 20 times each under the conditions that the item difficulty parameters followed the normal distribution and even distribution. The results were as follows： The results indicated that no matter difficulty parameters followed the normal distribution or even distribution. Every type of item selection strategies designed in this research had its strong and weak points. In general evaluation, under the condition that items were stratified appropriately, A stratified （medium）（ASM） had the best effect.