Below are several items that were either mentioned by Matt Tower or I came across them via offshoots of items that he linked to:

Future Universities Alliance Names Inaugural Innovation Sandbox Cohort — from provost.duke.edu
Program incubated by Duke brings together higher education innovators from 23 countries for year-long peer exchange

The Future Universities Alliance has selected 49 institutions from 23 countries for the inaugural cohort of its Innovation Sandbox, a 12-month peer learning program for higher education leaders advancing ambitious, institution-level innovation.The cohort brings together founders of new universities, administrators and faculty leading high-stakes changes within established institutions, and leaders of proven models exploring how their innovations can travel to new contexts. Participants were chosen through a competitive process that drew applicants from around the world in its inaugural year.

A makeover for college: No gym, no meal plan and two years of work — from npr.org by Jon Marcus

An entirely new college is being planned here to change not only how higher education is delivered, but at what price. It also proposes to highlight ways the current business model no longer works, as evidenced by the 152 colleges and universities that have closed or merged since 2016, and the 442 others that a new projection says are at risk.

So deeply entrenched are the problems confronting higher education that a growing chorus of innovators says the easiest way to fix them is to begin again from scratch.

All undergraduates should get work-based learning, v-cs say — from timeshighereducation.com by Jack Grove. NOTE: this item is behind a paywall.
Bold plan to support graduate employment would require placements for 1.4 million students annually

 

The Checklist That Didn’t Exist: A Field Guide to Cutting Extraneous Load — from learningguild.com by Cally Mervine Kiser

If the content is fine, what else could be getting in the way?

The answer, it turns out, has been sitting in educational psychology research for decades. Working memory is finite. When learners engage with training, they are managing three competing cognitive demands simultaneously:

  • The complexity of the subject matter
  • The effortful processing that builds understanding
  • The mental effort generated by how the content is presented, independent of the content itself

That third one is called extraneous cognitive load, and it is the one we almost never explicitly design against. We design for accuracy. We design for alignment. We design for engagement, or at least what we hope will feel like engagement. We almost never sit down and ask, “How much unnecessary mental effort is this design generating, and how do we reduce it?”

 

When Learning Feels Like a Vulnerability — from learningguild.com by George Hall

Why do some adult learners interpret training as a judgment about their competence, status, or identity?

Learning and development professionals often focus on content, platforms, courses, tools, and performance support. Those matter. But they are not enough. Learning is never just cognitive. It is also emotional and social.

A new skill can feel like evidence that old competence is no longer enough. Feedback can feel like judgment. A new model can feel like criticism of past practice. A request to change can feel like a loss of face.

It means learning can feel personally exposing. Adult learners do not only receive training. They interpret what needing training seems to say about their competence, status, identity, and future value. That interpretation can either open learning or shut it down.

 

 

 

Psalm 116:1-2

1 I love the Lord, for he heard my voice;
he heard my cry for mercy.
2 Because he turned his ear to me,
I will call on him as long as I live.

Romans 12:4-5

4 For just as each of us has one body with many members, and these members do not all have the same function, 5 so in Christ we, though many, form one body, and each member belongs to all the others.

From DSC:
I remember several times in my career thinking — no…wishing — I had more skills or capabilities than what I possessed. I was trying to make significant contributions, and I didn’t have all the skills to carry out my ideas. But I was likely too ambitious in my younger days. I was taught to be that way from the start. But primarily it came from my background as an athlete — where I was taught to compete with other people. Not to be in relationships with them, but to compete against them. (Legions of athletes are currently in the same boat, I’m sure. That’s how we were taught to be. That’s often how competition works.) 

So when a pastor told us a while back, “It’s not about you!” — that sounded shocking and confusing to my selfish, ambitious self. “You’re kidding me!,” I’m sure I felt and thought.

Romans 12:4-5 lets us know that we each have our God-given gifts and abilities — but no one person on this Earth has all of the gifts and abilities out there. We each play our role. Like the body, we each have different purposes and functions. It’s humbling. And it’s relational. 

Ephesians 2:10

For we are God’s handiwork, created in Christ Jesus to do good works, which God prepared in advance for us to do.

Isaiah 46:4 

Even to your old age and gray hairs I am he, I am he who will sustain you. I have made you and I will carry you; I will sustain you and I will rescue you.

