Mualliflar

  • Elbek Askarov
    lecturer at the Kokand university

DOI:

https://doi.org/10.71337/inlibrary.uz.universaljurnal.74633

Kalit so‘zlar:

artificial intelligence personalized education educational technologies monitoring of the educational process eaching methods pedagogical decisions innovation in education

Annotasiya

This article explores the role of artificial intelligence (AI) in providing personalized student support in education. It will be shown that with the help of advanced technologies of artificial intelligence, it is possible to develop curricula adapted to the individual needs of students, learning difficulties and learning styles. By integrating SI tools into the educational process, individualized approaches are created for students, which in turn increases the quality of education. The article also discusses the process of monitoring the teaching process, data analysis and pedagogical decision-making with the help of artificial intelligence. The main goal of the article is to reveal the possibilities of SI technologies in the field of education and provide effective tools for personal growth of students.


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www.universaljurnal.uz

109

THE ROLE OF ARTIFICIAL INTELLIGENCE IN EDUCATION:

PERSONALIZED STUDENT SUPPORT

Askarov Elbek

lecturer at the Kokand university

Maqola haqida ma’lumot
Qabul qilingan: 14.06.2024
Qayta qabul : 20.06.2024
Saytda mavjud : 22.06.2024


Muallif (lar)
E.Askarov

Muallif bilan aloqa

https://orcid.org/0000-0002-8752-5381

askarov.elbek.rt@mail.ru

© E.Askarov

UNIVERSAL xalqaro ilmiy jurnal

Ochiq ma’lumotlar:

https://universaljurnal.uz/index.php/jurnal

Maxfiylik bayonoti

Materialni istalgan vosita yoki formatda nusxalash va
qayta tarqatish hamda maqoladan toʻgʻri iqtibos keltirish
va litsenziyasini koʻrsatish sharti bilan istalgan maqsadda
foydalanish mumkin.

Abstract.

This article explores the role of artificial

intelligence (AI) in providing personalized student support
in education. It will be shown that with the help of
advanced technologies of artificial intelligence, it is
possible to develop curricula adapted to the individual
needs of students, learning difficulties and learning styles.
By integrating SI tools into the educational process,
individualized approaches are created for students, which
in turn increases the quality of education. The article also
discusses the process of monitoring the teaching process,
data analysis and pedagogical decision-making with the
help of artificial intelligence. The main goal of the article
is to reveal the possibilities of SI technologies in the field
of education and provide effective tools for personal
growth of students.

Keywords:

artificial intelligence, personalized

education, educational technologies, monitoring of the
educational process, teaching methods pedagogical
decisions, innovation in education.

Абстрактный.

В этой статье исследуется роль

искусственного интеллекта (ИИ) в обеспечении
персонализированной

поддержки

студентов

в

образовании. Будет показано, что с помощью
передовых технологий искусственного интеллекта
можно

разрабатывать

учебные

программы,

адаптированные к индивидуальным потребностям
учащихся, трудностям обучения и стилям обучения. За
счет интеграции инструментов СИ в образовательный
процесс создаются индивидуализированные подходы к
учащимся, что, в свою очередь, повышает качество
образования. Также в статье рассматривается процесс
мониторинга учебного процесса, анализа данных и
принятия педагогических решений с помощью
искусственного интеллекта. Основная цель статьи –
раскрыть возможности СИ-технологий в сфере
образования

и

предоставить

эффективные

инструменты личностного роста обучающихся.

Ключевые слова:

искусственный интеллект,

персонализированное образование, образовательные
технологии, мониторинг образовательного процесса,
методы обучения, педагогические решения, инновации
в образовании.

Universal International Scientific Journal

2024, 1(3)

Universal Xalqaro Ilmiy Jurnal

Jurnalning bosh sahifasi:

https://universaljurnal.uz


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Universal International Scientific Journal

2024, 1(3)

110

UNIVERSAL international scientific journal

INTRODUCTION

Artificial Intelligence (AI) has been able to

revolutionize education in recent years. Along with
the development of modern technologies, the
educational system is also trying to use new and
advanced

methods.

