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ZENODO
Dataset . 2025
Data sources: ZENODO
ZENODO
Dataset . 2025
Data sources: Datacite
ZENODO
Dataset . 2025
Data sources: Datacite
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INTEGRATION OF ARTIFICIAL INTELLIGENCE TECHNOLOGIES INTO HIGHER EDUCATION IN UZBEKISTAN: ASPECTS, CHALLENGES AND DEVELOPMENT PATHWAYS

Authors: Kendjaeva Dildora Khudayberganovna; Normo'minov Anvarjon Asqar o'g'li; Abdiraimova Zulxumor G`ofur qizi; Muxtorova Zilola Ziyoviddinovna; Pazilova Dilnoza Xaydaraliyevna;

INTEGRATION OF ARTIFICIAL INTELLIGENCE TECHNOLOGIES INTO HIGHER EDUCATION IN UZBEKISTAN: ASPECTS, CHALLENGES AND DEVELOPMENT PATHWAYS

Abstract

The article analyses the pre-conditions, current state and projected trajectories of integrating artificial intelligence (AI) into Uzbekistan’s higher-education system. Drawing upon a systematic review of 312 peer-reviewed articles, a two-round Delphi study with 22 national experts, institutional surveys covering 15 universities (n = 420) and multiple case studies, the paper identifies four dominant research clusters—adaptive learning, learning-analytics, generative academic support and AI ethics—and benchmarks domestic progress against leading international implementations. Empirical findings show that student AI adoption in Uzbekistan rose from 31 % in 2024 to 57 % in 2025, yet only 10 % of public institutions report fully integrated AI strategies. Key barriers include insufficient broadband capacity (< 100 Mbit s⁻¹ in 40 % of campuses), shortage of AI-literate faculty (0.8 specialists per 1 000 students) and limited regulatory guidance. Comparative evidence from Arizona State University and SeoulTech confirms measurable gains in grade-point averages (+0.2) and a 19 % reduction in course-completion times. The study proposes a phased roadmap (2025-2030) focused on infrastructure upgrading, compulsory AI-literacy modules, two-tier ethical governance and industry–academic laboratories. Implementing these measures could raise the share of AI-enabled courses to 35 % and improve Uzbekistan’s position in the Government AI Readiness Index by at least ten ranks.

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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average