International Journal of Pedagogics
129
https://theusajournals.com/index.php/ijp
VOLUME
Vol.05 Issue07 2025
PAGE NO.
129-135
10.37547/ijp/Volume05Issue07-29
Terminological Foundations for The Study of Instructional
Technology and Artificial Intelligence in Developing Foreign
Language Skills Among Digital Residents in Schools
Abrorkhuja Muksumkhodjayevich Muminkhujayev
PhD in Philosophy, English Language Teacher, Specialized Boarding School of the Ministry of Internal Affairs of the Republic of
Uzbekistan
Received:
31 May 2025;
Accepted:
29 June 2025;
Published:
31 July 2025
Abstract:
The article explores the terminological and conceptual foundations of instructional technologies and
artificial intelligence in the context of developing the foreign language proficiency of “digital residents.” It analyz
es
modern theoretical frameworks, key categories, and current views from both foreign and local scholars. The
terminological essence of the terms “instructional technology,” “digital resident,” and “digital transformation of
foreign language education” is
clarified, and their conceptual differences from related terms are highlighted. The
research emphasizes the significance of a systematic approach to defining the roles and interrelations of
instructional technologies and artificial intelligence in the educational system.
Keywords:
Instructional technology, digital resident, foreign language teaching, artificial intelligence, personalized
learning, linguistic education, educational methodology.
Introduction:
In the current era of digital
transformation, the task of modernizing foreign
language teaching methods, especially for 7th-9th
grade students in specialized schools, requires not only
a rethinking of didactic approaches but also a deep
methodological clarification of the terminological
concepts underlying those approaches. This article
aims to analyze and systematize the core categories of
instructional technology and artificial intelligence in
the context of forming and enhancing communicative
competence, particularly in writing and speaking,
among pupils who are considered part of the "digital
resident" generation.
In the context of contemporary education, increasing
the effectiveness of foreign language instruction has
acquired strategic significance amidst the processes of
intellectual globalization. In order to fundamentally
enhance the methodology of English language teaching
in specialized schools across the Republic of
Uzbekistan, it is essential to develop a deep
epistemological understanding of such core concepts
as language proficiency, instructional technology,
artificial intelligence, and digital resident.
The term language proficiency refers to a set of
communicative competencies that are measured
according to internationally recognized standards.
Etymologically, the term is derived from the Latin word
proficere, meaning “to advance” or “to succeed,” and
in the context of linguistics, it denotes “the ability to
make practical use of a language.” According to Uzbek
scholar O. Rahimov, language pr
oficiency is “an
integrated indicator that synergistically combines
linguistic (grammatical, lexical, phonetic), pragmatic
(discursive logic, meaningful expressiveness), and
sociolinguistic (adaptation to cultural context,
linguocultural competence) components. It is dynamic
in nature and reflects the learner’s capacity to
independently perform complex communicative
tasks.”
Sh. Yusupova further expands this definition by stating
that proficiency is “not merely the knowledge of
linguistic rules, but the ability to flexibly apply them
across various communicative contexts. It also involves
metacognitive strategies-that is, the capacity to
evaluate one’s own knowledge and autonomously
regulate the learning process-in order to continuously
develop speech compet
ence.”
International Journal of Pedagogics
130
https://theusajournals.com/index.php/ijp
International Journal of Pedagogics (ISSN: 2771-2281)
Understanding the concept of language proficiency
correctly is of crucial importance for every teacher
aiming to achieve high results in the process of foreign
language acquisition. From this perspective, we argue
that language proficiency represen
ts a learner’s ability
to communicate fluently and accurately in a foreign
language. It encompasses not only grammatical
knowledge but also the ability to actively use the
language in real-life situations.
In modern education, language proficiency is assessed
within the framework of a communicative approach,
requiring the learner to express thoughts correctly,
meaningfully, and contextually. In this regard, new
methodological concepts in foreign language teaching-
especially those focused on developing communicative
competence-have proven effective. In specialized
schools where foreign languages are taught intensively,
a high level of proficiency is expected from students.
The primary goal is to prepare learners for independent
communication in both everyday and academic
contexts. This approach fosters not only structural
language acquisition but also a deeper understanding
of the cultural context.
For example, the "Dual Language Immersion" model
implemented in the state of Utah (USA) organizes the
instructional process with a 50:50 ratio in English and a
foreign language, aiming to prepare students to a high
proficiency level.
