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A Quantitative Study of Artificial Intelligence in Foreign Language Talent Cultivation

Year: 2025

Type: article

Abstract: The integration of artificial intelligence (AI) in foreign language education is reshaping traditional pedagogical models, offering new opportunities for personalized learning, adaptive assessments, and data-driven instructional strategies. This paper explores the impact of AI on foreign language talent cultivation through quantitative analysis of AI-assisted teaching methods and their effects on learner outcomes. By employing a large-scale survey and experimental design, the study evaluates how AI tools—such as intelligent tutoring systems, machine learning-based assessment models, and natural language processing tools—affect students’ language acquisition, engagement, and motivation. Results demonstrate that AI-enhanced learning models significantly improve vocabulary retention, speaking fluency, and overall learner satisfaction compared to traditional methods. This paper proposes a framework for AI-driven foreign language talent cultivation, emphasizing teacher training, curriculum redesign, and AI-supported learning environments.

Source: English Language Teaching and Linguistics Studies

DOI: 10.22158/eltls.v7n2p24

Author: Xuanling Lü

Language: English

Topic: Artificial Intelligence in Education

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: diamond

OpenAlex ID: W4408535343

FWCI:

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