intelligent systems

Why Students Aren’t All In on AI—And What They Want From Colleges — from insidehighered.com by Colleen Flaherty
New Student Voice data reveal students are embracing AI as a learning tool while worrying about dependence, career disruption and inconsistent institutional responses.

Read on for six takeaways from the survey and additional insights—including how institutions can start to close the gap between students’ optimism about AI as a learning tool and their faith in their colleges’ ability to help them navigate change.

Takeaway 1: More students are using AI than ever for coursework, while a significant share—20 percent—remain resisters.

Takeaway 2: “Worried about dependence” is the most common student stance on AI.

Takeaway 3: A majority of all students expect AI to somewhat (39 percent) or very (16 percent) negatively impact their career prospects.

Takeaway 4: Just one in 10 students says that their institution is handling AI’s rise very well, in a thoughtful and proactive way.

…and more >>

Three items re: AI in our LE’s (involving corporate training, higher ed, and K-12)

On 06/10/2026, in 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, attention, colleges, communities of practice, community colleges, corporate / business world, corporate universities / corporate training, education, education reform, education technology, emerging technologies, engagement / engaging students, experimentation, faculty/staff, game-changing environment, generational differences, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, K-12 related, learning, learning ecosystem, Learning Experience Design, liberal arts, student-related, teachers, teaching & learning, training / L&D, United States, universities, youth, by Daniel Christian

Rethinking Learning Design in Elementary Schools — from edcircuit.com
Why K–5 leaders must redesign—not just adopt—technology to restore attention, deepen thinking, and align AI with how children actually learn

Rethinking learning design in elementary schools is critical as screen time and AI reshape attention, thinking, and student engagement.

Designing for Thinking, Not Just Doing
At its core, learning design must shift from task completion to thinking development.

This requires creating environments where students:

Spend time processing ideas
Work through confusion without immediate answers
Build persistence through challenge

It also requires clarity around the role of technology.

Technology should:

Extend thinking
Provide meaningful feedback
Support exploration

It should not:

Replace effort
Short-circuit reasoning
Eliminate productive struggle

The goal is not to reduce technology use.

It is to ensure that students remain the ones doing the thinking.

Should We Integrate AI into Our Teaching?: Evidence-Based Guidelines for Deciding When AI Belongs — from Faculty Focus by Norman Eng, EdD

Four Questions for Deciding Whether to Use AI

Question 1: Will this AI tool help students use, recall, and demonstrate understanding of core disciplinary content?
Question 2: Will this AI tool require students to apply their learning to a new context?
Question 3: Will this AI tool support—not replace—independent, evidence-based reasoning?
Question 4: Will this AI integration preserve meaningful human interaction?

Christian: Could this be a part of our future learning ecosystems?

On 06/09/2026, in 21st century, 24x7x365 access, adult learning, Artificial Intelligence/Agents/LLMs/and Related, career development, cloud-based computing / apps / other cloud-related, CMS/LMS, communities of practice, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, Daniel S. Christian, digital learning, education technology, emerging technologies, engagement / engaging students, experimentation, faculty/staff, future, future of higher education, game-changing environment, global / globalization, heutagogy, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, informal learning, innovation, instructional design, intelligent systems, intelligent tutoring, K-12 related, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning preferences, learning spaces, liberal arts, library / librarians, lifelong learning, love of learning, microlearning, more voice more choice more control, online learning, online media, passions, personalized/customized learning, platforms, professional development, skills, social media, streams of content, student-related, teachers, teaching & learning, technologies for your home, training / L&D, United States, user experience (UX), vendors, vision/possibilities, by Daniel Christian

From DSC:
Could this be a part of our future learning ecosystems? Education as a personalized content feed.

Coursera wants users to learn through shorter, faster content — from digitaltrends.com by Moinak Pal
Coursera wants online learning to feel more like TikTok
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Online learning platform Coursera is taking a page straight out of TikTok’s playbook. The company has launched a new AI-powered feed designed to serve short-form educational content in a scrollable, personalized format, signaling a major shift in how digital learning platforms may try to keep users engaged.

The feature introduces bite-sized video lessons, clips, and explainers curated through artificial intelligence based on a user’s interests, learning habits, career goals, and previous course activity. Instead of committing to hour-long lectures or full certification programs upfront, users can now discover short educational snippets designed to make learning feel more casual, accessible, and addictive.

Users scroll through a feed of short educational videos and AI-curated learning moments covering topics ranging from coding and business to AI, productivity, data science, and personal development.

Pinpoint, Explained | A guide to Google’s free tool, now open to all [Caplan]

On 06/05/2026, in adjunct faculty, Artificial Intelligence/Agents/LLMs/and Related, colleges, communities of practice, community colleges, content development, aggregation, repositories, data related items, digital audio, digital learning, digital video, education, education technology, faculty/staff, Google, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, IT in HE, journalism, K-12 related, languages and translation, learning, learning agents, learning ecosystem, liberal arts, library / librarians, research, teaching & learning, tools, United States, universities, vendors, by Daniel Christian

Pinpoint, Explained — from wondertools.substack.com by Jeremy Caplan
A guide to Google’s free tool, now open to all

.Jeremy prompted ChatGPT to generate illustrations in his post.

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Learn about Pinpoint— from support.google.com

Pinpoint is an AI-powered research platform designed to help journalists and academics analyze large collections of documents. With Pinpoint, you can:

Analyze massive collections: Easily search, filter, transcribe and organize thousands of documents, including PDFs, images, and audio files.
Leverage generative AI: Use Gemini’s capabilities to answer research questions together with supporting evidence found in your documents.
Foster collaborative research: share your work with colleagues and tackle large scale projects as a team. You can also publicly share – supporting community-driven research.

For assistance with Pinpoint, please consult our Community Forum or you can contact our support team.

Addendum:

AI Budgets in Education Show No Sign of Decline — from campustechnology.com by Rhea Kelly

Key Takeaways

Education AI budgets are holding steady or increasing: Wasabi found that 98% of education organizations expect AI infrastructure budgets to increase or remain steady, with 46% planning increases.
Storage costs are the top AI implementation challenge: Half of education respondents cited data storage issues, including storage and access costs, as the No. 1 challenge for AI projects.
Cloud security and ROI remain pressure points: Only 47% feel confident keeping data unaltered and operational after a cyberattack, 44% lost access to public cloud data after an attack, and 37% of AI projects currently show positive ROI.

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.

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

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

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

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

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

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.

This $10K AI School Promises to Future-Proof Your Career [Urwin]

On 05/12/2026, in 21st century, 24x7x365 access, accessibility / UDL, Alternatives, Artificial Intelligence/Agents/LLMs/and Related, collaboration, colleges, communications, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, cost of getting a degree, dangers of the status quo, Daniel S. Christian, digital learning, education, education reform, education technology, emerging technologies, entrepreneurship, experimentation, faculty/staff, Google, human-computer interaction (HCI), ideas, innovation, intelligent systems, intelligent tutoring, K-12 related, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning spaces, Microsoft, pace of change, platforms, productivity / tips and tricks, real-world assignments, reinvent, skills, staying relevant, student-related, teaching online, United States, universities, vendors, by Daniel Christian

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.

When anyone can build a course, the real job is deciding which ones shouldn’t exist [Hardman]

On 05/11/2026, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, business, communities of practice, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, innovation, instructional design, intelligent systems, learning ecosystem, Learning Experience Design, training / L&D, trends, UK, by Daniel Christian

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

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

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

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

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

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

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