In their commentary on our meta-analysis, Zitzmann and Orona (2025) used formal proof and cited methodological studies to argue that test reliability is important, Cronbach’s Alpha generally indicates test reliability, and cutoff values for alpha are indispensable. We agree that high reliability is important for all tests. Yet, alpha does not reflect the reliability of knowledge tests. Zitzmann and Orona’s arguments are based on the unwarranted assumption that knowledge is always homogeneous. Using a concrete example, we show how item interrelatedness (i.e., alpha) can be low for heterogeneous constructs such as knowledge, even when measurement error is minimal (i.e., reliability is high). After a brief discussion of how researchers can heuristically assess construct heterogeneity, we explore alternatives to alpha for evaluating the reliability of knowledge tests. We conclude that abandoning alpha as a reliability index does not compromise the quality of measurement. On the contrary, it is a step toward sounder methodological standards in the measurement of knowledge.

在他们对我们的荟萃分析的评论中，Zitzmann 和 Orona （2025） 使用形式证明并引用方法论研究来论证测试信度很重要，Cronbach 的 Alpha 通常表示测试信度，而 Alpha 的临界值是必不可少的。我们同意高可靠性对所有测试都很重要。然而，Alpha 并不能反映知识测试的可靠性。Zitzmann 和 Orona 的论点基于一个毫无根据的假设，即知识总是同质的。通过一个具体的例子，我们展示了即使测量误差很小（即可靠性很高），对于异构结构（如知识）的项目相关性（即 alpha）也是低的。在简要讨论了研究人员如何启发式评估结构异质性之后，我们探索了 alpha 的替代方案来评估知识测试的可靠性。我们得出的结论是，放弃 alpha 作为可靠性指标不会影响测量质量。相反，这是朝着知识测量中更健全的方法标准迈出的一步。