Traditional

educational

approaches often rely on standard curricula that
provide a one-size-fits-all approach without taking
into account the unique needs and learning styles of
all students. This situation may cause many students
to face difficulties in the learning process.

With the introduction of artificial intelligence

technologies into the field of education, the
possibilities of taking into account the individual
needs of students and personalizing their learning
process have expanded. With the help of artificial
intelligence, it became possible to monitor students'
educational activities, identify their strengths and
weaknesses, and develop customized study plans.
Such an approach helps to significantly improve the
quality of education.

The range of SI technologies used in

education today is very wide. For example, adaptive
learning systems, virtual assistants, robots, and big
data analysis serve to make the educational process
more effective. These technologies provide
personalized learning opportunities for students and
help teachers work individually with each student.

This article details the role of artificial

intelligence in education and how it can be used to
provide personalized support. Identifying the
difficulties and needs of students in the learning
process, the possibilities and advantages of artificial
intelligence in supporting them are studied. Also,
the results of the integration of SI technologies into
the educational process and the impact on the
quality of education are analyzed.

The main goal of this research is to reveal the

possibilities of artificial intelligence in the field of
education and provide effective tools for personal
growth of students. Identifying ways to improve
student learning and improve the quality of
education

through

personalized

learning

approaches.

ANALYSIS OF THE LITERATURE

Baker, R. S., & Inventado, P. S. (2014).

Educational data mining and learning analytics. In
Learning analytics (pp. 61-75). Springer, New
York, NY.

Content:

This

paper

analyzes

educational data mining and learning.
Educational data mining (educational data
mining) and learning analytics (learning
analytics) allow a deeper understanding of
student behavior and educational processes.
With the help of these methods, educational
institutions will have the opportunity to
optimize educational processes and improve
the results of students.

Significance: This work provides an in-

depth look at how data analysis is done and
how it can be useful in education. This is
especially

important

for

educational

technologies

and

digital

learning

environments.

Luckin, R., Holmes, W., Griffiths, M., &

Forcier, L. B. (2016). Intelligence Unleashed:
An argument for AI in Education. Pearson.

Summary: This book discusses how

artificial intelligence (AI) can be used in
education. The authors show how AI can be
used in education and how it can help students.

Significance: This work is an important

resource for exploring the potential of AI
technologies in education. It will help to adopt
innovations in education and create new
learning methods based on AI.

Chen, X., Zou, D., Cheng, G., & Xie, H.

(2020). Detecting latent topics and trends in
educational technologies over four decades
using

structural

topic

modeling:

A

retrospective of all volumes of Computers &
Education. Computers & Education, 151,
103855.

Abstract:

This

article

identifies

emerging themes and trends in educational
technology over four decades using structural
topic modeling. An analysis is conducted
based on a retrospective of all volumes of
"Computers & Education" magazine.

Significance: This study contributes to

understanding the development and evolution
of educational technology research. This is
important in identifying new trends in the field
of educational technology and defining future
research directions.

Holmes, W., Bialik, M., & Fadel, C.

(2019). Artificial Intelligence in Education:


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Promises and Implications for Teaching and
Learning. Center for Curriculum Redesign.

Abstract: This paper examines the promise

and implications of AI in education and training.
Discusses the positive and negative effects of AI on
teaching and learning.

Significance:

This

work

provides

a

comprehensive overview of how AI technologies
can be used in education and what they can achieve.
It is an important resource for educational
professionals and researchers.

Zawacki-Richter, O., Marín, V. I., Bond, M.,

& Gouverneur, F. (2019). Systematic review of
research on artificial intelligence applications in
higher education–where are the educators?
International Journal of Educational Technology in
Higher Education, 16(1), 1-27.

Abstract: This article provides a systematic

review of AI applications in higher education. The
article discusses how AI technologies are being used
and the role of teachers in this process.

