Tag: AI Upskilling

2025 Review – A Shared Conversation, Built Over Time

GenAI:N3
Estimated reading time: 9 minutes

From Individual Questions to Collective Practice

Since September, the GenAI:N3 blog has hosted a weekly series of reflections exploring what generative AI means for higher education: for teaching, learning, assessment, academic identity, and institutional responsibility. Early contributions captured a sector grappling with disruption, uncertainty, and unease, asking difficult questions about trust, integrity, creativity, and control at a moment when generative AI arrived faster than policy, pedagogy, or professional development could respond.

As the series unfolded, a clear shift began to emerge. Posts moved from individual reactions and early experimentation towards more structured sense-making, discipline-specific redesign, and crucially shared learning. The introduction of communities of practice as a deliberate strategy for AI upskilling marked a turning point in the conversation: from “How do I deal with this?” to “How do we learn, adapt, and shape this together?” Taken as a whole, the series traces that journey from disruption to agency, and from isolated responses to collective practice.

What makes this series distinctive is not simply its focus on generative AI, but the diversity of voices it brings together. Contributors include academic staff, professional staff, educational developers, students, and sector partners, each writing from their own context while engaging with a set of common challenges. The result is not a single narrative, but a constellation of perspectives that reflect the complexity of teaching and learning in an AI-shaped world.

29th September 2025 – Jim O’Mahony

Something Wicked This Way Comes

The GenAI:N3 blog series opens with a deliberately unsettling provocation, asking higher education to confront the unease, disruption, and uncertainty that generative AI has introduced into teaching, assessment, and academic identity. Rather than framing AI as either saviour or villain, this piece invites a more honest reckoning with fear, denial, and institutional inertia. It sets the tone for the series by arguing that ignoring GenAI is no longer an option; what matters now is how educators respond, individually and collectively, to a technology that has already crossed the threshold into everyday academic practice.

6th October 2025 – Dr Yannis

3 Things AI Can Do for You: The No-Nonsense Guide

Building directly on that initial unease, this post grounds the conversation in pragmatism. Stripping away hype and alarmism, it focuses on concrete, immediately useful ways AI can support academic work, from sense-making to productivity. The emphasis is not on replacement but augmentation, encouraging educators to experiment cautiously, critically, and with intent. In the arc of the series, this contribution marks a shift from fear to agency, demonstrating that engagement with AI can be practical, purposeful, and aligned with professional judgement.

13th October 2025 – Sue Beckingham & Peter Hartley

New Elephants in the Generative AI Room? Acknowledging the Costs of GenAI to Develop ‘Critical AI Literacy’

As confidence in experimentation grows, this post re-introduces necessary friction by surfacing the hidden costs of generative AI. Environmental impact, labour implications, equity, and ethical responsibility are brought into sharp focus, challenging overly simplistic narratives of efficiency and innovation. The authors remind readers that responsible adoption requires confronting uncomfortable trade-offs. Within the wider series, this piece deepens the discussion, insisting that values, sustainability, and social responsibility must sit alongside pedagogical opportunity.

20th October 2025 – Jonathan Sansom

Making Sense of GenAI in Education: From Force Analysis to Pedagogical Copilot Agents

Here the conversation turns toward structured sense-making. Drawing on strategic and pedagogical frameworks, this post explores how educators and institutions can move beyond reactive responses to more deliberate design choices. The idea of AI as a “copilot” rather than an autonomous actor reframes the relationship between teacher, learner, and technology. In the narrative of the series, this contribution offers conceptual tools for navigating complexity, helping readers connect experimentation with strategy.

27th October 2025 – Patrick Shields

AI Adoption & Education for SMEs

Widening the lens beyond universities, this post examines AI adoption through the perspective of small and medium-sized enterprises, highlighting the skills, mindsets, and educational approaches needed to support workforce readiness. The crossover between higher education, lifelong learning, and industry becomes explicit. This piece situates GenAI not just as an academic concern, but as a societal one, reinforcing the importance of education systems that are responsive, connected, and outward-looking.

