Talabalarning og‘zaki nutq qobiliyatlarini rivojlantirishda sun’iy intellektning ahamiyati

Annotasiya

Ushbu maqola sun’iy intellekt (SI)ning nutq ko‘nikmalarini rivojlantirishdagi roli, xususan, til o‘rganishdagi ahamiyatini tahlil qiladi. SI texnologiyalari, xususan, Avtomatlashtirilgan Nutqni Tanish(ASR), SI repetitorlari va Virtual Reallik (VR) va Kengaytirilgan Reallik (AR) ilovalari, individual fikr-mulohazalar, real vaqt rejimida mashq qilish va qulay muhitni taqdim etadi. Ushbu vositalar talaffuzni, ravonlik suhbatlashish ko‘nikmalarini yaxshilashda an’anaviy o‘qitish usullariga nisbatan ustunliklarni taqdim etadi. Biroq, SI texnologiyalarining ta’lim jarayoniga samarali integratsiyasi bir necha muammolarni hal etish zaruriyatini keltirib chiqaradi. Ushbu maqolada nutq ko‘nikmalarini rivojlantirishda SI texnologiyalarining foydalari va ularning o‘quv natijalariga ta’siri  masalalari ko‘rib chiqiladi.

Manba turi: Jurnallar
Yildan beri qamrab olingan yillar 2022
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doi
 
Chiqarish:
288-297
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Кўчирилди

Кўчирилганлиги хақида маълумот йук.
Ulashish
Ruziyeva, M. (2025). Talabalarning og‘zaki nutq qobiliyatlarini rivojlantirishda sun’iy intellektning ahamiyati. Xorijiy Lingvistika Va Lingvodidaktika, 3(1), 288–297. Retrieved from https://inlibrary.uz/index.php/foreign-linguistics/article/view/76144
Crossref
Сrossref
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Annotasiya

Ushbu maqola sun’iy intellekt (SI)ning nutq ko‘nikmalarini rivojlantirishdagi roli, xususan, til o‘rganishdagi ahamiyatini tahlil qiladi. SI texnologiyalari, xususan, Avtomatlashtirilgan Nutqni Tanish(ASR), SI repetitorlari va Virtual Reallik (VR) va Kengaytirilgan Reallik (AR) ilovalari, individual fikr-mulohazalar, real vaqt rejimida mashq qilish va qulay muhitni taqdim etadi. Ushbu vositalar talaffuzni, ravonlik suhbatlashish ko‘nikmalarini yaxshilashda an’anaviy o‘qitish usullariga nisbatan ustunliklarni taqdim etadi. Biroq, SI texnologiyalarining ta’lim jarayoniga samarali integratsiyasi bir necha muammolarni hal etish zaruriyatini keltirib chiqaradi. Ushbu maqolada nutq ko‘nikmalarini rivojlantirishda SI texnologiyalarining foydalari va ularning o‘quv natijalariga ta’siri  masalalari ko‘rib chiqiladi.


background image

Xorijiy lingvistika va lingvodidaktika –

Зарубежная лингвистика и
лингводидактика – Foreign

Linguistics and Linguodidactics

Journal home page:

https://inscience.uz/index.php/foreign-linguistics

The relevance of artificial intelligence in bolstering the
development of students’ speaking skills

Maftuna RUZIEVA

1

Navoi State University

ARTICLE INFO

ABSTRACT

Article history:

Received November 2024

Received in revised form
10 December 2024
Accepted 25 December 2024

Available online
25 January 2025

This article explores the role of Artificial Intelligence (AI) in

enhancing students’ speaking skills, particularly in language
learning. AI technologies such as Automated Speech Recognition

(ASR), interactive AI tutors, and immersive Virtual Reality (VR)

and Augmented Reality (AR) applications offer personalized

feedback, real-time practice, and engaging learning experiences.

These tools are shown to improve pronunciation, fluency, and
conversational abilities, providing distinct advantages over

traditional pedagogical methods. However, challenges like

privacy concerns, accessibility, and potential over-reliance on

technology must be addressed for effective and ethical
integration. The article includes case studies, such as AI-powered

speech recognition technology and AI-assisted English oral

teaching, demonstrating the positive impact of AI on student

speaking performance. Additionally, ethical considerations, such
as data security and equity, are discussed.

