liberal arts

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.”

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.

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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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.

Reflections on “Want Students to Build a Healthier Relationship With Technology? Start With The Arts” [Marshall]

On 05/16/2026, in Adobe, Apple, art, communications, communities of practice, content development, aggregation, repositories, creativity, Daniel S. Christian, design, digital audio, digital photography, digital storytelling, digital video, education technology, Emotion, engagement / engaging students, experimentation, faculty/staff, graphics, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, innovation, instructional design, IT in HE, K-12 related, learning, learning ecosystem, Learning Experience Design, learning preferences, liberal arts, library / librarians, media/film, multimedia, music, new media literacies, online media, presentations, productivity / tips and tricks, professional development, reading, real-world assignments, simulations, skills, STEAM-related, student-related, teachers, teaching & learning, technology (general), tools, United States, universities, vendors, vision/possibilities, web design and production, by Daniel Christian

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.
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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:

Want to boost early literacy skills? Try singing — from hechingerreport.org by Jackie Mader
Experts say music can help prepare children for reading success.

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.

Make learning accessible to all in higher education — from The Times Higher Education

When accessibility is placed at the heart of teaching and learning, rather than treated as a bolt-on, every student benefits. This week’s spotlight guide offers advice on designing universally accessible learning, in-person and online. Find out how to ease the burden of disability disclosure with universal design for learning, better support neurodivergent students and students with hearing or vision issues, design more accessible assessments and ensure digital tools work for all.

Also see:

Dr. Ian Kelleher’s introduction to his paper here on LinkedIn

Are we not shooting ourselves in the foot with AI and recent college graduates? [Christian]

On 03/24/2026, in 21st century, adjunct faculty, apprenticeships, Artificial Intelligence/Agents/LLMs/and Related, business, career development, change, changing business models, colleges, community colleges, corporate / business world, dangers of the status quo, Daniel S. Christian, emerging technologies, experimentation, faculty/staff, game-changing environment, higher education, human-computer interaction (HCI), intelligent systems, internships, learning ecosystem, liberal arts, marketplaces, parents/guardians, productivity / tips and tricks, reinvent, skills, society, sociology, strategy, student-related, teaching & learning, technologies for your home, tools, trends, United States, universities, vendors, vocational / trades, workplace, youth, by Daniel Christian

From DSC:
The types of postings/articles (such as the one below) make me ask, are we not shooting ourselves in the foot with AI and recent college graduates? If the bottom rungs continue to disappear, internships and apprenticeships can only go so far. There aren’t enough of them — especially valuable ones. So as this article points out, there will be threats to the long-term health of our talent pipelines unless we can take steps to thwart those impacts — and to do so fairly soon.

To me…vocational training and jobs are looking better all the time — i.e., plumbers, carpenters, electricians, mechanics, and more.

Can New Graduates Compete With AI? — from builtin.combyRichard Johnson
The increasing adoption of AI automation is compressing early-career jobs. How should new graduates get a foothold in the economy now?

Summary: AI is hollowing out entry-level roles by automating routine tasks, eliminating a rung on the career ladder. New graduates face intense competition and a rising skill floor. While firms gain short-term productivity, they risk a long-term talent shortage by eliminating junior training grounds.

Conversations about AI have covered all grounds: hype, fear and slop. But while some roll their eyes at yet another automation headline, soon?to?be graduates are watching the labor market with a very different level of urgency. They’re entering a world where the old paradox of needing experience to get experience is colliding with a new reality: AI is absorbing the standardized, routine tasks that once defined entry?level work. The result isn’t just a shift in job descriptions or skill-requirements, but rather a structural reshaping of the career pipeline.

Entry-level workers face an outsized disruption to their long-term career trajectories. They have the least buffer to adapt given their lack of relevant job market experience and heightened financial pressure to secure a job quickly with the student-debt repayment periods for recent graduates looming.

Momentum early in one’s career matters, and the first job on a resume shapes future compensation bands and opportunities. It also serves as a signal for perceived specialization or, at minimum, interest. Losing that foothold has compounding effects to one’s career ladder.

