The work presented in this paper defined conceptually the concepts of multidimensional discrimination and information, derived mathematical expressions for the concepts for a particular multidimensional item response theory (IRT) model, and applied the concepts to actual test data. Multidimensional discrimination was defined as a function of the slope of the item response surface in the direction specified by the multidimensional difficulty. For the multidimensional extension of the two-parameter logistic (MLPL) model, this definition resulted in a statistic that had the same relationship to multidimensional difficulty that "a" did to "b" for the unidimensional IRT models. This statistic was defined as the square root of the sum of squared a-parameters from the MLPL. Multidimensional information was defined by the same mathematical function as unidimensional information, but the directional derivative was substituted for the standard derivative in the numerator of the information expression. The use of the directional derivative resulted in an information measure that corresponded to a direction in ability space. The American College Testing Program's ACT Assessment Mathematics Usage Test was used to demonstrate the multidimensional discrimination and information. The multidimensional measures of item quality, item precision, and test precision provide tools to gain a better understanding of the measurement process. (PN)