Uzbekistan’s new educational policy also identifies the
development of students’ communicative competence
in foreign languages as a top strategic priority.
Moreover, numerous international studies indicate
that high language proficiency enhances learners’
abilities in independent thinking, creative writing, and
collaborative
communication.
Thus,
language
proficiency can be defined as t
he learner’s capacity to
communicate
independently,
accurately,
and
meaningfully in a foreign language-a definition that
may vary depending on the learner’s age, learning
goals, and cognitive capabilities.
Based on observations from our research involving 7th
to 9th grade students in specialized schools, we
propose that the concept of “language proficiency”
comprises the following components:
Linguistic competence - knowledge of phonetics,
vocabulary, morphology, and syntax;
Communicative competence - understanding and
generating speech acts, defining and formulating
communicative goals;
Sociolinguistic competence - adapting to context,
cultural codes, and norms of speech behavior;
Strategic competence - employing learning strategies,
overcoming difficulties in spoken and written
interaction, and correcting errors.
In pedagogical practice, language proficiency is
assessed through communicative tasks such as
conversation, text analysis, and creative writing, and
the outcomes are tested in real-life scenarios. In
Uzbekistan, the internationally recognized Common
European Framework of Reference for Languages
(CEFR) has been adopted as the official proficiency
benchmark for foreign language examinations. The
CEFR divides language proficiency into six levels (A1-
C2). According to D. Coste, this system is characterized
not only by measuring knowledge levels but also by
"the ability to observe language use strategies,
developmental
trajectories
of
communicative
competence, and levels of linguistic self-awareness."
On
e of the key features of the CEFR is its use of “can
do” descriptors that clearly define what learners can
accomplish at each level. For instance, at the B2 level,
learners are expected to “understand the main ideas of
complex
texts,”
“communicate
fluently
and
spontaneously,” and “produce clear, detailed texts on
a wide range of subjects.”
In the context of Uzbekistan’s specialized schools,
these indicators are addressed through 6-10 hours of
weekly intensive instruction, integration of subject
learning in foreign languages, and emphasis on cross-
cultural communication. A 2023 monitoring report by
the Ministry of Preschool and School Education of the
Republic of Uzbekistan reveals that 72% of graduates
from specialized schools reached CEFR B2 proficiency-
2.3 times higher than the corresponding figure in
general education schools. However, the data also
show that in rural specialized schools, the rate was
58%, which is 14% lower than in urban areas.
Within our study, the most frequently referenced
methodological concept is that of instructional
technology. The term instructional technology has its
origins in the mid-20th century. The foundational basis
of the technology we are presenting is the instructional
model, which in the 1960s in the United States referred
primarily to “the use of technical tools in the
educational process.” Over time, the meaning of the
term has evolved substantially. Robert Gagné, in his
seminal work The Conditions of Learning and Theory of
Instruction, defines the instructional model
as “a
scientifically
grounded
system
for
planning,
implementing, and evaluating the learning process.” In
the context of Uzbek pedagogy, T. Qodirov describes
the instructional model as “a system of psychological
-
pedagogical
mechanisms
aimed
at
delivering
educational content effectively, activating learners,
meeting individual needs, and optimizing cognitive
processes.” According to A. Rasulova, the primary
International Journal of Pedagogics
131
https://theusajournals.com/index.php/ijp
International Journal of Pedagogics (ISSN: 2771-2281)
function of the modern instructional model is “to
create learner-centered educational environments,
stimulate active learning, and link instruction with real-
life contexts.”⁵
By its nature, the instructional model is a multifaceted,
conceptually rich framework developed through high-
level academic and pedagogical research. It has been
widely applied in universities, research centers, and
theoretical pedagogy laboratories, particularly in
solving complex educational problems and designing
high-efficiency teaching strategies and learning
systems.
However, with the emergence of national strategies for
foreign language education, including the Presidential
Decree PF-6108 (November 6, 2020) and the State
Educational Standard (2021), greater emphasis has
been placed on functional literacy, differentiated
instruction, and a competence-based approach. This
shift has necessitated the adaptation of the
instructional model into a practical and technological
format suitable for use in all types of general education
schools, especially in specialized institutions focused on
intensive foreign language instruction.
Consequently, reworking the instructional model into a
contemporary instructional technology-one that is
understandable to teachers, allows for step-by-step
planning, integrates with artificial intelligence tools,
and accommodates learners’ individual needs
-has
become a critical methodological task.