2181-3701/© 2024 in Science LLC.
DOI:

https://doi.org/10.47689/2181-3701-vol3-iss1

/S

-pp288-297

This is an open-access article under the Attribution 4.0 International
(CC BY 4.0) license (

https://creativecommons.org/licenses/by/4.0/deed.ru

)

Keywords:

Artificial intelligence (AI),
automated speech
recognition (ASR),

natural language processing

(NLP),

virtual reality (VR),
augmented reality (AR).

Talabalarning og‘zaki nutq qobiliyatlarini rivojlantirishda
sun’iy intellektning ahamiyati

ANNOTATSIYA

Kalit so‘zlar:

Sun’iy intellekt (SI),

avtomatik nutqni
tanish(ASR),

tabiiy tilni qayta ishlash
(NLP),

virtual reallik (VR),
kengaytirilgan reallik (AR).

Ushbu maqola sun’iy intellekt (SI)ning nutq ko‘nikmalarini

rivojlantirishdagi roli, xususan, til o‘rganishdagi ahamiyatini tahlil
qiladi. SI texnologiyalari, xususan, Avtomatlashtirilgan Nutqni

Tanish(ASR), SI repetitorlari va Virtual Reallik (VR) va

Kengaytirilgan Reallik (AR) ilovalari, individual fikr-mulohazalar,

real vaqt rejimida mashq qilish va qulay muhitni taqdim etadi.

Ushbu vositalar talaffuzni, ravonlik suhbatlashish ko‘nikmalarini

1

Doctorate Student, Navoi State University.


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Xorijiy lingvistika va lingvodidaktika – Зарубежная лингвистика

и лингводидактика – Foreign Linguistics and Linguodidactics

Special Issue – 1 (2025) / ISSN 2181-3701

289

yaxshilashda an’anaviy o‘qitish usullariga nisbatan ustunliklarni

taqdim etadi. Biroq, SI texnologiyalarining ta’lim jarayoniga

samarali integratsiyasi bir necha muammolarni hal etish
zaruriyatini keltirib chiqaradi. Ushbu maqolada nutq

ko‘nikmalarini rivojlantirishda SI texnologiyalarining foydalari va

ularning o‘quv natijalariga ta’siri masalalari ko‘rib chiqiladi.

Актуальность

использования

искусственного

интеллекта в развитии навыков устной речи у студентов

АННОТАЦИЯ

Ключевые слова:

искусственный интеллект
(ИИ),

автоматическое

распознавание речи (ASR),
обработка естественного
языка (NLP),

виртуальная реальность
(VR),

дополненная реальность

(AR).

В

статье

рассматривается

роль

искусственного

интеллекта (ИИ) в развитии навыков устной речи у

студентов, особенно в изучении языков. Технологии ИИ,

такие как автоматическое распознавание речи (ASR),

интерактивные ИИ-репетиторы и погружающие приложения
виртуальной (VR) и дополненной реальности (AR),

предоставляют персонализированную обратную связь,

практику

в

реальном

времени

и

увлекательные

образовательные среды. Эти инструменты показали
эффективность в улучшении произношения, беглости речи и

разговорных навыков, предлагая явные преимущества по

сравнению с традиционными педагогическими методами.

Однако для эффективной и этичной интеграции необходимо
решить такие проблемы, как конфиденциальность данных,

доступность и потенциальная зависимость от технологий.

В статье приведены примеры, такие как технологии

распознавания речи, основанные на ИИ, и ИИ-платформы

для обучения английскому языку, демонстрирующие
положительное влияние ИИ на результаты студентов. Также

рассматриваются этические аспекты, такие как безопасность

данных и равенство.


INTRODUCTION

Artificial intelligence (AI) is a key technology in the age of digital transformation

that has the potential to completely disrupt a wide range of industries, including
education. AI has become a major force in redefining educational practices as institutions
and educators try to keep up with the quick speed of technological progress, especially
when it comes to communication abilities. Speaking is one of the most important of these;
it includes both the capacity to effectively engage and persuade people as well as the
ability to express ideas clearly and cohesively. Traditional pedagogical approaches
cannot often deliver sufficient individualized speaking instruction, largely due to the
constraints posed by large class sizes and limited instructor availability. This article
discusses the use of artificial intelligence as a strategic tool in academic contexts to help
students strengthen their speaking skills. By using AI-powered technologies, educational
institutions may break down traditional barriers, providing personalized learning
experiences and promoting an interactive, engaging atmosphere. This integration is not


