Create an institutional approach to generative AI that connects educational purpose with accountability. This guide covers use-case selection, data handling, staff development, pilot evaluation and ongoing review.
Use AI assistance in research while preserving source accuracy, confidentiality and human responsibility. This guide distinguishes discovery support from evidence verification and explains how to document meaningful AI use.
Respond to AI through clear expectations and credible assessment design. This guide helps institutions distinguish permitted assistance from misrepresentation, collect learning evidence and handle concerns through fair academic processes.
Develop the practical knowledge educators need to evaluate AI tools and outputs. This guide focuses on verification, pedagogical judgement, privacy, bias and professional learning rather than tool-specific tricks.
Create a coherent learning sequence across online and classroom settings. This guide explains activity selection, preparation, interaction, feedback and accessibility, with an example that avoids duplicating the same teaching twice.
Evaluate a learning management system against real institutional needs. This guide covers teaching workflows, accessibility, integration, support, lifecycle costs and exit planning, with a practical approach to demonstrations and pilots.
Use learning analytics to inform supportive action while respecting students and the limits of data. This guide covers purpose, interpretation, intervention design, governance and evaluation of analytics-based support.
Build practical protection around student information and essential academic services. This guide connects data inventories, access controls, vendor review, staff awareness and incident preparedness with clear institutional responsibility.
Use and create open educational resources with attention to quality, licensing and accessibility. This guide explains how to evaluate material, adapt it responsibly and maintain a resource that others can reuse.
Evaluate educational technology through a focused pilot and transparent decision criteria. This guide connects evidence of learning with implementation cost, accessibility, staff effort and the conditions required for sustainable adoption.
CARE Knowledge Centre publishes educational explainers, practical guides and institutional perspectives. The included guides were prepared with AI assistance and source checks; they are not peer-reviewed research studies. Sources and editorial notes appear with each article. Regulations, institutional requirements and funding conditions should be checked with the relevant authority before action.
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