Teaching, Learning, Assessment and GenAI: Moving from Reaction to Intentional Practice

By Dr Hazel Farrell & Ken McCarthy, South East Technological University & GenAI:N3
Estimated reading time: 7 minutes
A digital illustration depicting the intersection of technology and higher education. On the left, a glowing, translucent human brain composed of neural networks rises from an open, illuminated book. On the right, a group of educators and professionals sit in a circle at a glowing round table, engaged in a collaborative discussion. The background features subtle academic symbols like a graduation cap and a chalkboard, all set in a futuristic, tech-enabled environment. Image (and typos) generated by Nano Banana.
Moving from reaction to intentional practice: Exploring the collaborative future of Generative AI in higher education through human-led dialogue and pedagogical reflection. Image (and typos) generated by Nano Banana.

Generative AI has become part of higher education with remarkable speed.

In a short period of time, it has entered classrooms, assessment design, academic writing, feedback processes, and professional workflows. For many educators, its arrival felt sudden and difficult to make sense of, leaving little space to pause and consider what this shift means for learning, teaching, and academic practice.

Initial responses across the sector have often focused on risk, regulation, and control. These concerns are understandable. Yet they only tell part of the story. Alongside uncertainty and anxiety, there is also curiosity, experimentation, and a growing recognition that GenAI raises questions that are fundamentally pedagogical rather than purely technical.

On 21 January, we are delighted to host #LTHEchat to explore these questions together and to move the conversation from reaction towards more intentional, reflective practice.

The discussion will be grounded in the Manifesto for Generative AI in Higher Education, and informed by the wider work of GenAI:N3, a national initiative in Ireland supporting collaborative engagement with generative AI across higher education.

GenAI:N3: A Collaborative Project for the Sector

GenAI:N3 is a national network that was established in Ireland as part of the N-TUTORR programme, to support technological higher education institutions as they responded to the rapid emergence of generative AI. Rather than focusing on tools or technical solutions, the project centres on people, practice, and shared learning.

At its core, GenAI:N3 aims to build institutional and sectoral capacity by creating spaces where educators, professional staff, and leaders can explore GenAI together. Its work is grounded in collaboration across institutions and disciplines, recognising that no single university or role has all the answers.

The project focuses on several interconnected areas:

  • Supporting communities of practice where staff can share experiences, challenges, and emerging approaches
  • Encouraging critical and reflective engagement with GenAI in teaching, learning, assessment, and professional practice
  • Exploring the ethical, social, and institutional implications of GenAI, including questions of power, inclusion, sustainability, and academic judgement
  • Developing shared resources, events, and conversations that help the sector learn collectively rather than in isolation

GenAI:N3 is not about accelerating adoption for its own sake. It is about helping institutions and individuals make informed, values-led decisions that are aligned with the purposes of higher education.

The Manifesto as a Shared Thinking Space

The Manifesto for Generative AI in Higher Education emerged from this collaborative context. It did not begin as a formal deliverable or a policy exercise. Instead, it took shape gradually through workshops, conversations, reflections, and recurring questions raised by staff and students across the sector.

What became clear was a need for a shared language. Not a framework that closed down debate, but a set of statements that could hold complexity, uncertainty, and difference.

The Manifesto brings together 30 short statements organised across three themes:

  • Rethinking teaching and learning
  • Responsibility, ethics, and power
  • Imagination, humanity, and the future

It is intentionally concise and deliberately open. It does not offer instructions or compliance rules. Instead, it invites educators and institutions to pause, reflect, and ask what kind of learning we are designing for in a world where generative tools are readily available.

One of its central ideas is that GenAI does not replace thinking. Rather, it reveals the cost of not thinking. In doing so, it challenges us to look beyond surface solutions and to engage more deeply with questions of purpose, judgement, and educational values.

Why These Conversations Matter Now

Much of the early discourse around GenAI has centred on assessment integrity and detection. While these issues matter, they risk narrowing the conversation too quickly.

GenAI does not operate uniformly across disciplines, contexts, or learning designs. What is productive in one setting may be inappropriate in another. Students experience this inconsistency acutely, particularly when institutional policies feel disconnected from everyday teaching practice.

