What a disco ball teaches us about learning and leadership — from timeshighereducation.com by Lauren Flannery
By acknowledging that perspectives are evolving and relational, educators and leaders can encourage contribution and connection without sacrificing what makes people distinct

It also shows us that difference does not always need to be resolved. In teaching, learning and leadership, the aim is not to create uniformity but to create conditions in which different people can contribute, connect and shine without losing what makes them distinct.

In classrooms, inclusion is sometimes approached as ensuring access to the same knowledge, resources and opportunities for all students. The beach ball helps here: it encourages us to explore multiple perspectives. But the disco ball pushes us further to explore how learning environments can support students to bring their experiences, identities and knowledge into the room – not to smooth them out but to draw from them.

Designing for multiple perspectives also means recognising that expressing an opinion is not only about confidence; it is also about conditions. People are more likely to speak when they feel their contribution will be heard without being dismissed, appropriated or flattened. Creating those conditions may involve discussing uncertainty, welcoming challenge, slowing down decision-making or making space for quieter forms of participation. The aim is not to make everyone agree, but to allow different reflections to interact in ways that generate richer understanding.

 

Two years ago, AI broke assessment. Now, it’s helping us to reinvent it. — from linkedin.com by Dr. Philippa Hardman


Also from Dr. Hardman, see:


A new study shows AI helped deliver 1.5 years of maths progress in 8 weeks — here’s how. — from linkedin.com by Dr. Philippa Hardman

…a new study shows AI helped deliver 1.5 years of maths progress in 8 weeks — here’s how.

Google DeepMind just shared the results of a randomised trial involving 1,763 students. Half used Gemini’s “Guided Learning” to learn maths; half didn’t.

The result: the group working with AI gained the equivalent of 1.2 to 1.7 years of extra progress compared to those who didn’t.

It’s tempting to read this as “Gemini’s Guided Learning mode works!” But the key point here is that Gemini didn’t work alone….

Look closer, and what made the difference wasn’t just the tech — it was a great teacher making expert use of it.

 
 

Inside the latest global research on school cellphone bans — from hechingerreport.org by Jill Barshay
First wave of studies raises questions about other digital distractions and cellphones at home

But the first wave of rigorous research on those policies — including two major U.S. studies — does not point neatly in one direction. Some studies have found modest academic gains from cellphone restrictions. Others have found little to no effect on test scores, even when student phone use dropped sharply. Some studies suggest benefits for low-achieving students, others for girls, and still others for boys. In some places, attendance or student well-being improved. In others, they didn’t.

The scientific process can be messy. Cultural differences may explain why the bans are more effective in some places than others. But almost any education reform will get different results in different places, even within a single country. And the current confusion may also stem from how difficult it is to study cellphone bans in the real world.

Ideally, researchers would randomly assign some students to surrender their phones while others kept them, and then measure the effect on academic performance — the equivalent of a clinical trial for an education policy. But those experiments are difficult to enforce in schools, and so far only one study, conducted among college students in India, has attempted a randomized controlled trial. It produced a notably strong improvement in course grades for lower achieving students.

Instead, most studies rely on rougher real world comparisons that capture only partial effects of cellphone restrictions.

 

Why universities must become flexible lifelong partners, not one-time providers — from timeshighereducation.com by Sankar Sivarajah
As careers become increasingly non-linear and shaped by rapid change, universities must evolve beyond traditional degree provision, says Sankar Sivarajah. Here, he outlines strategies

From programmes to learning ecosystems
These pressures point towards a broader redefinition of higher education. Rather than viewing education as a one-time experience culminating in a degree, universities increasingly need to see themselves as partners in professional development across an entire career.

This means moving from a model centred on programmes to one focused on learning ecosystems that allow individuals to enter, leave and re-engage with higher education as their needs evolve.

Business schools may be particularly well placed to lead this shift because of their close engagement with employers and their long tradition of educating professionals at different stages of their careers.

But success will depend on more than introducing new modules or certificates. Universities must confront a fundamental question. Are the systems, structures and cultures that define higher education capable of supporting genuinely flexible learning?

