Bibliometric Analysis of AI Technology Developments in Education: Trends, Collaborations, and Future Impact
DOI:
https://doi.org/10.58812/wsis.v2i05.910Keywords:
AI Technology Developments, Education, Bibliometric AnalysisAbstract
This study employs bibliometric analysis to explore the landscape of artificial intelligence (AI) applications in education. Through an extensive review of thematic clusters, research trends, author collaborations, and potential future research topics, the study maps the evolution and current state of AI in educational settings. Key findings indicate a robust focus on integrating AI within higher education and a significant emphasis on educational technology across various specialized domains. Temporal analysis reveals a progressive shift toward exploring advanced topics such as generative AI, reflecting the field's rapid adaptation to new technological advancements. Additionally, the author collaboration network illustrates a vibrant and interconnected academic community, while also identifying less explored areas like language education and AI in art education as promising fields for future research. The study highlights the dynamic nature of AI research in education, showcasing both the depth of current integrations and the potential for innovative applications that could further transform educational practices.
References
S. Roy and S. K. Paul, “Revolutionizing Education: How Artificial Intelligence is transforming the Learning Landscape,” 2023.
M. Rizvi, “Exploring the landscape of artificial intelligence in education: Challenges and opportunities,” in 2023 5th International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA), IEEE, 2023, pp. 1–3.
A. Fitriani, R. Rosidah, and Z. Zafrullah, “Biblioshiny: Implementation of Artificial Intelligence in Education (1976-2023),” J. Technol. Glob., vol. 1, no. 01 SE-Articles, pp. 11–25, 2023.
F. Pedro, M. Subosa, A. Rivas, and P. Valverde, “Artificial intelligence in education: Challenges and opportunities for sustainable development,” 2019.
R. F. Kizilcec, “To advance AI use in education, focus on understanding educators,” Int. J. Artif. Intell. Educ., vol. 34, no. 1, pp. 12–19, 2024.
V. J. Owan, K. B. Abang, D. O. Idika, E. O. Etta, and B. A. Bassey, “Exploring the potential of artificial intelligence tools in educational measurement and assessment,” EURASIA J. Math. Sci. Technol. Educ., vol. 19, no. 8, p. em2307, 2023.
K. Zhang and A. B. Aslan, “AI technologies for education: Recent research & future directions,” Comput. Educ. Artif. Intell., vol. 2, p. 100025, 2021.
X. Zhou, J. Van Brummelen, and P. Lin, “Designing AI learning experiences for K-12: emerging works, future opportunities and a design framework,” arXiv Prepr. arXiv2009.10228, 2020.
B. Johnson and J. Smith, “Towards ethical data-driven software: filling the gaps in ethics research & practice,” in 2021 IEEE/ACM 2nd International Workshop on Ethics in Software Engineering Research and Practice (SEthics), IEEE, 2021, pp. 18–25.
R. F. Thompson et al., “Artificial intelligence in radiation oncology: a specialty-wide disruptive transformation?,” Radiother. Oncol., vol. 129, no. 3, pp. 421–426, 2018.
A. Bhutoria, “Personalized education and artificial intelligence in the United States, China, and India: A systematic review using a human-in-the-loop model,” Comput. Educ. Artif. Intell., vol. 3, p. 100068, 2022.
S. Lin, J. Hilton, and O. Evans, “Teaching models to express their uncertainty in words,” arXiv Prepr. arXiv2205.14334, 2022.
G. Bhardwaj, S. V. Singh, and V. Kumar, “An empirical study of artificial intelligence and its impact on human resource functions,” in 2020 International Conference on Computation, Automation and Knowledge Management (ICCAKM), IEEE, 2020, pp. 47–51.
L. Chen, P. Chen, and Z. Lin, “Artificial intelligence in education: A review,” Ieee Access, vol. 8, pp. 75264–75278, 2020.
G. F. Luger, Artificial Intelligence: Structures and Strategies for Complex Problem Solving, 5/e. Pearson Education India, 1998.
L. Harasim, Learning theory and online technologies. Routledge, 2017.
Y. K. Dwivedi et al., “Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy,” Int. J. Inf. Manage., vol. 57, p. 101994, 2021.
O. Zawacki-Richter, V. I. Marín, M. Bond, and F. Gouverneur, “Systematic review of research on artificial intelligence applications in higher education–where are the educators?,” Int. J. Educ. Technol. High. Educ., vol. 16, no. 1, pp. 1–27, 2019.
G. Salomon, D. N. Perkins, and T. Globerson, “Partners in cognition: Extending human intelligence with intelligent technologies,” Educ. Res., vol. 20, no. 3, pp. 2–9, 1991.
E. Kasneci et al., “ChatGPT for good? On opportunities and challenges of large language models for education,” Learn. Individ. Differ., vol. 103, p. 102274, 2023.
T. Malik et al., “‘So what if ChatGPT wrote it?’ Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy,” Int. J. Inf. Manage., vol. 71, p. 102642, 2023.
Y. K. Dwivedi et al., “Impact of COVID-19 pandemic on information management research and practice: Transforming education, work and life,” Int. J. Inf. Manage., vol. 55, p. 102211, 2020.
S. A. D. Popenici and S. Kerr, “Exploring the impact of artificial intelligence on teaching and learning in higher education,” Res. Pract. Technol. Enhanc. Learn., vol. 12, no. 1, p. 22, 2017.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Nanny Mayasari, I Gusti Ayu Niken Launingtia, Nanang Nanang, Nur Sehang Thamrin, Y. Claudia Dhian A. Harbelubun
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Facebook 
Instagram 
Twitter 
Youtube 
+62 821 1557 5700
westscience.journals@gmail.com