Gender fairness in immigration language testing: a study of differential options functioning on the CELPIP-G reading multiple-choice questions
by Amery D. Wu; Minjeong Park; Shun-Fu Hu
International Journal of Quantitative Research in Education (IJQRE), Vol. 5, No. 3, 2021

Abstract: The CELPIP-G test is used by the Canadian federal government to screen immigration eligibility for the skilled worker class. Differential option functioning is a technique used to detect potential bias in the options of multiple-choice items. The purpose of this paper is to investigate DOF in a CELPIP-G reading test form by way of multinomial logistic regression. The results showed that 13.7% of options were flagged as gender DOF. Nonetheless, 11.2% were negligible or small DOF. In the case of uniform gender DOF, twice as many options were found to function against female immigration applicants than against their male counterparts. Female test-takers were more likely to be disadvantaged when tackling questions that asked them to make direct inferences based on factual but unfamiliar information. In contrast, male test-takers were more likely to be disadvantaged when tackling questions that asked them to develop their own interpretations over different views. Moreover, test questions that required an understanding of more sophisticated ideas in complex language structure and allowing personal interpretation tended to show more marked and non-uniform gender DOF.

Online publication date: Tue, 21-Dec-2021

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