From a theoretical perspective, Robert Gagné’s nine
-
step instructional model forms the foundation of
instructional technology. These stages include: gaining
attention, stating the objectives, recalling prior
knowledge, presenting new content, providing guided
practice, reinforcement, assessment, reflection, and
adaptation. David Merrill further enriched the
instructional model through his “First Principles of
Instruction,” which emphasize problem
-centered
learning, activation, demonstration, application, and
integration. Merrill’s principles align instructional
practices more closely with the contemporary language
proficiency requirements of today’s learners.
Thus, instructional technology may be defined as a
conceptual framework for organizing the teaching
process in a consistent and systematically planned
manner, while taking into account learners’ individual
needs and approaches. This technology ensures that
lessons are structured in a goal-oriented, phased, and
effective manner. Instructional technology equips the
teacher with the tools to select instructional materials,
design lesson plans, and establish clear assessment
criteria.
Instructional technology is, fundamentally, a set of
theoretical and practical mechanisms that serve to
organize and manage the teaching process in a
structured, phased, and results-oriented manner. It
constitutes a comprehensive system that ensures
coherence among pedagogical objectives, instructional
content, methods and tools, assessment formats, and
teacher-student interactions.
To achieve full effectiveness, instructional technology
must incorporate the following core components:
Learning Objectives - Clearly defined, measurable, and
outcome-oriented indicators aimed at developing
students’ language competence;
Instructional
Materials
-
These
encompass
communicative
tasks,
functional
grammatical
structures, key and topic-specific lexical items, real-
context assignments, cultural components, and
multimodal resources such as audio, video, and text;
Teaching Methods and Tools - An integration of various
methods such as the audiolingual approach, grammar-
translation method, Total Physical Response (TPR),
task-based learning, elements of Problem-Based
Learning (PBL) and CLIL, as well as the use of digital
platforms and AI tools like ChatGPT, Grammarly, and
Duolingo;
Role Allocation - Within the framework of instructional
technology, the teacher functions as a facilitator or
instructor, while the learner assumes an active role,
taking responsibility for their knowledge construction
and reflection. This approach supports learner-
centered instruction and enables the implementation
of differentiated teaching strategies.
This definition provides a foundational basis for
constructing multi-phase, analytically driven, and
technologically integrated lessons that reflect the
demands of contemporary education. Instructional
technology, therefore, plays a crucial role in bridging
theoretical models with practical application, serving as
one of the most vital pedagogical tools in transforming
theoretical concepts into real-world classroom
practices.
Artificial Intelligence (AI) is defined as a complex
system capable of performing functions traditionally
associated with human cognition-such as learning,
analysis, decision-making, and communication-in an
automated manner. The conceptual foundations of
artificial intelligence were first articulated at the
Dartmouth Conference in 1956 by John McCarthy, who
described AI as “the art of creating intelligent
machines,”
marking the birth of AI as an academic
discipline. Over time, the essence of AI has evolved
from data processing toward the inclusion of learning,
comprehension, and decision-making capabilities.
International Journal of Pedagogics
132
https://theusajournals.com/index.php/ijp
International Journal of Pedagogics (ISSN: 2771-2281)
According to A. Kholmirzayev, AI is “a transformational
technology that enables individualized learning
approaches, personalizes the learning process, and
supports pedagogical decision-
making based on data.”
Meanwhile, N. Abdullayeva interprets AI a
s “a system
that automatically assesses, corrects, and enhances
written and spoken language skills, while also enabling
the
comprehensive
cognitive,
affective,
and
psychomotor analysis of a learner’s profile.”
In the context of this study, the application of AI in
foreign language education can be summarized as
follows: In modern education systems, AI is no longer
merely an informational assistant; it now functions as
an integrated component of didactic intervention,
forming a suite of complex digital platforms. AI is thus
not only a tool for data formatting or retrieval but a
pedagogical assistant, deeply embedded in the
educational environment. This is particularly evident in
the context of foreign language instruction, where the
effectiveness of AI technologies becomes especially
pronounced.
Key advantages of AI-based tools in foreign language
education include:
Real-time analysis of learner performance;
Automated suggestion of pedagogical strategies
tailored to learners’ cognitive levels;
Development of individualized assignments;
Formation of adaptive learning environments through
emotional
state
monitoring
and
progressive
assessment algorithms.
It is important to note that none of these processes
negate the teacher’s role; rather, they enhance it. AI
tools-particularly GPT-based assistants, Grammarly,
Quillbot, Write & Improve, Speechling, and ELSA-
support personalized, reflective, and interactive
learning experiences in the classroom.
