Mapping the Future: A Bibliometric Analysis of Engagement Trends in Artificial Intelligence within Higher Education

Digital Technologies Research and Applications

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Mapping the Future: A Bibliometric Analysis of Engagement Trends in Artificial Intelligence within Higher Education

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https://doi.org/10.54963/dtra.v4i3.1285
Ekundayo, T., & Ali Chaudhry, S. (2025). Mapping the Future: A Bibliometric Analysis of Engagement Trends in Artificial Intelligence within Higher Education. Digital Technologies Research and Applications, 4(3), 1–21. https://doi.org/10.54963/dtra.v4i3.1285
Volume 4 Issue 3: December 2025 (In Progress)
Copyright (c) 2025 Tosin Ekundayo, Shahid Ali Chaudhry
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Authors

  • Tosin Ekundayo

    Innovative Entrepreneurship Department, Synergy University, Dubai, United Arab Emirates
  • Shahid Ali Chaudhry

    Information Technology Department, Synergy University, Dubai, United Arab Emirates

Received: 31 March 2025; Revised: 1 September 2025; Accepted: 11 September 2025; Published: 29 September 2025

This study conducts a comprehensive bibliometric analysis to map the landscape and research trends of artificial intelligence (AI) applications within higher education. Utilizing data from the Scopus database, encompassing 4,696 datasets from 1939 to 2024, we employed VOSviewer for visualizing and analyzing co‑authorship networks, citation patterns, and keyword occurrences. The analysis identifies primary research areas, influential authors, and emerging topics, offering valuable insights into the dynamic field of AI in higher education. Key findings include the identification of significant research themes such as AI applications in education, student engagement, and the development of learning systems. Influential contributors were highlighted for their substantial impact on the research landscape. The study also revealed strong collaborative networks, particularly involving key figures, underscoring the importance of co‑authorship in advancing AI research. Strong collaborative networks refer to the co‑authorship and international partnerships that connect these contributors, producing high‑impact research through shared expertise, resources, and cross‑regional knowledge exchange. The findings validate the hypotheses that significant research areas and influential contributors can be identified, and that collaborative networks and emerging technologies play crucial roles in the field’s advancement. Influential contributors are the authors, institutions, or countries whose publications and citation impacts significantly shape the research landscape of AI in higher education, setting key directions for scholarship and practice. This study provides a roadmap for future research, emphasizing the importance of strategic collaborations and innovative technologies in shaping the future of AI in higher education.

Keywords:

Artificial Intelligence Higher Education Bibliometric Analysis VOSviewer Co‑Authorship Networks Citation Analysis Emerging Technologies Geographic Distribution

