A model to integrate Generative Artificial Intelligence to improve student academic performance in South African universities

Abstract

This paper explores the use of GenAI on university students in pursuit of academic excellence, with reference to South Africa. This study will embrace some of these salient issues: issues of high dropout rates occasioned by resource scarcity and meeting diverse learning needs by proposing a model that assists an individual learning experience using GenAI. This would be useful in highlighting recommendations toward effective adoption with reduced inequity in education and improvement of student achievement based on current literature and empirical investigations. Moreover, the paradigm proposed, named GAIA-SAU, would strongly focus on the development of personalized learning plans, continuous feedback mechanisms, and involvement of stakeholder engagement in delivering adaptive learning environments. This will lighten the burden for the country's path toward achieving high-quality and innovative learning, with further alignment to the goals of the National Education Strategy. Finally, the findings from this study will provide insight into educators, other stakeholders, and policymakers on ways in which best to capitalize on the use of GenAI in improving performance and equity in pursuing all students toward university education. This essay looks at how structurally advanced AI can solve these issues that stand in the way of realizing students' potential fully.