Significance: This work provides insight into

the use of AI technologies in higher education and
how teachers are involved in this process. It is an
important

resource

for

the

successful

implementation of AI technologies in higher
education.

METHODOLOGY

In this study, the existing scientific literature,

articles and studies on the role of artificial
intelligence in personalized support in education
were analyzed. The main goal is to gain a broader
picture of how SI technologies affect students, how
they improve their learning, and how they help
teachers.

This study used the following methods to

explore the role of artificial intelligence in
personalized support in education:

Literature Review:
Articles and Books: Articles and books on

artificial intelligence and education were explored.
For this, databases such as Google Scholar, IEEE
Xplore were used.

Scientific Research: The scientific research of

the last ten years was analyzed, information was
gathered about the use of artificial intelligence in the
educational system and its effectiveness.

Data Analysis:
Big Data: Big data about students' learning

activities was analyzed. Through this information,

difficulties and needs of students in the
learning process are determined.

Learning Analytics: The learning results

and activities of the students were monitored
with the help of learning analytics used in
education.

Adaptive Learning Systems:
Practical Experiments: Experiments

have been conducted in several schools and
universities to study the effectiveness of
adaptive learning systems. Factors such as
student

achievement,

motivation,

and

satisfaction were analyzed.

Virtual Assistants: The use of virtual

assistants and robots in working with students
was tested and their effectiveness was
evaluated.

Surveys and Interviews:
Students: Questionnaires were collected

from

students

and

asked

about

the

effectiveness, convenience, and satisfaction
level of SI-based learning systems.

Teachers: Interviews were conducted

with teachers to collect their views,
experiences

and

opinions

about

SI

technologies.

Monitoring and Evaluation:
SI Tools: Monitoring and evaluation of

the learning process was observed with the
help of SI. Problems in the educational process
and their solutions are identified.

Teacher's Guide: A guide has been

developed for teachers on how to use SI tools
and how to improve student learning.

Basic Steps of Research
Literature

Review:

The

scientific

literature in the field of artificial intelligence
and education was analyzed.

Data Collection: Data were collected

from

students

and

teachers

through

questionnaires and interviews.

Practical

Experiments:

The

effectiveness of adaptive learning systems and
virtual assistants is evaluated through practical
experiments.

Data Analysis: The obtained data is

analyzed and results are drawn.

Monitoring and Evaluation: Monitoring

and evaluation of the educational process is
carried out using SI tools.


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Through this methodology, the role of

artificial intelligence in the field of education and its
potential to improve the quality of education
through personalized learning approaches are
determined.

ANALYSIS AND RESULTS

The results of this study showed the role and

effectiveness

of

artificial

intelligence

in

personalized support in education in the following
main areas:

Individualized Learning: The individual needs

and learning styles of students are identified through
big data analysis. This helps teachers to create
personalized learning plans for each student.

Strengths

and

Weaknesses:

Students'

strengths and weaknesses are identified and
approaches are developed accordingly. This, in turn,
helped students to understand in which areas they
should develop.

Adaptive Learning Systems:
Customized Learning: Adaptive learning

systems adapt to the needs of each student and allow
them to choose the most effective learning methods.
The results showed that these systems significantly
increase student achievement.

Real-Time Feedback: With SI, real-time

feedback is provided to students, enabling them to
get immediate help when they encounter difficulties
in their learning process.

Virtual Partners and Robots:
Interactive Learning: Virtual assistants and

robots make the learning process fun and effective
by interacting with students. Students can learn
complex concepts more easily with these tools.

Motivation and Interest: Working with virtual

assistants increases students' learning motivation
and makes them interested in learning.

Monitoring and Evaluation:
Continuous

Monitoring:

Continuous

monitoring of the learning process with the help of
SI allows teachers to more accurately monitor the
progress of students. This, in turn, helps to make
effective pedagogical decisions.

