Research Hotspots and Emerging Trends in AI-Empowered Teacher Professional Development in Higher Education Using CiteSpace (2015–2025)

Authors

Kaizhou Qin UNIRAZAK
MuiYee Cheok UNIRAZAK

Keywords:

Artificial Intelligence, Teacher Professional Development, Higher Education, Faculty Development, CiteSpace, Scientometric Analysis

Abstract

Artificial intelligence (AI) is transforming teacher professional development in higher education by improving instructional design, pedagogical innovation, digital skills, and lifelong learning. While research on AI-empowered teacher professional development has grown rapidly, the field's knowledge structure, key areas of research, and emerging trends are not well understood. This study aims to systematically map the intellectual landscape of this field through scientometric analysis. Bibliographic data published between 2015 and 2025 was retrieved from the Web of Science Core Collection and analysed using CiteSpace. Publication trends, collaboration networks, keyword co- occurrence, cluster analysis, timeline visualisation, citation bursts and co-citation networks were employed to reveal the knowledge base and the evolution of the research. The findings are expected to highlight major research themes such as AI literacy, digital competence, faculty development, generative AI, teaching innovation and human – AI collaboration, and illustrate the shift from technology-assisted teacher training to AI- driven professional development. The study provides a comprehensive overview of the research landscape, offering theoretical insights and practical implications for the sustainable professional development of teachers in the era of artificial intelligence.

Author Biographies

Kaizhou Qin, UNIRAZAK

Artificial intelligence (AI) is transforming teacher professional development in higher education by improving instructional design, pedagogical innovation, digital skills, and lifelong learning. While research on AI-empowered teacher professional development has grown rapidly, the field's knowledge structure, key areas of research, and emerging trends are not well understood. This study aims to systematically map the intellectual landscape of this field through scientometric analysis. Bibliographic data published between 2015 and 2025 was retrieved from the Web of Science Core Collection and analysed using CiteSpace. Publication trends, collaboration networks, keyword co- occurrence, cluster analysis, timeline visualisation, citation bursts and co-citation networks were employed to reveal the knowledge base and the evolution of the research. The findings are expected to highlight major research themes such as AI literacy, digital competence, faculty development, generative AI, teaching innovation and human – AI collaboration, and illustrate the shift from technology-assisted teacher training to AI- driven professional development. The study provides a comprehensive overview of the research landscape, offering theoretical insights and practical implications for the sustainable professional development of teachers in the era of artificial intelligence.

MuiYee Cheok, UNIRAZAK

Artificial intelligence (AI) is transforming teacher professional development in higher education by improving instructional design, pedagogical innovation, digital skills, and lifelong learning. While research on AI-empowered teacher professional development has grown rapidly, the field's knowledge structure, key areas of research, and emerging trends are not well understood. This study aims to systematically map the intellectual landscape of this field through scientometric analysis. Bibliographic data published between 2015 and 2025 was retrieved from the Web of Science Core Collection and analysed using CiteSpace. Publication trends, collaboration networks, keyword co- occurrence, cluster analysis, timeline visualisation, citation bursts and co-citation networks were employed to reveal the knowledge base and the evolution of the research. The findings are expected to highlight major research themes such as AI literacy, digital competence, faculty development, generative AI, teaching innovation and human – AI collaboration, and illustrate the shift from technology-assisted teacher training to AI- driven professional development. The study provides a comprehensive overview of the research landscape, offering theoretical insights and practical implications for the sustainable professional development of teachers in the era of artificial intelligence.

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