Informations officielles
Avis de l’ICEQC et analyses fondées sur des sources concernant les données probantes, les politiques et les instruments réglementaires en matière d’éducation.
12 résultats affichés sur 43
1061 articles publiés
Quality improvement method
This practice note explains how education for sustainability through documented follow-up should be scoped, implemented and verified, with closure dependent on demonstrated effect.
Data and research analysis
The reliability of evidence on progress in teacher supply and retention is examined together with the limits that apply when findings inform consequential decisions.
Standards interpretation
Controls for governance arrangements for institutional AI policies are examined from initial evidence through exceptions, decision authority and continuing assurance.
Data and research analysis
The reliability of evidence on reporting learner agency is examined together with the limits that apply when findings inform consequential decisions.
Quality improvement method
Work on teacher supply and retention is structured around a defined baseline, accountable action, outcome evidence and verification before closure.
Quality improvement method
Improvement work concerning implementation of AI literacy obligations requires baseline evidence, responsible action, measurable outcomes, independent verification and follow-up.
Standards interpretation
This article examines how human oversight in automated education decisions is defined, evidenced and reviewed, keeping exceptions and unresolved limitations visible.
Data and research analysis
Evidence relevant to automated decision oversight is assessed for currency, coverage and comparability, with material uncertainty stated alongside the finding.
Quality improvement method
Improvement work concerning micro-credential quality requires baseline evidence, responsible action, measurable outcomes, independent verification and follow-up.
Quality improvement method
A controlled method for ownership and follow-through for data minimisation is set out through cause analysis, assigned responsibility, outcome measures and closure evidence.
Policy and regulatory analysis
Institutional responsibilities arising from automated decision oversight — responsible authority, implementation controls, affected parties and public accountability.
Data and research analysis
Timeliness and completeness of data on implementation of AI literacy obligations — source definitions, population coverage, data limitations and permitted conclusions.