3rd November 2025 – Tadhg Blommerde

Dr Strange-Syllabus or: How My Students Learned to Mistrust AI and Trust Themselves

Returning firmly to the classroom, this reflective account explores what happens when students are encouraged to engage critically with AI rather than rely on it unthinkingly. Through curriculum design and assessment choices, learners begin to question outputs, assert their own judgement, and reclaim intellectual agency. This post is a turning point in the series, showing how thoughtful pedagogy can transform AI from a threat to academic integrity into a catalyst for deeper learning.

10th November 2025 – Brian Mulligan

AI Could Revolutionise Higher Education in a Way We Did Not Expect

This contribution steps back to consider second-order effects, arguing that the most significant impact of AI may not be efficiency or automation, but a reconfiguration of how learning, expertise, and value are understood. It challenges institutions to think beyond surface-level policy responses and to anticipate longer-term cultural shifts. Positioned mid-series, the post broadens the horizon, encouraging readers to think systemically rather than tactically.

17th November 2025 – Kerith George-Briant & Jack Hogan

This Is Not the End but a Beginning: Responding to “Something Wicked This Way Comes”

Explicitly dialoguing with the opening post, this response reframes the initial sense of threat as a starting point rather than a conclusion. The authors emphasise community, dialogue, and shared responsibility, arguing that collective reflection is essential if higher education is to navigate GenAI well. This piece reinforces one of the central through-lines of the series: that no single institution or individual has all the answers, but progress is possible through collaboration.

24th November 2025 – Bernie Goldbach

The Transformative Power of Communities of Practice in AI Upskilling for Educators

This post makes the case that the most sustainable way to build AI capability in education is not through one-off training sessions, but through communities of practice that support ongoing learning, experimentation, and shared problem-solving. It highlights how peer-to-peer dialogue helps educators move from cautious curiosity to confident, critical use of tools, while also creating space to discuss ethics, assessment, and evolving norms without judgement. Positioned within the blog series, it serves as a bridge between individual experimentation and institutional change: a reminder that AI upskilling is fundamentally social, and that collective learning structures are one of the best defences against both hype and paralysis.

1st December 2025 – Hazel Farrell et al.

Teaching the Future: How Tomorrow’s Music Educators Are Reimagining Pedagogy

Offering a discipline-specific lens, this post explores how music education is being rethought in light of AI, creativity, and emerging professional realities. Rather than diluting artistic practice, AI becomes a catalyst for re-examining what it means to teach, learn, and create. Within the series, this contribution demonstrates how GenAI conversations translate into authentic curriculum redesign, grounded in disciplinary values rather than generic solutions.

8th December 2025 – Ken McCarthy

Building the Manifesto: How We Got Here and What Comes Next

This reflective piece pulls together many of the threads running through the series, documenting the collaborative process behind the Manifesto for Generative AI in Higher Education. It positions the Manifesto not as a prescriptive policy document but as a living statement shaped by diverse voices, shared concerns, and collective aspiration. In the narrative arc, it represents a moment of synthesis, turning discussion into a shared point of reference.

15th December 2025 – Leigh Graves Wolf

Rebuilding Thought Networks in the Age of AI

Moving from frameworks to cognition, this post explores how AI is reshaping thinking itself. Rather than outsourcing thought, the author argues for intentionally rebuilding intellectual networks so that AI becomes part of, not a replacement for, human sense-making. This contribution deepens the series philosophically, reminding readers that the stakes of GenAI are as much cognitive and epistemic as they are technical.

22nd December 2025 – Frances O’Donnell

Universities: GenAI – There’s No Stopping, Start Shaping!

The series culminates with a clear call to action. Acknowledging both inevitability and responsibility, this post urges universities to move decisively from reaction to leadership. The emphasis is on shaping futures rather than resisting change, grounded in values, purpose, and public good. As a closing note, it captures the spirit of the entire series: GenAI is already here, but how it reshapes higher education remains a choice.

With Thanks – and an Invitation

This series exists because of the generosity, openness, and intellectual courage of its contributors. Each author took the time to reflect publicly, to question assumptions, to share practice, and to contribute thoughtfully to a conversation that is still very much in motion. Collectively, these posts embody the spirit of GenAI:N3 – collaborative, reflective, and committed to shaping the future of higher education with care rather than fear.

