Quality improvement method
A corrective-action cycle for mathematics and reading performance
A corrective-action cycle for mathematics and reading performance — diagnosis, responsible ownership, effectiveness measures and closure evidence.
Información oficial
Avisos de ICEQC y análisis basados en fuentes sobre evidencias educativas, políticas e instrumentos normativos.
Se muestran 11 de 11 resultados
1061 artículos publicados
Quality improvement method
A corrective-action cycle for mathematics and reading performance — diagnosis, responsible ownership, effectiveness measures and closure evidence.
Quality improvement method
Testing whether improvements in governance of generative artificial intelligence are sustained — diagnosis, responsible ownership, effectiveness measures and closure evidence.
Quality improvement method
This practice note explains how SDG 4 at the midpoint should be scoped, implemented and verified, with closure dependent on demonstrated effect.
Quality improvement method
Improvement planning for SDG 4 at the midpoint under constrained resources — diagnosis, responsible ownership, effectiveness measures and closure evidence.
Quality improvement method
The article treats risk-based improvement planning for AI-supported assessment as a controlled process requiring clear ownership, outcome evidence and review of residual risk.
Quality improvement method
Work on global qualification recognition in force is structured around a defined baseline, accountable action, outcome evidence and verification before closure.
Quality improvement method
A controlled method for learner data privacy is set out through cause analysis, assigned responsibility, outcome measures and closure evidence.
Quality improvement method
Review of AI-supported assessment distinguishes completed activity from verified improvement and keeps unresolved action open to further examination.
Quality improvement method
This practice note explains how quality controls for academic integrity should be scoped, implemented and verified, with closure dependent on demonstrated effect.
Quality improvement method
The method for consistency in AI-supported assessment proceeds from diagnosis and ownership to effectiveness testing, residual risk and evidence of sustained effect.
Quality improvement method
This practice note explains how assurance and improvement in learner data privacy should be scoped, implemented and verified, with closure dependent on demonstrated effect.