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 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. 

 

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.

 

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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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.


 

Want Students to Build a Healthier Relationship With Technology? Start With The Arts — from techlearning.com by Adrianna Marshall
Arts classrooms demonstrate what technology integration at its best can look like

But at a moment defined by rapid AI adoption and ongoing debates about screen time, the argument for protecting and investing in arts education needs to take on a new tone. The arts continue to be one of the most effective places in school for students to build healthier, more intentional relationships with technology.

In short, in the age of AI, we need the arts more than ever.

Digital composition software, notation tools, and recording platforms allow students to experiment, revise, and refine their ideas in ways that would have been far more time-consuming a decade ago. Students can layer tracks, hear immediate playback, annotate their own scores, and collaborate across devices. The same is true in other contexts besides music; in visual arts, for instance, a variety of digital drawing and painting platforms enable students to practice with new mediums, styles, and techniques without having to worry about supplies or messes. But in either case, the core intellectual work of looking and listening critically, understanding structure, and making aesthetic choices remains entirely human and part of the learning.


From DSC:
I agree. At one of my previous positions, I spent 10 years supervising a digital studio — helping professors and students use a variety of applications to create things. The applications were from Adobe, Apple, and a variety of smaller vendors. The deliverables could be graphics, edited soundtracks, music, videos, flyers, posters, collages, edited photographs, presentations, websites, and more. I longed for people to discover the power of multimedia to communicate their messages, tell stories, stir emotion, powerfully engage themselves (and others), and unleash their creativity.

There were several obstacles to our digital studio being more impactful at that institution. It was under the IT department, not the academic side of the house. It was in the basement of the library, where few students and faculty traveled. During those years, it was highly uncommon for faculty members to require multimedia-based assignments — so many students had to WANT to develop these skills on their own time. The majority of students didn’t see the value in developing the types of digital skills that we were trying to build…or they didn’t have the time.


Also relevant/see:


 

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.

Higher education might be on the verge of a radical overhaul to bring it up to speed in the age of artificial intelligence. At the TED2026 conference, Khan Academy, TED and ETS announced that they’re partnering to establish the Khan TED Institute — a new program that reorients the college curriculum around AI. By joining forces, the education technology trio aims to develop an alternative to traditional universities that better tracks student progress, teaches more relevant skills and provides a more personalized learning experience.

Accessibility is another major tenet of the Khan TED Institute. Its virtual nature allows anyone with an internet connection to participate in the program and makes it easier for students to move at their preferred pace. And because its curriculum prioritizes competency over course credits, advanced learners can complete the program in a shorter period. Time isn’t the only thing students can save on, either: The Institute promises a bachelor’s degree for less than $10,000, offering a much more affordable alternative to the typical four-year degree. 


 

From DSC:
Faculty senates don’t do well with this pace of change. But to their credit, few organizations can begin to deal with this pace of change.

 
 

Let AI Interview You — from wondertools.substack.com by Jeremy Caplan & Jay Dixit
A smarter way to get past the blank page

There’s nothing wrong with using AI to get answers to your questions. But there’s another mode of interacting with AI that many people never consider — one I find much more useful for my creative process.

Here’s what I do instead: I flip the script and let the AI ask the questions. Instead of prompting AI, I get the AI to prompt me.

 

6 Reasons Universities Are Building Media Labs Now — from edtechmagazine.com by Brad Grimes
Digital production centers help institutions close the gap between academic training and professional practice.

Higher education is undergoing a significant transformation in how it prepares the next generation of media professionals. Across the country, universities are investing in state-of-the-art media labs — facilities built not around traditional classroom instruction, but around the tools, workflows and collaborative environments that define today’s professional production landscape. These spaces represent a fundamental rethinking of what it means to train students for careers in film, animation, gaming and digital storytelling.

 
 

The TalentLMS 2026 Annual L&D Benchmark Report — from talentlms.com
From year-over-year training benchmarks to learner–leader gaps, see the data that defines the new era of learning. To turn insight into action, the report lays out 10 evidence-backed interventions to hardwire development. Plus, lift the lid on Learning Debt: What it is and how to spot it.

Executive summary
The skills economy is being rewritten in real time. AI is reshaping what people need to know, do, and deliver, faster than organizational structures can adapt. The result is a workplace caught between acceleration and inertia. Companies are racing to reskill for an AI-driven future while relying on structures built for yesterday’s world.

This TalentLMS 2026 L&D Benchmark Report captures that inflection point. Based on data collected through 2025, and compared with earlier findings from 2022 to 2024, it explores how learning is evolving and what’s holding it back.

Our research integrates two vantage points: HR leaders overseeing learning initiatives and employees receiving formal training. Together, they offer a dual perspective on how learning is managed and how it’s experienced.

The analysis also draws on insights from external research and leading L&D practitioners, anchoring the report in both evidence and practice.

Combined, the findings point to a structural fault line: Learning is expanding in scope but contracting in space. Organizations are multiplying programs, tools, and ambitions, yet the conditions for learning — time, focus, and cognitive bandwidth — keep shrinking.

The data from this report underscores this critical conflict: According to half of the surveyed employees and learning leaders, high workloads leave little room for training, even when it’s needed.

Employees work inside a permanent sprint, where attention is fragmented and reflection is sidelined. The space for learning is collapsing under the weight of doing. Sixty-five percent of employees say performance expectations have risen this year, yet lack of time remains the biggest barrier to learning.

The numbers confirm what employees and learning leaders both feel: Technology can advance overnight. But people and cultures can’t.

 
© 2025 | Daniel Christian