Dialect and mathematics performance in African American children who use AAE: Insights from explanatory IRT and error analysis.

Little is known about mismatches between the language of mathematics testing instruments and the rich linguistic repertoires that African American children develop at home and in the community, in part because research paradigms with African American English (AAE) dialect speakers face complex challenges in measurement, historical exclusion, and other social, economic, cultural, and linguistic confounds. The current study aims to provide a proof of concept and novel explanatory item response design that uses error analysis to investigate the relationship between AAE child language and children's mathematics assessment outcomes. Here, we illustrate 2 and 3 grade children's qualitative patterns of performance on arithmetic tasks in relation to their AAE dialect use and elaborate a unified framework for examining child and item level linguistic characteristics.

Problem solving is embedded in context… so how do we measure it?

Problem solving encompasses the broad domain of human, goal-directed behaviors. Though we may attempt to measure problem solving using tightly controlled and decontextualized tasks, it is inextricably embedded in both reasoners' experiences and their contexts. Without situating problem solvers, problem contexts, and our own experiential partialities as researchers, we risk intertwining the research of information relevance with our own confirmatory biases about people, environments, and ourselves.

The Growth of Complex Syntax in School-Age African American Children Who Speak African American English.

Purpose: Syntax provides critical support for both academic success and linguistic growth, yet it has not been a focus of language research in school-age African American children. This study examines complex syntax performance of African American children in second through fifth grades.

Method: The current study explores the syntactic performances of African American children ( = 513) in Grades 2-5 on the Test of Language Development-Intermediate who speak African American English.

Developing a Longitudinal Scale for Language: Linking Across Developmentally Different Versions of the Same Test.

Purpose Many language tests use different versions that are not statistically linked or do not have a developmental scaled score. The current article illustrates the problems of scores that are not linked or equated, followed by a statistical model to derive a developmental scaled score. Method Using an accelerated cohort design of 890 students in Grades 1-5, a confirmatory factor model was fit to 6 subtests of the Test of Language Development-Primary and Intermediate: Fourth Edition ( Hammill & Newcomer, 2008a , 2008b ).

Individual Differences in Addition Strategy Choice: A Psychometric Evaluation.

The Strategy Choice Model (SCM) is a highly influential theory of human problem-solving. One strength of this theory is the allowance for both item and person variance to contribute to problem-solving outcomes, but this central tenet of the model has not been empirically tested. Explanatory Item Response Theory (EIRT) provides an ideal approach to testing this core feature of SCM, as it allows for simultaneous estimation of both item and person effects on problem-solving outcomes.

Measuring arithmetic: A psychometric approach to understanding formatting effects and domain specificity.

Using multitrait, multimethod data, and confirmatory factor analysis, the current study examined the effects of arithmetic item formatting and the possibility that across formats, abilities other than arithmetic may contribute to children's answers. Measurement hypotheses were guided by several leading theories of arithmetic cognition. With a sample of 1314 3rd grade students (age M=103.

Testing Math or Testing Language? The Construct Validity of the KeyMath-Revised for Children With Intellectual Disability and Language Difficulties.

Although it is often assumed that mathematics ability alone predicts mathematics test performance, linguistic demands may also predict achievement. This study examined the role of language in mathematics assessment performance for children with intellectual disability (ID) at less severe levels, on the KeyMath-Revised Inventory (KM-R) with a sample of 264 children, in grades 2-5. Using confirmatory factor analysis, the hypothesis that the KM-R would demonstrate discriminant validity with measures of language abilities in a two-factor model was compared to two plausible alternative models.