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without hurdles, but the potential benefits indicate a significant impact on educational
efficacy. The scope of this discussion will encompass a variety of AI technologies
currently employed or in developmental stages aimed at enhancing speaking skills.
Automated speech recognition (ASR), natural language processing (NLP), and immersive
technologies like virtual reality (VR) and augmented reality (AR), are examples of AI
technology that offers unique benefits such as real-time feedback, pronunciation
correction, and simulated public speaking scenarios. Through a comprehensive review of
these technologies, the article aims to highlight how AI can transform speaking exercises
from monotonous and generalized to dynamic and personalized learning experiences.
Furthermore, the debate will include real-world applications and case studies in which AI
tools have already demonstrated considerable gains in student results. This investigation
will not only show practical applications of AI in education, but it will also address
potential limitations and ethical considerations, such as privacy concerns and the digital
divide, which may have an impact on the accessibility and effectiveness of AI technologies
in educational settings. This article provides a detailed view of both AI's strengths and
obstacles in improving speaking skills, offering a path to effectively and ethically
integrate AI tools into the educational curriculum.

INTRODUCTION TO AI IN EDUCATIONAL SETTINGS

As educational institutions seek to enhance learning outcomes and adapt to the

evolving needs of students, AI technologies are becoming integral tools in the academic
landscape. AI in education encompasses a broad range of applications, from personalized
learning environments to automated grading systems, all aimed at improving the
efficiency and effectiveness of the teaching and learning processes.

AI technologies in education are diverse and multifaceted, each addressing

different aspects of the learning experience. Here are some notable examples:

Language Learning Apps:

1.

Duolingo

: Utilizes AI to provide personalized language lessons based on the

user’s proficiency and progress, adapting the difficulty of exercises accordingly. The study
of Loewen, S., Isbell, D. R., & Sporn, Z. evaluates the effectiveness of Duolingo as a language
learning tool and discusses its use of AI to personalize learning experiences [15].

2.

Babbel

: Employs speech recognition to help users practice pronunciation and

improve their speaking skills. In the article

"The Babbel Efficacy Study"

the authors

evaluate the effectiveness of Babbel as a language learning tool and discuss its
methodologies, including the use of AI to personalize learning experiences [23].

Virtual Tutors and Teaching Assistants:

1.

Socratic by Google

: It is an AI-powered app designed to help students with

their homework. It provides detailed explanations and resources across a variety of
subjects, making it an invaluable tool for learners seeking assistance outside the
classroom. Students can take pictures of their homework questions, and Socratic uses AI
to analyze and provide step-by-step solutions. The app covers multiple subjects,
including math, science, literature, and social studies, offering resources such as videos,
explanations, and practice problems. Also, Socratic's interface is user-friendly, making it
accessible for students of different age groups [16].

2.

Jill Watson:

It is an AI teaching assistant developed by Georgia Tech, designed

to support students by answering routine questions. This AI assistant helps to manage
large classes and allows human instructors to focus on more complex educational tasks.


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Jill Watson answers frequently asked questions about course logistics, deadlines, and
assignments, which typically take up a lot of instructors’ time. The AI participates in
online course discussions, providing students with guidance and feedback. Furthermore,
Jill Watson can handle queries from a large number of students simultaneously, making it
ideal for massive open online courses (MOOCs) and large university classes [6].

Automated Grading Systems:

1.

Gradescope

: It is an AI-driven platform that assists educators in grading

assignments quickly and consistently. It provides detailed feedback and analytics on
student performance, making the grading process more efficient and insightful.
Gradescope uses machine learning algorithms to group similar answers and apply
consistent grading across large sets of assignments. This reduces the time educators
spend on grading and ensures uniformity. The platform also allows instructors to create
detailed rubrics and provide specific feedback on student work, which helps students
understand their mistakes and learn from them. One of the greatest benefits of it is that
the analytics provided by Gradescope help educators identify common areas of difficulty,
allowing them to address these issues in their teaching [22]. This paper discusses the role
of automated grading systems like Gradescope in modern education.

2.

