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Good practice

NOOR — Saudi Arabia's National Education Management Information System

Saudi Arabia · Riyadh · See the Saudi Arabia profile

Saudi Arabia's national NOOR platform runs enrolment, attendance, grading and communications for over 12 million users across 33,000+ schools, layering in dashboards and early predictive-analytics features, though a 2025 peer review cautions its efficiency figures are ministry se

Details

Promoter
Ministry of Education of Saudi Arabia
Period
2012–ongoing
Keywords
education management information system, administration, digitalisation, decision support, e-government

Description

NOOR is the Saudi Ministry of Education's national Education Management Information System (EMIS), first launched around 2012 as part of the Kingdom's broader digital-government push and expanded under Vision 2030. It centralises enrolment, attendance, grade processing, and family/teacher communications for the entire public and much of the private school system, and has since been extended into decision-support dashboards intended to move toward predictive analytics for at-risk students.

According to ministry-published statistics, NOOR now serves over 12 million users, including roughly 6.5 million students and 500,000 teachers, across more than 33,000 schools and 400+ digital services. The Ministry reports administrative processing time down 65%, grade-processing time down 70%, data-entry error rates falling from 15% to under 3%, administrative errors down roughly 45%, inter-departmental information exchange time down almost 60%, and 99.5% system uptime. In 2013 NOOR won the Saudi E-Government Achievement Award (following a 2012 WSIS Award), and the underlying EduWave platform it is built on has also been deployed, in adapted form, in Jordan, Bahrain, Oman and elsewhere.

A 2025 peer-reviewed profile in MDPI's Encyclopedia journal — co-authored by researchers from Saudi, Spanish and Lebanese universities — is unusually candid about the limits of this evidence: it states that "access to detailed system data is highly restricted" and that the quantitative indicators in the literature are "derived primarily from officially published statistics, ministry reports, and secondary literature rather than direct data extraction," explicitly warning that "associations reported between the NOOR platform and educational outcomes must not be interpreted as causal effects." The same review describes NOOR's predictive/AI-driven analytics as an emerging rather than fully deployed capability, with "enhanced advanced analytics and predictive features" framed as a future direction rather than a current, evaluated feature.

NOOR is best read, honestly, as a mature, very-large-scale national EMIS with real digitisation gains and an AI/predictive-analytics layer that is still nascent and not yet independently evaluated for causal impact on learning or dropout outcomes.

Read the full analysis: https://www.mdpi.com/2673-8392/5/4/216

Implementation

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