Studies of internationalmathematics achievement such as the Trends in Mathematicsand Science Study (TIMSS) have employed classical test theory and item responsetheory to rank individuals within a latent ability continuum. Although these approacheshave provided insights into comparisons between countries, they have yet toexamine howspecific attributemastery affects student performance and howthey canprovide information for curricular instruction. In the 2007 administration of TIMSS,two benchmark participants—Massachusetts andMinnesota—were tested followingthe same procedural methods, providing an opportunity for comparison within andacross the United States. Overall comparison of their performance showed Massachusettsand Minnesota to significantly outperform the United States. However,this article shows that there is a greater wealth of fine-grained information that canbe translated directly for classroom application at the attribute level when a cognitivediagnostic model (CDM) such as the deterministic, inputs, noisy, “and” gate (Junker& Sijtsma, 2001) model is used. Results showed a significant disparity betweenproportions of correctly answering and mastering skills required to solve an item.Advantages ofCDMsare discussed aswell as a CDM-basedmethod to filter distractorresponse categories that can aid instructors to diagnose a student’s attribute mastery.