Mualliflar

  • Nazirova Xilola Ro‘zaliyevna

DOI:

https://doi.org/10.71337/inlibrary.uz.ustozlar.106541

Kalit so‘zlar:

Keywords:Artificial intelligence language learning EdTech ChatGPT adaptive learning digital education speech recognition.

Annotasiya

Abstract: Artificial Intelligence (AI) has revolutionized the landscape of education, particularly in the field of language learning. This paper explores the ways in which AI-driven tools—such as intelligent tutoring systems, machine translation, chatbots, and adaptive learning platforms—enhance language acquisition. It also discusses the challenges and ethical considerations of AI integration and its future potential in shaping personalized, accessible, and efficient language education globally.


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Ustozlar uchun

pedagoglar.org

73-son 2–to’plam Iyun-2025

Sahifa: 144

THE IMPACT OF ARTIFICIAL INTELLIGENCE

ON LANGUAGE LEARNING

Nazirova Xilola Ro‘zaliyevna

Oltiariq tumani 1-son politexnikumi o‘qituvchisi

Abstract:

Artificial Intelligence (AI) has revolutionized the landscape of education,

particularly in the field of language learning. This paper explores the ways in which AI-
driven tools—such as intelligent tutoring systems, machine translation, chatbots, and
adaptive learning platforms—enhance language acquisition. It also discusses the
challenges and ethical considerations of AI integration and its future potential in shaping
personalized, accessible, and efficient language education globally.

Keywords

:Artificial intelligence, language learning, EdTech, ChatGPT, adaptive

learning, digital education, speech recognition.


The advent of Artificial Intelligence (AI) in education has opened new horizons for

personalized and interactive learning. In language education, AI technologies offer novel
solutions to age-old challenges: lack of immersion, motivation, individualized feedback,
and accessibility. From real-time translation to AI conversation partners, learners today
have access to tools that accelerate both comprehension and production of language.This
article investigates how AI technologies support language learning, their current
applications, their effectiveness, and the future trajectory of AI-powered linguistics
education.

Key Applications of AI in Language Learning

1.

Intelligent Tutoring Systems (ITS)

AI-based tutoring platforms can assess student proficiency and adapt instruction

accordingly. For example, Duolingo uses machine learning to adjust difficulty levels and
repeat weak areas for learners, making it one of the most widely used language apps
globally (Loewen et al., 2020).

2.

Speech Recognition and Pronunciation Feedback

Apps like Elsa Speak and Google Speech-to-Text utilize AI to help learners practice

and improve their pronunciation through real-time, individualized corrections

3.

Chatbots and Conversational AI

AI chatbots simulate natural dialogues, helping learners practice speaking in realistic

settings. Tools like Replika or ChatGPT enable users to interact in multiple languages,
increasing fluency and confidence.


Artificial Intelligence has already made substantial contributions to language

learning by offering adaptive, accessible, and engaging tools. While challenges remain,


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Ustozlar uchun

pedagoglar.org

73-son 2–to’plam Iyun-2025

Sahifa: 145

especially in terms of equity and ethics, the future of AI in language education is bright.
As technology advances, its role in bridging linguistic barriers and fostering global
communication will only expand.

The intelligent application of AI can transform language learning into a personalized,

interactive, and more human experience than ever before.

References:

1. Loewen, S., Isbell, D. R., & Sporn, Z. (2020). The effectiveness of app-based

language instruction for developing receptive linguistic knowledge and oral
communicative ability. Foreign Language Annals, 53(2), 209–233.

2. Koehn, P. (2020). Neural Machine Translation. Cambridge University Press.
3. Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021). On the

Dangers of Stochastic Parrots: Can Language Models Be Too Big? Proceedings of the
2021 ACM Conference on Fairness, Accountability, and Transparency, 610–623.

4. Godwin-Jones, R. (2019). Artificial intelligence in language learning. Language

Learning & Technology, 23(1), 3–8.

5. Wang, Y., & Vasquez, C. (2012). The effectiveness of mobile apps for language

learning. CALICO Journal, 29(3), 443–456.




Bibliografik manbalar

Loewen, S., Isbell, D. R., & Sporn, Z. (2020). The effectiveness of app-based language instruction for developing receptive linguistic knowledge and oral communicative ability. Foreign Language Annals, 53(2), 209–233.

Koehn, P. (2020). Neural Machine Translation. Cambridge University Press.

Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021). On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 610–623.

Godwin-Jones, R. (2019). Artificial intelligence in language learning. Language Learning & Technology, 23(1), 3–8.

Wang, Y., & Vasquez, C. (2012). The effectiveness of mobile apps for language learning. CALICO Journal, 29(3), 443–456.