Universities are evolving their approach to artificial intelligence, moving beyond simply detecting AI-generated content to actively and ethically embedding AI as a tool for enhanced learning and development. This image visually outlines this critical shift, showcasing how institutions are now focusing on integrating AI within a robust ethical framework to foster personalised learning, collaborative environments, and innovative educational practices. Image (and typos) generated by Nano Banana.
Source
HEPI
Summary
Rather than focusing on detection and policing, this blog argues universities should shift toward ethically embedding AI as a pedagogical tool. Based on research commissioned by Studiosity, evidence shows that when AI is used responsibly, it correlates with improved outcomes and retention—especially for non-traditional students. The blog presents a “conduit” metaphor: AI is like an overhead projector—helpful, but not replacing core learning. A panel at the Universities UK Annual Conference proposed values and guardrails (integrity, equity, transparency, adaptability) to guide institutional policy. The piece calls for sandboxing new tools, centring student support and human judgment in AI adoption.
Key Points
The narrative needs to move from detection and restriction to development and support of AI in learning.
Independent research found a positive link between guided AI use and student attainment/retention, especially for non-traditional learners.
AI should be framed as a conduit (like projectors) rather than a replacement of teaching/learning.
A values-based framework is needed: academic integrity, equity, transparency, responsibility, resilience, empowerment, adaptability.
Universities should use “sandboxing” (controlled testing) and robust governance rather than blanket bans.
by Jim O’Mahony, SFHEA – Munster Technological University
The true test of a professor’s intelligence: finding the lost remote control. Image generated by Nano Banana
I remember as a 7-year-old having to hop off the couch at home to change the TV channel. Shortly afterwards, a futuristic-looking device called a remote control was placed in my hand, and since then I have chosen its wizardry over my own physical ability to operate the TV. Why wouldn’t I? It’s reliable, instant, multifunctional, compliant and most importantly… less effort.
The Seduction of Less Effort
Less effort……….as humans, we’re biologically wired for it. Our bodies will always choose energy saving over energy-consuming, whether that’s a physical instance or a cognitive one. It’s an evolutionary aid to conserve energy.
Now, my life hasn’t been impaired by the introduction of a remote control, but imagine for a minute if that remote control replaced my thinking as a 7-year-old rather than my ability to operate a TV. Sounds fanciful, but in reality, this is exactly the world in which our students are now living in.
Within their grasp is a seductive all-knowing technological advancement called Gen AI, with the ability to replace thinking, reflection, metacognition, creativity, evaluative judgement, interpersonal relationships and other richly valued attributes that make us uniquely human.
Now, don’t get me wrong, I’m a staunch flag bearer for this new age of Gen AI and can see the unlimited potential it holds for enhanced learning. Who knows? Someday, it may even solve Bloom’s 2 sigma problem through its promise of personalised learning?
Guardrails for a New Age
However, I also realise that as the adults in the room, we have a very narrow window to put sufficient guardrails in place for our students around its use, and urgent considered governance is needed from University executives.
Gen AI literacy isn’t the most glamorous term (it may not even be the most appropriate term), but it encapsulates what our priority as educators should be. Learn what these tools are, how they work, what are the limitations, problems, challenges, pitfalls, etc, and how can we use them positively within our professional practice to support rather than replace learning?
Isn’t that what we all strive for? To have the right digital tools matched with the best pedagogical practices so that our students enter the workforce as well-rounded, fully prepared graduates – a workforce by the way, that is rapidly changing, with more than 71% of employers routinely adopting Gen AI 12 months ago (we can only imagine what it is now).
Shouldn’t our teaching practices change then, to reflect the new Gen AI-rich graduate attributes required by employers? Surely, the answer is YES… or is it? There is no easy answer – and perhaps no right answer. Maybe we’ve been presented with a wicked problem – an unsolvable situation where some crusade to resist AI, and others introduce policies to ‘ban the banning’ of AI! Confused anyone?
Rethinking Assessment in a GenAI World
I believe a common-sense approach is best and would have us reimagine our educational programmes with valid, secure and authentic assessments that reward learning both with and without the use of Gen AI.
Achieving this is far from easy, but as a starting point, consider a recent paper from Deakin University, which advocates for structural changes to assessment design along with clearly communicated instructions to students around Gen AI use.
To facilitate a more discursive approach regarding reimagined assessment protocols, some universities are adopting ‘traffic light systems’ such as the AI Assessment scale, which, although not perfect (or the whole solution), at least promotes open and transparent dialogue with students about assessment integrity – and that’s never a bad thing.
The challenge will come from those academics who resist the adoption of Gen AI in education. Whether their reasons relate to privacy, environmental issues, ethics, inherent bias, AGI, autonomous AI or cognitive offloading concerns (all well-intentioned and entirely valid by the way), Higher Ed debates and decision making around this topic in the coming months will be robust and energetic.
Accommodating the fearful or ‘traditionalist educators’ who feel unprepared or unwilling to road-test Gen AI should be a key part of any educational strategy or initiative. Their voices should be heard and their opinions considered – but in return, they also need to understand how Gen AI works.