The sector has already embraced the language of lifelong learning – the next step is ensuring that universities themselves are built to deliver it.


From DSC:
Long-time readers of this blog have seen this graphic of mine posted over the last 12+ years:
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Also relevant/see:

What if the undergraduate journey were a four-year internship? — from timeshighereducation.com by Michelle Seref
Treating work placements and co-curricular programmes as optional or supplementary misses deeper questions about whether traditional degrees prepare students for careers. Michelle Seref explains

Attending workshops or polishing a résumé in their final semester does not make students career-ready. They need to practise how to work – how to collaborate, navigate ambiguity, manage projects and apply knowledge in context – throughout their academic experience. The reality is that career readiness is not a co-curricular programme; it is an essential part of an integrated curriculum.

To be clear, employers do not expect classrooms to become training centres. What they are asking for – implicitly and explicitly – is graduates who can function in complex environments from day one. That means graduates who can work in teams, communicate professionally with stakeholders, adapt when plans change, apply theory to real constraints and learn continuously on the job.

These capabilities do not develop through passive learning. But experiential learning is often misunderstood as a single, high-impact activity: an internship, a capstone project or study abroad. In reality, its power comes from repetition and progression. One experience introduces exposure. A sequence of experiences builds competence.

We are proposing a paradigm shift: repositioning the undergraduate journey as a four-year professional internship rather than a continuation of the K-12 classroom environment. 

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From DSC:

The problem with this innovative idea is that faculty often are not out in the “real world.” The best chance higher ed has to deliver on this idea is via the adjunct faculty members out there. Often, they are the ones practicing what they are teaching. They are constantly pulse-checking — and actively involved with — their industries and have more up-to-date, practical knowledge.

But this is a problem for traditional institutions of higher education, which have treated their adjunct faculty members poorly through the years. Adjunct faculty members hardly make minimum wage, have no benefits, no retirement plans, etc. — plus they have little to no say in faculty senates. 

Organizational change would be a requirement.

 
 

A New Era of Security: Frontier AI Defense — from paloaltonetworks.com by Sam Rubin

For the last several months, we have had early, unbounded access to the latest frontier AI models. What we’ve seen from that vantage point has made it clear that the window for organizations to get ahead of what’s coming is shorter than most leaders realize.

We have moved past the era of incremental AI improvements into a threat landscape shift. Our testing has revealed a step-change in capability that demonstrates an intuitive understanding of software vulnerabilities. This is more than faster code generation, it is a shift from AI as an assistant to AI as an autonomous agent capable of discovering and chaining flaws at a scale that most defenders aren’t prepared for.

These capabilities will not stay confined to controlled environments for long. When Mythos first launched, we predicted a six-month window before attackers gained access. We now believe that timeline has accelerated significantly.

 

 

When anyone can build a course, the real job is deciding which ones shouldn’t exist — from drphilippahardman.substack.com by Dr. Philippa Hardman
Why deciding is the only L&D skill AI can’t replace.

The biggest AI risk that L&D faces isn’t that it gets left behind: it’s that we build more — and flood the organisation with meh-quality content nobody needed in the first place.

In this post, I’ll make the case that:

  • The L&D job has just split in two — and most of us are still working on the wrong half.
  • There’s a new operating model coming for the role, and it’s already running inside a lot of the companies you’ve heard of.
  • The smartest critique of everything I’m about to argue comes from Ethan Mollick — and I think he’s half right.

The question we’ve been asking for the last two years — “how do I get faster at building?” — was the wrong one.

The real question is: can I look at fifteen AI-generated learning assets and decide which three are worth scaling — and put my name to that decision?

 
 

The “Cognitive Offloading” Paradox — from drphilippahardman.substack.com by Dr. Philippa Hardman
New research shows that offloading learning tasks to AI can improve – rather than erode – human thinking and learning

The Rise of the “Offloading Paradox”
In March 2026, the International Journal of Educational Technology in Higher Education published a study that went beyond the question “does offloading hurt?” and asked a harder one: when students form genuine partnerships with AI — treating it as an intellectual collaborator rather than a passive tool — what actually happens to the way they think and learn? Specifically, do two cognitive responses — critical evaluation of AI outputs (what the researchers call cognitive vigilance) and strategic delegation to AI (cognitive offloading) — compete with each other, or can they coexist?

