Advancing Accessibility, Personalization, and User Engagement in Smart Educational Portals for High Schools in Gauteng Province, South Africa: A Systematic Literature Review of Natural Language Processing and Machine Learning Driven Approaches

The evolution of smart educational platforms has been significantly driven by the global development of ML (Machine Learning), particularly through the application of NLP (Natural Language Processing) to personalize student learning experiences. However, high schools in Gauteng Province face significant challenges in adopting smart educational portals. This is due to inadequate accessibility to resources, insufficient personalization mechanisms, and low student engagement frameworks caused by the failure to adapt to proven teaching methods. Despite the successful adoption of NLP and ML in global case studies and implementations, local gaps persist. Specifically, pretrained LLMs (Large Language Models) such as BERT (Bidirectional Encoder Representations from Transformers) require fine-tuning for African languages, yet little testing of these tools in Gauteng’s public high schools has been done. This review uses a structured literature review methodology, which examines peer-reviewed studies, case reports, and technical documents published between 2014–2026. Findings indicate that multilingual NLP resources for South African languages remain severely underdeveloped. Furthermore, it demonstrates that current smart-learning portals lack inclusive design adjustments for multilingual and low-resource contexts. Based on these findings, the paper recommends strategies for enhancing accessibility, personalization, and engagement. This includes the development of multilingual NLP resources, optimization of ML architectures for constrained infrastructure, and context-aware pedagogical adaptations. The review follows a two-layer design, consisting of (i) a global systematic synthesis of NLP and ML applications in education, and (ii) a contextual interpretation of these findings for Gauteng high schools using regional policy documents, infrastructure reports, and educational statistics. The conclusions pertain to implications and recommendations for Gauteng high schools, rather than evaluation of an existing local portal. This paper highlights the potential of NLP and ML to transform education in Gauteng but highlights the urgency of localized research and ML implementation.