Adaptive System of English-Speaking Learning Based on Artificial Intelligence

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Lili Qin, Weixuan Zhong

Abstract

Delve into the innovative realm of adaptive systems for English-speaking learning, underpinned by artificial intelligence (AI). Proficiency in spoken English is increasingly pivotal in today's interconnected world, spanning across professional, academic, and social spheres. However, conventional methods of language learning often struggle to accommodate the diverse needs and learning styles of individual learners. Enter AI-powered adaptive systems, offering a transformative approach to language education. These systems harness the capabilities of machine learning algorithms and natural language processing to deliver personalized learning experiences. Through real-time analysis of learners' performance, they provide targeted feedback and dynamically adjust learning materials to suit individual preferences and abilities, focusing on areas such as pronunciation, fluency, grammar, and vocabulary usage.


Moreover, the adaptive nature of AI-based systems revolutionizes the learning process, allowing for continuous progress monitoring and adaptation to learners' evolving needs. Unlike traditional classroom settings with standardized pacing, adaptive systems empower learners to progress at their own pace, honing in on areas that require improvement while bypassing mastered concepts. This personalized approach not only enhances learning efficiency but also fosters motivation and engagement by aligning with learners' interests and goals. By bridging the gap between individual learning needs and traditional educational frameworks, AI-powered adaptive systems represent a groundbreaking advancement in language education, promising to make English-speaking learning more accessible, effective, and enjoyable for learners worldwide.

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