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<p>This systematic review analyzes 85 peer-reviewed studies to conceptualize the transformative role of Large Language Models (LLMs) in educational ecosystems. Grounded in constructivist and sociomatrical learning theories, the paper synthesizes pedagogical, epistemological, and ethical implications of LLM adoption. By synthesizing and analyzing existing research and case studies, we explore how LLMs facilitate personalized learning, enhance content creation and delivery, and provide educators and students with unparalleled access to information and resources. Additionally, the article examines the broader implications of LLM adoption, including concerns around educational equity, data privacy, and the development of critical thinking skills. It offers a comprehensive analysis of the opportunities and challenges presented by LLMs in education and provides insights into future research and practice in this rapidly evolving field. This research examines the impact of LLM-based technologies on education and shows significant improvements across various categories. Using the PRISMA 2020 framework and (Braun &amp; Clarke, <i>Qualitative Research in Psychology</i>, <i>3</i>(2), 77–101, <CitationRef CitationID="CR3">2006</CitationRef>) thematic analysis, the review synthesizes 85 peer-reviewed studies published between 2019 and 2024. Findings reveal that LLM-based learning environments enhance educational performance across multiple dimensions—most notably a 30.11% improvement in adoption cost efficiency and a 20.11% increase in learning outcomes—while also redefining teacher–student dynamics through AI-mediated personalization. The paper concludes by proposing an integrative ethical and sociotechnical model for implementing LLMs in education, emphasizing transparency, inclusivity, and epistemic accountability.</p>

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Transformative role of large language models in education and comparative analysis with traditional technologies

  • 期刊论文

  • 发表日期：

    2025年12月5日

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  • Anurag Rana,
  • Pankaj Vaidya,
  • Yu-Chen Hu

摘要

This systematic review analyzes 85 peer-reviewed studies to conceptualize the transformative role of Large Language Models (LLMs) in educational ecosystems. Grounded in constructivist and sociomatrical learning theories, the paper synthesizes pedagogical, epistemological, and ethical implications of LLM adoption. By synthesizing and analyzing existing research and case studies, we explore how LLMs facilitate personalized learning, enhance content creation and delivery, and provide educators and students with unparalleled access to information and resources. Additionally, the article examines the broader implications of LLM adoption, including concerns around educational equity, data privacy, and the development of critical thinking skills. It offers a comprehensive analysis of the opportunities and challenges presented by LLMs in education and provides insights into future research and practice in this rapidly evolving field. This research examines the impact of LLM-based technologies on education and shows significant improvements across various categories. Using the PRISMA 2020 framework and (Braun & Clarke, Qualitative Research in Psychology, 3(2), 77–101, 2006) thematic analysis, the review synthesizes 85 peer-reviewed studies published between 2019 and 2024. Findings reveal that LLM-based learning environments enhance educational performance across multiple dimensions—most notably a 30.11% improvement in adoption cost efficiency and a 20.11% increase in learning outcomes—while also redefining teacher–student dynamics through AI-mediated personalization. The paper concludes by proposing an integrative ethical and sociotechnical model for implementing LLMs in education, emphasizing transparency, inclusivity, and epistemic accountability.