Psalm 121:1-2

A song of ascents.
1 I lift up my eyes to the mountains—
where does my help come from?
2 My help comes from the Lord,
the Maker of heaven and earth.

 

MIT’s Ad Hoc Committee on AI Use in Teaching, Learning, and Research Training — from aiandeducation.mit.edu

However, what we learned as a group quickly convinced us that the Institute community, particularly the faculty, must tackle a set of deeper questions about the structure, meaning, and value of an MIT education in an era in which AI is one of several factors complicating the Institute’s mission.
…

In this report, we:

  • Highlight key aspects of the current educational landscape at MIT.
  • Share eight principles we relied on and that we hope will guide the Institute in the work ahead.
  • Recommend immediate and long-term actions for both instructors and the administration.

On somewhat related notes:

 

How a studio-based format transforms online teaching — from timeshighereducation.com by multiple authors from Cranfield University in England
Online teaching works best when teaching, facilitation and technical delivery are treated as complementary professional roles. Read guidance on studio-based delivery

Our experience of studio-based delivery suggests the need for a different approach. In this model, teaching is delivered as a live, facilitated learning experience in which academics focus on teaching and interaction, while facilitators and production staff manage interaction, session flow and technology.

Responsibilities are intentionally divided to enable more effective online pedagogy: academics concentrate on explaining concepts, facilitating discussion and responding to students while production staff manage the technical environment, transition between activities, recordings, multimedia integration, chat moderation, breakout rooms and troubleshooting, enabling a more engaging and authentic learning experience.

The most transferable lesson is that online teaching works best when teaching, facilitation and technical delivery are treated as complementary professional roles and when it is underpinned by pedagogical design. 

 

‘You can’t just lecture students any more’ — from timeshighereducation.com by Debra Page
GenAI does not make lecturers redundant, but it does weaken one-way content delivery as a reason to bring students together, writes Debra Page. She shares four practical shifts to teaching in the age of AI

This does not make lecturers redundant; it makes one-way content delivery a weaker reason to bring students together. Expert explanation, intellectual storytelling and the modelling of disciplinary thinking still matter, but in-person teaching must also help students apply knowledge, question claims, build arguments and encounter perspectives beyond their own.

The problem is not lecturing; it is speaking for an hour and treating content coverage as evidence that learning has occurred.

These four practical shifts can make lectures more valuable in the age of AI.

 

OpenAI’s chief scientist says no lab should keep scaling at maximum speed — from thenextweb.com by Ana Maria Constantin
OpenAI put out two posts on Sunday. Its research organisation now uses 3.1 agent-workdays for every human one, and its chief scientist says no lab has solved alignment well enough to keep scaling at full speed. The case for an OpenAI slowdown arrived with the numbers against it.

Chief scientist Jakub Pachocki wrote the second post, an essay called An Alien Mind. It closes on a line that reads oddly from the man who runs research at the company shipping fastest.

“Currently I believe that no lab has solved alignment and monitoring to a sufficient degree to continue responsibly scaling at maximum speed for much longer,” he wrote.

…
He is not gentle about the stakes either. “This is a time that calls for extreme caution. I am concerned no one is prepared for the consequences of a continued rapid rise in machine intelligence,” Pachocki wrote.

 

The Disappearing Bottom Rung in L&D — from drphilippahardman.substack.com by Dr Philippa Hardman
Junior roles are rapidly disappearing from L&D. Here’s the data + my hypothesis about why it’s happening

TL;DR: the bottom rung of L&D isn’t just narrowing — it’s being automated. The humans who remain move up the ladder, and the profession re-forms around a new set of AI and domain specialisms.
…
Is AI responsible for reshaping knowledge work, including L&D? My hypothesis is a resounding YES, primarily because of what I see in L&D job ads in 2026…

…..


The AI Workflow Redesign Method: How the Top 6% of Users Get Real Returns from AI— from drphilippahardman.substack.com by Dr Philippa Hardman
A practical three-step method to redesign your workflow & get ~2X value from AI

One pattern I see emerging from that research is this: the people getting the most value from AI aren’t the ones using it most, or the ones with the most advanced technical skills: they’re the ones who redesigned their day to day workflows around AI’s capabilities.
…

How to Redesign a Workflow in Three Steps
In my bootcamp we use a task-mapping process that distils workflow redesign down to three steps: map the work, tag each task by the impact you want AI to have, then validate whether what you want is possible.

