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Noncompensatory Multidimensional Item Response Theory Models: An Application of Assessing Math Ability in English Language Learners

Thu, April 16, 12:00 to 1:30pm, Sheraton, Floor: Fourth Level, Chicago VI&VII


Accurate estimation of English Language Learners’ (ELLs) math ability may be confounded with linguistically complex word problems. Since high math ability cannot compensate for low English language proficiency (ELP), a non-compensatory model of MIRT is most appropriate; however, the most commonly employed MIRT model is compensatory. This simulation study, therefore, aims at investigating bias in ability estimates resulting from applying the compensatory model onto underlying non-compensatory data. Findings show that examinees like ELLs, being high on math but low on ELP, are systematically underestimated with respect to their high math ability. Such a finding supports the use of non-compensatory models for estimating ELLs’ math ability when linguistically complex items are present.