Diagnostic classification models (DCMs) are psychometric models designed to classify examinees according to their proficiency or non-proficiency of specified latent characteristics. These models are well-suited for providing diagnostic and actionable feedback to support formative assessment efforts. Several DCMs have been developed and applied in different settings. This study proposes a DCM with functional form similar to the 1-parameter logistic item response theory model. Using data from a large-scale mathematics education research study, we demonstrate that the proposed DCM has measurement properties akin to the Rasch and 1-parameter logistic item response theory models, including test score sufficiency, item-free and person-free measurement, and invariant item and person ordering. We discuss the implications and limitations of these developments, as well as directions for future research.

翻译：诊断分类模型（DCMs）是一种心理测量模型，旨在根据被试是否掌握特定潜在特征对其进行分类。这些模型非常适合提供诊断性和可操作的反馈，以支持形成性评估工作。目前已有多类DCM在不同情境中得到开发和应用。本研究提出一种功能形式与单参数逻辑斯蒂克项目反应理论模型相似的DCM。通过使用大规模数学教育研究数据，我们证明所提出的DCM具有与Rasch模型和单参数逻辑斯蒂克项目反应理论模型相似的测量属性，包括测验总分充分性、项目无关与个体无关测量以及项目与个体的不变排序。我们讨论了这些发展的启示与局限性，以及未来研究方向。