Three steps get you to a plan: two or three tasks worth building, each with a written standard. Turning that plan into a redesign takes two more moves, which I’ll cover after the steps. I’m flagging that now because the moves are the bit most people skip, and they’re where the redesign actually happens.

Here’s a how to for each step:

 

College Is an Expensive Career Exploration Tool. Here’s an Alternative. — from humanistxyz.substack.com by Patrick O’Donnell and Allison Dulin Salisbury
“Young people know that sitting in a classroom for twelve years isn’t going to show them how to find a job, let alone a career they love.”

This interview is part of a series on AI, high school, and the Experience Gap. Our report, Closing the Experience Gap, makes the case for a high-school model in which at least 50 percent of formal learning is experience-based.

College is an expensive career exploration tool. It is also poorly designed for the job.

Patrick O’Donnell tells the story of a student who entered a four-year nursing program certain she wanted to become a nurse. Once enrolled, she discovered that the work was a poor fit. Earlier immersion in healthcare, she told him, would have moved that discovery forward by several years. Now she needed to transfer to a community college and remap her plans.

Her predicament is familiar. We ask teenagers to choose a college and course of study with little direct knowledge of the work on the other side. Many spend their first years of college trying to answer a question high school gave them few opportunities to explore: What kind of work fits me?


From DSC:
College is an expensive career exploration tool. It is also poorly designed for the job.

This assertion resonated with me instantly — and I agree with it 100%. As a bit of background as to why I say this…I thought that I was going to be a doctor all through K-12 and even in my first year at college. But then I got to about halfway through my fall semester in my sophomore year, and I dropped out of pre-med. It was the best decision of my life.

But then what?

I had very little idea of what I wanted to do in the future or what my skills, interests, passions, and abilities were. K-12 and college offered next to nothing in terms of career preparation back in that period of time. It wasn’t until my late 20’s that I even began to get a clue on what’s all out there. What were my choices and what was a good fit for me? What did I enjoy doing and what did I not enjoy doing? 

So I agree completely…college is an expensive career exploration tool/setting. But I’m glad to see more and better options these days within K-12. Colleges could do much better.

 

Illustrator Spotlight: Musubu Hagi

Illustrator Spotlight: Musubu Hagi — from booooooom.com

 

Escaping The Backrooms Of Workforce Development — by Ryan Craig

Which makes sense. Because far too many find themselves in a liminal space, neither in school nor a career. Needing to make a living in an era of digital transformation and AI, they’re having a horrific time finding their way into and around work. So it’s not just education and training wonks who think workforce is the defining issue of our time. The success of Backrooms demonstrates Gen Z thinks so, too.

It’s happening everywhere. Young people around the world are angry at how hard it’s become to launch careers. This summer an entire protest movement arose in India – the world’s largest Gen Z population – around entrance exams for medical school, one of the few remaining sure bets. In the UK, youth unemployment is over 16%; it’s 15% across the EU and over 25% in Sweden. Back home, nearly 400,000 young Americans stopped looking for work in June alone. So it’s urgent that we identify what actually works to help young people get good first jobs.

The answer lies between apprenticeship perfection and train-and-pray scale. We desperately need a scalable training-first model that’s as proximate as possible to employment opportunities, employers, and actual employment. That can only mean work-based learning: real work experience completed during or connected with a training, certificate, or degree program. Work-based learning can take many forms: rotations, clinics, co-ops, internships, short projects. It can be integrated into coursework or independent. But what all forms require are bona fide employers, which regulate scale. Such programs can enroll only as many as can fit within the constraint of available work-based learning opportunities.


Also see:


Also see:

Is Your College A Zombie? — from forbes.com by Ann Kirschner; via Ryan Craig

I want to be careful here, because this is not an argument that universities are doing nothing. They are doing an enormous amount. New programs, AI task forces, employability frameworks, microcredentials, and shifts in how they enable lifelong learning.

Activity is not the problem; what has not changed is the machinery that decides what counts. Too many institutions move in herds rather than forging an independent path. When one college launches a new program, say, data science and AI, fifty will follow without asking whether their version serves their students or simply checks a competitive box.

Meanwhile, 88% of American professionals believe colleges and universities should be the ones providing AI training, and nearly half say their employers have offered no AI resources whatsoever.¹

 
 
 
 
© 2025 | Daniel Christian