No abstract

Cognitive complexity level is important for measuring both aptitude and achievement in large-scale testing. Tests for standards-based assessment of mathematics, for example, often include cognitive complexity level in the test blueprint. However, little research exists on how mathematics items can be designed to vary in cognitive complexity level. In fact, determining the cognitive complexity level of items is usually based on correspondence to definitions rather than on empirically and theoretically justifiable variables that can predict item difficulty. In the current study, mathematical problem-solving items were designed for varying cognitive complexity levels based on a cognitive model of item processing. Structural variants of item models were designed to vary on two aspects of the cognitive model, the equation source and the number of subgoals. Participants were randomly assigned to test forms that contained different structural variants of the item models. Results from the linear logistic test model, the two-parameter-logistic—constrained model, and a corresponding linear mixed modeling procedure indicated that the item design variables affected both item difficulty and response time. Implications of the results for using structural variants in item generation and for the plausibility of the hypothesized cognitive model are discussed.

Synopsis A novel solid state lithium battery design enables surface-and bulk-sensitive soft X-ray absorption spectroscopy of battery materials under operating conditions.Abstract O K edge and Co L edge near edge X-ray absorption fine structure (NEXAFS) was used to examine the cathode of an intact solid-state lithium ion battery. The novel technique allowed for the simultaneous acquisition of partial electron yield and fluorescence yield data during the first charge cycle of a LiCoO 2 -based battery below the intercalation voltage. The chemical environments of oxygen and cobalt at the surface are shown to differ chemically from those in the bulk. The present design enables a wide variety of in situ spectroscopies, microscopies, and scattering techniques.

No abstract

No abstract