Turnitin

: Turnitin is widely known for its plagiarism detection capabilities, but

it also uses AI to provide comprehensive feedback on student writing. It evaluates
grammar, style, and originality, offering detailed insights that help students improve
their writing skills. It scans student papers against a vast database of academic works,
websites, and other sources to detect potential instances of plagiarism. The platform uses
natural language processing (NLP) to analyze writing quality, offering suggestions on
grammar, style, and overall structure. This helps students refine their writing. Turnitin
generates detailed originality reports that highlight similarities to other sources and
provide a basis for educators to discuss academic integrity with their students [8].

The integration of AI into educational settings represents a significant

advancement in how education is delivered and experienced. By providing personalized
learning experiences, immediate feedback, and scalable educational practices, AI is
helping to address some of the longstanding challenges in education. As these
technologies continue to evolve, they hold the promise of creating more efficient,
effective, and inclusive learning environments for all students. Furthermore René
F. Kizilcec

in his article "To Advance AI Use in Education, Focus on Understanding

Educators" discusses the importance of considering educators' perspectives and needs
when implementing AI in educational settings. It emphasizes that for AI to be effectively
integrated into education, it is crucial to understand how educators interact with these
technologies, what challenges they face, and how AI can support their teaching practices.
The focus is on ensuring that AI tools are designed with educators in mind, promoting
better adoption and more impactful outcomes in the classroom.

AI Applications Specifically for Enhancing Speaking Skills

AI technologies are significantly advancing the way we enhance and practice

speaking skills. Among these technologies, Automated Speech Recognition (ASR)
systems, interactive AI tutors and chatbots, and Virtual Reality (VR) and Augmented
Reality (AR) applications stand out for their effectiveness in improving accent,
pronunciation, and fluency and providing immersive learning experiences.


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Automated Speech Recognition (ASR) Systems convert spoken language into text,

facilitating various applications such as accent training, pronunciation correction, and

fluency improvement. These systems are integral to language learning apps and speech

therapy tools. ASR systems help users practice different accents by comparing their

speech to native speakers and providing corrective feedback. What is also important is

that by analyzing phonetic details, ASR systems can pinpoint pronunciation errors and

suggest improvements, helping learners achieve more accurate speech [13]. It can

measure speech rate and continuity, offering exercises and feedback to help learners

speak more fluently. When it comes to benefits it can’t go without saying that ASR

systems provide immediate, personalized feedback, which is crucial for improving

speaking skills. These systems are also widely accessible through language learning apps,

making quality speech training available to a broad audience.

When it comes to Interactive AI tutors and chatbots, they offer real-time

conversation practice and feedback, mimicking natural interactions with human

speakers. These tools are invaluable for learners needing practice in conversational skills

and spontaneous speech. AI tutors and chatbots engage users in dialogues, simulating

real-life conversations to practice language skills. These tools also provide instant

feedback on vocabulary usage, sentence structure, and conversational appropriateness,

helping learners refine their speaking abilities. Last but not the least, AI tutors adjust the

difficulty and complexity of conversations based on the learner's proficiency level,

ensuring an optimal learning curve [26]. All these make learning engaging and

interactive, which can enhance motivation and retention.

Virtual Reality (VR) and Augmented Reality (AR) Applications create immersive

environments for language learning and public speaking practice. These technologies

offer unique opportunities for learners to engage in realistic simulations and scenarios.

The functionality is that VR and AR applications place learners in virtual environments

where they can interact with native speakers or practice in specific contexts, such as

markets, airports, or business meetings. VR applications simulate public speaking

scenarios, allowing learners to practice speeches and presentations in front of virtual

audiences. Practicing in virtual environments can reduce anxiety associated with public

speaking and language use, helping learners build confidence [11].

AI applications such as Automated Speech Recognition (ASR) systems, interactive

AI tutors and chatbots, and Virtual Reality (VR) and Augmented Reality (AR) technologies

are revolutionizing the way we enhance speaking skills. These tools provide personalized

feedback, real-time practice, and immersive learning experiences, making language

learning more effective and engaging. As AI continues to evolve, its applications in

improving speaking skills are likely to expand, offering even more sophisticated and

accessible learning solutions.

ANALYSIS

The application of AI in education, particularly in enhancing speaking skills, has

shown promising results across various case studies and implementations. This section

highlights successful implementations of AI in improving speaking skills and provides a

comparative analysis of traditional teaching methods versus AI-enhanced methods.