We would like to extend our sincere thanks to all who have contributed to the blog to date, and to those who have engaged with the posts through reading, sharing, and discussion. The conversation does not end here. If you are experimenting with generative AI in your teaching, supporting others to do so, grappling with its implications, or working with students as partners in this space, we warmly invite you to write a blog post of your own. Your perspective matters, and your experience can help others navigate this rapidly evolving landscape.

If you would like to contribute, please get in touch (blog@genain3.ie) we would love to hear from you.

DateTitleAuthorLink
29 September 2025Something Wicked This Way ComesJim O’Mahonyhttps://genain3.ie/something-wicked-this-way-comes/
6 October 20253 Things AI Can Do for You: The No-Nonsense GuideDr Yannishttps://genain3.ie/3-things-ai-can-do-for-you-the-no-nonsense-guide/
13 October 2025New Elephants in the Generative AI Room? Acknowledging the Costs of GenAI to Develop ‘Critical AI Literacy’Sue Beckingham & Peter Hartleyhttps://genain3.ie/new-elephants-in-the-generative-ai-room-acknowledging-the-costs-of-genai-to-develop-critical-ai-literacy/
20 October 2025Making Sense of GenAI in Education: From Force Analysis to Pedagogical Copilot AgentsJonathan Sansomhttps://genain3.ie/making-sense-of-genai-in-education-from-force-analysis-to-pedagogical-copilot-agents/
27 October 2025AI Adoption & Education for SMEsPatrick Shieldshttps://genain3.ie/ai-adoption-education-for-smes/
3 November 2025Dr Strange-Syllabus or: How My Students Learned to Mistrust AI and Trust ThemselvesTadhg Blommerdehttps://genain3.ie/dr-strange-syllabus-or-how-my-students-learned-to-mistrust-ai-and-trust-themselves/
10 November 2025AI Could Revolutionise Higher Education in a Way We Did Not ExpectBrian Mulliganhttps://genain3.ie/ai-could-revolutionise-higher-education-in-a-way-we-did-not-expect/
17 November 2025This Is Not the End but a Beginning: Responding to “Something Wicked This Way Comes”Kerith George-Briant & Jack Hoganhttps://genain3.ie/this-is-not-the-end-but-a-beginning-responding-to-something-wicked-this-way-comes/
24 November 2025The Transformative Power of Communities of Practice in AI Upskilling for EducatorsBernie Goldbachhttps://genain3.ie/the-transformative-power-of-communities-of-practice-in-ai-upskilling-for-educators/
1 December 2025Teaching the Future: How Tomorrow’s Music Educators Are Reimagining PedagogyHazel Farrell et al.https://genain3.ie/teaching-the-future-how-tomorrows-music-educators-are-reimagining-pedagogy/
8 December 2025Building the Manifesto: How We Got Here and What Comes NextKen McCarthyhttps://genain3.ie/building-the-manifesto-how-we-got-here-and-what-comes-next/
15 December 2025Rebuilding Thought Networks in the Age of AILeigh Graves Wolfhttps://genain3.ie/rebuilding-thought-networks-in-the-age-of-ai/
22 December 2025Universities: GenAI – There’s No Stopping, Start Shaping!Frances O’Donnellhttps://genain3.ie/universities-genai-theres-no-stopping-start-shaping/

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The Transformative Power of Communities of Practice in AI Upskilling for Educators

GenAI:N3
By Bernie Goldbach, RUN EU SAP Lead
Estimated reading time: 5 minutes
A diverse group of five educators collaboratively studying a glowing, holographic network of digital lines and nodes on a table, symbolizing their shared learning and upskilling in Artificial Intelligence (AI) within a modern, book-lined academic setting. Image (and typos) generated by Nano Banana.
The power of collaboration: Communities of Practice are essential for educators to collectively navigate and integrate new AI technologies, transforming teaching and learning through shared knowledge and support. Image (and typos) generated by Nano Banana.

When the N-TUTORR programme ended in Ireland, I remained seated in the main Edtech25 auditorium to hear some of the final conversations by key players. They stood at a remarkable intersection of professional development and technological innovation. And some of them issued a call to action for continued conversation, perhaps engaging with generative AI tools within a Community of Practice (CoP).

