learning ecosystem

4 Strategies For Teaching With AI Effectively — from techlearning.com by Erik Ofgang
Health sciences professor Humberto López Castillo urges students to use AI to help with science research, but never to lose sight of the human element.

Castillo, a trained pediatrician and professor in the Department of Health Sciences, has also seen students use AI in creative ways to promote public health understanding, and as a research tool. For one project, Castillo asks students to explain health concepts from class to non-experts, and since he started encouraging students to use AI, he’s seen the projects get better. Students have created health-themed board games and Hamilton-style rap songs. Others have designed AI to aid in health research in ways that wouldn’t be possible without the technology.

This compassionate and student-centered approach to AI use is part of why Castillo was named Superhuman (formerly Grammarly’s) 2026 Educator of the Year.
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“You are the one who’s responsible for that writing,” Castillo tells his students. “Your name is the only name that’s going to be among the published authors, so you are the one who needs to verify those sources.”

He adds that rather than being a drawback, allowing students to make these types of mistakes with AI use in the college setting has value.

“It is a teaching opportunity,” Castillo says. “This is the moment to make those mistakes.”

What Michigan schools reveal about reversing chronic absenteeism | Time-intensive home visits show promise [Barshay]

On 06/01/2026, in education, education reform, K-12 related, leadership, learning ecosystem, Michigan, parents/guardians, participation, research, society, strategy, student-related, teachers, United States, youth, by Daniel Christian

What Michigan schools reveal about reversing chronic absenteeism — from hechingerreport.org by Jill Barshay
Time-intensive home visits show promise

Absenteeism is a huge and seemingly intractable problem for the nation’s public schools. And Michigan has one of the worst attendance rates in the country.
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Yet a new study released in May offers hope. Researchers found that some Michigan schools appear to be substantially better than others at getting students to show up, and identified one intervention — frequent home visits to families whose children are absent from class — that was used more often by schools making a difference.

The findings are a reminder that “best practices” recommendations often overstate what researchers actually know. Schools can make a meaningful difference in attendance, but identifying genuinely successful schools is hard, isolating why they succeed is even harder, and simple solutions rarely hold up under scrutiny.

GenAI practice blossoms through the open exchange of insights — from timeshighereducation.com by Samuel Doherty, who is the education and innovation coordinator at the University of Newcastle in Australia
How a structured GenAI professional development series, built around practice, peer voices and multiple entry points, fosters open exchange among colleagues, universities and industry

Connect internal practice to sector-wide thinking
Whatever is happening within any single institution is only part of the picture. Effective GenAI practice grows through open exchange of insights among colleagues, universities, professional bodies and industry, and a development programme that is entirely inward-looking risks missing both useful knowledge and important shifts in expectation.

Our AI sector voices sessions aim to bring external contributors into the programme: researchers, practitioners and sector representatives working at the intersection of GenAI and higher education. The aim is to situate institutional practice within the wider conversation and to signal to staff that the institution is genuinely engaged with that conversation, not just managing it internally.

In the Australian context, the Tertiary Education Quality and Standards Agency (Teqsa) people pillar positions staff as drivers, enablers, users and innovators of GenAI practice, and identifies a lack of information or understanding as one of the primary barriers to ethical and effective engagement. That framing is useful regardless of regulatory context: institutions that treat their people as active participants in shaping practice, rather than recipients of policy, are likely to develop more durable capability.

Regular, lightweight communications, a weekly community of practice update and a monthly all-staff digest can maintain momentum between sessions without adding significantly to anyone’s workload.

What AI-Enabled Education Actually Looks Like When It’s Working for Workforce Students — from gettingsmart.com by Stephen Griffin

Key Points

Institutions can use AI to make skills, pathways, and job outcomes visible to students and employers in ways traditional transcripts cannot.
Academic affairs, workforce development, career services, and employers need a shared definition of readiness and competency before tools can deliver meaningful value.

The second is portable competency records. Learning and employment records — AI-enabled documentation of what a student knows and can do, expressed in language employers recognize — are the infrastructure that makes credentials legible across the education-to-employment continuum. When a student can show an employer not just “completed Supply Chain Management 101” but “demonstrated proficiency in inventory optimization, route planning, and logistics software at the industry-recognized level,” the credential stops being abstract. It becomes evidence. Building these records requires investment in tools, yes — but more importantly, it requires faculty, workforce development staff, and employer partners to agree on what competency actually looks like before the technology is ever purchased.

