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Bibliometric analysis of ChatGPT in education

Gulnoza SabirovaTashkent Institute of Irrigation and Agricultural Mechanization Engineers” National Research University, Tashkent, UzbekistanSholpan K. ZharkynbekovaEurasian National University, Astana, KazakhstanZulfiya KannazarovaTashkent Institute of Irrigation and Agricultural Mechanization Engineers” National Research University, Tashkent, UzbekistanKhurshid MamatkulovNational University in Uzbekistan, Tashkent, UzbekistanNigora GoyibovaTashkent Institute of Irrigation and Agricultural Mechanization Engineers” National Research University, Tashkent, UzbekistanUsmanova Shokhsanam AvazovnaThe University of World Economy and Diplomacy, Tashkent, UzbekistanLola ShasaidovaUzbek World Languages University, Tashkent, Uzbekistan
2026en
ABI

Аннотация

This research delivers a bibliometric study of ChatGPT-related research in education using Web of Science (WoS) data for the period 2023–2024. The study applies the PRISMA protocol for systematic screening and selection of articles, combined with bibliometric mapping approaches to analyze publication trends, authorship patterns, and thematic structures. Unlike previous studies that mainly focused on early-stage or descriptive statistics, this research offers an updated, methodologically in-depth analysis based on PRISMA screening and science-mapping techniques, delivering a more thorough understanding of the developing research landscape. The main contribution of this study lies in integrating PRISMA-based systematic selection with bibliometric visualization to identify emerging trends, research gaps, and cooperation networks in ChatGPT-related educational research during 2023–2024.

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