DISCRIMINANT ANALYSIS OF MATHEMATICS ACHIEVEMENT AND PROBLEM-SOLVING SKILLS ON GENDER OF SENIOR SECONDARY SCHOOLS STUDENTS
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Mathematics is expected to model how real life problems could be solve. However, most students find it difficult to transfer problem solving skills learnt from Mathematics concepts to new situations and this could hinder their ability to solve real life problems. Similarly, researchers often used the wrong approach to measure students’ achievement in Mathematics and skills in solving mathematics as regards gender. This study examined if achievement in Mathematics and problem-solving skills could reliably discriminate between male and female students. Non-experimental design of correlational research type was adopted in this study. Population consist of SSS 2 Mathematics students in Ibadan, Oyo State. Simple random sampling technique was used to select three local governments from the eleven LGAs in Ibadan metropolis and eight public senior secondary schools (four in each LGA). An intact class from the arms of classes of SSS 2 Mathematics students was used and a total 520 students formed the sample of the study. Mathematics Achievement Test (r=0.72) and Problem Solving Skills Test (r=0.68) was used for data collection. Content validity of the instruments was established using Table of Specification of Mathematics Concepts while internal consistency was established using Cronbach Alpha. Three research questions were raised and analysed using R 4.2.2 software. Results reveal that achievement in Mathematics is a potent and reliable predictor that can discriminate between male and female students in Mathematics. Also, result show that problem solving skills do not reliably discriminate between male and female students. It is therefore of importance to have a proper knowledge of variables that could reliably discriminate between categorical dependent variables using discriminant analysis. The study recommended that cognitive scales should not be categorised and used for categorical dependent variable if the focus is on discriminant analysis.
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