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Transforming Education: A Comprehensive Review of Generative Artificial Intelligence in Educational Settings through Bibliometric and Content Analysis

Author

Listed:
  • Zied Bahroun

    (Department of Industrial Engineering, College of Engineering, American University of Sharjah, Sharjah P.O. Box 26666, United Arab Emirates)

  • Chiraz Anane

    (Department of Foreign Languages, College of Arts, Humanities and Social Sciences, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates)

  • Vian Ahmed

    (Department of Industrial Engineering, College of Engineering, American University of Sharjah, Sharjah P.O. Box 26666, United Arab Emirates)

  • Andrew Zacca

    (Department of Industrial Engineering, College of Engineering, American University of Sharjah, Sharjah P.O. Box 26666, United Arab Emirates)

Abstract

In the ever-evolving era of technological advancements, generative artificial intelligence (GAI) emerges as a transformative force, revolutionizing education. This review paper, guided by the PRISMA framework, presents a comprehensive analysis of GAI in education, synthesizing key insights from a selection of 207 research papers to identify research gaps and future directions in the field. This study begins with a content analysis that explores GAI’s transformative impact in specific educational domains, including medical education and engineering education. The versatile applications of GAI encompass assessment, personalized learning support, and intelligent tutoring systems. Ethical considerations, interdisciplinary collaboration, and responsible technology use are highlighted, emphasizing the need for transparent GAI models and addressing biases. Subsequently, a bibliometric analysis of GAI in education is conducted, examining prominent AI tools, research focus, geographic distribution, and interdisciplinary collaboration. ChatGPT emerges as a dominant GAI tool, and the analysis reveals significant and exponential growth in GAI research in 2023. Moreover, this paper identifies promising future research directions, such as GAI-enhanced curriculum design and longitudinal studies tracking its long-term impact on learning outcomes. These findings provide a comprehensive understanding of GAI’s potential in reshaping education and offer valuable insights to researchers, educators, and policymakers interested in the intersection of GAI and education.

Suggested Citation

  • Zied Bahroun & Chiraz Anane & Vian Ahmed & Andrew Zacca, 2023. "Transforming Education: A Comprehensive Review of Generative Artificial Intelligence in Educational Settings through Bibliometric and Content Analysis," Sustainability, MDPI, vol. 15(17), pages 1-40, August.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:17:p:12983-:d:1227548
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    References listed on IDEAS

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    1. Chokri Kooli, 2023. "Chatbots in Education and Research: A Critical Examination of Ethical Implications and Solutions," Sustainability, MDPI, vol. 15(7), pages 1-15, March.
    2. Thomas Adams & Syed Muslim Jameel & Jamie Goggins, 2023. "Education for Sustainable Development: Mapping the SDGs to University Curricula," Sustainability, MDPI, vol. 15(10), pages 1-32, May.
    3. S M Jamil Uddin & Alex Albert & Anto Ovid & Abdullah Alsharef, 2023. "Leveraging ChatGPT to Aid Construction Hazard Recognition and Support Safety Education and Training," Sustainability, MDPI, vol. 15(9), pages 1-22, April.
    4. Mei-Hua Hsu & Tien-Ming Chan & Chi-Shun Yu, 2023. "Termbot: A Chatbot-Based Crossword Game for Gamified Medical Terminology Learning," IJERPH, MDPI, vol. 20(5), pages 1-15, February.
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    Cited by:

    1. Leonardo Gambacorta & Han Qiu & Shuo Shan & Daniel M Rees, 2024. "Generative AI and labour productivity: a field experiment on coding," BIS Working Papers 1208, Bank for International Settlements.
    2. Prema Nedungadi & Kai-Yu Tang & Raghu Raman, 2024. "The Transformative Power of Generative Artificial Intelligence for Achieving the Sustainable Development Goal of Quality Education," Sustainability, MDPI, vol. 16(22), pages 1-27, November.
    3. Danah Henriksen & Punya Mishra & Rachel Stern, 2024. "Creative Learning for Sustainability in a World of AI: Action, Mindset, Values," Sustainability, MDPI, vol. 16(11), pages 1-20, May.

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