Throughout my 40 year teaching career, I have walked pathways to genuine job satisfaction that extended far beyond simple skill acquisition. In my specific case, this satisfaction emerged from the synergy between collaborative learning, pedagogical innovation, and an excitement that the uncharted territory is unfolding alongside peers who share their commitment to educational excellence.

Finding Professional Fulfillment Through Shared Learning

The journey of upskilling in generative AI feels overwhelming when undertaken in isolation. I am still looking for a structured CoP for Generativism in Education. This would be a rich vein of collective discovery. At the moment, I have three colleagues who help me develop my skills with ethical and sustainable use of AI.

Ethan Mollick, whose research at the Wharton School has illuminated the practical applications of AI in educational contexts, consistently emphasises that the most effective learning about AI tools happens through shared experimentation and peer discussion. His work demonstrates that educators who engage collaboratively with AI technologies develop more sophisticated mental models of how these tools can enhance rather than replace pedagogical expertise. This collaborative approach alleviates the anxiety many educators feel about technological change, replacing it with curiosity and professional confidence.

Mairéad Pratschke, whose work emphasises the importance of collaborative professional learning, has highlighted how communities create safe spaces where educators can experiment, fail, and succeed together without judgment. This psychological safety becomes the foundation upon which genuine professional growth occurs.

Frances O’Donnell, whose insights at major conferences have become invaluable resources for educators navigating the AI landscape, directs the most effective AI workshops I have attended. O’Donnell’s hands-on training at conferences such as CESI (https://www.cesi.ie), EDULEARN (https://iceri.org), ILTA (https://ilta.ie), and Online Educa Berlin (https://oeb.global) have illuminated the engaging features of instructional design that emerge when educators thoughtfully integrate AI tools. Her instructional design frameworks demonstrate how AI can support the creation of personalised learning pathways, adaptive assessments, and multimodal content that engages diverse learners. O’Donnell’s emphasis on the human element in AI-assisted design resonates deeply with Communities of Practice

And thanks to Frances O’Donnell, I discovered the AI assistants inside H5P.

Elevating Instructional Design Through AI-Assisted Tools

The quality of instructional design, personified by clever educators, represents the most significant leap I have made when combining AI tools with collaborative professional learning. The commercial version of H5P (https://h5p.com) has revolutionised my workflow when creating interactive educational content. The smart import feature of H5P.com complements my teaching practice. I can quickly design rich, engaging learning experiences that would previously have required specialised technical skills or significant time investments. I have discovered ways to create everything from interactive videos with embedded questions to gamified quizzes and sophisticated branching scenarios.

I hope I find a CoP in Ireland that is interested in several of the H5P workflows I have adopted. For the moment, I’m revealing these remarkable capabilities while meeting people at education events in Belgium, Spain, Portugal, and the Netherlands. It feels like I’m a town crier who has a notebook full of shared templates. I want to offer links to the interactive content that I have created with H5P AI and gain feedback from interested colleagues. But more than the conversations at the conferences, I’m interested in making real connections with educators who want to actively participate in vibrant online communities where sustained professional learning continues.

Sustaining Innovation with Community

Job satisfaction among educators has always been closely tied to their sense of efficacy and their ability to make meaningful impacts on student learning. Communities of Practice focused on AI upskilling amplify this satisfaction by creating networks of mutual support where members celebrate innovations, troubleshoot challenges, and collectively develop best practices. When an educator discovers an effective way to use AI for differentiation or assessment design, sharing that discovery with colleagues who understand the pedagogical context creates a profound sense of professional contribution.

These communities also combat the professional tension that currently faces proficient AI users. Mollick’s observations about blowback against widespread AI adoption in education reveal a critical imperative to stand together with a network that validates the quality of teaching and provides constructive feedback. When sharing with a community, individual risk-taking morphs into collective innovation, making the professional development experience inherently more satisfying and sustainable.

We need the spark of N-TUTORR inside an AI-focused Community of Practice. We need to amplify voices. Together we need to become confident navigators of innovation. We need to co-create contextually appropriate pedagogical approaches that effectively leverage AI in education.

Bernard Goldbach

RUN-EU SAP Lead

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