To efficiently obtain information about both the general abilities and detailed cognitive profiles of examinees from a single model that uses a single-calibration process, higher-order cognitive diagnostic computerized adaptive testing (CD-CAT) that employ higher-order cognitive diagnostic models have been developed. However, the current item selection methods used in higher-order CD-CAT adaptively select items according to only the attribute profiles, which might lead to low precision regarding general abilities; hence, an appropriate method was proposed for this CAT system in this study. Under the framework of the higher-order models, the responses were affected by attribute profiles, which were governed by general abilities. It is reasonable to hold that the item responses were affected by a combination of general abilities and attribute profiles. Based on the logic of Shannon entropy and the generalized deterministic, inputs, noisy “and” gate (G-DINA) model discrimination index (GDI), two new item selection methods were proposed for higher-order CD-CAT by considering the above combination in this study. The simulation results demonstrated that the new methods achieved more accurate estimations of both general abilities and cognitive profiles than the existing methods and maintained distinct advantages in terms of item pool usage.

中文翻译：

---

使用高阶认知诊断模型的计算机自适应测试中的双目标项目选择方法

为了从使用单一校准过程的单一模型中有效地获取有关受试者的一般能力和详细认知概况的信息，采用高阶认知诊断模型的高阶认知诊断计算机化自适应测试（CD-CAT）已经被提出。发达。然而，当前高阶CD-CAT中使用的项目选择方法仅根据属性概况自适应地选择项目，这可能导致一般能力的精度较低；因此，本研究中为该 CAT 系统提出了一种合适的方法。在高阶模型的框架下，响应受到属性概况的影响，属性概况受一般能力的控制。认为项目响应受到一般能力和属性概况的组合影响是合理的。基于香农熵的逻辑和广义确定性、输入、噪声“与”门（G-DINA）模型判别指数（GDI），考虑上述组合，提出了两种新的高阶 CD-CAT 项目选择方法在这项研究中。模拟结果表明，新方法比现有方法能够更准确地估计一般能力和认知概况，并在项目池使用方面保持明显的优势。本研究中考虑上述组合，提出了两种新的高阶 CD-CAT 项目选择方法。模拟结果表明，新方法比现有方法能够更准确地估计一般能力和认知概况，并在项目池使用方面保持明显的优势。本研究中考虑上述组合，提出了两种新的高阶 CD-CAT 项目选择方法。模拟结果表明，新方法比现有方法能够更准确地估计一般能力和认知概况，并在项目池使用方面保持明显的优势。