References

  1. Ekundayo, T.; Khan, Z.; Nuzhat, S. Evaluating the Influence of Artificial Intelligence on Scholarly Research: A Study Focused on Academics. Hum. Behav. Emerg. Technol. 2024, 2024, 8713718. DOI: https://doi.org/10.1155/2024/8713718
  2. Nguyen, A.; Hong, Y.; Dang, B.; et al. Human-AI Collaboration Patterns in AI-Assisted Academic Writing. Stud. High. Educ. 2024, 49, 847–864. DOI: https://doi.org/10.1080/03075079.2024.2323593
  3. Crompton, H.; Burke, D. Artificial Intelligence in Higher Education: The State of the Field. Int. J. Educ. Technol. High. Educ. 2023, 20, 22. DOI: https://doi.org/10.1186/s41239-023-00392-8
  4. Menzli, L.J.; Smirani, L.K.; Boulahia, J.A.; et al. Investigation of Open Educational Resources Adoption in Higher Education Using Rogers’ Diffusion of Innovation Theory. Heliyon 2022, 8, e09885. DOI: https://doi.org/10.1016/j.heliyon.2022.e09885
  5. Orduna-Malea, E.; Martín-Martín, A.; López-Cózar, E.D. Google Scholar as a Source for Scholarly Evaluation: A Bibliographic Review of Database Errors. Rev. Esp. Doc. Cient. 2017, 40, 1–33. DOI: https://doi.org/10.3989/redc.2017.4.1500
  6. Radha, L.; Arumugam, J. The Research Output of Bibliometrics Using Bibliometrix R Package and VOS Viewer. Shanlax Int. J. Arts Sci. Humanit. 2021, 9, 44–49. DOI: https://doi.org/10.34293/sijash.v9i2.4197
  7. Romero, C.; Ventura, S. Educational Data Mining and Learning Analytics: An Updated Survey. Wiley Interdiscip. Rev. Data Min. Knowl. Discov. 2020, 10, e1355. DOI: https://doi.org/10.1002/widm.1355
  8. Luckin, R.; Holmes, W.; Griffiths, M.; et al. Intelligence Unleashed: An Argument for AI in Education. UCL Knowledge Lab: London, UK, 2016.
  9. Selwyn, N. What’s the Problem with Learning Analytics? J. Learn. Anal. 2019, 6, 11–19. DOI: https://doi.org/10.18608/jla.2019.63.3
  10. Shareefa, M.; Moosa, V. The Most-Cited Educational Research Publications on Differentiated Instruction: A Bibliometric Analysis. Eur. J. Educ. Res. 2020, 9, 331–349. DOI: https://doi.org/10.12973/eu-jer.9.1.331
  11. Guilherme, A. AI and Education: The Importance of Teacher and Student Relations. AI Soc. 2019, 34, 47–54. DOI: https://doi.org/10.1007/s00146-017-0693-8
  12. Akinwalere, S.N.; Ivanov, V. Artificial Intelligence in Higher Education: Challenges and Opportunities. Border Cross. 2022, 12, 1–15. DOI: https://doi.org/10.33182/bc.v12i1.2015
  13. Perrotta, C.; Selwyn, N. Deep Learning Goes to School: Toward a Relational Understanding of AI in Education. Learn. Media Technol. 2020, 45, 251–269. DOI: https://doi.org/10.1080/17439884.2020.1686017
  14. Geels, F.W. From Sectoral Systems of Innovation to Socio-Technical Systems: Insights About Dynamics and Change From Sociology and Institutional Theory. Res. Policy 2004, 33, 897–920. DOI: https://doi.org/10.1016/j.respol.2004.01.015
  15. Zhang, X.; Nutakor, F.; Minlah, M.K.; et al. Can Digital Transformation Drive Green Transformation in Manufacturing Companies?—Based on Socio-Technical Systems Theory Perspective. Sustainability 2023, 15, 2840. DOI: https://doi.org/10.3390/su15032840
  16. Hester, A.J. Socio-Technical Systems Theory as a Diagnostic Tool for Examining Underutilization of Wiki Technology. Learn. Organ. 2014, 21, 48–68. DOI: https://doi.org/10.1108/TLO-10-2012-0065
  17. Yu, X.; Xu, S.; Ashton, M. Antecedents and Outcomes of Artificial Intelligence Adoption and Application in the Workplace: The Socio-Technical System Theory Perspective. Inf. Technol. People 2023, 36, 454–474. DOI: https://doi.org/10.1108/ITP-04-2021-0254
  18. Saunders, M.N.K.; Lewis, P.; Thornhill, A. Research Methods for Business Students, 4th ed.; Pearson: London, UK, 2007.
  19. Grad Coach. Available online: https://gradcoach.com/saunders-research-onion (accessed on 10 June 2024).
  20. Mardiana, S. Modifying Research Onion for Information Systems Research. Solid State Technol. 2020, 63, 5304–5313.
  21. Guo, S.; Zheng, Y.; Zhai, X. Artificial Intelligence in Education Research During 2013–2023: A Review Based on Bibliometric Analysis. Educ. Inf. Technol. 2024, 29, 16387–16409. DOI: https://doi.org/10.1007/s10639-024-12491-8
  22. Lin, Y.; Yu, Z. A Bibliometric Analysis of Artificial Intelligence Chatbots in Educational Contexts. Interact. Technol. Smart Educ. 2024, 21, 189–213. DOI: https://doi.org/10.1108/ITSE-12-2022-0165
  23. Ivanova, M.; Grosseck, G.; Holotescu, C. Unveiling Insights: A Bibliometric Analysis of Artificial Intelligence in Teaching. Informatics 2024, 11, 10. DOI: https://doi.org/10.3390/informatics11010010
  24. Scopus Preview. Available online: https://www.scopus.com (accessed on 15 June 2024).
  25. Singh, V.K.; Singh, P.; Karmakar, M.; et al. The Journal Coverage of Web of Science, Scopus and Dimensions: A Comparative Analysis. Scientometrics 2021, 126, 5113–5142. DOI: https://doi.org/10.1007/s11192-021-03948-5
  26. Zawacki-Richter, O.; Marín, V.I.; Bond, M.; et al. Systematic Review of Research on Artificial Intelligence Applications in Higher Education – Where Are the Educators? Int. J. Educ. Technol. High. Educ. 2019, 16, 39. DOI: https://doi.org/10.1186/s41239-019-0171-0
  27. Chen, M.; Claramunt, C.; Çöltekin, A.; et al. Artificial Intelligence and Visual Analytics in Geographical Space and Cyberspace: Research Opportunities and Challenges. Earth-Sci. Rev. 2023, 241, 104438. DOI: https://doi.org/10.1016/j.earscirev.2023.104438
  28. Lampropoulos, G.; Sidiropoulos, A. Impact of Gamification on Students’ Learning Outcomes and Academic Performance: A Longitudinal Study Comparing Online, Traditional, and Gamified Learning. Educ. Sci. 2024, 14, 367. DOI: https://doi.org/10.3390/educsci14040367
  29. Ferri, P. The Impact of Artificial Intelligence on Scientific Collaboration: Setting the Scene for a Future Research Agenda. In Proceedings of the Eu‑SPRI 2022: “Challenging Science and Innovation Policy,” Utrecht, The Netherlands, 1–3 June 2022.
  30. Atchley, P.; Pannell, H.; Wofford, K.; et al. Human and AI Collaboration in the Higher Education Environment: Opportunities and Concerns. Cogn. Res. Princ. Implic. 2024, 9, 20. DOI: https://doi.org/10.1186/s41235-024-00547-9
  31. Gill, S.S.; Xu, M.; Ottaviani, C.; et al. AI for Next Generation Computing: Emerging Trends and Future Directions. Internet Things 2022, 19, 100514. DOI: https://doi.org/10.1016/j.iot.2022.100514
  32. Adadi, A.; Lahmer, M.; Nasiri, S. Artificial Intelligence and COVID-19: A Systematic Umbrella Review and Roads Ahead. J. King Saud Univ. Comput. Inf. Sci. 2022, 34, 5898–5920. DOI: https://doi.org/10.1016/j.jksuci.2021.07.010
  33. Adiguzel, T.; Kaya, M.H.; Cansu, F.K. Revolutionizing Education with AI: Exploring the Transformative Potential of ChatGPT. Contemp. Educ. Technol. 2023, 15, ep429. DOI: https://doi.org/10.30935/cedtech/13152