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| Open Access | ENHANCING PROFESSIONAL SPEECH SKILLS OF AI STUDENTS THROUGH AUTOMATED LINGUISTIC-ANALYTICAL APPROACHES
Gulkhumor Kakhkhorova Sulaymonjon kizi , Independent researcher, Department of Uzbek Language and Language Teaching, Fergana State Technical University, Fergana, 150102, UzbekistanAbstract
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.
Keywords
automated feedback, professional speech, corpus linguistics, AI students, language education
References
Qahhorova, G. (2023). Ingliz tilida tinglash mahoratini yaxshilash usullari. Journal of Science-Innovative Research in Uzbekistan, 1(9), 1249-1254.
Qahhorova, G. (2023). O‘quvchilarning tinglash malakasini oshirish uchun diktantlardan samarali foydalanish usullari. Journal of Science-Innovative Research in Uzbekistan, 1(9), 1255-1260.
Gulkhumor Kakhkhorova. (2025). Verbalizing code and model architecture and a linguistic-analytical technique for AI students. Shokh Articles Library, 1(1).
Gulkhumor Kakhkhorova. (2025). The impact of a linguistic-analytical approach on AI students’ professional speech skills. Shokh Articles Library, 1(1).
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