From Resistance to Fluency
Within each department, faculty, staffroom, T&L department – even among the rows of your students, you will find early adopters and digital champions who are a little further along this dimly lit path to Gen AI enlightenment. Seek them out, have coffee with them, reflect on their wisdom and commit to trialling at least one new Gen AI tool or application each week – here’s a list of 100 to get you started. Slowly build your confidence, take an open course, learn about AI fluency, and benefit from the expertise of others.
I’m not encouraging you to be an AI evangelist, but improving your knowledge and general AI capabilities will make you better able to make more informed decisions for you and your students.
Now, did anyone see where I left the remote control?
Jim O’Mahony
University Professor | Biotechnologist | Teaching & Learning Specialist Munster Technological University
I am a passionate and enthusiastic University lecturer with over 20 years experience of designing, delivering and assessing undergraduate and postgraduate programmes. My primary focus as an academic is to empower students to achieve their full potential through innovative educational strategies and carefully designed curricula. I embrace the strategic and well-intentioned use of digital tools as part of my learning ethos, and I have been an early adopter and enthusiastic advocate of Artificial Intelligence (AI) as an educational tool.
While AI teaching tools are certainly not a ‘panacea’ for all educational challenges, they possess immense potential as a ‘force multiplier,’ significantly enhancing learning experiences. This image visually contrasts AI’s limitations with its power to augment human capabilities, underscoring a nuanced approach to its integration in the classroom. Image (and typos) generated by Nano Banana.
Source
The New Indian Express
Summary
The author argues that while AI teaching tools are gaining attention, their value shows only when paired with thoughtful pedagogy, not when used in isolation. Meta-analyses and classroom studies suggest AI tools (adaptive quizzes, personalised feedback) can enhance student performance and time management—but only in learning environments where human feedback, active engagement, and scaffolding remain central. AI should assist, not replace, the relational, ethical, and mentoring roles of teachers. Without integrating AI into active learning, its benefits are diluted; it risks becoming mere decoration.
Key Points
AI tools deliver gains when embedded into active, interactive teaching—not used as standalone replacements.
Meta-studies show stronger outcomes when technology is personalised and integrated rather than simply overlaid.
Students report improved time management and performance when AI offers real-time feedback and adaptive quizzing.
Pedagogical design (feedback loops, scaffolding, mentor oversight) remains essential; AI alone doesn’t do that work.
AI cannot replicate human qualities such as creativity, ethics, judgement, and emotional understanding.
As AI increasingly integrates into daily student life, professors are actively experimenting with new pedagogical approaches and tools to harness its potential. This image captures a dynamic classroom setting where educators are at the forefront of exploring how AI can enrich learning, adapt teaching methods, and prepare students for an AI-driven future. Image generated by Nano Banana.
Source
The Globe and Mail
Summary
AI has shifted from novelty to necessity in Canadian higher education, with almost 60% of students now using it. Professors are experimenting with different approaches: some resist, others regulate, and many actively integrate AI into assessments. Concerns remain about diminished critical thinking, but educators like those at the University of Toronto and University of Guelph argue that ignoring AI leaves graduates unprepared. Strategies include teaching students to refine AI-generated drafts, redesigning assignments to require human input, and adopting oral assessments. The consensus is that policies alone cannot keep pace; practical, ethical, and reflective engagement is essential for preparing students to use AI responsibly.
Key Points
Nearly 60% of Canadian students use AI for coursework, rising globally to over 90%.
Professors face a choice: resist, regulate, or embrace AI; ignoring it is seen as untenable.
Innovative teaching methods include refining AI drafts, training prompt skills, and oral assessments.
Concerns persist about weakening critical thinking and creativity.
Preparing students for AI-rich workplaces requires embedding literacy, ethics, and adaptability.
While children are rapidly learning about AI through pervasive social media platforms, educators face the challenge of integrating this knowledge into formal learning environments. This image highlights the growing disconnect between how children are acquiring AI literacy informally and the efforts teachers must make to bridge this gap and keep classroom instruction relevant and engaging. Image (and typos) generated by Nano Banana.
Source
The Conversation
Summary
Students are learning to use AI mainly through TikTok, Discord, and peer networks, while teachers rely on informal exchanges and LinkedIn. This creates quick but uneven knowledge transfer that often skips deeper issues such as bias, equity, and ethics. A Canadian pilot project showed that structured teacher education transforms enthusiasm into critical AI literacy, giving educators both vocabulary and judgment to integrate AI responsibly. The article stresses that without institutional clarity and professional development, AI adoption risks reinforcing inequity and mistrust.
Key Points
Informal learning (TikTok, Discord, staff rooms) drives AI uptake but lacks critical depth.
Teacher candidates benefit from structured AI education, gaining language and tools to discuss ethics and bias.
Institutional AI policies are fragmented, leaving instructors without support and creating confusion.
Equity and bias are central concerns; multilingual learners may be disadvantaged by uncritical AI use.
Embedding AI literacy in teacher education and learning communities is critical to move from casual adoption to critical engagement.
