Claims

Authorship of AIED systematic reviews is concentrated in Asia and Europe, with China, Spain, and the United States the most productive countries

Claim · All claims
Evidence · 1 study · review r2 · q2
Currency · newest study 2024 · not yet checked against its sources · not reviewed by a person

Subclaims

Reading the evidence codes

q is the design tier, i the impact, n the sample, and the kind with its r the rigour judged within that kind: what each code means.

This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.

q2 i? Most included reviews were conducted in Asia (49%) and Europe (25%), with far fewer in North America (9%), Oceania (7%), Africa (6%), and South America (4%). → Yao Fu 2024

Evidence

Yao Fu 2024

Yao Fu, Zhenjie Weng, Jiaxi Wang. (2024). Examining AI Use in Educational Contexts: A Scoping Meta-Review and Bibliometric Analysis. International Journal of Artificial Intelligence in Education. https://doi.org/10.1007/s40593-024-00442-w

q2 · i? · review · r2

Analysis of the first author's country/region across the 126 included reviews, visualized in Fig. 4. The article reports the continental percentages as printed and notes authorship was distributed across 40 different countries/regions, with China, Spain, and the United States as the top three contributors.

"most studies were conducted in Asia (49%), followed by Europe (25%). Far less systematic reviews were conducted in North America (9%), Oceania (7%), Africa (6%), and South America (4%)"

Discussion

Page metadata
Field Value
type claim
id aied-review-authorship-geographic-distribution
title Authorship of AIED systematic reviews is concentrated in Asia and Europe, with China, Spain, and the United States the most productive countries
description Authorship of AIED systematic reviews is concentrated in Asia and Europe, with China, Spain, and the United States the most productive countries
status review
evidence_strength moderate
newest_evidence 2024
generated by process:wiki-ingest on 2026-10-27
trust unverified — no one has confirmed this page's content
sources 1 — yao-fu-2024

Frontmatter is the page's machine-readable record — see the Schema & Guide.