From Early Growth to Conceptual Formation: A Bibliometric Analysis of Generative AI Research in Higher Education
DOI:
https://doi.org/10.46328/ijte.8463Keywords:
Generative AI (GenAI), Higher education, Bibliometric analysis, Scientific production, Co-citation analysis, International collaborationAbstract
This study aimed to analyze the scientific output related to the use of generative artificial intelligence (GenAI) in higher education from a bibliometric perspective. The current analysis sought to uncover research growth trends, identify the most contributing publication sources, and identify the most prolific authors, as well as to examine the conceptual and intellectual framework and international collaboration networks. The study used a bibliometric analysis methodology on a sample of 959 studies extracted from the Web of Science database for the period 2021–2025, prepared by 2,881 researchers. The results revealed a research boom in the field, with an annual growth rate of 25.99% and an average of 10.28 citations per study, in spite of the relatively short lifespan of the documents. The journal of Education Sciences emerged as the most frequently published scientific source, while researcher Bozkurt A. was identified as the most productive author, reflecting the early stages of research development in this discipline. At the conceptual level, the analysis revealed that literature is centered around the axes of academic performance, motivation, technology acceptance, and modern teaching strategies. The shared citation map also showed that the field's intellectual framework is based on studies that combine applied educational dimensions with Technology Acceptance Models (TAM), extending to the technical foundations of these tools. Regarding international collaboration, the results demonstrated research leadership from the United States, China, and the United Kingdom, with notable contributions from Saudi Arabia, India, and Singapore. The study concludes that research in GenAI represents a dynamic and fast evolving field where educational and technological frameworks intersect, with a growing trend toward strengthening worldwide knowledge collaboration networks.
References
Al-Hafdi, F. S., & Alhalafawy, W. S. (2026). Learning analytics for reducing student dropout in digital video platforms. PeerJ Computer Science, 12, e3532. https://doi.org/10.7717/peerj-cs.3532
Alharbi, T. S., Al-Hafdi, F. S., & Alhalafawy, W. S. (2025). Exploring the Framework for Intelligent Operations (FiOps) for Teachers in the Era of Generative AI (GenAI). International Journal of Learning, Teaching and Educational Research, 24(8), 942-964. https://doi.org/10.26803/ijlter.24.8.42
Almassaad, A., Alajlan, H., & Alebaikan, R. (2024). Student Perceptions of Generative Artificial Intelligence: Investigating Utilization, Benefits, and Challenges in Higher Education. Systems, 12(10), Article 385. https://doi.org/10.3390/systems12100385
Alsayed, W. O., Al-Hafdi, F. S., & Alhalafawy, W. S. (2025). Chatbots in education. In Empowering STEM Educators With Digital Tools (pp. 137-154). IGI Global Scientific Publishing. https://doi.org/10.4018/979-8-3693-9806-7.ch006
Alsulami, M. R., Al-Hafdi, F. S., & Alhalafawy, W. S. (2025). The Potential of Generative AI in Scientific Publishing: Exploration of Researchers' Journeys from Draft to Publication. International Journal of Interactive Mobile Technologies, 19(21). https://doi.org/10.3991/ijim.v19i21.56133
Baidoo-Anu, D., & Ansah, L. O. (2023). Education in the era of generative artificial intelligence (AI): Understanding the potential benefits of ChatGPT in promoting teaching and learning. Journal of AI, 7(1), 52-62. https://doi.org/10.61969/jai.1337500
Bhutoria, A. (2022). Personalized education and artificial intelligence in the United States, China, and India: A systematic review using a human-in-the-loop model. Computers and Education: Artificial Intelligence, 3, 100068. https://doi.org/10.1016/j.caeai.2022.100068
Bower, M., Torrington, J., Lai, J. W. M., Petocz, P., & Alfano, M. (2024). How should we change teaching and assessment in response to increasingly powerful generative Artificial Intelligence? Outcomes of the ChatGPT teacher survey. Education and Information Technologies, 29(12), 15403-15439. https://doi.org/10.1007/s10639-023-12405-0
Bozkurt, A. (2024). GenAI et al.: Cocreation, Authorship, Ownership, Academic Ethics and Integrity in a Time of Generative AI. Open Praxis, 16(1), 1-10. https://doi.org/10.55982/openpraxis.16.1.654