Case Study 1:

AI-Powered Speech Recognition Technology

A study published in 2023 investigated the impact of AI-powered speech

recognition technology on improving English pronunciation and speaking skills among

learners. The findings suggest that such technology can significantly enhance learners’

speaking abilities by providing immediate feedback and personalized practice.[30]


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Case Study 2:

The article, “Study of Artificial Intelligence-Assisted English Oral

Teaching,” highlights the effectiveness of AI technology in improving students’ English-

speaking abilities, particularly for those learning English as a foreign language. The

research demonstrates that AI-assisted teaching platforms significantly enhance

students’ fluency, confidence, and active participation in spoken English practice. The

authors emphasize the potential of AI to transform English oral teaching, calling for

further integration of AI technology in education to achieve comprehensive

improvements in students’ speaking skills.[31]

Case study 3:

Study by Li, Chen, & Liu (2019)

: This study compared the

effectiveness of traditional teaching methods and AI-enhanced methods in improving

speaking skills among English learners. The results showed that students using AI tools

like speech recognition software demonstrated significantly higher improvements in

pronunciation and fluency compared to those relying solely on traditional methods [14].

Meta-Analysis by Klimova & Poulova (2020)

: A meta-analysis of various studies

on AI applications in language learning found that AI-enhanced methods consistently

outperformed traditional methods in terms of student engagement, feedback quality, and

overall speaking proficiency gains [11].

Challenges and Ethical Considerations.

The integration of AI in education, while promising, presents several challenges

and ethical considerations. Key issues include privacy and data security, accessibility and

equity, and the potential dependency on technology.

Privacy and Data Security:

The use of AI tools in education involves the collection

and processing of large amounts of student data, raising significant concerns about

privacy and data security. AI tools often collect sensitive information, including students'

personal details, academic performance, and interaction data. This raises concerns about

how this data is stored, processed, and used. Educational institutions and AI providers

must ensure robust security measures to prevent data breaches that could expose

student information to unauthorized parties. Additionally, it is crucial to obtain informed

consent from students and their guardians before collecting data, ensuring they

understand what data is being collected and how it will be used. According to Kay and

Knaack (2017), maintaining privacy and security in educational technology is paramount

to protecting student information [10]. The Harvard Business Review also highlights the

importance of protecting student privacy in the age of AI [27].

Accessibility and Equity:

While AI tools have the potential to democratize

education, issues of accessibility and equity must be addressed to ensure that all students

benefit from these technologies. Access to AI tools can be limited by socioeconomic

factors, with students from low-income families potentially lacking the necessary devices

or internet access. AI tools must be designed to accommodate diverse learning needs,

including those of students with disabilities or language barriers. Additionally, schools

and educational institutions must ensure equitable resource allocation to provide all

students with access to AI-enhanced learning tools. Selwyn (2019) discusses the

challenges of ensuring equitable access to digital educational tools, emphasizing the need

for inclusive design [21]. The World Economic Forum also underscores the importance of

bridging the digital divide in education to ensure all students have equal opportunities.

Dependency on Technology

:

The increasing use of AI in education raises concerns

about potential over-reliance on technology, which could impact both teaching and

learning processes. Over-reliance on AI tools could reduce face-to-face interactions


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between teachers and students, potentially impacting the development of soft skills and

human connections. There is also a risk that teachers may become overly dependent on

AI tools for lesson planning, assessment, and feedback, which could undermine their

professional autonomy and judgment. Additionally, excessive use of AI tools might limit

students' opportunities to develop critical thinking and problem-solving skills, as they

may rely on technology to provide answers and solutions. Knox (2016) explores the

implications of AI on the future of education, highlighting the need to balance

technological use with human interaction [12].

While AI has the potential to revolutionize education, it also presents significant

challenges and ethical considerations. Ensuring privacy and data security, addressing
accessibility and equity issues, and avoiding over-reliance on technology are crucial for
the responsible integration of AI in educational settings. By addressing these concerns,
educators and policymakers can harness the benefits of AI while safeguarding the
interests of all students.

Future Directions in AI for Enhancing Speaking Skills

As AI technology continues to advance, its potential for transforming the

development of speaking skills in educational settings is becoming increasingly evident.
The future of AI in education is marked by the emergence of innovative tools and the
integration of AI with traditional teaching methods to create hybrid educational models.
This section explores promising new AI technologies and discusses how these
innovations might be blended with conventional approaches for optimal educational
outcomes.

