arbiter
JournalsPricingAccount

Teachers in transition: mapping the impact of artificial intelligence on teachers

Bicheng Diao et al.

International Journal of Information and Learning Technology2026https://doi.org/10.1108/ijilt-08-2025-0241article
ABDC C
Weight
0.50

What the paper says

Purpose This study examines the evolving influence of artificial intelligence on teachers over the past 2 decades, reflecting a broader computational turn in education. Design/methodology/approach Using bibliometric methods on literature indexed in Scopus and Web of Science Core Collection, it identifies key shifts in scholarly attention, theoretical perspectives and pedagogical implications. Through keyword co-occurrence, burst analysis and multidimensional scaling, the study maps the field’s evolution across four developmental stages (2002–2024). Findings The findings reveal a gradual transition from belief-based discourse to attitude-behavior frameworks, reflecting how AI integration has reshaped the professional expectations and cognitive roles of educators. Emerging themes such as burnout, perceived risk and role transformation highlight broader challenges facing teachers in adapting to technological change. Originality/value This review uncovers structural patterns within the literature and also offers critical insights into the redefinition of teaching in the AI era. It calls for historically grounded, interdisciplinary inquiry, thereby informing both future research and educational quality.

Open paper page →

Cite this paper

https://doi.org/https://doi.org/10.1108/ijilt-08-2025-0241

Or copy a formatted citation

@article{bicheng2026,
  title        = {{Teachers in transition: mapping the impact of artificial intelligence on teachers}},
  author       = {Bicheng Diao et al.},
  journal      = {International Journal of Information and Learning Technology},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1108/ijilt-08-2025-0241},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

Teachers in transition: mapping the impact of artificial intelligence on teachers

Flags are reviewed by the Arbiter methodology team within 5 business days.

Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.