Also relevant/see:

New Anthropic Institute to Study Risks and Economic Effects of Advanced AI — from campustechnology.com by John K. Waters

Key Takeaways

Anthropic has launched the Anthropic Institute, a new research effort focused on the biggest societal challenges posed by more powerful AI systems.
The institute will study how advanced AI could affect the economy, the legal system, public safety, and broader social outcomes.
Anthropic co-founder Jack Clark will lead the institute in a new role as the company’s head of public benefit.
The new unit brings together Anthropic’s existing red-teaming, societal impacts, and economic research work, while adding new hires and new research areas.

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:

The five levels of learning designer support — from timeshighereducation.com by Daniel Searson
Learning designers and academics may have different expectations when it comes to collaborating on course design. Here’s how a five-point scale can help
Harness the power of your university librarian in the age of information chaos — from timeshighereducation.com by Ben Meunier
Find out how to tap the mine of knowledge your university library has, for trustworthy research sources, data expertise and information literacy advice
How employability teams can strengthen academic programmes — from timeshighereducation.com by Hanene Duprat
Working like recruitment partners, rather than just career advisers, can help align teaching with industry needs, writes Hanene Duprat
Excerpts:

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.

The benefits of engaging third space practitioners in curriculum development — from timeshighereducation.com by Steve Briggs
Third space practitioners are often overlooked in the curriculum development process, to everyone’s detriment. Here’s a look at the viewpoints they can offer and how to engage them better
Teaching deaf, deafblind and hard-of-hearing students: practical steps that benefit everyone — from timeshighereducation.com by Annelies Kusters
When educators design communication to work across multiple modes from the outset, classrooms become more accessible – and more effective – for everyone, says Annelies Kusters

“The Future of College in an AI World” [Selingo] + other items re: AI in our learning ecosystems

On 03/18/2026, in 21st century, 24x7x365 access, adjunct faculty, Artificial Intelligence/Agents/LLMs/and Related, bots, colleges, communities of practice, community colleges, corporate / business world, digital learning, emerging technologies, experimentation, faculty/staff, future, future of higher education, game-changing environment, generational differences, Google, higher education, human-computer interaction (HCI), ideas, innovation, intelligent systems, K-12 related, leadership, learning ecosystem, liberal arts, Michigan, multimedia, music, Open AI, student-related, teachers, teaching & learning, tools, United States, universities, vendors, by Daniel Christian

The Future of College in an AI World — from linkedin.com by Jeff Selingo
In today’s issue: The tension over AI in higher ed; application inflation continues and testing is back; what’s the future of the original classroom technology, the learning management system.

Hundreds of higher ed and industry leaders gathered Tuesday for a summit
on AI and the future of learning at the University of Michigan.
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Conversations like the one we had at Michigan this week are necessary, but the action rarely matches the ambition.

We say the humanities are the operating system of an AI world, yet students and parents don’t believe it. They’re voting with their feet toward STEM, business, and narrowly tailored majors they believe will lead to a job.
Meanwhile, colleges are quietly eliminating the very humanities degrees the panelists were championing, employers are cutting the entry rungs off the career ladder for new graduates, and as Podium Education co-founder Christopher Parrish reminded us yesterday, there’s a yawning gap between demand for experience and the internships that actually exist.

AI Music Generators: Teaching With These Catchy AI Tools — from techlearning.com by Erik Ofgang
AI music generators are getting better and better, and there are more applications in the classroom as a result.

Are All AI Music Generators More Or Less The Same?
No. After experimenting with a few various free ones, I found a wide range of quality with the same prompts.

Gemini is the only one I’d currently recommend. It’s user-friendly but limited and only creates 30-second clips. Other music generators could potentially outperform Gemini with prompt adjustments. The ones I tried did better with the instrumentals but struggled more with the lyrics, and that kind of defeated the purpose of the tool for me.

ChatDOC: Teaching With The AI Summarizing Tool — from techlearning.com by Erik Ofgang
ChatDOC lets users turn any PDF into an AI chatbot that can summarize the text, answer questions, and generate quizzes.

What Is ChatDOC?
ChatDOC is an AI designed to help users interact with PDFs of various types, be it research papers, short stories, or chapters from larger works. Users upload a PDF and then have the opportunity to “chat” with that document, that is speak with a chatbot that bases its answers off of the uploaded text.