Emerging AI Technologies

. Recent advancements in AI are introducing new tools

and technologies that have the potential to significantly enhance the development of
speaking skills. One of the most notable developments is in the field of advanced speech
synthesis and generation technologies. Modern Text-to-Speech (TTS) engines, such as
Google's WaveNet, produce high-quality, human-like speech from text inputs, providing
learners with realistic pronunciation examples and interactive practice scenarios [28].
These TTS engines enable language learning apps to offer dynamic, lifelike speech
experiences for learners, which can be instrumental in practicing pronunciation and
fluency.

Additionally, speech-to-speech translation technologies, like Google's Translate

Conversations, facilitate real-time conversations between different languages, enabling
immersive language practice and conversation simulations [5]. These tools provide
learners with opportunities to engage in practical conversations and receive immediate
feedback on their language skills, thus enhancing their speaking proficiency in a variety
of linguistic contexts.

Another significant advancement is in AI-powered pronunciation correction tools.

For instance, platforms like Pronunciation Coach use deep learning algorithms to offer
detailed feedback on pronunciation and accent, providing personalized exercises for
improvement [29]. These tools are designed to detect pronunciation errors with high
precision and suggest specific corrections, thereby offering learners targeted practice
opportunities. Moreover, language learning platforms such as ELSA Speak are
continuously refining their AI algorithms to deliver more accurate feedback on learners'
pronunciation and fluency [18]. These technologies represent the forefront of AI-driven
language education, promising even greater advancements in the future.


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Integrating AI with Traditional Teaching Methods.

Looking ahead, the future of

education will likely involve blending AI technologies with traditional teaching methods
to create hybrid educational models that leverage the strengths of both approaches. One
promising model is the blended learning environment, which combines AI-driven tools
with traditional classroom instruction to offer a more flexible and personalized learning
experience. In this model, AI tools provide additional practice and feedback outside of
class, while in-person sessions focus on interactive discussions and problem-solving [4].
This approach allows for a more tailored learning experience, where AI supports learners
with personalized feedback and practice opportunities, while face-to-face interactions
facilitate deeper engagement with the material.

Another innovative model is the flipped classroom, where students use AI tools for

initial learning and practice outside of class, and classroom time is reserved for
collaborative activities and teacher-led discussions (Journal of Educational Technology,
2020). This model optimizes the use of AI for repetitive tasks and leverages in-person
interactions for more complex learning experiences. The flipped classroom approach
allows educators to focus on facilitating discussions and guiding students through
advanced concepts, while AI tools handle the more routine aspects of instruction.

AI technologies also hold promise for augmenting teacher support systems.

AI-assisted lesson planning tools can help educators design effective lesson plans by
providing data-driven insights into student needs and progress [28]. Additionally, AI
systems can automate administrative tasks such as grading and attendance, which can
free up time for teachers to focus more on instructional activities and direct student
interactions [1]. These advancements will likely lead to more efficient and effective
teaching practices, as AI tools take on routine tasks and provide teachers with valuable
insights for improving their instructional methods.

The future of AI in education is poised for transformative developments that

promise to enhance the teaching and learning of speaking skills. Emerging AI
technologies, such as advanced speech synthesis and AI-powered pronunciation
correction tools, are setting new standards for language learning and practice.
Additionally, innovative hybrid educational models that combine AI with traditional
teaching methods offer exciting opportunities for creating more flexible and effective
learning environments. As these technologies continue to evolve, they will shape the
future of education, providing new tools and approaches for developing students'
speaking skills and addressing the evolving needs of learners.

By exploring these future directions, educators and policymakers can develop

strategies that harness the potential of AI while ensuring that educational practices
remain effective, equitable, and student-centered.

This comprehensive exploration of future directions in AI for enhancing speaking

skills highlights both the potential of emerging technologies and the benefits of
integrating these innovations with traditional teaching methods to create effective
educational models.

CONCLUSION

The integration of artificial intelligence (AI) into educational settings presents a

promising frontier for enhancing the development of students’ speaking skills. This
article has explored various aspects of AI’s role in education, focusing on the current
state of speaking skills, the benefits and applications of AI technologies, successful case


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studies, and the challenges and ethical considerations associated with AI in educational
contexts. In this conclusion, we summarize the key points discussed, reflect on the
transformative potential of AI in education, and propose actionable steps for educators,
technologists, and policymakers.

