There is a high level of rural learners and girls being excluded from quality education leading to low STEM uptake and inequality in the labour market in South Africa. High and persistent inequality in South Africa is hampering inclusive growth and the hope of lifting many vulnerable rural populations, especially women out of poverty. Labour market inequality, fuelled by the skills gap contributes to more than 60% of the high inequality in South Africa. Tackling educational exclusion will go a long way in redressing the main underlying causes of inequality and unemployment. Currently, the gap in access to, and outcome of education along gender lines, rural/urban and the well-off/previously disadvantaged is significant. In this context, inequality becomes intergenerational, and transmitted mainly through educational gap channels.

The purpose of this project is to leverage on the e-learning concept being developed by the AIIG’s technology partner – Social Coding, to formalise and test its efficacy in improving educational access and performance for rural girls and learners in general in South Africa. The project will use secondary data to assess the role of digital technologies in equalising education in South Africa, and Science, Technology, Engineering and Mathematics (STEM) uptake. It will use a Discrete Choice Experiments (DCE) to elicit rural learners’ preference for technology in learning in order to fine-tune the e-learning Artificial Intelligence (AI) concept and assess its efficacy in a Randomised Control Trial (RCT) framework in a rural school in one of the poorest provinces in South Africa. 

This work will help to understand the usefulness of AI in enabling learners, particularly girls, to access extra learning, and the benefits this will mean in terms of performance of rural learners relative to business as usual. We expect that the intervention will improve learner performance and enhance educational pass rates for vulnerable learners especially girls. The research will provide information and data to train an AI model for the development of a robotic tutorship programme which can be scaled to other schools across the county and beyond. The findings and off-shoots of the project will be proposed to the departments of education, women, youths and persons with disability with the hope of integrating it into their digital education strategies.