ChatDOC can perform tasks such as provide a short summary, search for specific terms, explain the overall theme if it’s a work of literature, or unpack the science in a research paper.

Other similar tools are out there, but ChatDOC is definitely one of the better PDF readers I’ve used. Its free version is quick and easy-to-use, and delivers on its promise of providing an AI that can discuss a given document with users and even quiz them on it.

From AI access to workforce readiness — from chieflearningofficer.com by Johnny Hamilton, Amy Stratbucker, & Brad Bigelow
Is your workforce using the right tool with an outdated mindset and playbook? Why old playbooks fall short — and what learning leaders must do next.

The leadership opportunity
Organizations do not need to predict every future AI capability. They need systems that allow people to explore with curiosity, practice safely, reflect deeply and adapt continuously — starting with what they already have and extending as capabilities evolve.

For CLOs, this is a moment to lead from the center of change — designing workforce readiness that keeps pace with accelerating technology while making work more rewarding for employees and more valuable for the organization. That is how AI moves from the promise of transformation to demonstrated readiness and, ultimately, from promise to performance.

Addendums on 3/19/26:
How to Build Practice-Based Learning Activities with AI — from drphilippahardman.substack.com by Dr Philippa Hardman
Four evidence-based methods for designing, building & deploying active learning activities with your favourite LLM

Most L&D teams are using AI to make content faster. The real opportunity is using it as a practice engine.

The Synthesia 2026 AI in L&D Report f2026 AI in L&D Report found that the fastest-growing areas of planned AI adoption aren’t in content creation — they’re in assessments and simulations (36%), adaptive pathways (33%), and AI tutors (29%). In other words: L&D teams are starting to realise that the most powerful use of AI isn’t producing learning materials. It’s creating environments where learners actually practise.

And you can build these right now — no dev team, no custom platform, no code. Each method below includes a prompt you can paste into your preferred AI tool to generate a working interactive prototype: a self-contained practice activity with a briefing screen, a live AI interaction, and a debrief — all running in the browser, ready to share with stakeholders or deploy to learners.

OpenAI Adds Interactive Math and Science Learning Tools to ChatGPT — from campustechnology.com by Rhea Kelly

Key Takeaways

ChatGPT adds interactive learning tools: OpenAI introduced interactive math and science visualizations that allow users to explore formulas, variables, and relationships in real time.
The tool currently covers over 70 core math and science topics and is aimed initially at high school and college-level learners.
Users can adjust variables, manipulate formulas, and immediately see how changes affect graphs and outcomes.

2026 Survey of College and University Presidents — from insidehighered.com, Liaison, & Jenzabar
Download and explore exclusive insights from the 2026 Survey of College and University Presidents to see how these campus leaders are responding to financial volatility, political interference, rapid advances in AI, and where they believe the biggest risks and opportunities lie as they look toward 2030.

In this year’s survey, presidents share perspectives on:

How presidents assess the second Trump administration’s impact on higher education
Which emerging or evolving educational models they plan to add or expand in the coming years
How effective they believe higher education has been in shaping national conversations arout AI
The issues presidents expect will have the greatest impact on higher education by 2030

“Teach Smarter with AI” [Caplan & Eaton] + other items re: AI in our learning ecosystems

On 03/08/2026, in 21st century, 24x7x365 access, adult learning, Artificial Intelligence/Agents/LLMs/and Related, bots, business, career development, 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, emerging technologies, experimentation, faculty/staff, Google, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, K-12 related, learning, learning agents, learning ecosystem, liberal arts, platforms, skills, teachers, teaching & learning, tools, training / L&D, United States, universities, vendors, by Daniel Christian

Teach Smarter with AI — from wondertools.substack.com by Jeremy Caplan and Lance Eaton
10 tested strategies from two educators who actually use them

I recently talked with Lance Eaton, Senior Associate Director of AI and Teaching & Learning at Northeastern University and writer of AI + Education = Simplified. We traded ideas about what’s actually working. We came up with 10 specific, practical ways anyone who teaches, coaches, or leads can put AI to work.

