Proceedings of the 7th International Conference on Modern Approaches in Humanities and Social sciences
The Role of Machine Learning in Education Decolonization: A Mini Literature Review
In recent times, the topic of decolonizing education in Africa has gained significant relevance, especially as academic sectors strive to foster fairness and diversity. The utilization of machine learning may have a substantial impact on this procedure as it can detect and correct biases within evaluations and educational materials, while also tailoring the learning journey to suit each student’s individual needs. This compact analysis examines the present status of studies regarding how machine learning can contribute to the process of decolonizing education in Africa. By conducting a comprehensive analysis of pertinent scholarly materials, this assessment brings attention to the advantageous aspects of utilizing machine learning to advance fairness and diversity in the realm of education. This analysis concentrates on two significant aspects – implementing machine learning procedures to tailor educational programs to meet the diverse requirements of individual students, particularly from underrepresented communities, and applying machine learning techniques to uncover and rectify biases in course content and evaluation methods. This paper reveals that utilizing machine learning could have a meaningful impact on decolonizing education. However, there remains a need for additional research to examine how machine learning can be effectively incorporated into educational structures to foster equal opportunities, inclusivity, and social fairness.
keywords: Africa, Machine learning, Education decolonization, Bias, Personalized learning, Inclusivity, Equity, Social justice