Workplace Readiness: Can Higher Education Develop AI-Ready Students? — from learningguild.com by Eddie Lin and Roshan Bharwaney

For higher education to remain relevant, curricula must evolve. Here are some overarching recommendations for directions in higher education to bridge the skills gaps between universities and workplaces:

AI ethics and safety: Prepare students to navigate issues of fairness, bias, privacy, and societal impact.
Tackling complex questions: Emphasize open-ended challenges that blend structured and unstructured skills and reduce reliance on standardized tests and repetitive drills.
Critical thinking: Develop new assessments for judgment, creativity, and metacognition—essential to supervise AI outputs.
Human-AI synergy: Embed AI fluency across all disciplines, encouraging students to find the niches where human value is maximized.
Industry connection: Maintain close industry partnerships and collaborations including open innovation opportunities and collective intelligence approaches (Bharwaney & Sleeva, 2024).

Experiential learning and communities of practice are central to this vision. Internships, simulations, and cross-disciplinary projects can help students practice human-AI collaboration, resilience, and decision-making in environments that mirror the workplace’s ambiguity and complexity.

Universities that condemn the use of AI by students risk isolating themselves from the realities of today’s workplace, where interns and new hires are expected to be or quickly become adept at using AI for routine tasks and complex projects.

Students say law school isn’t prepping them to use AI in practice, new survey shows [Hill]

On 05/31/2026, in faculty/staff, law schools, learning ecosystem, Legal operations, legal reform, legal technologies, legislatures / government / legal, United States, universities, by Daniel Christian

Students say law school isn’t prepping them to use AI in practice, new survey shows — from abajournal.com by Julianne Hill; note this may be behind a paywall

Just 30% of third-year law students think that their school is preparing them for artificial intelligence in practice, leaving 70% of soon-to-be bar candidates to learn best practices for the emerging technology on their own.

That’s according to the results of the Thomson Reuters Institute’s 2026 Law Student Pulse Survey of 1,874 U.S. law students between April 6 and April 19.

Also see:

Grads of non-ABA-accredited law school can sit for Washington state bar exam — from abajournal.com by Julianne Hill; note this may be behind a paywall

As of Sept. 1, graduates of non-ABA-accredited law schools will be allowed to sit for the bar exam in Washington state after a policy change by the state’s bar association.

Law.com reported Thursday that the change had been formally adopted by the Washington State bar Association’s Board of Governors.

Can colleges still deliver in the age of AI? One Ivy League school is investing $30 million to improve career outcomes — from cnbc.com by Jessica Dickler

Key Points

College students are increasingly worried about what an AI-driven jobs apocalypse could mean for their employment prospects.
To that end, many colleges and universities are racing to recalibrate.
Even at nation’s most elite schools, the focus is shifting to career readiness.

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 [Sivarajah]

On 05/28/2026, in adjunct faculty, apprenticeships, business, career development, change, changing business models, colleges, community colleges, corporate / business world, credentialing, curriculum, Daniel S. Christian, Europe, faculty/staff, future of higher education, game-changing environment, generational differences, higher education, ideas, innovation, internships, leadership, learning ecosystem, lifelong learning, MBA, new business models, organizational change, pace of change, participation, pathways, professional development, skills, strategy, student-related, teaching & learning, technology (general), UK, United States, universities, vision/possibilities, workplace, by Daniel Christian

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.

Three items re: AI in our learning ecosystems

On 05/26/2026, in adjunct faculty, business, career development, colleges, community colleges, corporate / business world, corporate universities / corporate training, digital learning, education technology, emerging technologies, experimentation, faculty/staff, future of higher education, game-changing environment, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, law schools, learner profiles, learning, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, liberal arts, policy, productivity / tips and tricks, student-related, teaching & learning, training / L&D, United States, universities, vision/possibilities, workplace, by Daniel Christian

I Was a University AI Czar. I’m Not Equipped to Teach in the Age of AI. — from jgellers.substack.com by Josh Gellers, PhD

The reason that I claim I am not well-suited to thrive as an instructor in the age of AI is because both AI Enthusiasts and AI Resisters put a lot of thought and energy into completely redesigning their classes in response to AI. This is the one takeaway that I don’t think the Exhausted Majority has fully accepted yet—to excel as a teacher in this AI era, you need to totally revise how you teach and how you assess what students learn in your classes.

I can say this much—whatever solution our industry comes up with, it’s likely to emerge from teaching and learning centers. Contrary to what Paul Schofield wrote in the Chronicle of Higher Education, pedagogy experts are the best hope we have to equip today’s faculty with the tools required to succeed in this uncertain educational environment. As I always tell my students, “I was trained for 7 years to become a researcher and 2 days to become a teacher.” The idea that only disciplinary experts know how to teach and have nothing to learn from so-called “nonscholars” is so laughable that one has to wonder whether an AI agent jokingly wrote that sad opinion piece to troll the whole academe.