The transformative potential of AI in education is vast, particularly in the realm of

developing speaking skills. As we have seen, AI technologies offer innovative solutions
for providing personalized feedback, creating immersive learning experiences, and
supporting both students and educators in new and effective ways. The integration of
AI with traditional teaching methods holds the promise of creating more engaging and
adaptive educational environments that cater to the diverse needs of learners.

To harness the full potential of AI in education, educators, technologists, and

policymakers must take proactive steps to explore and invest in these technologies.
Educators should seek out opportunities for professional development to better
understand and utilize AI tools in their teaching practices. Technologists should focus on
creating accessible, user-friendly AI tools that address diverse educational needs and
consider the ethical implications of their designs. Policymakers should support research
and funding initiatives that promote the development and equitable distribution of
AI technologies in education.

By working together to advance these goals, stakeholders can help shape the future

of education in ways that enhance speaking skills and contribute to the broader
objectives of student success and lifelong learning.

REFERENCES:

1.

Anthony Rebora (2020) "

AI Tools for Teacher Support: Enhancing Efficiency and

Effectiveness

" (2020) –

Educational Leadership

.

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Blatchford, P., Russell, A., & Bassett, P. (2004).

The Class Size Debate: Is Small

Better?

Open University Press.

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Fraleigh, D. M., & Tuman, J. S. (2016).

Speak Up: An Illustrated Guide to Public

Speaking

. Bedford/St. Martin's.

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Garrison, D. R., & Vaughan, N. D. (2008).

Blended Learning in Higher Education:

Framework, Principles, and Guidelines.

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Google Translate’s New Features: Real-Time Speech Translation

" –

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Goel, A., & Polepeddi, L. (2016). „

Jill Watson: A Virtual Teaching Assistant

for Online Education

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to Achievement

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Joe Myers (2021) "

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"

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Economic Forum.

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Kay, D., & Knaack, L. (2017). "

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Klimova, B., & Poulova, P. (2020). "

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Learning: A Literature Review.

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Knox, J. (2016). "

The Future of Education: How AI Will Change Teaching

and Learning

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Oxford University Press.


background image

Xorijiy lingvistika va lingvodidaktika – Зарубежная лингвистика

и лингводидактика – Foreign Linguistics and Linguodidactics

Special Issue – 1 (2025) / ISSN 2181-3701

297

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Li, H., Deng, L., & Haeb-Umbach, R. (2017). "

Speech Recognition:

Technology and Applications

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Learning: A Comparative Study

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Instruction: Examining the Effects of Duolingo as a Language Learning Tool.

"

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"

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Powered Assistance

"

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Automated Speech Recognition in Language

Learning: A Review

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Natalie Gross (2021) „

How AI is Transforming Pronunciation Practice in

Language Learning

“ –

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Speaking Up: The Unintended Costs of

Silence in the Classroom

. New York: Academic Press

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To Advance AI Use in Education, Focus on

Understanding Educators

” – International Journal of Artificial Intelligence in Education

(2024) 34:12–19. https://doi.org/10.1007/s40593-023-00351-4

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Singh, M., & Wasson, B. (2017). "

Automated Grading Systems: Enhancing

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Artificial Intelligence in Education

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Vesselinov, R., & Grego, J. (2016). "The Babbel Efficacy Study."

City

University of New York

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Vesselinov, R., & Grego, J. (2016). "Duolingo Effectiveness Study."

City

University of New York.

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Brookings Institution

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Wollny, E., Schneider, J., & Specht, M. (2020). "Conversational Agents in

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Yacoub, S., & Lee, Y. (2021). "Advances in Speech Synthesis Technologies for

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Correction in Language Learning."

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Nutprapha K. Dennis, “Using AI-Powered Speech Recognition Technology to

Improve English Pronunciation and Speaking Skills,” IAFOR Journal of Education:
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University, Thailand.

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of Saint Joseph, Macao, China. ISSN: 2664-9640.

Bibliografik manbalar

Anthony Rebora (2020) "AI Tools for Teacher Support: Enhancing Efficiency and Effectiveness" (2020) - Educational Leadership.

