The AI Integration Review (AIR), developed by GenAI:N3, is a reflective resource designed to support educators in reviewing and developing their use of generative AI in teaching and learning. It encourages critical reflection, informed decision-making and thoughtful integration of AI into academic practice.
The AI Integration Review (AIR) is a free, web-based resource developed by GenAI:N3 to help educators and programme teams critically examine and plan how generative AI is integrated into higher education curricula. It provides structured, guided reviews at both module and programme level, supporting informed decisions about learning outcomes, teaching approaches, assessment practices and graduate capabilities.
How the resource can be used
At module level, educators can review how generative AI relates to their learning outcomes, teaching and learning activities, and assessment strategies. Guided questions encourage consideration of where AI use may be appropriate, how it might support student learning, and where changes to existing practices may be needed.
At programme level, teams can take a broader view, examining the AI capabilities graduates should develop, how these capabilities progress throughout a programme, and whether teaching and assessment approaches are coherent across modules. The review helps identify gaps, duplication and opportunities for more purposeful integration.
A particularly valuable feature is the connection between programme and module reviews. Programme teams can share priorities and questions with module coordinators, while module teams can contribute their findings to the wider programme review. This supports collaboration and helps ensure that decisions about AI integration are not made in isolation.
From review to action
AIR supports the development of a Programme AI Integration Statement, drawing on the findings of the programme review. This editable statement provides a way for programme teams to articulate their shared approach to generative AI, document their decisions and identify priorities for further development.
Benefits for educators and institutions
The resource supports curriculum development, programme review, assessment redesign and academic professional development. It can be used independently by lecturers, collaboratively by programme teams, or as part of facilitated workshops led by academic developers and instructional designers.
AIR encourages a considered, discipline-sensitive approach rather than prescribing particular technologies or assuming that generative AI should be used in every learning activity. Its focus is on making purposeful educational decisions that reflect the needs of students, programmes and disciplines.
Accessible and reusable
AIR is freely available, requires no account and stores review information locally in the user’s browser. Reviews can be saved, exported and imported, allowing individuals and teams to share work and revisit their decisions over time. Programme AI Integration Statements can also be copied or saved as PDFs.
Developed by Dr Hazel Farrell in collaboration with Ken McCarthy, AIR is an open educational resource designed to support practical, collaborative and pedagogically informed approaches to generative AI integration across higher education.
Creative Commons Attribution-NonCommercial-ShareAlike (CC BY-NC-SA)
This work is licensed under a CC BY-NC-SA license, allowing sharing and adaptation for non-commercial use with proper attribution, provided derivative works use the same license.
https://creativecommons.org/licenses/by-nc-sa/4.0/
Links open in a new tab.
If you have modified or adopted this resource, share your version here. Tracking adaptations helps us measure impact and connects others with useful updates.
Explore resources sharing the topics attached to this record.
This Open Educational Resource (OER) provides educators with a practical checklist for designing gamified learning experiences in Canvas. Grounded in Self-Determination Theory, it offers actionable strategies to enhance student motivation, engagement, and participation by supporting autonomy, competence, and relatedness within an inclusive, student
LogiCraft is an interactive digital logic circuit simulator that helps students, educators, and instructional designers build, test, and analyze logic circuits through a visual canvas interface. It supports hands-on learning in digital logic, computer architecture, and electronics by combining drag-and-drop design, real-time simulation.
The final report of UCC’s SATLE-funded Smart Support? AI-assisted school placement project. It examines how Professional Master of Education student teachers use generative AI during school placement, how their AI literacy and professional judgement develop, and the implications for teacher education and placement partnerships.
