ILMIY TADQIQOTLAR VA ULARNING YECHIMLARI JURNALI
JOURNAL OF SCIENTIFIC RESEARCH AND THEIR SOLUTIONS
VOLUME 4, ISSUE 01, MART 2025
WORLDLY KNOWLEDGE NASHRIYOTI
worldlyjournals.com
11
ARTIFICIAL INTELLIGENCE IN EDUCATION: HELPER OR RIVAL FOR
TEACHERS
Saparov Bobur
Assistant of the Department of Engineering Graphics and Mechanics
Rakhimov Murodullo
Doctor of Philosophy in Technical Sciences, Associate Professor, Department of Engineering
Graphics and Mechanics
Sokhibov Kholruzi
Trainee teacher of the Department of Automation and Digital Control
Tashkent Instıtute of Chemıcal Technology
Khalmuratova Zebo
"Science and Development" State Enterprise
2nd year basic doctoral student
Sultonova Husnora
Student of group 22-17
Abstract:
Artificial intelligence (AI) is transforming the education sector by automating
administrative tasks, enhancing personalized learning, and optimizing the efficiency of
knowledge acquisition. However, concerns persist regarding its potential impact on educators,
particularly regarding job security and pedagogical effectiveness. This study explores whether
AI functions as an assistant or a competitor to teachers. Through a qualitative analysis of
academic literature, expert insights, and empirical case studies, this research examines AI’s
contributions to education, its limitations, and its broader implications for the teaching
profession. The findings suggest that AI enhances efficiency in lesson delivery, assessment
automation, and adaptive learning while lacking the human-centric qualities necessary for
fostering emotional intelligence, creativity, and mentorship. The study concludes that AI should
be embraced as a complementary tool rather than a replacement for human instructors, with a
focus on ethical and pedagogical considerations in its implementation.
Keywords:
Artificial Intelligence, Education, Personalized Learning, Teacher Assistance, AI
Integration, Pedagogical Innovation.
1.
Introduction
The rapid advancement of artificial intelligence (AI) has led to significant changes in various
industries, including education. AI-driven technologies, such as intelligent tutoring systems,
automated grading software, and adaptive learning platforms, are increasingly being adopted in
educational institutions worldwide. These innovations promise to enhance learning outcomes by
providing personalized instruction, automating routine tasks, and offering real-time feedback.
However, the growing reliance on AI raises critical questions about its role in education: Does
AI serve as a beneficial assistant to teachers, or does it pose a threat to their professional roles?
This study aims to explore the potential benefits and challenges associated with AI in education,
focusing on its impact on teachers and students alike.
2.
Methodology
This research employs a qualitative approach, analyzing peer-reviewed academic literature,
Scopus-indexed journal articles, and empirical case studies related to AI in education. A
comparative analysis is conducted between AI-driven teaching methodologies and traditional
pedagogical approaches to assess their effectiveness. Data is sourced from educational
technology reports, surveys conducted among educators and students, and real-world
implementations of AI tools in schools and universities. The research methodology involves
content analysis, expert interviews, and case study evaluations to provide a comprehensive
understanding of AI’s role in the educational landscape.
3.
Results
ILMIY TADQIQOTLAR VA ULARNING YECHIMLARI JURNALI
JOURNAL OF SCIENTIFIC RESEARCH AND THEIR SOLUTIONS
VOLUME 4, ISSUE 01, MART 2025
WORLDLY KNOWLEDGE NASHRIYOTI
worldlyjournals.com
12
The study identifies several key contributions of AI in the education sector:
Personalized Learning:
AI algorithms analyze student performance data to provide
customized learning experiences, addressing individual strengths and weaknesses.
Automated Assessment and Feedback:
AI-powered tools streamline grading processes,
reducing the administrative burden on teachers and ensuring timely, objective evaluations.
Real-Time Knowledge Access:
AI facilitates instant access to vast educational resources,
enabling students to supplement their learning beyond traditional classroom settings.