Also from Dr. Gellers, see:

The Worst AI Policy in Higher Ed
How Berkeley Law Boalt-ed From Expertise in Favor of Abstinence

Last week, one of the top law schools in the United States, the University of California, Berkeley School of Law, released its final policy on artificial intelligence, effective summer 2026. In the span of a breezy 1.5 pages, the school outlined the challenge AI poses to legal education and how it plans to address this problem. Despite these intentions, this AI policy is, in my estimation, the worst AI policy in higher education I have seen.

From AI Tutors to AI Study Mates— from drphilippahardman.substack.com by Dr Philippa Hardman
New research reveals how AI can enable real learning — not just productivity gains

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The point isn’t that AI is inherently bad for learning — it’s that the meta-analyses showing that LLMs improve assignment and performance scores are measuring the wrong thing. They’re measuring performance with the AI present, not learning that persists once it’s gone.

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From DSC:
Notice that when an AI-based learning system can remember what you’ve worked on and how you are doing — where you are struggling or doing well — it can have a positive impact on your longer-term learning. That, to me, is where long-term based learner profiles come in.

Later in the article, Dr. Hardman points out that “if we want to deliver AI tooling which supports substantive learning, we need to intentionally create a new category of AI tool for ‘learning at work’ which prioritises learning and development over productivity.” While I agree with that, I do wonder if businesses will care, so long as the work gets done and gets done well. But this calls into mind the word “experience” — something that traditionally has been hard fought to get in the corporate world. But the corporate realm often doesn’t like to pay for experience (beyond key AI-based jobs) when they perceive it’s getting too expensive. Ask all those 50 and over who had or have a target on their backs.

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What is L&D’s role when AI is already part of work, information and capability? [Taylor & Vinauskaite]

On 05/21/2026, in 21st century, 24x7x365 access, adult learning, Artificial Intelligence/Agents/LLMs/and Related, business, communities of practice, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, emerging technologies, human-computer interaction (HCI), instructional design, intelligent systems, learning, learning ecosystem, Learning Experience Design, training / L&D, United States, by Daniel Christian

Here is Don Taylor’s posting on LinkedIn.com

Also relevant/see:

Here is Egle Vinauskaite’s posting on LinkedIn.com

Deans for Impact Releases New Edition of The Science of Learning — from deansforimpact.org
Second edition of seminal report reflects new research amidst growing momentum for evidence-based instruction in teacher preparation and PK-12.

AUSTIN, Texas (May 19, 2026) – Deans for Impact (DFI) today released the second edition of The Science of Learning, a report translating cognitive-science research into practical implications for teaching. The updated edition includes new research on memory, attention, motivation, and learning misconceptions, offering educators a research-based foundation for understanding how to support durable student learning.

First released in 2015, The Science of Learning is DFI’s most widely-used and cited resource, with more than one million downloads. Since its publication, DFI has supported nearly 300 teacher-preparation programs to make instructional quality a priority in the way teachers are prepared, directly impacting more than 110,000 teachers over the last decade.

The second edition arrives at a moment when more than 40 states have made meaningful investments in strengthening evidence-based instruction, particularly in early literacy, mathematics, and the use of high-quality instructional materials. The science of learning supports future teachers to build a comprehensive foundation for instructional decision-making that cuts across content areas and grade levels.
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The report has been endorsed by more than 100 field experts and leading organizations across the United States and internationally.

Download the report at deansforimpact.org/thescienceoflearning.

An example excerpt:

“The sad fact is that we don’t teach learners how to be good at learning. Whether K12, higher ed, or organizations, it’s just not there.”

— from Clark Quinn’s posting entitled, Thoughts on meta-coaching!

From DSC:
I agree. We could do a much better job at this.

Putting college on the fast track — from hechingerreport.org by Jon Marcus
As students grow impatient, colleges try three-year bachelor’s degrees

Some colleges and the accreditors and states that oversee them are adding and approving three-year bachelor’s degrees that require fewer credits than the traditional four-year kind.

Institutions facing enrollment declines hope the new three-year degrees will attract students unwilling to spend the usual amount of time and money that it takes to graduate. States need those graduates to fill jobs.

Nearly 60 universities and colleges are planning, considering or have already launched reduced-credit, three-year bachelor’s degrees in some disciplines. They’re calling them “applied” or “career-focused” bachelor’s degrees.