Blatchford, P., Russell, A., & Bassett, P. (2004). The Class Size Debate: Is Small Better? Open University Press.

Fraleigh, D. M., & Tuman, J. S. (2016). Speak Up: An Illustrated Guide to Public Speaking. Bedford/St. Martin's.

Garrison, D. R., & Vaughan, N. D. (2008). Blended Learning in Higher Education: Framework, Principles, and Guidelines.

"Google Translate’s New Features: Real-Time Speech Translation" - TechCrunch.

Goel, A., & Polepeddi, L. (2016). „Jill Watson: A Virtual Teaching Assistant for Online Education“ - Proceedings of the AAAI Conference on Artificial Intelligence.

Hattie, J. (2009). Visible Learning: A Synthesis of Over 800 Meta-Analyses Relating to Achievement. Routledge.

Howard, R. M., & Davies, L. (2016). "Turnitin and the Debate on Plagiarism Detection." - Journal of Academic Ethics

Joe Myers (2021) "Bridging the Digital Divide in Education" - World Economic Forum.

Kay, D., & Knaack, L. (2017). "Privacy and Data Security in Educational Technology."

Klimova, B., & Poulova, P. (2020). "Virtual Reality as a Tool for Language Learning: A Literature Review."

Knox, J. (2016). "The Future of Education: How AI Will Change Teaching and Learning." - Oxford University Press.

Li, H., Deng, L., & Haeb-Umbach, R. (2017). "Speech Recognition: Technology and Applications." - IEEE Signal Processing Magazine

Li, H., Chen, G., & Liu, Q. (2019). "The Effectiveness of AI-Enhanced Language Learning: A Comparative Study."

Loewen, S., Isbell, D. R., & Sporn, Z. (2020). "The Effectiveness of L2 Instruction: Examining the Effects of Duolingo as a Language Learning Tool."

Marcelo Maggioni (2020) "How Socratic by Google Helps Students with AI-Powered Assistance" - Google AI Blog.

Michael Carrier (2017) "Automated Speech Recognition in Language Learning: A Review" - Journal of Educational Technology Systems

Natalie Gross (2021) „How AI is Transforming Pronunciation Practice in Language Learning“ - EdTech Magazine.

Petrini, Maria, and Harold Taggart. 2022. Speaking Up: The Unintended Costs of Silence in the Classroom. New York: Academic Press

René F. Kizilcec (2023). “To Advance AI Use in Education, Focus on Understanding Educators” - International Journal of Artificial Intelligence in Education (2024) 34:12–19. https://doi.org/10.1007/s40593-023-00351-4

Selwyn, N. (2019). "Equity and Education in the Digital Age." - Routledge.

Singh, M., & Wasson, B. (2017). "Automated Grading Systems: Enhancing Efficiency and Consistency in Educational Assessment." - International Journal of Artificial Intelligence in Education

Vesselinov, R., & Grego, J. (2016). "The Babbel Efficacy Study." - City University of New York.

Vesselinov, R., & Grego, J. (2016). "Duolingo Effectiveness Study." City University of New York.

West, D. M. (2016). "The Future of Work: Robots, AI, and Automation." - Brookings Institution.

Wollny, E., Schneider, J., & Specht, M. (2020). "Conversational Agents in Language Learning: A Systematic Literature Review." Journal of Educational Technology & Society.

Wilson A. David "Protecting Student Privacy in the Age of AI" - Harvard Business Review.

Yacoub, S., & Lee, Y. (2021). "Advances in Speech Synthesis Technologies for Language Learning."

Zhou, L., & Zhao, Y. (2020). "Deep Learning Approaches for Pronunciation Correction in Language Learning."

Nutprapha K. Dennis, “Using AI-Powered Speech Recognition Technology to Improve English Pronunciation and Speaking Skills,” IAFOR Journal of Education: Technology in Education, vol. 12, no. 2 (2024): 107–128, Ubon Ratchathani Rajabhat University, Thailand.

Jing Wang, Jieren Zhang, Lina Chen, and Jianbiao Dai, “Study of Artificial Intelligence-Assisted English Oral Teaching,” Scientific Journal of Intelligent Systems Research, vol. 6, no. 8 (2024): 1-8p, Institute for Data Engineering and Science, University of Saint Joseph, Macao, China. ISSN: 2664-9640.