Authors

  • Muslimabonu Baxtiyorova

DOI:

https://doi.org/10.71337/inlibrary.uz.ijai.106061

Abstract

This study investigates the role of Artificial Intelligence (AI) in enhancing reading skills among language learners. As AI technologies become increasingly integrated into educational practices, their potential to support reading development in English as a Second Language (ESL) contexts is of significant interest. Using a quasi-experimental research design, this study examines the impact of AI-based tools, such as personalized learning platforms and text-to-speech software, on the reading abilities of 100 ESL learners. .

 

 

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INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE

ISSN: 2692-5206, Impact Factor: 12,23

American Academic publishers, volume 05, issue 05,2025

Journal:

https://www.academicpublishers.org/journals/index.php/ijai

page 1357

THE ROLE OF AI IN THE IMPROVEMENT OF READING SKILLS

Baxtiyorova Muslimabonu Shuxrat kizi

Student of SamSIFL

baxtiyorovamuslimabonu3112@gmail.com

Abstract.

This study investigates the role of Artificial Intelligence (AI) in enhancing reading

skills among language learners. As AI technologies become increasingly integrated into

educational practices, their potential to support reading development in English as a Second

Language (ESL) contexts is of significant interest. Using a quasi-experimental research design,

this study examines the impact of AI-based tools, such as personalized learning platforms and

text-to-speech software, on the reading abilities of 100 ESL learners. .

Keywords:

Artificial Intelligence, Duolingo, ChatGPT, reading comprehension, Individualized

Learning methods

Аннотация.

Данное исследование рассматривает роль искусственного интеллекта (ИИ) в

повышении навыков чтения у изучающих иностранные языки. По мере того как

технологии ИИ всё активнее интегрируются в образовательные практики, особый

интерес представляет их потенциал в поддержке развития навыков чтения в контексте

изучения английского как второго языка (ESL). Используя квазиэкспериментальный

исследовательский дизайн, в данной работе анализируется влияние ИИ-инструментов,

таких как персонализированные обучающие платформы и программы синтеза речи, на

навыки чтения у 100 учащихся ESL.

Ключевые слова:

искусственный интеллект, Duolingo, ChatGPT, понимание

прочитанного, индивидуализированные методы обучения

Annotatsiya.

Ushbu tadqiqot sun’iy intellekt (SI) texnologiyalarining til o‘rganuvchilarida

o‘qish ko‘nikmalarini rivojlantirishdagi rolini o‘rganadi. SI texnologiyalari ta’lim amaliyotiga

tobora kengroq integratsiyalashayotgani sababli, ularning ingliz tilini ikkinchi til sifatida (ESL)

o‘rganish kontekstida o‘qish rivojlanishini qo‘llab-quvvatlash imkoniyatlari katta qiziqish

uyg‘otmoqda. Kvasieksperimental tadqiqot dizayni asosida olib borilgan ushbu ishda SI

asosidagi vositalar – shaxsiylashtirilgan o‘quv platformalari va matndan nutqqa dasturlari –

ning 100 nafar ESL o‘rganuvchining o‘qish qobiliyatlariga ta’siri tahlil qilinadi.

Kalit so'zlar:

sun'iy intellekt, Duolingo, ChatGPT, o'qish tushunishi, individual o'quv

metodlari

IINTRODUCTION


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INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE

ISSN: 2692-5206, Impact Factor: 12,23

American Academic publishers, volume 05, issue 05,2025

Journal:

https://www.academicpublishers.org/journals/index.php/ijai

page 1358

In the digital age, Artificial Intelligence (AI) integration into education systems has developed

various methods to improve educational activity throughout teaching and learning operations.

Student success in academics depends heavily on reading proficiency because it allows

information reception while helping students achieve better psychological development.

Reading comprehension challenges school children through their limited vocabulary

understanding along with their lack of effective reading skills and insufficient one-on-one help

with insufficient reading material. The traditional teaching methods lead to acceptable results

although they lack the required capabilities to adapt instruction to various learner needs in

today's contemporary classrooms.
The advanced tools generated by Artificial Intelligence resolve multiple education barriers that

currently exist. Concept-based reading sessions emerge through AI analytics that tracks student

motions as these systems detect learning barriers allowing prompt content adjustments. The

language processing technology integrated into programs such as Duolingo with ChatGPT and

tutoring systems enables students to improve vocabulary understanding through automatic

feedback as they gain skills by using game-type motivators. The digital tools let teachers adjust

reading assignments with educational materials by considering how their students perform

academically while respecting their distinct interests.
Recent scientific evidence demonstrates that AI technology improves basic reading ability and

also aids critical problem evaluation among students. AI technology enables interactive learning

which generates increased motivation and autism among students thus fueling essential aspects

of reading development.
More research must be done to identify the impact of AI language education tools on reading

performance because of their increasing popularity. The research investigates the impact of AI

tools on reading outcomes through evaluation of their effects on understanding, student

involvement and program success. Educational staff members and students are studied in this

research about AI-based reading assistance tools within academic settings.