Chan, C. K. Y. (2024). Students' perceptions of 'AI-giarism': investigating changes in understandings of academic misconduct. Education and Information Technologies. https://doi.org/10.1007/s10639-024-13151-7
Chan, C. K. Y., & Hu, W. J. (2023). Students' voices on generative AI: perceptions, benefits, and challenges in higher education. International journal of educational technology in higher education, 20(1), Article 43. https://doi.org/10.1186/s41239-023-00411-8
Chan, C. K. Y., & Lee, K. K. W. (2023). The AI generation gap: Are Gen Z students more interested in adopting generative AI such as ChatGPT in teaching and learning than their Gen X and millennial generation teachers? Smart Learning Environments, 10(1), Article 60. https://doi.org/10.1186/s40561-023-00269-3
Chen, A. X., Xiang, M. T., Zhou, J. Y., Jia, J. Y., Shang, J. J., Li, X. Y., Gasevic, D., & Fan, Y. Z. (2025). Unpacking help-seeking process through multimodal learning analytics: A comparative study of ChatGPT vs Human expert. Computers & Education, 226, 18, Article 105198. https://doi.org/10.1016/j.compedu.2024.105198
Chiu, T. K. (2024). The impact of Generative AI (GenAI) on practices, policies and research direction in education: A case of ChatGPT and Midjourney. Interactive learning environments, 32(10), 6187-6203. https://doi.org/10.1080/10494820.2023.2253861
Chiu, T. K. F. (2022). Applying the self-determination theory (SDT) to explain student engagement in online learning during the COVID-19 pandemic. Journal of Research on Technology in Education, 54, S14-S30. https://doi.org/10.1080/15391523.2021.1891998
Chiu, T. K. F. (2024). A classification tool to foster self-regulated learning with generative artificial intelligence by applying self-determination theory: a case of ChatGPT. Etr&D-Educational Technology Research and Development, 72(4), 2401-2416. https://doi.org/10.1007/s11423-024-10366-w
Choi, G. W., Kim, S. H., Lee, D., & Moon, J. (2024). Utilizing Generative AI for Instructional Design: Exploring Strengths, Weaknesses, Opportunities, and Threats. Techtrends, 68(4), 832-844. https://doi.org/10.1007/s11528-024-00967-w
Cooper, G. (2023). Examining Science Education in ChatGPT: An Exploratory Study of Generative Artificial Intelligence. JOURNAL OF SCIENCE EDUCATION AND TECHNOLOGY, 32(3), 444-452. https://doi.org/10.1007/s10956-023-10039-y
Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2024). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, 61(2), 228-239. https://doi.org/10.1080/14703297.2023.2190148
Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of business research, 133, 285-296. https://doi.org/10.1016/j.jbusres.2021.04.070
Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., ... & Wright, R. (2023). "So what if ChatGPT wrote it?" Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71, Article 102642. https://doi.org/10.1016/j.ijinfomgt.2023.102642
Evmenova, A. S., Borup, J., & Shin, J. K. (2024). Harnessing the Power of Generative AI to Support ALL Learners. Techtrends, 68(4), 820-831. https://doi.org/10.1007/s11528-024-00966-x
Farazouli, A., Cerratto-Pargman, T., Bolander-Laksov, K., & McGrath, C. (2024). Hello GPT! Goodbye home examination? An exploratory study of AI chatbots impact on university teachers' assessment practices. Assessment & Evaluation in Higher Education, 49(3), 363-375. https://doi.org/10.1080/02602938.2023.2241676
Francis, N. J., Jones, S., & Smith, D. P. (2025). Generative AI in Higher Education: Balancing Innovation and Integrity. BRITISH JOURNAL OF BIOMEDICAL SCIENCE, 81, Article 14048. https://doi.org/10.3389/bjbs.2024.14048
Guo, H., Yi, W., & Liu, K. (2024). Enhancing Constructivist Learning: The Role of Generative AI in Personalised Learning Experiences. https://doi.org/10.5220/0012688700003690
Hastuty, A., Maswati, M., Saharuddin, M., Sukri, A. M., & Halik, A. (2025). Artificial intelligence: A review of the philosophy of Islamic educational science. Journal of Research in Instructional, 5(1), 90-102. https://doi.org/10.30862/jri.v5i1.573
Herath, D. B., Ode, E., & Herath, G. B. (2025). Can AI replace humans? Comparing the capabilities of AI tools and human performance in a business management education scenario [; Early Access]. British Educational Research Journal, 24. https://doi.org/10.1002/berj.4111
Hernández-Torrano, D., Somerton, M., & Helmer, J. (2022). Mapping research on inclusive education since Salamanca Statement: a bibliometric review of the literature over 25 years. International Journal of Inclusive Education, 26(9), 893-912. https://doi.org/10.1080/13603116.2020.1747555
