Browsing by Author "Ogbebor, U."

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    Differential item functioning methods as an item bias indicator
    (2012-04) Ogbebor, U.; Onuka, A. O. U.
    Differential item functioning is an approach that is widely used to find out items that are bias. This study investigated items that are bias using differential item functioning approach in relation to school type (private and public schools) school location (urban and rural schools) using National Examination Council (NECO) economics questions for 2010. The research design employed in this study was comparative research type of design. The study sample comprised students in Delta state, Nigeria. Four hundred and forty seven (447) students were used. And the test contains 60 items which was administered to the students. Logistics regression was used to analysis the data. The research finding showed that out of sixty items in NECO economic questions, 10 were biased in relation to school type and 8 items in relation to school location. The implication of these findings is that NECO economics examinations questions have presences of differential items functioning (DIF). From the result of the findings, it was then recommended that test experts and developers should explore the use of DIF approach to detect biased items.
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    Differential item functioning of economics question papers of national examinations council in Delta state, Nigeria
    (2013) Ogbebor, U.; Onuka, A. O. U.
    This study attempted to detect item bias using differential item functioning approach in relation to gender (male and female) and school type (private and public schools). Using National Examinations Council (NECO) Economics questions for 2010. The research design employed in this study was a comparative research type of design. The study sample comprised students in Ethiope East local government area of Delta state. Four hundred and fourty seven (447) students were used. The test contains 60 items which was adminstered to the students. To detect items bias in relation to gender and school type, logistic regression was used; the result showed that there were item biases in terms of gender and school type. It was then recommended that items should be constructed in future taking cognizance of gender and school type.