Leveraging AI in Language Acquisition: A Pedagogical Framework for Integrating Artificial Intelligence in Language Learning Platforms
Abstract
Background. Artificial Intelligence (AI) has significantly influenced various fields, and its application in language acquisition has the potential to revolutionize language learning platforms. AI-powered tools offer personalized, adaptive learning experiences that can cater to individual learner needs, providing immediate feedback, language modeling, and data-driven insights. However, the integration of AI into pedagogical frameworks for language learning remains underexplored, particularly in designing systematic approaches that ensure effective learning outcomes.
Purpose. This study aims to develop a pedagogical framework for integrating AI in language learning platforms, focusing on how AI technologies can be leveraged to enhance language acquisition. The framework will address key elements such as personalized learning, real-time feedback, and adaptive learning pathways.
Method. The study employs a qualitative research approach, reviewing current literature on AI in education, particularly language learning platforms. Case studies and existing AI-based language tools were analyzed to identify best practices and gaps. Additionally, a conceptual framework was developed based on theoretical models of language acquisition and AI pedagogical approaches.
Results. The proposed framework emphasizes personalized, adaptive learning pathways powered by AI, where learners engage in real-time practice, feedback, and self-regulation. The integration of AI enhances motivation, learner autonomy, and language retention.
Conclusion. AI integration in language learning platforms can significantly enhance language acquisition by providing personalized, adaptive learning experiences. The framework developed in this study offers practical guidelines for educators and developers to effectively incorporate AI in language learning.
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Authors
Copyright (c) 2026 Feerlie Moonthana Indhra, Yusuf Haji, Robert Grech
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