Watch the full conversation above, or read highlights below.

Beyond Audio Summaries: How to Use NotebookLM to *Actually* Design Better Learning — from drphilippahardman.substack.com by Dr. Philippa Hardman
Five methods to maximise the value of NotebookLM’s features

In practice, what makes NotebookLM different for learning designers is four things:

Answers grounded in your sources (with citations):
Source toggling:
Multi-format studio & multi-source summaries:
Persistent workspace:

…
5 Evidence-Based Methods NotebookLM Operationalises…

Shadow AI Isn’t a Threat: It’s a Signal — from campustechnology.com by Damien Eversmann
Unofficial AI use on campus reveals more about institutional gaps than misbehavior.

Key Takeaways

Shadow AI is widespread in higher education: Faculty, researchers, students, and staff are using AI tools outside official IT channels, including consumer platforms and public cloud services that may involve sensitive data.
Unauthorized AI use creates data, compliance, and cost risks: Consumer AI tools may store or reuse user data, while uncoordinated adoption drives redundant licenses, unpredictable cloud costs, and weaker security oversight.
Institutions are shifting from restriction to enablement: Some campuses are making approved paths easier by offering ready-to-use research environments, campus-managed AI tools, clear guidance on data and vendors, and streamlined approval processes.

How L&D Can Lead in the Age of AI Even If Your Company’s Not Ready — from learningguild.com

How to lead even when your company doesn’t allow AI
Even if your corporation isn’t ready for AI, you can still research tools personally to stay ahead of the curve, so when organizational restrictions lift, you are ready to use AI for learning right away. Here are some tools you can test at home if they’re restricted in your workplace:

Content generation – Start testing text-based tools to get a taste of how AI can accelerate content creation. Then take it to the next level by exploring tools that generate voices, music, and sound effects.
AI coaching tools – Have AI pose as a customer co-worker or customer to get a taste of what it’s like to use it as a conversation coach. Next, use the voice and video capabilities in an app like ChatGPT to explore how AI can coach someone through tasks.
In-the-flow learning assistants – Test turning documents into a conversational avatar and interacting with it to see how it feels. Then think about how the technology could potentially transform static content into dynamic learning experiences for employees.
Vibe-coded simulations – Experiment with this technology by creating a simple, fun game. Afterwards, brainstorm some ideas on how it could quickly create simulations for your learners in the future.

The Higher Ed Playbook for AI Affordability — from campustechnology.com by Jason Dunn-Potter

Key Takeaways

Affordable AI adoption focuses on evolving existing systems: Universities are embedding AI into current devices, workflows, and legacy systems rather than rebuilding infrastructure or investing in new data centers.
Edge AI reduces costs and improves access: Running AI models on local devices or networks lowers cloud processing costs, enhances security, and supports learning use cases such as tutoring, translation, transcription, and adaptive learning.
Enterprise integration and governance drive impact: Institutions are applying AI across admissions, advising, facilities, and research workflows, supported by shared resource hubs, data governance, AI literacy, and outcome-driven implementation.

The Campus AI Crisis — by Jeffrey Selingo; via Ryan Craig
Young graduates can’t find jobs. Colleges know they have to do something. But what?

Only now are colleges realizing that the implications of AI are much greater and are already outrunning their institutional ability to respond. As schools struggle to update their curricula and classroom policies, they also confront a deeper problem: the suddenly enormous gap between what they say a degree is for and what the labor market now demands. In that mismatch, students are left to absorb the risk. Alina McMahon and millions of other Gen-Zers like her are caught in a muddled in-between moment: colleges only just beginning to think about how to adapt and redefine their mission in the post-AI world, and a job market that’s changing much, much faster.

“Colleges and universities face an existential issue before them,” said Ryan Craig, author of Apprentice Nation and managing director of a firm that invests in new educational models. “They need to figure out how to integrate relevant, in-field, and hopefully paid work experience for every student, and hopefully multiple experiences before they graduate.”

Learning Ecosystems

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

6 Reasons Universities Are Building Media Labs Now [Grimes]

Across the divide: reimagining faculty-staff collaboration in higher education [van de Gevel]; plus several other items from timeshighereducation.com

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