Artificial Intelligence and Language: Bridging Arabic and English with Technology

Abstract

The article examines the transformative impact of Artificial Intelligence (AI) on language learning, focusing on Arabic and English. It explores how AI technologies, including language learning platforms, translation and interpretation tools, and natural language processing (NLP), reshape traditional language education methods. AI-driven solutions offer personalized, adaptive, and dynamic learning experiences, moving beyond conventional approaches. By integrating AlAfnan’s Taxonomy of Educational Objectives, which emphasizes the cognitive, affective, and psychomotor domains, AI provides a more comprehensive framework for language learning and assessment. The article discusses how AI enhances language assessments by offering personalized feedback and adaptive testing that caters to individual learner progress in real-time. In the classroom, AI facilitates not only knowledge acquisition (cognitive domain) but also emotional engagement and cultural sensitivity (affective domain), as well as practical communication skills such as speaking and writing (psychomotor domain). Integrating AlAfnan’s Taxonomy ensures that AI-driven education addresses all facets of language mastery, from technical proficiency to emotional intelligence and cultural awareness. The ethical and cultural considerations of using AI in language learning are also analyzed, emphasizing the importance of inclusivity, respect, and responsible AI development. As AI continues to advance, it holds the potential to bridge linguistic and cultural gaps, making language learning more accessible and practical. AI, when aligned with AlAfnan’s Taxonomy, not only enhances the language learning process for Arabic and English learners but also promotes cross-cultural communication and global understanding, fostering more profound and meaningful language acquisition.