Construct Relevant and Irrelevant Variables in Math Problem Solving Assessment
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In this study, I examined the relation between various construct relevant and irrelevant variables and a math problem solving assessment. I used independent performance measures representing the variables of mathematics content knowledge, general ability, and reading fluency. Non-performance variables included gender, socioeconomic status, language proficiency and special education qualification. Using a sequential regression and commonality analysis, I determined the amount of variance explained by each performance measure on the Oregon state math assessment in third grade. All variables were independently predictive of math problem solving scores, and used together, they explained 58% score variance. The math content knowledge measure explained the most variance uniquely (12%), and the measures of math content and general ability explained the most variance commonly (16%). In the second analysis, I investigated whether additional variance was explained once student demographic characteristics were controlled and how this affected the unique variance explained by each independent performance measure. By controlling for demographics, the model explained slightly more than 1% additional variance in math scores. The unique variance explained by each independent measure decreased slightly. This study highlighted the influence of various construct relevant and irrelevant variables on math problem solving scores, including the extent to which a language-free measure of general ability might help to inform likely outcomes. The use of variance partitioning expanded understanding of the unique and common underlying constructs that affect math problem solving assessment. Finally, this study provided more information regarding the influence demographic information has on outcomes related to state math assessments.