Original article | International Journal of Educational Researchers 2024, Vol. 15(1) 58-67
Rioborue Alexander Oghenerume & Friday Egberha
pp. 58 - 67 | DOI: https://doi.org/10.29329/ijer.2024.652.4 | Manu. Number: MANU-2311-14-0001.R6
Published online: March 31, 2024 | Number of Views: 138 | Number of Download: 772
Abstract
This investigation aimed to comparatively analyze the item statistics of West African Senior School Examination (WASSCE) and National Examinations Council Senior School Certificate Examination (NECO SSCE) 2023 Data Processing multiple choice tests using IRT 3PLM. Three hypothesized questions were expressed. In this study, survey research design was utilized. The population of this work comprised of 10,800 Data Processing SS 3 students in 21 public senior secondary schools in Abuja Municipal Area Council (AMAC). Multistage sampling procedure was used to pick a sample size of 1,080 Data Processing SS 3 students for this study. The instruments used for the current study were WASSCE and NECO SSCE 2023 Data Processing multiple choice tests. The data collected were subjected to IRT 3PLM using jMetrik psychometric software to generate the item parameters. All hypothesized questions were tested for significance utilizing independent samples t-test statistics. The findings of the study indicated no significant differences in the discrimination and difficulty parameters between WASSCE and NECO SSCE 2023 Data Processing multiple choice items. However, a significant difference existed in the guessing parameters between the two. The practical implication highlighted in the findings suggested that employing IRT 3PLM to determine the item statistics before administering the tests could further enhance the quality of Data Processing multiple choice items constructed by WAEC and NECO.
Keywords: Data Processing, Item Statistics, West African Senior School Certificate Examination (WASSCE), National Examinations Council Senior School Certificate Examination (NECO SSCE), Item Response Theory Three Parameter Logistic Model (IRT 3PLM).
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