Address infrastructure, accessibility, teacher preparedness, curriculum alignment, data governance, and institutional support when scaling AI-supported mathematics learning¶
Strategy · All strategies
Evidence · 2 claims (1 for, 1 mixed) · 2 studies (2 review),q2· 0 of 2 report an effect size · 2 claims rest on one study
Description¶
The review identifies implementation conditions shaping ITS effectiveness: "infrastructure, accessibility, teacher preparedness, curriculum alignment, data governance, and institutional support". Scaling requires attention to affordability, interoperability, technical support, and responsible data governance, because technical scalability does not equal equitable educational access. A platform may serve many users while remaining inaccessible to learners without devices, connectivity, electricity, digital literacy, or teacher assistance.
Design Implications¶
Context¶
Requirements¶
- Affordable, reliable infrastructure and device access; curricular and linguistic alignment of content; institutional support and data governance arrangements.
Constraints¶
- Without these conditions, the review states AI may reproduce or intensify existing educational inequalities rather than expand meaningful learning opportunities.
Target Learners¶
- mathematics learners in under-resourced and Global South settings, and learners with limited digital access
Target Learning Goals¶
- equitable access to personalised mathematics support and sustained implementation of ITS-based instruction
Affordances¶
Claims¶
- Infrastructure and access constraints were reported in 18 of 54 studies (33%) as the second higher-order technical limitation category [+W]
- Infrastructure, connectivity or limited access is the most frequent barrier (45.2%) to digitally supported teacher education [~W]
Related Strategies¶
Examples¶
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Key Sources¶
- Ogunsakin IB, Ayanwale MA, Falebita OS and Felemu OJ (2026) Reimagining mathematics education through intelligent tutoring: evidence, opportunities, and implementation challenges. Front. Educ. 11:1943906. https://doi.org/10.3389/feduc.2026.1943906
Page metadata
| Field | Value |
|---|---|
type |
strategy |
id |
its-implementation-conditions-strategy |
title |
Address infrastructure, accessibility, teacher preparedness, curriculum alignment, data governance, and institutional support when scaling AI-supported mathematics learning |
description |
The review identifies implementation conditions shaping ITS effectiveness: "infrastructure, accessibility, teacher preparedness, curriculum alignment, data governance, and institutional support". |
status |
review |
generated |
by process:wiki-ingest on 2026-10-11 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — ogunsakin-ib-2026 |
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