Teacher Agency and Generative Artificial Intelligence in Education: Bibliometric Analysis and Science Mapping (2022-2026)
DOI:
https://doi.org/10.70577/vk70zn70Keywords:
teacher agency; generative artificial intelligence; teacher education; bibliometrics; science mapping.Abstract
Generative artificial intelligence has introduced new forms of assistance, automation, and co-production in teaching, intensifying debates about teacher agency, pedagogical judgment, and professional autonomy. This study aimed to characterize the evolution, thematic structure, and research fronts connecting teacher agency with generative artificial intelligence between 2022 and 10 September 2026. An exploratory bibliometric analysis was conducted on a verified corpus of 30 DOI-bearing publications retrieved through structured searches of open scholarly metadata and cross-checked against publisher records. Temporal productivity, source concentration, conceptual recurrence, and thematic relationships were examined. Output was absent in 2022, incipient in 2023-2024, and accelerated in 2025-2026, which accounted for 80.0% of the corpus. Mapping identified four clusters: agency and professional judgment, teacher education, professional knowledge for AI integration, and assessment-governance. Recent literature shifts attention from technology adoption toward negotiated control, critical validation of algorithmic outputs, and preservation of professional responsibility. The field is therefore in an early consolidation phase, characterized by fragmented authorship and increasing conceptual convergence around human-AI relations. Future research should expand longitudinal evidence, include Latin American contexts, and examine institutional conditions that strengthen or constrain teacher agency.
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Copyright (c) 2026 Oscar Antonio Martínez Molina, Ana María Villón Tomalá, Luis Enrique Hernández Amaro, Richard Antonio Martínez Villegas (Autor/a)
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