Due to psychological differences between individuals, no test item can function exactly the same manner in these individuals. Differential item functioning (DIF) will always occur as a result of these differences in the person parameter of these individuals being examined even when item parameters remain constant during testing. This postulate of item response theory (IRT) was proven in this work. This study investigated if DIF detection methods will have the same DIF detection sensitivity. Comparative research design formed the framework of the study. Transformed item difficulties (TID), Mantel-Haenszel (MH), standardization, logistic regression, Ragu’s area, and Lord’s chi-square methods were compared. The study used 400 vocational one students (200 male as reference group and 200 female as focal group) in Rivers state, Nigeria. The multiple choice items of 2019 computer science for the junior school certificate examination (JSCE) was adapted as the instrument for data collection, which were administered to students and scored dichotomously. Difficulty and discrimination parameters of the items were analyzed using the 2PL model of IRT with the help of ltm package. Ogives of the items were plotted with ggplot2 package. Individual DIF methods and DichoDif in DifR were used to detect DIF and compare the methods. The results revealed that all the items of the test functioned differently between the reference group and the focal group as shown in the item characteristic curves (ICCs). In comparison of the DIF detection methods, standardization method detected most of the DIF items followed by logistic regression method, and then lord’s chi-square methods. Transformed item difficulties method detected more than mantel-Haenszel method. Raju’s area method could not detect any. In the light of the finding, it was recommended that the best DIF detection methods (possibly combination of them) should be used to identify DIF items in tests.