Keywords
Children with disabilities
Competitive intelligence
Educational intelligence
Teacher data literacy
Inclusive education
How to Cite
Abstract
Purpose: This review explores the ways in which teachers use observations, assessments, family knowledge, and service records to interpret and form educational intelligence for making judgments and providing support to children with disabilities regarding school readiness.
Methodology/approach: Using a structured integrative design, the review synthesized 34 peer-reviewed articles published between 2020 and 2025. Sources were located through targeted searches and citation chaining, then checked against publisher records and DOI metadata. Evidence was coded by readiness domain, intelligence-cycle stage, source, decision use, organizational condition, and ethical safeguard.
Originality/Relevance: The article adapts competitive-intelligence logic to inclusive early childhood education without treating children or schools as competitors. Educational intelligence is framed as an ethical capacity to scan signals, triangulate evidence, interpret uncertainty, coordinate action, and learn from outcomes.
Key findings: Useful intelligence comes when one integrates the process of observing with developmentally appropriate assessment, family voice, a multidisciplinary approach and contextual information. Data, by themselves, do not lead to better decisions. Teacher data literacy, team structures and workflows, data records, organizational structures and supports, and mitigations against deficit labeling, surveillance, and inaccurate precision are all key factors in quality.
Theoretical/methodological contributions: The review outlines an Inclusive Educational Intelligence Cycle and six propositions relating to scanning breadth, triangulation, interpretive competence, family engagement, organisational learning and ethical governance with readiness support. It also outlines a research agenda focused on access, inclusion and responsible decision-making.
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