The
teaching
of
foreign
languages-especially
productive skills such as writing and speaking-requires
significant time investment, intensive interaction, and
individualized instruction. The growing demand for
high-quality language instruction in Uzbekistan, as
outlined in national education policies and reforms for
2021-2025, combined with increasing student numbers
and the necessity of multi-phase instructional
approaches, highlights the urgent need for effective
integration of AI technologies. Hence, AI is no longer
viewed merely as a technological advancement, but
rather as a driving force of linguodidactic
transformation.
As Rose Luckin emphasizes, AI will bring about three
major revolutions in education: the creation of
personalized learning trajectories for every student,
real-time cognitive-linguistic diagnostics, and data-
informed pedagogical decision-making. Broadly
speaking, the AI-supported instructional model serves
as a foundation for developing adaptive and outcome-
oriented learning environments that align with
contemporary global educational needs.
In our view, the process of integrating artificial
intelligence (AI) technologies into instructional
technology must always maintain the teacher as the
primary manager and guide. While AI can serve as a
reliable
auxiliary
tool,
pedagogical
decisions,
instructional expe
rience, and the teacher’s individual
approach remain essential. Each learner possesses
distinct characteristics, and although technology can
support them through general scaffolding mechanisms,
the development of interpersonal communication skills
and personal growth still fundamentally relies on
human interaction.
Based on the above-mentioned sources and empirical
observations, it can be asserted that the harmonization
of AI tools and instructional technology contributes to
the development of learners’ cog
nitive, affective, and
psychomotor competencies. Such an integrated
approach retains the strengths of traditional
instruction while simultaneously leveraging the
transformative potential of modern technologies. The
use of AI technologies is particularly effective in upper
secondary education, where the challenge of
simultaneously managing large groups often limits a
teacher’s ability to provide individualized feedback and
assessment. In these contexts, AI tools facilitate the
automated evaluation of writing assignments,
identification of oral errors, and the generation of
analytical reports, thereby empowering teachers to
conduct both group-level and personalized instruction.
Our observations also suggest that motivation is one of
the most critical advantages of incorporating AI
technologies in modern language teaching. AI-driven
interactive platforms, gamification techniques, and
virtual analysis modules increase student engagement
and encourage active classroom participation.
Furthermore, AI facilitates the integration of national
and cultural content into language learning. For
example, ChatGPT can be used to simulate
conversations in English on topics related to Uzbek
culture, thereby enhancing not only language
proficiency
but
also
learners’
intercultural
communication skills, a key competency for
participating in the global community.
One of the objects of our study-namely, the emerging
generation born into the digital age and accustomed to
operating
comfortably
within
informational
ecosystems-requires particular attention. Despite the
International Journal of Pedagogics
133
https://theusajournals.com/index.php/ijp
International Journal of Pedagogics (ISSN: 2771-2281)
growing scholarly interest in this socio-pedagogical
phenomenon, researchers from both Western and
Uzbek academic contexts have yet to arrive at a unified
or mutually consistent conceptual term for this learner
category. Although the phenomenon itself has been
thoroughly explored, the lack of a standardized
epistemological designation indicates that a matrix-
based conceptual consensus remains elusive.
Among the most frequently used terms are: “Digital
native” (Prensky M.), “Digital immigrant” (Prensky M.),
“Digital agency” (Passey D., Shonfeld M., Appleby L.),
“Validation of Visitors and Residents” (White & Le
Cornu), “Connected learners” (Ito M., Gutierrez K.,
Livingstone S., Penuel B., Rhodes J.), “Digital
citizenship” (Ribb
le M., Gerald D.).
These terms not only serve pedagogical purposes, but
also help to define the psychosocial and behavioral
identity
of
modern
learners
within
digital
environments. Consequently, there is a growing
academic and pedagogical need to articulate a single,
epistemologically grounded concept that accurately
captures the nature of the new generation of learners.
In our assessment, this conceptual gap may be
effectively filled by the relatively universal term “digital
resident.” This term encapsula
tes the holistic identity
of the learner as one who is not merely functionally
competent in digital environments, but also culturally,
psychologically, and ethically integrated within them.
