Transforming Teacher Competencies in the Era of Generative Artificial Intelligence: Mapping the Research Landscape and Future Research Agenda
DOI:
https://doi.org/10.63822/3knvef92Keywords:
Generative Artificial Intelligence; Teacher Competencies; AI Literacy; Professional Development; Bibliometric Analysis.Abstract
The rapid development of Generative Artificial Intelligence (GenAI) has reshaped educational practices and created new demands for teachers' professional competencies. This study aims to map the global research landscape on teacher competency transformation in the GenAI era through a bibliometric analysis of Scopus-indexed publications. A total of 383 open-access journal articles published between 2023 and 2026 were analysed using performance analysis and science mapping with VOSviewer version 1.6.21. The findings reveal a substantial increase in scientific publications, with approximately 89.3% published in 2025–2026. China emerged as the leading contributor, while Indonesia ranked fifth. The research landscape is primarily structured around artificial intelligence, AI literacy, professional development, teacher training, digital competence, and AI in education. Thematic evolution indicates a shift from foundational discussions of AI literacy and professional development toward empirical investigations of technology acceptance, behavioral intention, decision-making, and academic integrity. The findings highlight the need for comprehensive teacher competency frameworks, effective continuous professional development, and stronger institutional governance to support responsible AI integration. This study contributes to understanding the intellectual development and emerging priorities of research on teacher competencies in AI-enhanced educational environments.
References
Caruana, I., Gilar-Corbi, R., & Palomar, M. (2026). Bridging the AI Skills Gap for Sustainable Education: A Structural Model of In-Service Teachers’ Learning Intentions and Behaviors. Sustainability (Switzerland), 18(6). https://doi.org/10.3390/su18063133
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. https://doi.org/10.1016/j.jbusres.2021.04.070
Fteiha, M., Al-Rashaida, M., & Ghazal, M. (2025). General and special education teachers’ readiness for artificial intelligence in classrooms: A structural equation modeling study of knowledge, attitudes, and practices in select UAE public and private schools. PLOS ONE, 20(9 September). https://doi.org/10.1371/journal.pone.0331941
Griche, M. S., & Bennis, M. (2026). Generative Artificial Intelligence Integration in Foreign Language Education in Higher Education: A Systematic Literature Review. Technology in Language Teaching and Learning, 8. https://doi.org/10.29140/tltl.2026.102827
Huynh, L., Le, T. H., Dang, B., An, B. T., Vu, C. T., & Nguyen, A. (2025). Mindset matters: Fostering teachers’ responsible AI use through professional development. Journal of New Approaches in Educational Research, 14(1). https://doi.org/10.1007/s44322-025-00043-y
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., … Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. In Learning and Individual Differences (Vol. 103). https://doi.org/10.1016/j.lindif.2023.102274
Li, X., Park, J. M., & Mitchell, J. P. (2026). Perception in the Loop: Understanding AI Chatbot Efficiency Through the Lens of Role, Support, and Technology Use in Higher Education. Student Success, 17(1), 32–48. https://doi.org/10.63608/ssj.3877
Lišnić, B., Zaharija, G., & Mladenović, S. (2025). Integration of Artificial Intelligence in K-12: Analysis of a Three-Year Pilot Study. AI (Switzerland), 6(3). https://doi.org/10.3390/ai6030049
Martín-Martín, A., Thelwall, M., Orduna-Malea, E., & Delgado López-Cózar, E. (2021). Google Scholar, Microsoft Academic, Scopus, Dimensions, Web of Science, and OpenCitations’ COCI: a multidisciplinary comparison of coverage via citations. Scientometrics, 126(1). https://doi.org/10.1007/s11192-020-03690-4
Muchtarom, M., & Suryaningsih, A. (2026). AI as a Pedagogical Partner: A Value-Based Framework for Digital Ethics in Civic Education. Journal of Culture and Values in Education, 9(1), 313–334. https://doi.org/10.46303/jcve.2026.14
Nuryadin, A., Karlimah, K., & Rizki Nugraha, M. (2026). Generative Artificial Intelligence in Education: A Systematic Literature Review on Instructional Materials Development. Participatory Educational Research, 13(2), 226–247. https://doi.org/10.17275/per.26.27.13.2
Özüdoğru, G., & Durak, H. Y. (2025). Conceptualizing pre-service teachers’ artificial intelligence readiness and examining its relationship with various variables: The role of artificial intelligence literacy, digital citizenship, artificial intelligence-enhanced innovation and perceived threats from artificial intelligence. Information Development, 41(3 Special Issue: “Artificial Intelligence initiatives”), 916–932. https://doi.org/10.1177/02666669251335657
Plaatjies, B. O., & van Wyk, M. M. (2025). Prompt Literacy as an Enhancer of Students’ Academic Writing in Higher Education Institutions: A Systematic Literature Review. Journal of Teaching and Learning, 19(4), 114–134. https://doi.org/10.22329/jtl.v19i4.10017
Qi, L., Xu, X., Wu, Y., Wang, F., & Wei, W. (2026). Investigating AI competence among Chinese secondary school teachers: Insights from the UNESCO framework. Acta Psychologica, 267. https://doi.org/10.1016/j.actpsy.2026.107053
Redecker, C. (2017). European framework for the digital competence of educators: DigCompEdu. In Joint Research Centre (JRC) Science for Policy report. https://doi.org/10.2760/159770
Safdar, G., Aftab, M. J., & Abdelhafiz, K. M. (2026). Training Needs Assessment for Teachers on ICT and AI in 21st Century Inclusive Classrooms. Journal of Education and Training Studies, 14(3), 177–189. https://doi.org/10.11114/jets.v14i3.8537
Tlili, A., Shehata, B., Adarkwah, M. A., Bozkurt, A., Hickey, D. T., Huang, R., & 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). https://doi.org/10.1186/s40561-023-00237-x
van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2). https://doi.org/10.1007/s11192-009-0146-3
Xia, Q., Yang, Y., Weng, X., Cilsalar-Sagnak, H., Cheng, W. K., & Chiu, T. K. F. (2026). Generative artificial intelligence competency self-efficacy scale for teachers and researchers (GAICS-TR) in higher education. Journal of Computers in Education, 13(2), 769–793. https://doi.org/10.1007/s40692-025-00373-y
Zupic, I., & Čater, T. (2015). Bibliometric Methods in Management and Organization. Organizational Research Methods, 18(3). https://doi.org/10.1177/1094428114562629
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Markus Hadinata (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
