Innovating Remote Learning through Artificial Intelligence in Developing Economies: Benefits, Barriers, and Prospects - Ogwuegbu, David Azunna; Ajobiewe, Damilola Nnamaka (Faculty of Natural and Applied Sciences Journal of Computing and Applications, 2025)
The paper examines the integration of artificial intelligence (AI) with remote learning as a means to overcome the digital gap in underdeveloped countries. Although remote learning is an essential mechanism for addressing issues such as inadequate infrastructure and instructor deficits, several current solutions remain unattainable for students without dependable internet connection and equipment. AI-driven technologies such as intelligent tutoring systems, adaptive learning platforms, and chatbots were emphasized as viable alternatives. Nonetheless, this paper also identifies significant obstacles to adoption, such as erratic internet connectivity, unstable electricity supply, and inadequate digital literacy. To address these difficulties, this paper advocates for a comprehensive strategy that encompasses the creation of affordable, offline AI solutions, the cultivation of public-private collaborations, and the enactment of supporting governmental laws. This paper asserts that a unified, scalable approach is crucial for effectively using AI to improve educational fairness in emerging nations.