Acquisition of Language, Linguistics Via Computer (AI) in Higher Education Institutions and Its Effects

The ever-evolving realm of higher education offers revolutionary prospects for educators and learners through the merging of language studies, linguistics, and artificial intelligence (AI). This paper examines the interdisciplinary integration of these fields, highlighting their combined capacity to improve teaching methods, research innovation, and educational results in higher education institutions. The study initiates by analyzing conventional methods of language and linguistics instruction, pinpointing enduring pedagogical issues like student engagement, assessment precision, and linguistic diversity. It subsequently examines the transformative influence of AI technologies—such as natural language processing (NLP), machine learning, speech recognition, and automated evaluation—in tackling these issues. The paper illustrates how AI-powered technologies may customize learning, support multilingual education, and enhance linguistic research through a comprehensive examination of existing literature, theoretical frameworks, and case studies.

Authors

Institutions

Publication Details

Journal
Forum for Linguistic Studies
Published
2025-08-04
DOI
https://doi.org/10.30564/fls.v7i8.10687
Primary Topic
Foreign Language Teaching Methods
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Acquisition of Language, Linguistics Via Computer (AI) in Higher Education Institutions and Its Effects

Zuleykha Murad Baghirzadeh, Elchin Mirzayev, Ruhangiz Mammad Aliyeva, L.I. Aliyeva et al.
Forum for Linguistic Studies
Foreign Language Teaching Methods
article

Acquisition of Language, Linguistics Via Computer (AI) in Higher Education Institutions and Its Effects

Zuleykha Murad Baghirzadeh, Elchin Mirzayev, Ruhangiz Mammad Aliyeva, L.I. Aliyeva, Minavvar Mammadova, Banovsha Mammadova, Venkata Siva Kumari Narayanam, Saadat Jahangir Aliyeva, Tamilla Ramin Ahmadzadeh, Lala Zahir Allahverdiyeva, Gunel Vilayat Bayramova Mehdiyeva
article en

Abstract

The ever-evolving realm of higher education offers revolutionary prospects for educators and learners through the merging of language studies, linguistics, and artificial intelligence (AI). This paper examines the interdisciplinary integration of these fields, highlighting their combined capacity to improve teaching methods, research innovation, and educational results in higher education institutions. The study initiates by analyzing conventional methods of language and linguistics instruction, pinpointing enduring pedagogical issues like student engagement, assessment precision, and linguistic diversity. It subsequently examines the transformative influence of AI technologies—such as natural language processing (NLP), machine learning, speech recognition, and automated evaluation—in tackling these issues. The paper illustrates how AI-powered technologies may customize learning, support multilingual education, and enhance linguistic research through a comprehensive examination of existing literature, theoretical frameworks, and case studies.

Forum for Linguistic StudiesVol. 7(8)
Azerbaijan State University of Economics (AZ), Institute of Geography Named after Academician Hasan Aliyev (AZ), Azerbaijan Scientific-Research & Design-Prospecting Power Engineering Institute (AZ), Nakhchivan University (AZ), Azerbaijan State Pedagogical University (AZ), Baku Engineering University (AZ), Nakhchivan State University (AZ), Azerbaijan University (AZ), Koneru Lakshmaiah Education Foundation (IN)
Openalex Percentile: Top 78%
Foreign Language Teaching Methods
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.