Emerging Trends of Artificial Intelligence in Education (2021–2026): A Bibliometric Analysis of Curriculum and Vocational Education Transformation
DOI:
https://doi.org/10.30596/tjpt.v6i1.623Keywords:
Artificial Intelligence in Education, Bibliometric Analysis, VOSviewer, Curriculum Transformation, Vocational EducationAbstract
Artificial intelligence (AI) increasingly reshaped educational practices, prompting growing scholarly inquiry into its pedagogical, curricular, and environmental implications. However, existing bibliometric reviews of Artificial Intelligence in Education (AIED) predominantly predated the generative AI inflection point and rarely disaggregated vocational education as a distinct theme. This study examined the intellectual structure and thematic evolution of AIED research published between 2021 and 2026, focusing on how curriculum development and vocational education transformation were represented within the field. Bibliographic data were retrieved from Scopus using the query "Artificial Intelligence" AND "Education" across title, abstract, and keyword fields, yielding 420 initial records. Following a four-stage Identification-Screening-Eligibility-Inclusion process, 107 peer-reviewed journal articles were retained. Publication output rose from five articles annually in 2021-2022 to 55 in 2025, with 83.2% of the dataset concentrated in 2023-2025, confirming a measurable post-generative AI acceleration. Arts and Humanities (45.0%) and Social Sciences (35.0%) dominated the disciplinary distribution, while China and the United States jointly led geographical output. Keyword co-occurrence mapping identified four clusters, with vocational education and training co-anchoring a cluster alongside deep and reinforcement learning, indicating an established rather than emergent research domain. This study offered the first structured mapping of vocational education's position within the post-2023 AIED landscape, informing curriculum developers, researchers, and policymakers.
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