Huang, X. Y., Yang, Z. Y., Zhang, J. N., Wang, R. J., Fan, J. H., Zhang, H., Xu, R., Li, X., Yu, S. Y., Long, L. N., & Huang, H. (2022). A Bibliometric Analysis Based on Web of Science: Current Perspectives and Potential Trends of SMAD7 in Oncology. Frontiers in Cell and Developmental Biology, 9, Article 712732. https://doi.org/10.3389/fcell.2021.712732
Ibrahim, H. O., Al-Hafdi, F. S., & Alhalafawy, W. S. (2024). Ethnographic Insights of Educational Digital Life Behaviours: A Study of Affluent Schools. Journal of Ecohumanism, 3(7), 4413-4428. https://doi.org/10.62754/joe.v3i7.4556
Jauhiainen, J. S., & Guerra, A. G. (2024). Generative AI in education: ChatGPT-4 in evaluating students' written responses [; Early Access]. Innovations in Education and Teaching International, 15. https://doi.org/10.1080/14703297.2024.2422337
Javaid, M., Haleem, A., Singh, R. P., Suman, R., & Gonzalez, E. S. (2022). Understanding the adoption of Industry 4.0 technologies in improving environmental sustainability. Sustainable Operations and Computers, 3, 203-217. https://doi.org/10.1016/j.susoc.2022.01.008
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., Stadler, M., Weller, J., Kuhn, J., & Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274
Kelly, S., Kaye, S.-A., & Oviedo-Trespalacios, O. (2023). What factors contribute to the acceptance of artificial intelligence? A systematic review. Telematics and Informatics, 77, 101925. https://doi.org/10.1016/j.tele.2022.101925
Kim, J., Yu, S., Detrick, R., & Li, N. (2025). Exploring students' perspectives on Generative AI-assisted academic writing. Education and Information Technologies, 30(1), 1265-1300. https://doi.org/10.1007/s10639-024-12878-7
Koo, M. (2025). ChatGPT Research: A Bibliometric Analysis Based on the Web of Science from 2023 to June 2024. Knowledge, 5(1), 4. https://doi.org/10.3390/knowledge5010004
Kucukkuya, A., Bodur, G., Ozata, S. Y., & Goktas, P. (2025). Tapping into awareness: assessing nursing students’ water consumption behaviors and sustainability perceptions through a cross‐sectional study with machine learning approach. Public Health Nursing, 42(1), 444-456. https://doi.org/10.1111/phn.13468
Kurtz, G., Amzalag, M., Shaked, N., Zaguri, Y., Kohen-Vacs, D., Gal, E., Zailer, G., & Barak-Medina, E. (2024). Strategies for Integrating Generative AI into Higher Education: Navigating Challenges and Leveraging Opportunities. Education Sciences, 14(5), Article 503. https://doi.org/10.3390/educsci14050503
Kyrpa, A., Stepanenko, O., Zinchenko, V., Datsiuk, T., Karpan, I., & Tilniak, N. (2024). Artificial intelligence tools in teaching social and humanitarian disciplines. Information Technologies and Learning Tools, 100(2), 162-179. https://doi.org/10.33407/itlt.v100i2.5563
Li, K. C., & Wong, B. T. M. (2023). Artificial intelligence in personalised learning: a bibliometric analysis. Interactive Technology and Smart Education. https://doi.org/10.1108/itse-01-2023-0007
Lim, W. M., Gunasekara, A., Pallant, J. L., Pallant, J. I., & Pechenkina, E. (2023). Generative AI and the future of education: Ragnarok or reformation? A paradoxical perspective from management educators. International Journal of Management Education, 21(2), 13, Article 100790. https://doi.org/10.1016/j.ijme.2023.100790
McGrath, C., Farazouli, A., & Cerratto-Pargman, T. (2024). Generative AI chatbots in higher education: a review of an emerging research area. Higher Education. https://doi.org/10.1007/s10734-024-01288-w
McGrath, C., Farazouli, A., & Cerratto-Pargman, T. (2025). Generative AI chatbots in higher education: A review of an emerging research area. Higher Education, 89(6), 1533-1549. https://doi.org/10.1007/s10734-024-01288-w
Michel-Villarreal, R., Vilalta-Perdomo, E., Salinas-Navarro, D. E., Thierry-Aguilera, R., & Gerardou, F. S. (2023). Challenges and Opportunities of Generative AI for Higher Education as Explained by ChatGPT. Education Sciences, 13(9), Article 856. https://doi.org/10.3390/educsci13090856
Moorhouse, B. L., Yeo, M. A., & Wan, Y. W. (2023). Generative AI tools and assessment: Guidelines of the world's top-ranking universities. Computers and Education Open, 5, Article 100151. https://doi.org/10.1016/j.caeo.2023.100151
Nguyen, A., Hong, Y., Dang, B., & Huang, X. S. (2024). Human-AI collaboration patterns in AI-assisted academic writing. Studies in Higher Education, 49(5), 847-864. https://doi.org/10.1080/03075079.2024.2323593
