A multilevel analysis of learner and school contextual factors associated with educational quality

Abstract

The South African schools act, (number 5, 1996), asserts that all learners have a right to access both basic and quality education without discrimination of any sort. Since the implementation of the Millennium Development Goals there has been a drive by the Department of Education to ensure that all learners have access to basic education by 2015. However what remains a challenge after almost 20 years of democracy is the poor quality of education and this is clear from the results of international assessment studies. Results from studies like the Trends in International Mathematics and Science Study and Southern and East Africa Consortium for Monitoring Educational Quality, show that South African children perform well below international averages. In this study learner Mathematics achievement scores taken from the Trends in International Mathematics and Science Study 2011 cycle will serve as a proxy for educational quality. Using multilevel analysis the current study aims to use a 2-level Hierarchical Linear Model to firstly; determine the learner and family background factors associated with education quality. Secondly; factors at the school level will be identified and proven to be associated with education quality. Variables selected for the study was based on Creamer’s theory of school effectiveness which looked at school, classroom level inputs as well as learner background variables to explain student level achievement. The results show that at the learner’s level the most significant factors were the age of the leaner, in the sense that grade age appropriate learners obtained higher scores than overage learners. Learner’s perception of mathematics is extremely important and has a positive effect on mathematics performance. In the current study mathematics perception refers to learners valuing and liking mathematics as well learner confidence in learning mathematics. Learners who said they were bullied as school generally scored lower than learners who were not bullied. At the school level the most significant factors were teacher working conditions, teachers’ specialisation in mathematics, school socio-economic status, and general infrastructure. Interesting to note at the school level is when socioeconomic status was included in the model as a single variable the score difference between low socio-economic status and high socio-economic status schools was almost 46 points. However when the factors mentioned above were added to the model the difference in scores dropped by almost half.