Infrastructure and access constraints were reported in 18 of 54 studies (33%) as the second higher-order technical limitation category¶
Claim · All claims
Evidence · 1 study · reviewr2·q2
Currency · newest study 2026 · checked against its sources 2026-10-20 (automated, 1 of 1 entry) · 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q2 i? Infrastructure and access constraints — unstable internet connectivity, outdated hardware, software incompatibility, licensing restrictions, limited platform availability, and insufficient technical support — were reported in 18 studies (33%). → Espinoza-Celi V and Vargas-Saritama A 2026
Evidence¶
Espinoza-Celi V and Vargas-Saritama A 2026¶
Espinoza-Celi V and Vargas-Saritama A (2026) Technical and pedagogical limitations of artificial intelligence in undergraduate EFL higher education: a systematic review. Front. Educ. 11:1948091. https://doi.org/10.3389/feduc.2026.1948091
q2 · i? · review · r2
Study-level frequency analysis across the 54 included studies identifies infrastructure and access constraints as the second technical category, "reported in 18 studies (33%)", with barriers spanning connectivity, hardware, licensing, and technical support. Descriptive prevalence only.
"Infrastructure and access constraints constituted the second higher-order analytical category and were reported in 18 studies (33%). The reviewed evidence identified barriers related to unstable internet connectivity, outdated hardware, software incompatibility, licensing restrictions, limited platform availability, and insufficient technical support."
Discussion¶
Related Claims¶
- Large shares of students faced technology problems serious enough to impede course participation: 44 percent internet connectivity and 23 percent hardware/software issues — related
- Learners used products outside class despite infrastructure limits: 65% of surveyed students reported doing software work outside class while mobile access was largely unavailable — related
- In informal virtual programs, technology access was the first and most significant barrier to participating in Hero Elementary — related
- Nearly half of STEM students experienced internet connectivity problems that interfered with course participation after the COVID shift to remote instruction — related
- Teachers' technology use increased during COVID-19 remote learning, but infrastructure and device barriers hindered effective integration — related
- Technical issues (login scanning, internet connectivity, projector setup, and glitches) frustrated students and created a significant barrier to playlist implementation — related
- Unreliable AI-generated output is the most frequently reported technical limitation of AI-supported undergraduate EFL instruction, appearing in 22 of 54 studies (41%) — related
- Infrastructure, connectivity or limited access is the most frequent barrier (45.2%) to digitally supported teacher education — related
- Teachers identify attendance, unreliable devices, prior academic gaps, and COVID-related disruption as compounding contextual barriers to persistence — related
- Infrastructure inequities — chronic bandwidth limitations, power outages, and device incompatibility — severely disrupt proctored assessments and exacerbate educational disadvantages in low-resource settings — a narrower finding that bears on this claim
- Technical difficulties were the most frequently reported implementation limitation, mentioned in ten of the thirteen studies — related
- Persistent technical limitations constitute an authenticity gap in AI-powered nursing simulations — a narrower finding that bears on this claim
- Integrating scientific visualization into secondary education faces three named problems: basic scientific practices, classroom-format incompatibility, and infrastructure needs — related
- Infrastructure barriers — limited internet speed, connectivity problems and lack of technical support — hinder effective AI use in nursing education institutions — possibly the same claim (merge candidate)
- Community survey of power-and-energy researchers and practitioners finds barriers to running AI models are nearly universal, affecting even experienced users — related
- Participants who accessed the report card site with mobile devices had more difficulty using it — a narrower finding that bears on this claim
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
infrastructure-access-constraints-ai-efl |
title |
Infrastructure and access constraints were reported in 18 of 54 studies (33%) as the second higher-order technical limitation category |
description |
Infrastructure and access constraints were reported in 18 of 54 studies (33%) as the second higher-order technical limitation category |
status |
review |
evidence_strength |
moderate |
newest_evidence |
2026 |
source_checked |
2026-10-20 |
generated |
by process:wiki-ingest on 2026-10-10 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — espinoza-celi-v-and-vargas-saritama-a-2026 |
Frontmatter is the page's machine-readable record — see the Schema & Guide.