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Two case studies are presented to demonstrate the importance of intentionally utilizing subject matter expert and psychometrician expertise throughout the development process for cognitive and affective mathematical instruments. While the cases are unique, both empirically support the need for continued and thoughtful collaborative efforts during mathematical instrument development to produce meaningful measures. 

The purpose of this proceeding is to share a component to a validity argument for a new, computer adaptive mathematics Problem-Solving Measure that is designed for grades six through eight (PSM 6-8). The PSM is a single test, which uses computer adaptive features to measure students’ performance using instructional standards. It is intended to measure students’ problem-solving performance related to instructional standards. 

Depth-of-knowledge (DOK) is a means to communicate the cognitive demand of tasks and is often used to categorize assessment items. Webb’s (2002) framework has been applied across content areas. The aim of this two-phase iterative study was to modify Webb’s DOK framework for word problems. Through work with school partners, this iterative design-research based study provides supportive evidence for a modified DOK framework reflecting levels of complexity in word problems. The resulting modified DOK framework presents an opportunity for mathematics educators to reflect on various aspects of cognitive complexity. 

Abstract Determining the most appropriate method of scoring an assessment is based on multiple factors, including the intended use of results, the assessment's purpose, and time constraints. Both the dichotomous and partial credit models have their advantages, yet direct comparisons of assessment outcomes from each method are not typical with constructed response items. The present study compared the impact of both scoring methods on the internal structure and consequential validity of a middle‐grades problem‐solving assessment called the problem solving measure for grade six (PSM6). After being scored both ways, Rasch dichotomous and partial credit analyses indicated similarly strong psychometric findings across models. Student outcome measures on the PSM6, scored both dichotomously and with partial credit, demonstrated strong, positive, significant correlation. Similar demographic patterns were noted regardless of scoring method. Both scoring methods produced similar results, suggesting that either would be appropriate to use with the PSM6.