The work of GenAI:N3, and the thinking captured in the Manifesto, keeps this complexity in view. It foregrounds ideas such as transparency as a foundation for trust, academic judgement as something that can be supported but not automated, and ethical leadership as an institutional responsibility rather than an individual burden.

These ideas play out in very practical ways, in curriculum design, in assessment briefs, in conversations with students, and in decisions about which tools are used and why.

Why #LTHEchat?

#LTHEchat has long been a space for thoughtful, practice-led discussion across higher education. That makes it an ideal forum to explore generative AI not simply as a technology, but as a catalyst for deeper pedagogical and institutional reflection.

This chat is not about promoting a single position or reaching neat conclusions. Instead, it is an opportunity to surface experiences, tensions, and emerging practices from across the sector.

The questions we will pose are designed to open up dialogue around issues such as abundance, transparency, disciplinary difference, and what it means to keep learning human in a GenAI-rich environment.

An Invitation to Join the Conversation

Whether you are actively experimenting with generative AI, approaching it with caution, or still forming your views, your perspective is welcome.

Bring examples from your own context. Bring uncertainties and unfinished thinking. The Manifesto itself is open to use, adapt, and challenge, and GenAI:N3 continues to evolve through the contributions of those engaging with its work.

As the Manifesto suggests, the future classroom is a conversation. On 21 January, we hope you will join that conversation with us through #LTHEchat.

Links

LTHE Chat Website: https://lthechat.com/

LTHE Chat Bluesky: https://bsky.app/profile/lthechat.bsky.social

Dr Hazel Farrell

GenAI Academic Lead
SETU

Hazel Farrell has been immersed in the AI narrative since 2023 both through practice-based research and the development of guidelines, frameworks, tools, and training to support educators and learners throughout the HE sector. She led the national N-TUTORR GenAI:N3 project which was included in the EDUCAUSE 2025 Horizon Report as an exemplar of good practice. She is the SETU Academic Lead for GenAI and Chair of the university’s GenAI Steering Committee. The practical application of GenAI provides a strong foundation for her research, with student engagement initiatives for creative disciplines at the forefront of her work. Hazel recently won DEC24 Digital Educator Award for her GenAI contributions to the HE sector. She has presented extensively on a variety of GenAI related topics and has several publications in this space.

Ken McCarthy

Head of Centre for Academic Practice
SETU

Ken McCarthy is the Head of the Centre for Academic Practice at SETU, Ken leads strategic initiatives to enhance teaching, learning, and assessment across the university. He works with academic staff, professional teams, and students to promote inclusive, research-informed, and digitally enriched education. He is the current vice-president of ILTA (Irish Learning Technology Association) and was previously the university lead for the N-TUTORR programme. He has a lifelong interest in technology and education and combines this in his professional role. He has written and presented on technology enhanced learning in general and in GenAI in particular over the past number of years.

Keywords


AI May Be Scoring Your College Essay: Welcome to the New Era of Admissions


A stylized visual showing a college application essay page with glowing red marks and scores being assigned by a disembodied robotic hand emerging from a digital screen, symbolizing the automated and impersonal nature of AI-driven admissions scoring. Image (and typos) generated by Nano Banana.
The gatekeepers go digital: Welcome to the new era of college admissions, where artificial intelligence is increasingly being used to evaluate student essays, fundamentally changing the application process. Image (and typos) generated by Nano Banana.

Source

AP News

Summary

This article explores the expanding use of AI systems in U.S. university admissions processes. As applicant numbers rise and timelines tighten, institutions are increasingly turning to AI tools to assist in reviewing essays, evaluating transcripts and identifying key indicators of academic readiness. Supporters of AI-assisted admissions argue that the tools offer efficiency gains, help standardise evaluation criteria and reduce human workload. Critics raise concerns about fairness, particularly regarding students whose writing styles or backgrounds may not align with the patterns AI systems are trained to recognise. Additionally, the article notes a lack of transparency from some institutions about how heavily they rely on AI in decision-making, prompting public scrutiny and calls for clearer communication. The broader significance lies in AI’s movement beyond teaching and assessment into high-stakes decision processes that affect students’ educational and career trajectories. The piece concludes that institutions adopting AI must implement strong auditing mechanisms and maintain human oversight to ensure integrity and trust.

