BRIDGING THE GENDER GAP IN ARTIFICIAL INTELLIGENCE EDUCATION: A SYSTEMATIC REVIEW OF STEM-BASED EMPOWERMENT STRATEGIES FOR AFRICAN GIRLS

Abstract

Purpose: This study examines how STEM-based initiatives are being used to bridge the gender gap in artificial intelligence (AI) education among African girls. It aims to identify key barriers, explore existing interventions, and highlight strategies that promote inclusive participation in AI-related learning across the continent. Design/Methodology/Approach: The study adopted a systematic review design using a narrative synthesis approach. Five research objectives and corresponding research questions guided the study. Relevant literature published between 2015 and 2025 was retrieved from databases such as Scopus, Web of Science, ERIC, AJOL, and Google Scholar, alongside grey literature from international organisations. A keyword-based search strategy with Boolean operators was used to identify studies focusing on STEM education, gender inclusion, and AI in Africa. Selected studies were screened through titles, abstracts, and full-text reviews based on defined inclusion and exclusion criteria. Data were analysed thematically to identify recurring patterns and key insights. Findings: The findings reveal that African girls continue to face barriers such as cultural stereotypes, limited access to quality STEM education, inadequate digital infrastructure, and lack of mentorship. However, several effective strategies were identified, including grassroots digital empowerment programmes, mentorship and scholarship initiatives, coding and AI training camps, and continent-wide programmes such as African Girls Can Code. The study also found that partnerships between governments, NGOs, and private organisations play a critical role in expanding access and improving participation. Implication: The study suggests that increasing girls’ participation in AI education requires a combination of policy support, investment in digital infrastructure, and gender-responsive STEM curricula. There is also a need for sustained mentorship programmes, teacher training, and targeted funding to ensure that interventions are scalable and sustainable across different African contexts. Originality/Value: This study is original and contributes to existing literature by providing a consolidated and upto-date synthesis of STEM-based strategies aimed at promoting gender inclusion in AI education in Africa. It offers practical insights for policymakers, educators, and development partners seeking to design effective and contextrelevant interventions.