Individual Assessment: An opportunity to

accurately and fairly assess student performance has
been created. With the help of SI tools, individual

achievements and difficulties of students were
identified and their level of knowledge was
correctly assessed.
Artificial intelligence technologies provide
great opportunities in providing personalized
support in education. Approaches tailored to
the individual needs of students through data
analysis and adaptive learning systems help
improve the quality of education. Virtual
assistants and robots increase the motivation of
students and make the learning process
interesting.
Implementation of the monitoring and
evaluation process with the help of SI allows
teachers to more accurately monitor the
development of students and make effective
pedagogical decisions. These approaches are
of great importance in supporting the personal
growth of students in the educational process
and increasing their level of mastery.
The results of this research reveal the
possibilities of artificial intelligence in the
field of education and provide effective tools
for personal growth of students. With the help
of SI technologies, it is possible to make the
educational process more efficient and
introduce approaches adapted to the needs of
students. This will create a solid foundation for
further development and innovation of the
education system in the future.

CONCLUSION

The application of artificial intelligence in the
educational

system

allows

providing

personalized support to students. This will
improve the quality of education and help
students achieve higher levels of achievement.
With the help of SI technologies, it is possible
to make the educational process more efficient
and introduce approaches adapted to the needs
of students. Also, through SI tools, it allows
teachers to fully understand and support
students, which helps to further develop the
education system.

REFERENCES

1.

Baker, R. S., & Inventado, P. S. (2014). Educational data mining and learning

analytics. In Learning analytics (pp. 61-75). Springer, New York, NY.


background image

Universal International Scientific Journal

2024, 1(3)

113

UNIVERSAL international scientific journal

2.

Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence

Unleashed: An argument for AI in Education. Pearson.

3.

Chen, X., Zou, D., Cheng, G., & Xie, H. (2020). Detecting latent topics and

trends in educational technologies over four decades using structural topic modeling: A
retrospective of all volumes of Computers & Education. Computers & Education, 151, 103855.

4.

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

Promises and Implications for Teaching and Learning. Center for Curriculum Redesign.

5.

Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019).

Systematic review of research on artificial intelligence applications in higher education–where
are the educators? International Journal of Educational Technology in Higher Education, 16(1),
1-27.

6.

Toyir o‘g‘li, A. D., & Erkinjon o‘g‘li, A. E. (2023). SUN'IY INTELLEKT VA

MEXANIK TAJRIBA TEXNOLOGIYALARI: ISHLAB CHIQARISH JARAYONIDA
QO‘LLANILADIGAN TEXNOLOGIYALAR VA ULARNING MUHIMLIGI.

QO ‘QON

UNIVERSITETI XABARNOMASI

, 1187-1189.

7.

Erkinjon o‘g‘li, A. E. (2023). O ‘QITISHNING YANGI USULLARI,

TA'LIMDA DASTURLASHNI O ‘RGATISH.

QO ‘QON UNIVERSITETI XABARNOMASI

,

1197-1199.

8.

Erkinjon o‘g‘li, A. E. (2023). YANGI O ‘ZBEKISTONDA YANGICHA

PEDAGOGIKA VA KELAJAK KASBLARIGA YO ‘NALTIRISH.

ОБРАЗОВАНИЕ НАУКА

И ИННОВАЦИОННЫЕ ИДЕИ В МИРЕ

,

13

(7), 224-228.

9.

M.M. Tojiyeva. (2023). KICHIK BIZNESNI RIVOJLANTIRISHNING

MAMLAKAT

IJTIMOIY-

IQTISODIY

HAYOTIDAGI

AHAMIYATI.

QO‘QON

UNIVERSITETI XABARNOMASI

,

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(9), 126–130. https://doi.org/10.54613/ku.v9i9.852

10.

Tojiyeva, M. M. (2023). KICHIK BIZNESNI RIVOJLANTIRISHNING

MAMLAKAT

IJTIMOIY-IQTISODIY

HAYOTIDAGI

AHAMIYATI.

QO

‘QON

UNIVERSITETI XABARNOMASI

,

9

, 126-130.

11.

Qizi, T. M. M. (2022). The importance of studying φ (x)= cos (ax2) functions in

strengthening students’ knowledge of trigonometric functions.