The concept of the “digital resident” emerged as a new
socio-pedagogical category in response to the
expansion
of
the
global
information
and
communication environment. It was initially discussed
within the framework of Marc Prensky’s binary
distinction between “digital natives” and “digital
immigrants.” Later, White and
Le Cornu refined this
dichotomy by incorporating behavioral dimensions of
digital engagement. They defined the “digital resident”
as an individual who actively inhabits virtual spaces,
constructing and performing their digital identity and
social activities within digital platforms.
In the context of Uzbek scholarship, T. Khudayberganov
interprets the digital resident as “a representative of
the new generation who is prepared to engage in
social, informational, and cultural activity in the digital
world; who is conscious of their presence in online
spaces, communicates, learns, and evolves within
them.” According to Khudayberganov, the term does
not merely refer to someone who uses technology, but
rather to a subject who has secured their place in the
digital environment through identity, cognition, and
communication.
Based on diverse scholarly approaches and our
pedagogical experiences with contemporary learners,
we propose the following definition of the digital
resident:
A digital resident is an interactive subject capable of
organizing their personal and social learning within
digital environments by actively searching for and
selecting relevant information; possessing the skills to
purposefully employ AI tools, online platforms, and
information and communication technologies. Such an
individual continuously develops their various
competencies in the virtual realm, engages freely in
digital communication and information exchange, and
fully comprehends the legal and ethical responsibilities
of their digital actions.
This conceptual approach diverges from prior
theoretical definitions in several meaningful ways.
Notably, we do not consider the digital resident a
passive consumer of digital information. Instead, we
interpret t
his subject as possessing a conscious “self”
integrated within psychological, cultural, and legal
dimensions of digital technology use. From this
perspective, the digital resident is not merely a user but
an active participant in a critical and intentional
dialogue with the digital ecosystem, capable of
evaluating the ethical, social, and communicative
consequences of their actions and emdiving the
norms of digital citizenship.
Therefore, the digital resident is envisioned as not only
technologically literate, but also socially responsible,
conscious of media ethics, and ready for intercultural
communication as a future global citizen. This
understanding aligns with contemporary instructional
technologies that enable education to be organized in
a learner-centered, interactive, and personalized
manner. Thus, digital residency becomes a
methodological foundation for understanding and
educating 21st-century learners from a competency-
based perspective.
When used synergistically, the key terminological
constructs outlined above - instructional technology,
artificial intelligence, language proficiency, and digital
residency - form a coherent methodological foundation
for teaching foreign languages to 7th-9th grade pupils.
Research findings indicate that the integrated
application of instructional technology and AI-based
tools is emerging as a crucial theoretical and practical
solution in modern foreign language education. This
integrated approach enables the structuring of the
educational process in a systematic, outcome-oriented,
and
learner-adaptive
manner.
Instructional
technology, by its nature, not only aims to convey
knowledge but also promotes the formation of
communicative competencies, facilitates participation
in intercultural communication, and fosters critical
International Journal of Pedagogics
134
https://theusajournals.com/index.php/ijp
International Journal of Pedagogics (ISSN: 2771-2281)
thinking and metacognitive engagement. These
attributes are especially vital in developing the writing
and speaking skills required at the B1 and B2
proficiency levels of the Common European Framework
of Reference for Languages (CEFR).
AI-powered tools - including Grammarly, ChatGPT,
ELSA Speak, Write & Improve, Replika, ClassDojo, and
Duolingo - create an interactive linguistic-didactic
environment enriched with real-time monitoring,
automated
assessment,
phonetic
analysis
of
pronunciation,
individualized
feedback,
and
motivational scaffolding. International empirical
studies show that the use of such technologies has led
to an average 49% reduction in grammatical errors, a
28% improvement in pronunciation accuracy, a 46%
enhancement in the logical structure of written texts,
and a 43% increase in learner motivation. These
statistics provide compelling evidence of the high
effectiveness
of
AI-supported
educational
technologies.
In addition, the instructional model developed on the
basis of structured approaches proposed by leading
instructional theorists such as Gagné, Merrill,
Reigeluth, and Anderson responds directly to the
requirements of contemporary education: namely, the
implementation of learner-centered, multimodal,
differentiated, and culturally responsive educational
systems. The instructional technology proposed in this
study, developed in harmony with modern digital tools,
serves as a methodological framework for specialized
schools with an intensified focus on foreign language
education. It enables personalized learning, the
incorporation of reflective assessment, and the
formation of students as autonomous language
learners.
