AI-Powered E-Learning Platforms for STEM Education: Evaluating Effectiveness in Low-Bandwidth and Remote Learning Environments
Onuh Matthew Ijiga, Ginikachi Prisca Ifenatuora, Mariam Olateju
Abstract
The integration of Artificial Intelligence (AI) into e-learning platforms has revolutionized the educational landscape, offering personalized learning experiences and enhancing access to education. This paper explores the effectiveness of AI-powered e-learning platforms in Science, Technology, Engineering, and Mathematics (STEM) education, with a particular focus on their application in low-bandwidth and remote learning environments. These platforms have the potential to overcome challenges such as limited internet access and resource scarcity, which are prevalent in many parts of the world. This review critically assesses the existing literature on AI-driven STEM education platforms, evaluates their impact on student engagement, learning outcomes, and accessibility, and examines the strategies employed to optimize these platforms for low-bandwidth settings. Additionally, it highlights key challenges such as data privacy, technological infrastructure, and scalability in underserved regions. The paper concludes by proposing future directions for research and development to further enhance the effectiveness of AI-powered e-learning platforms for STEM education in resource-constrained environments.