Based on previous research, Wang and Zhang hypothesised that cognitive offloading would hurt transformative learning. They expected the familiar story: delegation reduces cognitive struggle, struggle is where learning happens, therefore delegation undermines learning.

The study — 912 students across China, Europe, and the United States, using a three-wave time-lagged survey design that measured partnership orientation first, cognitive strategies two weeks later, and learning outcomes two weeks after that — found something more interesting than a simple reversal.

 
 

The Course Is Dying as the Unit of Learning — from drphilippahardman.substack.com by Dr Philippa Hardman
Here’s why, and what’s replacing It

What the Bleeding Edge Looks like in Practice
So what does “the new stack” actually look like when organisations lean into this? Here are four real patterns already in play.

Engineering: from engine courses to in-workflow AI coaching.
Product development: from courses to craft-specific agents.
Compliance: from annual course to nudge systems.|
Enablement systems, not catalogues.

 

Here is Chris Martin’s posting on LinkedIn.com:


Here is Dominik Mate Kovacs’ posting on LinkedIn.com:


The AI ‘hivemind’: Why so many student essays sound alike — from hechingerreport.org by Jill Barshay
A study of more than 70 large language models found similar answers to brainstorming and creative writing prompts

The answers were frequently indistinguishable across different models by different companies that have different architectures and use different training data. The metaphors, imagery, word choices, sentence structures — even punctuation — often converged. Jiang’s team called this phenomenon “inter-model homogeneity” and quantified the overlaps and similarities. To drive the point home, Jiang titled her paper, the “Artificial Hivemind.” The study won a best paper award at the annual conference on Neural Information Processing Systems in December 2025, one of the premier gatherings for AI research.


AI Has No Moral Compass. Do You? — from michelleweise.substack.com by Michelle Weise & Dana Walsh
Why the Age of AI Demands We Take Character Formation Seriously

Here’s something to chew on:

Anthropic, the company behind Claude — a chatbot used by 30 million users per month — has exactly one person (whom we know of) working on AI ethics. One. A young Scottish philosopher is doing the vital work of training a large language model to discern right from wrong.

I don’t say this to shame Anthropic. In fact, Anthropic appears to be the only company (that we know of) being explicit about the moral foundations and reasoning of its chatbot. Hundreds of millions of users worldwide are leveraging tools from other LLMs that do not appear to have an explicit moral compass being cultivated from within.

I raise this because this is yet another example of where we are: extraordinary technical power advancing without an equally strong moral infrastructure to support it.

Why do we keep producing people who are skilled but not wise?

 

Across the divide: reimagining faculty-staff collaboration in higher education — from timeshighereducation.com by Saskia van de Gevel
Academic units do best when they harness different viewpoints – from field scientists and curriculum designers to extension professionals – to drive innovation and relevance. Saskia van de Gevel offers proactive advice

Universities are not sustained by individual leaders or isolated units. They are sustained by teams of people who bring different kinds of expertise to a shared mission. When faculty and professional staff collaborate as genuine partners – aligned around outcomes, clear about roles and committed to mutual respect – institutions become more resilient, innovative and effective.

Also from timeshighereducation.com, see:

Again, we don’t send them 200 CVs. We might send 20, but they’re meticulously shortlisted. The employer saves time, the student feels they are being taken seriously and trust builds quickly on both sides.

And because we work closely with employers, we learn something universities often struggle to find out early enough: what the market is asking for now.

What academics need to know: we can’t do this without you
If I could say one thing to academic colleagues anywhere, it’s that employability can’t sit next to the curriculum. It has to live with it.

 

Dueling Hares and Leaping Toads Top the 2026 British Wildlife Photography Awards — from thisiscolossal.com by Kate Mothes & various photographers


Also see:

Spectral Birds Endemic to New Zealand Find New Life in Fiona Pardington’s Portraits — from thisiscolossal.com by Kate Mothes and Fiona Pardington

 
© 2025 | Daniel Christian