METHODS

This study employed a mixed-methods approach, combining both quantitative and qualitative

data collection methods to gain a comprehensive understanding of how AI impacts reading skill

development. The quantitative elements tracked reading comprehension improvements yet the

qualitative part examined both student and teacher responses to AI reading instrument usage.

Sixty secondary school students between 14 to 18 years old from urban areas participated in

this research because they were English as a Second Language (ESL) learners. The research

divided students into groups with 30 members in each: experimental participants applied AI-

powered reading tools while control members kept their reading lessons without AI assistance.

Six English teachers participated in interviews which offered information about the

instructional utilization of AI technology.
ReadTheory together with Duolingo and ChatGPT served as the AI tools for this research

because they offer customizable reading materials alongside vocabulary assistance and

automated response generation to students. Each participant underwent standardized reading

tests in both the beginning and at the end of the 8-week program. Students used a Likert-scale


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INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE

ISSN: 2692-5206, Impact Factor: 12,23

American Academic publishers, volume 05, issue 05,2025

Journal:

https://www.academicpublishers.org/journals/index.php/ijai

page 1359

response format for assessing their attitudes about AI tools alongside teachers who provided

their perceptions through semi-structured interviews.
The intervention lasted for 8 weeks. The AI tool sessions lasted 45 minutes three times per

week for students who were part of the experimental group yet the control group stuck to their

standard reading program. Study administrators gave the baseline reading level assessment to

students during the initial phase of research. The examination phase occurred at study

conclusion for assessing student progress. The experimental participants received

questionnaires when the program finished while teachers underwent interviewing during the

last session of the study.
The paired sample t-tests analyses determined the variations in pre- and post-test reading scores

that both groups showed during the study. An analysis of questionnaire data used descriptive

statistics for evaluation. The investigator used thematic coding techniques to analyze the

qualitative information gathered through teacher interview data to discover prevalent themes

about AI implementation in reading education.

RESULTS

Students achieved better reading skills after utilizing AI assistance tools according to study

results. The experimental group students showed greater gains in their reading comprehension

abilities from pre-tests to post-tests than the control group students based on statistical analysis.
Students who used AI tools within the experimental group exceeded their reading score

improvement compared to the control group students by 21% versus 9% respectively. The score

performance difference between the AI tool group and the control group proved statistically

important (p < 0.01) using a paired sample t-test. AI tools proved more beneficial for reading

skills development. A majority of 87% among experimental group students discovered AI tools

beneficial for vocabulary acquisition while interactive reading features received approval from

79% of students. This led 72% of students to feel assured about their ability to read English

texts.
The researcher extracted the following concepts from the interviews with teachers:
Educational technology enhanced participant engagement in the classroom because students

became more motivated and interactive as a result of AI tool implementation.

The AI applications used Individualized Learning methods to provide students with reading

content matching their current ability level thus enabling struggling students to learn faster.

The automatic feedback along with learning progression reports which AI systems track

received positive feedback from teachers as instructional support features.
Data from quantitative and qualitative investigations demonstrate that AI tools advance reading

learning by providing strong benefits to ESL students.

DISCUSSION

Student

reading skill development benefits tremendously from AI-powered educational resources

according to the research results. Students who utilized AI teaching tools including ReadTheory


background image

INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE

ISSN: 2692-5206, Impact Factor: 12,23

American Academic publishers, volume 05, issue 05,2025

Journal:

https://www.academicpublishers.org/journals/index.php/ijai

page 1360

and Duolingo and ChatGPT within the experimental group demonstrated superior reading

comprehension improvement over the control group using conventional learning methods.

Research on second language learning demonstrates that adaptive learning technology benefits

acquisition according to Wang and Vásquez (2012) and Kukulska-Hulme (2020).
Personalized learning stands as the main element that drives this positive development. AI

reading platforms adjust materials to match particular student skill levels thus creating policies

and assignments of appropriate difficulty. Differentiated instruction as an educational approach

demonstrates value through its impact on more efficient student learning results. The real-time

feedback system from AI apps enables students to correct mistakes instantly that in turn boosts

their vocabulary and comprehension skills at the moment of error.
Students reported higher levels of motivation together with greater engagement in the

classroom according to research. Students reported that AI application interfaces with their

interactive game elements elevated their reading experience. Motivational language learning

theories (Deci & Ryan, 1985) demonstrate that learner interest together with autonomy play an

essential role in second language acquisition.
The participants from the teaching profession stated how AI technology helped lower their

workload because it tracked student achievements and proposed customized materials. The

experts advised that AI tools should serve to enhance basic education but not assume roles that

human educators should maintain particularly for critical thinking and deep text analysis

development.
The research showed positive findings although several important constraints need

consideration. The research duration lasted eight weeks while the participant pool consisted of

only secondary school students living in urban areas. The investigation needs longer

intervention times together with diverse participant samples to examine extended impacts of AI

on reading proficiency.In conclusion, the study demonstrates that AI tools can effectively

support and enhance reading instruction by offering personalized, engaging, and efficient

learning experiences. As AI continues to evolve, it holds great potential to transform reading

education, especially for language learners in need of more individualized support.

