ОБРАЗОВАНИЕ НАУКА И ИННОВАЦИОННЫЕ ИДЕИ В МИРЕ
https://scientific-jl.org/obr
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THE SCIENTIFIC-THEORETICAL FOUNDATIONS OF USING
ARTIFICIAL INTELLIGENCE-BASED BLENDED LEARNING METHOD
The University of Public
Safety of the Republic of Uzbekistan
The department of language learning
Islomkhujayeva Sayyora
Annotation
: This article explores the scientific-theoretical foundations of using
AI-based blended learning, highlighting its pedagogical value, technological
underpinnings, and practical applications in modern classrooms.This hybrid approach
has proven to be highly effective, especially in language learning and higher education,
as it offers personalized, flexible, and interactive learning experiences.
Keywords:
Artificial Intelligence, Blended Learning, Higher Education,
Language Teaching, Pedagogical Technology, Adaptive Learning, Machine Learning,
Innovation in Education, Digital Tools, Learning Efficiency.
In the digital era, the integration of Artificial Intelligence (AI) in education has
brought transformative changes to teaching and learning practices. One such
innovation is the application of AI within the blended learning method, which
combines traditional face-to-face instruction with digital learning tools. Blended
learning is rooted in constructivist learning theory, which emphasizes active
knowledge construction through experience and interaction. The Zone of Proximal
Development (ZPD) proposed by Vygotsky also supports blended learning by
highlighting the role of scaffolding and guided instruction, both of which can be
enhanced by AI tools. In addition, Bloom's Taxonomy aligns well with AI-based
platforms that support different cognitive levels—from remembering and
understanding to analyzing and creating.
AI brings several capabilities to education, such as:
1.
Machine Learning algorithms that analyze student performance and
adapt content accordingly.
ОБРАЗОВАНИЕ НАУКА И ИННОВАЦИОННЫЕ ИДЕИ В МИРЕ
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2.
Natural Language Processing (NLP) for grammar checking,
translation, and automated feedback.
3.
Speech recognition systems that aid in pronunciation practice and
listening comprehension.
For instance, AI-powered platforms like Duolingo, Coursera, and ChatGPT use
real-time learner data to personalize instruction, provide immediate feedback, and
suggest learning paths based on individual needs.
When AI is integrated into blended learning, it enhances both the digital and
traditional elements. For example:
1)
Flipped classrooms can be supported by AI systems that deliver pre-
class materials and assess understanding before face-to-face lessons.
2)
Virtual teaching assistants powered by AI can answer student
questions 24/7, allowing teachers to focus on more complex tasks.
3)
Learning Management Systems (LMS) integrated with AI (e.g.,
Moodle with AI plugins) track progress, detect learning gaps, and suggest
remedial materials.
At the Republic of Uzbekistan MG Public Security University, cadets undergo
English language training using a blended model enriched with AI tools. Lessons
incorporate: warm-up activities via gamified apps, vocabulary practice using AI-based
flashcard generators, listening tasks powered by speech-recognition software,
automated writing evaluations using tools like Grammarly, speaking practice through
conversational bots and virtual role-play. This approach not only increases learner
motivation but also ensures consistent language exposure and individualized feedback.
Despite its numerous advantages, AI-based blended learning also faces several
significant challenges that must be addressed for effective implementation. One of the
primary concerns is data privacy and ethics, particularly regarding the collection,
storage, and usage of learner data by AI systems. Without robust safeguards, there is a
risk of sensitive information being misused or inadequately protected. Another critical
ОБРАЗОВАНИЕ НАУКА И ИННОВАЦИОННЫЕ ИДЕИ В МИРЕ
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issue is the digital divide, which refers to unequal access to digital devices and stable
internet connections among learners, especially in rural or economically disadvantaged
areas. This gap can hinder the equitable distribution of educational opportunities.
Additionally, teacher readiness remains a persistent barrier, as many educators may
lack the necessary training or confidence to integrate AI technologies into their
teaching practices. Continuous professional development and support are essential to
help educators adapt to this evolving landscape. Cultural sensitivity also poses a
challenge, as AI tools are often developed within specific cultural and linguistic
contexts that may not align with the local values, customs, or languages of the learners.
These concerns highlight the need for comprehensive strategic planning, strong
government support, and ongoing academic and technological research to ensure that
AI-based blended learning is implemented ethically, inclusively, and effectively.
Conclusion
The scientific-theoretical foundations of AI-based blended learning underscore its
potential to revolutionize education, particularly in language instruction and
professional military training. By merging pedagogy with technology, it enables
personalized, efficient, and scalable learning. However, successful implementation
depends on addressing ethical, infrastructural, and professional challenges. Continued
innovation, teacher training, and evidence-based research are vital for maximizing the
benefits of this educational paradigm.
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