THE IMPACT OF CORPUS-BASED LINGUISTIC ANALYSIS ON PROFESSIONAL LANGUAGE COMPETENCE

This study examines the effectiveness of corpus-based linguistic analysis in enhancing the professional language competence of 60 undergraduate artificial intelligence students at Fergana State Technical University. Over the course of a semester, students in the experimental group engaged in hands-on analysis of authentic AI-related texts using specialized corpus linguistics tools, namely AntConc and Sketch Engine. These tools enabled students to explore language data through frequency lists, lemmatization, collocation identification, and topic modeling, providing deep insights into the usage of domain-specific vocabulary and phraseology. In contrast, the control group followed the traditional curriculum, which focused on theoretical instruction and instructor-led exercises without exposure to corpus technologies. Pre- and post-intervention assessments measured students’ proficiency in using technical terminology, constructing professional sentences, and recognizing collocations relevant to the AI field.本研究旨在探究基于语料库的语言学分析对费尔干纳国立技术大学（Fergana State Technical University）60名人工智能专业本科生专业语言能力的提升效果。在一学期的教学周期内，实验组学生借助专业语料库语言学工具AntConc与Sketch Engine开展真实人工智能相关文本的实操分析。此类工具可支持学生通过频率列表、词形还原、搭配识别以及主题建模等方式探索语言数据，使其深入洞悉领域专属词汇与惯用表达的使用规律。与之相对，对照组沿用传统课程体系，仅聚焦理论授课与教师主导的练习，未接触语料库相关技术。本研究通过干预前与干预后的测评，衡量学生在人工智能领域技术术语使用、专业语句构建以及相关搭配识别三方面的语言能力水平。