Artificial intelligence in educational assessment in the age of generative AI: A bibliometric review
The rapid diffusion of artificial intelligence (AI), particularly generative AI tools, has significantly reshaped educational assessment practices, creating new opportunities and challenges for feedback, academic integrity, and curriculum design. Despite the growing volume of scholarship, research in this area remains fragmented, making it difficult to discern dominant trends, key contributors, and emerging themes. This study employs a bibliometric review to map the intellectual structure and evolution of research on AI in educational assessment between 2015 and 2025. Using open-access journal articles indexed in the Dimensions.ai database and aligned with Sustainable Development Goal 4 (Quality Education), a curated dataset of 89 studies was analysed. Bibliometric techniques, including co-authorship, citation, co-citation, and keyword co-occurrence analyses, were applied using VOSviewer and descriptive statistics. The findings reveal a sharp growth in publications following the emergence of generative AI, with influential clusters focusing on assessment redesign, feedback, academic integrity, and higher education applications. While established institutions and authors dominate the field, collaboration networks remain fragmented, and contributions from non-Western contexts are comparatively limited. The study highlights the need for stronger international collaboration and context-sensitive research to support equitable and responsible integration of AI in educational assessment.
Alkouk, W. A., & Khlaif, Z. N. (2024). AI-resistant assessments in higher education: Practical insights from faculty training workshops. Frontiers in Education, 9, 1499495. https://doi.org/10.3389/feduc.2024.1499495
Bahroun, Z., Anane, C., Ahmed, V., & Zacca, A. (2023). Transforming education: A comprehensive review of generative artificial intelligence in educational settings through bibliometric and content analysis. Sustainability, 15(17), 12983. https://doi.org/10.3390/su151712983
Bearman, M., Tai, J., Dawson, P., Boud, D., & Ajjawi, R. (2024). Developing evaluative judgement for a time of generative artificial intelligence. Assessment & Evaluation in Higher Education, 49(6), 893–905. https://doi.org/10.1080/02602938.2024.2335321
Bradford, S. C. (1934). Sources of information on specific subjects. Engineering, 137, 85–86.
Chan, K. S., & Zary, N. (2019). Applications and challenges of implementing artificial intelligence in medical education: Integrative review. JMIR Medical Education, 5(1), e13930. https://doi.org/10.2196/13930
Chiu, T. K. F. (2023). 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. (2024). Future research recommendations for transforming higher education with generative AI. Computers and Education: Artificial Intelligence, 6, 100197. https://doi.org/10.1016/j.caeai.2023.100197
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
Ifenthaler, D., & Yau, J. Y.-K. (2020). Utilising learning analytics to support study success in higher education: A systematic review. Educational Technology Research and Development, 68(4), 1961–1990. https://doi.org/10.1007/s11423-020-09788-z
Khlaif, Z. N., Alkouk, W. A., Salama, N., & Abu Eideh, B. (2025). Redesigning assessments for AI-enhanced learning: A framework for educators in the generative AI era. Education Sciences, 15(2), 174. https://doi.org/10.3390/educsci15020174
Khlaif, Z. N., Ayyoub, A., Hamamra, B., Bensalem, E., Mitwally, M. A. A., Ayyoub, A., Hattab, M. K., & Shadid, F. (2024). University teachers› views on the adoption and integration of generative AI tools for student assessment in higher education. Education Sciences, 14(10), 1090. https://doi.org/10.3390/educsci14101090
Kohnke, L., Zou, D., Ou, A. W., & Gu, M. M. (2025). Preparing future educators for AI-enhanced classrooms: Insights into AI literacy and integration. Computers and Education: Artificial Intelligence, 8, 100398. https://doi.org/10.1016/j.caeai.2025.100398
Lim, W. M., Gunasekara, A., Pallant, J. L., Pallant, J. I., & Pechenkina, E. (2023). Generative AI and the future of education: Ragnarök or reformation? A paradoxical perspective from management educators. The International Journal of Management Education, 21(2), 100790. https://doi.org/10.1016/j.ijme.2023.100790
Lotka, A. J. (1926). The frequency distribution of scientific productivity. Journal of the Washington Academy of Sciences, 16(12), 317–323.
Lye, C. Y., & Lim, L. (2024). Generative artificial intelligence in tertiary education: Assessment redesign principles and considerations. Education Sciences, 14(6), 569. https://doi.org/10.3390/educsci14060569
Miao, F., Holmes, W., Huang, R., & Zhang, H. (2021). AI and education: Guidance for policy-makers. United Nations Educational, Scientific and Cultural Organization. https://doi.org/10.54675/PCSP7350
Ou, A. W., Stöhr, C., & Malmström, H. (2024). Academic communication with AI-powered language tools in higher education: From a post-humanist perspective. System, 121, 103225. https://doi.org/10.1016/j.system.2024.103225
Pritchard, A. (1969). Statistical bibliography or bibliometrics? Journal of Documentation, 25(4), 348–349.
Tai, J., Ajjawi, R., Bearman, M., Boud, D., Dawson, P., & Jorre de St Jorre, T. (2023). Assessment for inclusion: Rethinking contemporary strategies in assessment design. Higher Education Research & Development, 42(2), 483–497. https://doi.org/10.1080/07294360.2022.2057451
UNESCO. (n.d.). Monitoring SDG 4. Global Education Monitoring Report. Accessed November 28, 2025. https://www.unesco. org/gem-report/en/monitoring-sdg4
Van Eck, N. J., & Waltman, L. (2018). VOSviewer manual (Version 1.6.10). Leiden University. Accessed September 29, 2025. https://www.vosviewer.com/documentation/Manual_ VOSviewer_1.6.10.pdf
Zipf, G. K. (1949). Human behavior and the principle of least effort. Addison-Wesley Press.