Abstract
Abstract:
he socio-economic and demographic factors have been indicated to predict mathematics success. However, there is paucity of research to verify if these factors differ in predicating mathematics success based on gender (male and female). Hence, this paper reports on a study of gender socio-economic and demographic factors as predictors of mathematics success for civil and built environment students at a comprehensive university in South Africa. Data was obtained through, questionnaire survey from 199 students who were purposive sampled. However, two questionnaires were not valid. The questionnaire was developed from exiting literature. The data was analysed using Statistical Package fo! r the Social Sciences (SPSS) version 22. The statistical analyses computed were both descriptive and inferential. Inferential statistics were used to determine gender socio-economic and demographic variables influencing mathematics success. This was computed using binary logistic regression, splitting gender into male and female. The result established that when male and female socio-economic and demographic variables were tested they were poor predictors of mathematics success. Hence all the variables were insignificant, as the p-values were less than 0.05. However, the descriptive statistics on the socio-economic and demographic factors indicated that male students outperformed the female students in mathematics at high school and at the university. In terms of weekly income majority of the students earned less than R200, with 54% male and 55% for female. It is interesting to note that female students’ parents’ highest education were far better than male students, as 38% of ! female students indicated their parents highest education level was university degree compared to 30% of male students. However, the arithmetic difference is not too wide. Furthermore, majority of female students i.e. 74% compared to 61% male students pursued the building course, whereas male students were the majority in civil engineering technology compared to their female counterparts. This study informs university policy makers that where male and female students are accommodated, their age, passing high school mathematics, amount of weekly allowance, entry level to the university and type of education sponsors does not predict passing mathematics at university. However, further research is advocated as these variables are not exhaustive