Language Learning Enhancement:
AI-driven applications, such as chatbots and speech
recognition software, support language acquisition through interactive exercises and adaptive
learning models.
Smart Content Creation:
AI tools generate and curate educational materials, including
video lectures, interactive simulations, and digital textbooks, improving accessibility to high-
quality learning resources.
However, despite these advantages, the study also highlights critical limitations of AI in
education:
Lack of Human Interaction:
AI lacks the emotional intelligence and mentorship
capabilities essential for fostering creativity, critical thinking, and social development in students.
Over-Reliance on Technology:
Excessive dependence on AI-driven tools may lead to
reduced teacher engagement, diminishing the human element in education.
Job Security Concerns:
While AI can enhance efficiency, some educators fear that
automation may replace certain teaching roles, leading to workforce displacement.
Ethical and Bias Issues:
AI systems may inadvertently reinforce biases present in training
data, potentially leading to unfair assessment outcomes and inequitable learning experiences.
4.
Discussion
The findings suggest that AI in education should not be perceived as a competitor to teachers but
rather as an assistive tool that enhances pedagogical efficiency. AI can handle repetitive tasks,
such as grading and data analysis, allowing educators to focus on interactive and high-order
teaching activities. Moreover, AI-driven insights can help teachers identify students who require
additional support, enabling early intervention and personalized instruction. Nonetheless, the
integration of AI into education must be approached with caution. Policymakers and educational
institutions must ensure that AI complements, rather than replaces, human instruction. The
ethical implications of AI, including data privacy, algorithmic bias, and accessibility, must also
be addressed to ensure equitable learning opportunities for all students.
To optimize the benefits of AI while mitigating its challenges, it is essential to establish
collaborative frameworks where AI and human educators work in tandem. Teacher training
programs should incorporate AI literacy to equip educators with the necessary skills to leverage
AI effectively in the classroom. Additionally, interdisciplinary research involving education
specialists, AI developers, and policymakers is needed to create AI solutions that align with
pedagogical best practices.
5.
Conclusion
AI is reshaping the educational landscape by offering innovative solutions that enhance
personalized learning, streamline assessment processes, and improve access to information.
However, it cannot replace the human aspects of teaching, such as emotional intelligence,
mentorship, and ethical guidance. The future of AI in education lies in its integration as a
complementary tool that supports educators rather than displaces them. By fostering a balanced
approach that combines technological advancements with human expertise, AI can serve as a
catalyst for improving educational quality and accessibility. Future research should focus on
developing AI-driven educational frameworks that prioritize inclusivity, ethical considerations,
and pedagogical effectiveness.
References
ILMIY TADQIQOTLAR VA ULARNING YECHIMLARI JURNALI
JOURNAL OF SCIENTIFIC RESEARCH AND THEIR SOLUTIONS
VOLUME 4, ISSUE 01, MART 2025
WORLDLY KNOWLEDGE NASHRIYOTI
worldlyjournals.com
13
1. Anderson, C. A., & Dill, K. E. (2000). Video games and aggressive thoughts, feelings, and
behavior in the laboratory and in life. Journal of Personality and Social Psychology, 78(4), 772–
790.
2, Baker, R. S. J. d., & Inventado, P. S. (2014). Educational Data Mining and Learning Analytics.
In Learning Analytics (pp. 61–75). Springer.
3. Guskey, T. R. (2003). How Classroom Assessments Improve Learning. Educational
Leadership, 60(5), 6-11.
4. Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial Intelligence in Education: Promises and
Implications for Teaching and Learning. Center for Curriculum Redesign.
5. Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence Unleashed: An
Argument for AI in Education. Pearson.
6. Selwyn, N. (2019). Should Robots Replace Teachers? AI and the Future of Education. Polity
Press.
7. Siemens, G. (2013). Learning Analytics: The Emergence of a Discipline. American
Behavioral Scientist, 57(10), 1380–1400.
