AI in Schools / Education Ops

A practical guide for schools navigating academic integrity in the AI era. Neither panic nor dismissal—balanced approaches that maintain integrity while preparing students for the future.

Learn how to apply data minimization principles when deploying AI in schools. Practical strategies for reducing student data exposure while maintaining functionality.

A step-by-step playbook for responding to data breaches involving student information. Covers the critical first 72 hours, notification requirements, and recovery.

Practical consent frameworks for schools using AI tools. Includes templates, tiered consent approaches, and jurisdiction-specific guidance for Singapore, Malaysia, and Thailand.

A practical framework for schools to evaluate EdTech AI vendors through a data protection lens. Includes due diligence checklist and DPA requirements.

Understand the heightened requirements for protecting student data when deploying AI systems. Covers PDPA compliance in Singapore, Malaysia, and Thailand.

Transform scattered school data into actionable insights with AI analytics. A practical guide covering dashboards, predictive models, and data governance.

Learn how to implement AI in school communications—improving translations, personalization, and efficiency while maintaining the human touch families expect.

Discover how AI scheduling tools can reduce timetabling time by 70-90% while improving constraint satisfaction. A practical implementation guide for schools.

Learn how to implement AI in school admissions responsibly—automating administrative tasks while maintaining fairness and compliance with data protection requirements.

Practical guide for school administrators exploring AI. Covers high-value applications, implementation roadmap, governance essentials, and getting started with AI in schools.

A practical guide for school administrators on enforcing AI policies effectively, including investigation procedures, progressive discipline, and prevention strategies.