While earning bachelor’s degrees with fewer credits may appeal to some students, the idea is so new that there’s a key unanswered question: whether employers, graduate schools and licensing agencies will accept them.

From DSC:
Given the often high price of obtaining a degree these days…whether it’s a 4-year program or a 3-year program, the key is whether a student can get a good job coming out of that program. I think the required time doesn’t help as much as making the necessary changes to offer more responsive curricula, relevant programs, and real-world learning experiences (including apprenticeships and internships). I appreciate the experiment to lower the overall costs, but like so many other “innovations,” it’s playing at the fringes. It’s really the same old, same old — just on a shorter time frame.

At current prices, families are FORCED to consider employment prospects. They are demanding a ROI, because they have to.

I was at a meeting earlier this year with other parents and family members who were interested in a particular program at a Michigan-based university. One set of parents really wanted to know if their student would be getting a good job coming out of the program. They didn’t want to take a second mortgage out if the investment wasn’t going to pay off.

Also see:

Here is the link to Chris Mayer’s posting on LinkedIn.

Three items re: AI in our learning ecosystems

On 05/16/2026, in 21st century, 24x7x365 access, adjunct faculty, adult learning, Artificial Intelligence/Agents/LLMs/and Related, bots, career development, change, cloud-based computing / apps / other cloud-related, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, education technology, emerging technologies, faculty/staff, game-changing environment, generational differences, higher education, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, learning, learning ecosystem, Learning Experience Design, liberal arts, library / librarians, organizational change, pace of change, skills, student-related, teachers, teaching & learning, training / L&D, trends, United States, universities, vendors, workplace, by Daniel Christian

LinkedIn Grad’s Guide 2026: Starting your career in the AI era — from linkedin.com by Gianna Prudente
To help you head off in the right direction, we’ve identified where those starting their careers are finding opportunity, based on data from millions of LinkedIn member profiles.

While all of this is happening, colleges are still catching up. Many students are graduating without having spent much time learning how AI actually fits into day-to-day work — even as employers seek out those exact skills.

“Colleges are moving into an era of, we’ll let the faculty decide, which leads to a very uneven experience for students because some faculty are really into AI and other faculty are not,” says Jeff Selingo, a higher education strategist. “Employers are the same; they don’t really know how to act around early careers.”

Taken together, new grads are entering a uniquely challenging environment: fewer traditional entry points, slower turnover and a workplace that’s evolving faster than the systems preparing people for it.

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I knew my writing students were using AI. Their confessions led to a powerful teaching moment — from theguardian.com by Micah Nathan
The problem wasn’t just the perfectly polished, yet mediocre prose. It’s what’s lost when we surrender the struggle to translate thought into words

For a few moments, all was quiet except the classroom’s ticking radiators. Then, a teary-eyed confession: one of the ostensible authors said she only used AI because she was scared of looking stupid, of being criticized for bad writing. She said she loved writing stories and hated having used AI. But she couldn’t stop herself, recounting a sequence similar to an addict’s descent: at first she fed her story into AI for a grammar check, it suggested line edits and she accepted, then it asked if she wanted structural edits, then it offered to rewrite the entire piece.

The other would-be author admitted he had never written a short story before and he had an idea but didn’t know where to start. I asked him why he didn’t reach out to me for help. He shrugged.

One of the other students raised her hand, saying she didn’t understand why it was bad for AI to write stories as long as the stories are based on their ideas. More students spoke: one wanted to know how using AI was any different from using a human editor. Another wanted me to answer why, at a university that launched one of the world’s first AI research programs in 1959, were we even having this debate? Isn’t AI meant to make everyone’s life easier? Less stressful? Isn’t the point of AI to free humans from the tedium of rote tasks?

The conversation that followed their confessions was one of the most productive teaching moments of my eight years at MIT. Writing, I told them, isn’t supposed to be easy, and of course it can be tedious but that doesn’t make it rote. Writing isn’t just the production of sentences – it’s the training of endurance by way of sustained attention. It’s a way of learning what one thinks by attempting to say it.

This $10K AI School Promises to Future-Proof Your Career — from builtin.com by Matthew Urwin
Khan Academy, TED and ETS are starting a new program to equip students and professionals with the skills to thrive in an increasingly AI-driven economy. Here’s what you need to know.

Summary: The Khan TED Institute is a higher-education program that will teach students and workers how to use AI through interactive learning. The program’s AI-centric curriculum is an unproven approach, though, casting doubt on whether it will actually improve learning outcomes and career prospects.

Learning Ecosystems

Students say law school isn’t prepping them to use AI in practice, new survey shows [Hill]

Two items re: experiments within higher ed as well as offering alternative college models

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