Design and Implementation of AI-Driven Personalized Learning Tools for Tanzanian Secondary Schools

Authors

  • Juliana Kamaghe The Open University of Tanzania, Department of Mathematics and ICT, Tanzania

DOI:

https://doi.org/10.31695/IJASRE.2025.1.2

Keywords:

AI-driven, Adaptibility, Artificial intelligence, Secondary schools

Abstract

This study investigates the effectiveness of AI-powered personalised learning tools in Tanzanian secondary schools. The research explores the potential of these tools to address the unique challenges these schools face, including large class sizes, limited resources, and significant language diversity. Through a comparative analysis of various AI tools, the study examines their adaptability to Tanzania's educational context, considering language diversity, cultural relevance, and infrastructure constraints. The research employs qualitative design, incorporating comparative case study elements to evaluate the functionalities and adaptability of selected AI-driven personalised learning tools. Data collection involves a systematic review of available tools, semi-structured interviews with educators and AI experts, and a survey to gather information specific to the Tanzanian educational context.    Key findings indicate that AI-powered personalised learning tools offer significant potential for enhancing education in Tanzanian secondary schools. These tools can adapt to individual student needs, providing personalized learning experiences that traditional methods cannot achieve.    However, the study also identifies challenges, including limited language support, the need for culturally relevant content, and infrastructural constraints. Addressing these challenges is crucial for maximizing the effectiveness of these tools in the Tanzanian context.    The study concludes that AI tools can significantly contribute to personalized learning in Tanzania, but their successful implementation requires careful consideration of local needs and challenges.   Recommendations include prioritizing AI tools with high adaptability, robust multilingual support, and mobile-first designs to cater to Tanzania's diverse linguistic landscape and technological infrastructure. Future research should focus on empirical testing within Tanzanian classrooms and refining AI tools to align better with local educational needs.

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How to Cite

Juliana Kamaghe. (2025). Design and Implementation of AI-Driven Personalized Learning Tools for Tanzanian Secondary Schools. International Journal of Advances in Scientific Research and Engineering (IJASRE), ISSN:2454-8006, DOI: 10.31695/IJASRE, 11(1), 10–22. https://doi.org/10.31695/IJASRE.2025.1.2