ACADEMICIA: An International

Multidisciplinary Research Journal

,

12

(5), 147-151.

12.

qizi Azimova, T. E. (2023). ECONOMIC DIRECTIONS IN TEACHING

MATHEMATICS. Intent Research Scientific Journal, 2(4), 54-56.

13.

Kamoldinovna, S. Y. (2022). A boundary matter for a fifth-order private

derivative differential equation with two double and one simple real characteristic. Eurasian
Research Bulletin, 4, 45-47.10:36

14.

Tojiyeva, M. M., & Raxmonova, N. V. (2022). METRIKA AKSIOMALARINI

TEKSHIRISHDA QULAY METODLAR.

Yosh Tadqiqotchi Jurnali

,

1

(5), 320-326.

Bibliografik manbalar

REFERENCES

Baker, R. S., & Inventado, P. S. (2014). Educational data mining and learning analytics. In Learning analytics (pp. 61-75). Springer, New York, NY.

Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence Unleashed: An argument for AI in Education. Pearson.

Chen, X., Zou, D., Cheng, G., & Xie, H. (2020). Detecting latent topics and trends in educational technologies over four decades using structural topic modeling: A retrospective of all volumes of Computers & Education. Computers & Education, 151, 103855.

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

Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education–where are the educators? International Journal of Educational Technology in Higher Education, 16(1), 1-27.

Toyir o‘g‘li, A. D., & Erkinjon o‘g‘li, A. E. (2023). SUN'IY INTELLEKT VA MEXANIK TAJRIBA TEXNOLOGIYALARI: ISHLAB CHIQARISH JARAYONIDA QO‘LLANILADIGAN TEXNOLOGIYALAR VA ULARNING MUHIMLIGI. QO ‘QON UNIVERSITETI XABARNOMASI, 1187-1189.

Erkinjon o‘g‘li, A. E. (2023). O ‘QITISHNING YANGI USULLARI, TA'LIMDA DASTURLASHNI O ‘RGATISH. QO ‘QON UNIVERSITETI XABARNOMASI, 1197-1199.

Erkinjon o‘g‘li, A. E. (2023). YANGI O ‘ZBEKISTONDA YANGICHA PEDAGOGIKA VA KELAJAK KASBLARIGA YO ‘NALTIRISH. ОБРАЗОВАНИЕ НАУКА И ИННОВАЦИОННЫЕ ИДЕИ В МИРЕ, 13(7), 224-228.

M.M. Tojiyeva. (2023). KICHIK BIZNESNI RIVOJLANTIRISHNING MAMLAKAT IJTIMOIY- IQTISODIY HAYOTIDAGI AHAMIYATI. QO‘QON UNIVERSITETI XABARNOMASI, 9(9), 126–130. https://doi.org/10.54613/ku.v9i9.852

Tojiyeva, M. M. (2023). KICHIK BIZNESNI RIVOJLANTIRISHNING MAMLAKAT IJTIMOIY-IQTISODIY HAYOTIDAGI AHAMIYATI. QO ‘QON UNIVERSITETI XABARNOMASI, 9, 126-130.

Qizi, T. M. M. (2022). The importance of studying φ (x)= cos (ax2) functions in strengthening students’ knowledge of trigonometric functions. ACADEMICIA: An International Multidisciplinary Research Journal, 12(5), 147-151.

qizi Azimova, T. E. (2023). ECONOMIC DIRECTIONS IN TEACHING MATHEMATICS. Intent Research Scientific Journal, 2(4), 54-56.

Kamoldinovna, S. Y. (2022). A boundary matter for a fifth-order private derivative differential equation with two double and one simple real characteristic. Eurasian Research Bulletin, 4, 45-47.10:36

Tojiyeva, M. M., & Raxmonova, N. V. (2022). METRIKA AKSIOMALARINI TEKSHIRISHDA QULAY METODLAR. Yosh Tadqiqotchi Jurnali, 1(5), 320-326.