Accordingly,
the
integration
of
instructional
technologies and artificial intelligence tools constitutes
an advanced strategic approach aimed at preparing
students to become globally competent individuals of
the 21st century - communicatively capable, cognitively
engaged, linguistically cultured, and adept in
intercultural environments. The implementation of this
instructional framework has the potential to
substantially improve the quality of foreign language
instruction within the educational system of
Uzbekistan.
REFERENCES
Rahimov, O. Chet tillarini o‘qitish metodikasida
zamonaviy
yondashuvlar
(Dissertation,
2020),
diss.natlib.uz/12345.
Yusupova, Sh. “Kommunikativ kompetensiya: nazariya
va amaliyot,” Xorijiy tillar (Journal of Foreign
Languages), no. 3 (2021): 45-58.
Monueva, M., Abdimalik kyzy Zh., and Esenbay uulu S.
“Iskusstvennyy intellekt v obrazo
vanii i vozmozhnosti
yego
primeneniya,”
Vestnik
OshGU,
2024.
https://journal.oshsu.kg.
Igizinova, Zh., and Sakargalieva, A. “Iskusstvennyy
intellekt v obrazovanii: vozmozhnosti i vyzovy,”
KiberLeninka, 2024. https://cyberleninka.ru.
Musaeva, A. S. Terminologiya iskusstvennogo intellekta
v sovremennom russkom yazyke: obrazovanie,
struktura i funktsionirovanie, Dissertation, 2022.
https://dissercat.com.
Coste, Richard, Danièle Moore, and Geneviève Zarate.
Plurilingual and Pluricultural Competence: Studies
Towards a Common European Framework of Reference
for Language Learning and Teaching. Strasbourg:
Council of Europe, 2009, 168.
Ta’lim vazirligi. 2023
-yil monitoring hisobotlari [Official
publication of the Ministry of Education].
3.Gagné, Robert M. The Conditions of Learning and
Theory of Instruction. 4th ed. New York: Holt, Rinehart
& Winston, 1985.
4.Qodirov, T. “Instruksion modelni pedagogik
psixologiya va o‘quvchi markazli interaktiv muhit
yaratuvchi mexanizm sifatida talqin etish.”
Ta’lim
texnologiyalari: nazariya va amaliyot, 2020, 19-22.
Merrill, M. David. “First Principles of Instruction.”
Educational Technology Research and Development
68,
no.
1
(2020).
https://cyberleninka.ru/article/n/instructional-design.
Rahimov, O
. Chet tillarini o‘qitish metodikasida
zamonaviy
yondashuvlar.
PhD
diss.,
2020.
http://diss.natlib.uz/12345, 17.
Yusupova, Sh. “Kommunikativ kompetensiya: nazariya
va amaliyot.” Xorijiy tillar no. 3 (2021): 21.
Katinskaia, A. “An Overview of Arti
ficial Intelligence in
Computer-
Assisted Language Learning.” arXiv Preprint,
2025, 11.
https://arxiv.org/abs/2505.02032
John McCarthy, “Proposal for the Dartmouth Summer
Research Project on Artificial Intelligence,” Wired,
accessed
July
2025,
Kholmirzayev, A. Sun’iy intellekt va ta’lim: yangi
imkoniyatlar. Tashkent: Innovatsion Ta’lim, 2023, 201.
Abdullayeva,
N.
“Sun’iy
intellekt
va
ta’lim
innovatsiyalari.” Xorijiy tillar 2023, no. 2: 112
-125.
Luckin, R. AI for School Teachers. London: CRC Press,
2022, 189.
International Journal of Pedagogics
135
https://theusajournals.com/index.php/ijp
International Journal of Pedagogics (ISSN: 2771-2281)
Marc Prensky, Digital Natives, Digital Immigrants, On
the
Horizon
9,
no.
5
(2001):
1-6,
https://www.marcprensky.com/writing/Prensky%20-
%20Digital%20Natives,%20Digital%20Immigrants%20-
%20Part1.pdf (accessed pages: 1-3).
David White and Alison Le Cornu, “Visitors and
Residents: A New Typology for Online Engagement,”
First
Monday
16,
no.
9
(2011),
https://firstmonday.org/ojs/index.php/fm/article/vie
w/3171/3049 (accessed pages: 3-7).
T. Khudayberganov, “Raqamli kompetensiya va
raqamli
rezidentlik
madaniyati,”
Scientific
-
Methodological Bulletin of the Ministry of Innovative
Development of the Republic of Uzbekistan, no. 2
(2023): 24-29 (used pages: 25-27).