Noroozi, O., Soleimani, S., Farrokhnia, M., & Banihashem, S. K. (2024). Generative AI in Education: Pedagogical, Theoretical, and Methodological Perspectives [Article]. International Journal of Technology in Education, 7(3), 373-385. https://doi.org/10.46328/ijte.845
O'Dea, X. (2024). Generative AI: is it a paradigm shift for higher education? Studies in Higher Education, 49(5), 811-816. https://doi.org/10.1080/03075079.2024.2332944
Öztürk, O., Kocaman, R., & Kanbach, D. K. (2024). How to design bibliometric research: an overview and a framework proposal. Review of Managerial Science, 18(11), 3333-3361. https://doi.org/10.1007/s11846-024-00738-0
Padovano, A., & Cardamone, M. (2024). Towards human-AI collaboration in the competency-based curriculum development process: The case of industrial engineering and management education. Computers and Education: Artificial Intelligence, 7, 100256. https://doi.org/10.1016/j.caeai.2024.100256
SDAIA. (2023). Generative Artificial Intelligence in Education. https://sdaia.gov.sa/ar/MediaCenter/KnowledgeCenter/ResearchLibrary/GenAIE.pdf
Tenakwah, E. S., Boadu, G., Tenakwah, E. J., Parzakonis, M., Brady, M., Kansiime, P., Said, S., Ayilu, R., Radavoi, C., & Berman, A. (2023). Generative AI and higher education assessments: A competency-based analysis. https://doi.org/10.21203/rs.3.rs-2968456/v2
Tlili, A., Shehata, B., Adarkwah, M. A., Bozkurt, A., Hickey, D. T., Huang, R. H., & Agyemang, B. (2023). What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education. Smart Learning Environments, 10(1), 24, Article 15. https://doi.org/10.1186/s40561-023-00237-x
Tupper, M., Hendy, I. W., & Shipway, J. R. (2024). Field courses for dummies: To what extent can ChatGPT design a higher education field course? Innovations in Education and Teaching International. https://doi.org/10.1080/14703297.2024.2316716
UNESCO. (2024). Guidance for generative AI in education and research. https://www.unesco.org/en/articles/guidance-generative-ai-education-and-research
Valle, N., Brishke, J., Shenkman, E., & Ritzhaupt, A. D. (2022). Design, Development and Evaluation of the Citizen Science Cancer Curriculum (CSCC): a Design and Development Case Study. Techtrends, 66(4), 666-680. https://doi.org/10.1007/s11528-022-00737-6
van den Berg, G., & du Plessis, E. (2023). ChatGPT and Generative AI: Possibilities for Its Contribution to Lesson Planning, Critical Thinking and Openness in Teacher Education. Education Sciences, 13(10), Article 998. https://doi.org/10.3390/educsci13100998
Wang, T., Lund, B. D., Marengo, A., Pagano, A., Mannuru, N. R., Teel, Z. A., & Pange, J. (2023). Exploring the Potential Impact of Artificial Intelligence (AI) on International Students in Higher Education: Generative AI, Chatbots, Analytics, and International Student Success. Applied Sciences-Basel, 13(11), Article 6716. https://doi.org/10.3390/app13116716
Xue, L., Mahat, J., & Ghazali, N. (2026). Technology Acceptance Model in Artificial Intelligence in Education: A Meta-Analysis. Sage Open, 16(1), 21582440251409441. https://doi.org/10.1177/21582440251409441
Yu, H., Liu, Z., & Guo, Y. (2023). application Status, Problems and Future Prospects of Generative ai in education. 2023 5th International Conference on Computer Science and Technologies in Education (CSTE), Apr. 2023, pp. 1–7. https://doi.org/10.1109/cste59648.2023.00065
Yusuf, A., Pervin, N., & Román-González, M. (2024). Generative AI and the future of higher education: a threat to academic integrity or reformation? Evidence from multicultural perspectives. International Journal of Educational Technology in Higher Education, 21(1), Article 21. https://doi.org/10.1186/s41239-024-00453-6
Záková, K., Urbano, D., Cruz-Correia, R., Guzmán, J. L., & Matisák, J. (2025). Exploring student and teacher perspectiveson ChatGPT's impact in higher education. Education and Information Technologies, 30(1), 649-692. https://doi.org/10.1007/s10639-024-13184-y
Zheng, Y., Wang, Y. B., Liu, K. S. X., & Jiang, M. Y. C. (2024). Examining the moderating effect of motivation on technology acceptance of generative AI for English as a foreign language learning. Education and Information Technologies, 29(17), 23547-23575. https://doi.org/10.1007/s10639-024-12763-3
Zhou, X., & Schofield, L. (2024). Using social learning theories to explore the role of generative Artificial Intelligence (AI) in collaborative learning. Journal of Learning Development in Higher Education, 30. https://doi.org/10.47408/jldhe.vi30.1031
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