Computer Adaptive Multistage Testing (ca-MST), which take the advantage of computer technology and adaptive test form, are widely used, and are now a popular issue of assessment and evaluation. This study aims at analyzing the effect of different panel designs, module lengths, and different sequence of a parameter value across stages and change in b parameter range on measurement precision in ca-MST implementations. The study has been carried out as a simulation. MSTGen simulation software tool was used for that purpose. 5000 simulees derived from normal distribution (N (0,1)) were simulated. 60 different conditions (two panel designs (1-3-3; 1-2-2), three module lengths (10-15-20), 5 different a parameter sequences (“0.8; 0.8; 0.8” - “1.4; 0.8; 0.8”-“0.8;1.4; 0.8” - “0.8; 0.8;1,4” - “1.4; 1,4; 1.4”) and two b parameter difference (small; large) conditions) were taken into consideration during analysis. Correlation, RMSE and AAD values of conditions were calculated. Conditional RMSE values corresponding to each ability level are given in a graph. Dissimilar to other studies in the literature, this study examines b parameter difference condition in three-stage tests and its interaction with a parameter sequence. Study results show that measurement precision increases as the number and length of the modules increase. Errors in measurement decrease as item discrimination values increase in all stages. Including items with a high value of item discrimination in the second or last stage contributes to measurement precision. In extreme ability levels, large difficulty difference condition produces lower error values when compared to small difficulty difference condition.

中文翻译：

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在计算机自​​适应多级测试中分析不同的模块特性

利用计算机技术和自适应测试形式的优势的计算机自适应多阶段测试（ca-MST）已被广泛使用，并且现已成为评估和评估的热门问题。本研究旨在分析不同面板设计，模块长度以及跨阶段参数值的不同顺序以及b参数范围的变化对ca-MST实施中的测量精度的影响。该研究已作为模拟进行。为此，使用了MSTGen仿真软件工具。模拟了从正态分布（N（0,1））导出的5000个模拟。60种不同条件（两种面板设计（1-3-3; 1-2-2），三种模块长度（10-15-20），5种不同的参数序列（“ 0.8; 0.8; 0.8”-“ 1.4; 0.8”） ; 0.8“-” 0.8; 1.4; 0.8“-” 0.8; 0.8; 1,4“-” 1.4; 1,4; 1.4“）和两个b参数差异（小；分析）。计算条件的相关性，RMSE和AAD值。在图表中给出了与每个能力级别相对应的条件RMSE值。与文献中的其他研究不同，本研究在三阶段测试中考察了b参数差异条件及其与参数序列的相互作用。研究结果表明，随着模块数量和长度的增加，测量精度也随之提高。测量误差随着项目判别值在所有阶段的增加而减小。在第二阶段或最后阶段包含具有较高的项目判别价值的项目有助于提高测量精度。在极限能力水平下，与小难度差异条件相比，大难度差异条件产生的误差值较低。