ENHANCING PROFESSIONAL SPEECH SKILLS OF AI STUDENTS THROUGH AUTOMATED LINGUISTIC-ANALYTICAL APPROACHES

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Authors: Gulkhumor Kakhkhorova Sulaymonjon qizi
Cited by: 0

Abstract

This paper presents a comprehensive experimental study involving 60 artificial intelligence students from Fergana State Technical University, aiming to evaluate the effectiveness of automated linguistic-analytical platforms in cultivating students’ professional speech skills. The research focuses on integrating AI-powered corpus linguistics tools into the academic curriculum to provide real-time, automated feedback on students’ professional writing tasks. Throughout the semester, students in the experimental group submitted various written assignments, which were analyzed by advanced software capable of performing frequency, collocation, and concordance analyses. These analyses enabled the platform to supply highly specific, individualized feedback, targeting each student’s use of professional terminology, syntactic structure, and error patterns. In contrast, the control group received traditional teacher commentary without access to automated analysis.

Fields of Study & Subjects

Second Language Acquisition and Learning Artificial Intelligence in Education Natural Language Processing Techniques

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
30 January 2026
Document type
Dataset