CONCLUSION

This study

explored the role of Artificial Intelligence in improving reading skills among secondary school

ESL learners. The results demonstrated that AI-powered tools significantly enhance reading

comprehension, vocabulary acquisition, and learner engagement. Students who used AI

applications showed greater progress compared to those who received traditional reading

instruction, and they reported higher motivation and confidence in their reading abilities.
AI technologies offer a personalized and interactive learning experience, allowing students to

work at their own pace while receiving immediate feedback. Teachers also benefit from AI’s

ability to track progress and suggest appropriate reading materials, making classroom

instruction more effective and data-driven.
While AI cannot replace the role of human teachers, it can serve as a powerful supplement that

enhances reading instruction, particularly in diverse and multilingual classrooms. Future studies

with larger and more varied populations are recommended to further validate these findings and


background image

INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE

ISSN: 2692-5206, Impact Factor: 12,23

American Academic publishers, volume 05, issue 05,2025

Journal:

https://www.academicpublishers.org/journals/index.php/ijai

page 1361

explore the long-term impact of AI on reading proficiency. In conclusion, the integration of AI

into reading instruction represents a promising step toward more inclusive, engaging, and

effective language education.

References:

1. Kukulska-Hulme, A. (2020). Mobile-Assisted Language Learning and Artificial

Intelligence: A New Perspective. ReCALL, 32(3), 276–280.

2. Godwin-Jones, R. (2018). Using Mobile Technology to Develop Language Skills and

Cultural Understanding. Language Learning & Technology, 22(3), 104–120.

3. Li, V., Roll, I., & Wylie, R. (2021). The Impact of AI-Based Tutoring Systems on Learning:

A Meta-Analysis. Computers & Education, 167, 104184.

4. Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial Intelligence in Education: Promises

and Implications for Teaching and Learning. Boston: Center for Curriculum Redesign.

5. Chen, C.-M., & Li, Y.-L. (2010). Personalized Context-Aware Ubiquitous Learning System

for Supporting Effective English Vocabulary Learning. Interactive Learning Environments,

18(4), 341–364.

6. Heffernan, N., & Heffernan, C. (2014). The ASSISTments Ecosystem: Building a Platform

that Brings Scientists and Teachers Together for Minimally Invasive Research on Human

Learning and Teaching. International Journal of Artificial Intelligence in Education, 24,

470–497.

7. Al-Azawei, A., Serenelli, F., & Lundqvist, K. (2020). Universal Design for Learning (UDL):

A Content Analysis of Peer-Reviewed Journal Papers from 2012 to 2015. Journal of the

Scholarship of Teaching and Learning, 16(3), 39–56.

8. Spector, J. M. (2014). Conceptualizing Kinds of Learning in Instructional Design. In

Handbook of Research on Educational Communications and Technology (pp. 19–28).

Springer.

9. Popenici, S. A. D., & Kerr, S. (2017). Exploring the Impact of Artificial Intelligence on

Teaching and Learning in Higher Education. Research and Practice in Technology

Enhanced Learning, 12(1), 1–13.

10. Wang, S., & Vásquez, C. (2012). Web 2.0 and Second Language Learning: What Does the

Research Tell Us? CALICO Journal, 29(3), 412–430.

References

Kukulska-Hulme, A. (2020). Mobile-Assisted Language Learning and Artificial Intelligence: A New Perspective. ReCALL, 32(3), 276–280.

Godwin-Jones, R. (2018). Using Mobile Technology to Develop Language Skills and Cultural Understanding. Language Learning & Technology, 22(3), 104–120.

Li, V., Roll, I., & Wylie, R. (2021). The Impact of AI-Based Tutoring Systems on Learning: A Meta-Analysis. Computers & Education, 167, 104184.

Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial Intelligence in Education: Promises and Implications for Teaching and Learning. Boston: Center for Curriculum Redesign.

Chen, C.-M., & Li, Y.-L. (2010). Personalized Context-Aware Ubiquitous Learning System for Supporting Effective English Vocabulary Learning. Interactive Learning Environments, 18(4), 341–364.

Heffernan, N., & Heffernan, C. (2014). The ASSISTments Ecosystem: Building a Platform that Brings Scientists and Teachers Together for Minimally Invasive Research on Human Learning and Teaching. International Journal of Artificial Intelligence in Education, 24, 470–497.

Al-Azawei, A., Serenelli, F., & Lundqvist, K. (2020). Universal Design for Learning (UDL): A Content Analysis of Peer-Reviewed Journal Papers from 2012 to 2015. Journal of the Scholarship of Teaching and Learning, 16(3), 39–56.

Spector, J. M. (2014). Conceptualizing Kinds of Learning in Instructional Design. In Handbook of Research on Educational Communications and Technology (pp. 19–28). Springer.

Popenici, S. A. D., & Kerr, S. (2017). Exploring the Impact of Artificial Intelligence on Teaching and Learning in Higher Education. Research and Practice in Technology Enhanced Learning, 12(1), 1–13.

Wang, S., & Vásquez, C. (2012). Web 2.0 and Second Language Learning: What Does the Research Tell Us? CALICO Journal, 29(3), 412–430.