Key Points

  • AI now used in admissions decision-making.
  • Faster processing of applications.
  • Concerns about bias and fairness.
  • Public criticism where transparency lacking.
  • Indicates AI entering core institutional processes.

Keywords

URL

https://apnews.com/article/87802788683ca4831bf1390078147a6f

Summary generated by ChatGPT 5.1


Faculty innovate with, and avoid, AI in the classroom


A split image contrasting two distinct classroom approaches to AI. On the left, a bright, modern classroom shows faculty and students collaboratively engaging with holographic displays and laptops, demonstrating "Innovative Integration" and "Collaborative Research AI." On the right, a darker, traditional classroom features a blackboard with a large red 'X' over "AI" and "NO AI TOOLS" written below it, with faculty and students avoiding technology, symbolizing resistance to AI. Image (and typos) generated by Nano Banana.
The academic world is currently experiencing a bifurcated response to artificial intelligence: while some faculty are enthusiastically innovating with AI to transform learning, others are deliberately avoiding its integration, advocating for traditional methods. This image vividly illustrates these contrasting approaches within university classrooms, highlighting the ongoing debate and diverse strategies faculty are employing regarding AI. Image (and typos) generated by Nano Banana.

Source

Cornell Chronicle

Summary

Cornell faculty are experimenting with hybrid approaches to AI: some integrate generative AI into coursework, others push back by returning to in-person, pencil-and-paper assessments. In nutrition and disease classes, AI is used to simulate patient case studies, generating unpredictable errors that prompt students to think critically. In parallel, some professors now include short “job interview” chats or oral questions to verify understanding. A campus survey found 70% of students use GenAI weekly or more, but only 44% of faculty do. Cornell is responding via workshops, a GenAI education working group, and guidelines to preserve academic integrity while embracing AI’s pedagogical potentials.

Key Points

  • AI is used to generate case studies, simulate patients, debate AI arguments, and help faculty draft content.
  • Some faculty moved back to paper exams, in-class assessments, or short oral checks (“job interviews”) to guard learning.
  • A campus survey showed 70% of students use GenAI weekly, vs. 44% of faculty.
  • Cornell’s GenAI working group develops policies, workshops, and academic integrity guidelines around AI use.
  • The approach is not binary acceptance or rejection, but navigating where AI can support without eroding students’ reasoning and agency.

Keywords

URL

https://news.cornell.edu/stories/2025/10/faculty-innovate-and-avoid-ai-classroom

Summary generated by ChatGPT 5


We are lecturers in Trinity College Dublin. We see it as our responsibility to resist AI


Five distinguished individuals, appearing as senior academics in traditional robes, stand solemnly behind a large wooden table in an ornate, historic library. In front of them, a glowing orange holographic screen displays 'AI' with complex data and schematics. The scene conveys a sense of responsibility and potential resistance to AI within a venerable academic institution. Generated by Nano Banana.
In the hallowed halls of institutions like Trinity College Dublin, some educators are taking a principled stand, viewing it as their inherent responsibility to critically engage with and even resist the pervasive integration of AI into academic life. This image reflects a serious, considered approach to safeguarding traditional educational values amidst technological change. Image generated by Nano Banana.

Source

The Irish Times

Summary

Lecturers at Trinity College Dublin argue that even if all technical and ethical issues around generative AI were resolved, the use of GenAI still undermines fundamental elements of university education: fostering authentic human thinking, cultivating critique, and resisting the commodification of learning. They emphasise that GenAI produces plausible but shallow output, contributes to environmental and ethical harms, and can flatten student voice. The authors believe universities should reject the narrative that GenAI’s integration is inevitable, and instead double down on preserving human-centered pedagogies, critical thinking, and academic values.

Key Points

  • GenAI produces plausible but often shallow/false output; lacks true understanding.
  • Ethical, environmental, and social harms are tied to GenAI use.
  • Even with perfect versions, GenAI undermines authentic student thinking and writing.
  • Narratives of inevitability are resisted: universities can choose otherwise.
  • Universities should reaffirm critical, human intellectual labour and values.

Keywords

URL

https://www.irishtimes.com/opinion/2025/09/04/opinion-we-are-lecturers-in-trinity-college-we-see-it-as-our-responsibility-to-resist-ai/

Summary generated by ChatGPT 5