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ENHANCING LANGUAGE LEARNING IN NIGERIA: THE POTENTIALS OF ARTIFICIAL INTELLIGENCE IN MODERN PEDAGOGY

This paper investigates the transformative potential of Artificial Intelligence (AI) in enhancing language learning within the Nigerian educational context, characterized by its complex linguistic landscape and diverse learner demographics. As traditional pedagogical approaches often fail to meet the individualized needs of students, AI technologies - encompassing personalised learning platforms, intelligent tutoring systems, chatbots, and virtual assistants -emerge as effective solutions to enhance engagement, accessibility, and instructional efficacy. This article hinges on three theories: Constructivism, Connectivism, and the Technological Pedagogical Content Knowledge (TPACK) framework. Employing a qualitative methodology grounded in a comprehensive review of secondary literature, this study identifies five major themes: personalised and adaptive learning, accessibility and scalability, real-time feedback and autonomous learning, interactive and contextualised learning environments, and the necessity of ethical frameworks and educator preparedness. While AI offers significant benefits such as real-time feedback and the capacity for personalised instruction, challenges concerning digital divide, data privacy, and algorithmic bias necessitate careful scrutiny and responsible implementation. This study advocates for a collaborative approach involving educators, policymakers, and technology developers to optimise AI applications in language education. Through targeted investments, training, and ethical considerations, Nigeria can harness AI's capabilities to create an inclusive and dynamic language learning environment, thus providing linguistic proficiency and contributing to the country's socio-economic advancement.

KEYWORDS: Artificial Intelligence (AI), language learning, traditional pedagogy, Learning Management System (LMS), modern pedagogy, Nigeria.

Moses Ofome Asak And Eriabome Ebi Asak
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ISSN(Hardcopy)

2630 - 7200

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2659 - 1057

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5.693

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