Modelling achievment in mathematics: The predictive role of affective variables among students

Abstract

The purpose of this study was to model a pathway using affective variables to predict academic achievement in mathematics among students. Causal-comparative research design with a total of 739 students were used for the study. Multivariate statistical techniques-multiple regression and path analysis procedures were used for data analysis. The result showed that all the variables combined had a strong effect in predicting achievement in mathematics. The result indicated that the most meaningful causal model had thirteen significant pathways and that 68.22% of the total effect of the affective variables in predicting achievement in mathematics were direct while 31.69% were indirect. It was also revealed that all the six affective variables directly impacted students 'achievement in mathematics. Learners' sociability and academic optimism were found to contribute most significantly to the prediction of students' achievement in mathematics. The implications of the study were discussed, and policy suggestions made.