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Artificial Intelligence Community of Practice
The Artificial Intelligence Community of Practice (AiCoP) provides a supportive, collegial space to share practice examples about artificial intelligence in their practice.
GenAI presents both opportunities and risks for higher education practice. Motivated by a shared commitment to enhancing and protecting the student experience, the AiCoP brings colleagues together to explore these tensions through interprofessional collaboration, experience sharing and critically reflective dialogue.
The AiCoP exists to support staff in making sense of GenAI in ways that are responsible, effective and ethical. Rather than promoting specific tools or prescribing approaches, the community focuses on developing shared understanding of how GenAI influences curriculum design, assessment, feedback, academic integrity and student engagement—recognising that these questions are best addressed collectively rather than in isolation.
The community provides a platform for staff to:
- Explore emerging uses of GenAI and the implications for higher education practice
- Share evidence-informed and critically reflective accounts of GenAI use in learning, teaching and assessment
- Consider ethical issues, bias and professional responsibility in GenAI-driven tools
- Develop confidence and capability in GenAI-informed pedagogy
- Contribute to institutional thinking, guidance and frameworks around GenAI integration
Have you got a story you would like to share? Use the Expression of Interest Form to contribute
In keeping with this ethos
AiCoP models transparent and reflective use of GenAI in its own work. Generative AI tools may be used to support drafting, sense-making and refinement of resources (including this web content), with all outputs subject to human judgement, professional values and institutional principles. This is supported by the approach described by JISC in this blog post
The AiCoP is intended as a space where uncertainty is expected, questions are welcomed, and learning is shared—supporting thoughtful experimentation while maintaining academic integrity and professional trust.
| AiCoP is: | AiCoP is not: |
|---|---|
| A developmental community of practice | A policy-setting or compliance body |
| A safe space for discussion, uncertainty and experimentation | A monitoring or surveillance mechanism |
| Focused on pedagogy, assessment, integrity and feedback | A space that promotes tools over pedagogy |
| Informed by evidence, professional judgement and values | Technology led |
Ai CoP Sessions
The AiCoP is open to all university staff, including but not restricted to academic colleagues, professional services staff, learning technologists, researchers and those supporting teaching and assessment.
No prior knowledge of artificial intelligence is required
The community welcomes colleagues who are:
- curious about GenAI but unsure where to start
- cautious or concerned about its implications
- already experimenting and keen to share learning
The AiCoP recognises that confidence, context and constraints vary across disciplines and roles. Participation is voluntary, flexible and respectful of professional experience, making the community relevant whether GenAI feels distant, disruptive or already embedded in day-to-day practice.
AiCoP sessions are designed to be interactive, reflective and grounded in practice. They prioritise dialogue over presentation and encourage colleagues to learn from one another’s experiences across disciplines and roles.
Typical features of sessions include:
- news updates
- short provocations or scenarios to prompt discussion
- case studies drawn from real teaching, assessment and feedback contexts
- exploration of ethical dilemmas and professional judgement
- focused conversations about assessment design, academic integrity and student use of GenAI
Sessions are offered in a mix of online and face-to-face formats to support participation across the university. They are intentionally informal, with no expectation that colleagues arrive with answers or expertise. The emphasis is on shared exploration rather than demonstration.
While topics evolve in response to practice and emerging developments, AiCoP commonly focuses on:
- GenAI and assessment design, including assessment integrity and authenticity
- student use of GenAI and implications for learning and feedback
- academic integrity and integrity-by-design approaches
- ethical, inclusive and accessible practice
- professional standards, PSRB considerations and disciplinary contexts
- developing GenAI literacy for staff and students
Themes are shaped by participant interests and institutional priorities, ensuring discussions remain timely, relevant and practice-led.
The AiCoP contributes to institutional understanding of GenAI through practice-informed insight rather than formal decision-making. Discussions and shared learning from the community help to:
- inform the development and review of guidance, frameworks and principles
- shape staff development and CPD activity
- surface examples of effective and ethical practice
- support scholarship and evaluation related to GenAI in higher education
The AiCoP does not set policy or make compliance decisions. Instead, it acts as a reflective space where emerging issues can be explored before they are translated into formal processes.
How to get involved
Colleagues are welcome to engage with the AiCoP in ways that suit their interests and availability.
You can get involved by:
- complete the Expression of Interest Form
- emailing the community aicop@ulster.ac.uk
- joining the AiCoP Teams channel
- attending sessions on a drop-in basis
- contributing questions, cases or reflections from practice
Semester 2 25/26: To attend a meeting, book a place using Evolve
- Wednesday 18 February 2pm to 3:30pm Online
- Wednesday 18 March 2pm to 3:30pm Online
- Wednesday 22 April 2pm to 3:30pm Online
- Wednesday 20 May 2pm to 3:30pm Online
- Wednesday 24 June 2pm to 3:30pm Online
There is no expectation of prior expertise or sustained commitment. Participation is voluntary, flexible and shaped by professional interest.
