community colleges

AI working competency is now a graduation requirement at Purdue [Pacton] + other items re: AI in our learning ecosystems

On 12/16/2025, in 21st century, 24x7x365 access, adjunct faculty, adult learning, Alternatives, Artificial Intelligence/Agents/LLMs/and Related, Asia, Australia, bots, career development, change, changing business models, cloud-based computing / apps / other cloud-related, CMS/LMS, collaboration, colleges, communities of practice, community colleges, computer science, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, education technology, experimentation, faculty/staff, future of higher education, game-changing environment, generational differences, higher education, human-computer interaction (HCI), India, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, law schools, 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, microlearning, online media, personalized/customized learning, platforms, productivity / tips and tricks, student-related, teachers, teaching & learning, technologies for your home, the downsides of how people use tech, tools, training / L&D, trends, UK, United States, universities, vendors, vision/possibilities, youth, by Daniel Christian

AI Has Landed in Education: Now What? — from learningfuturesdigest.substack.com by Dr. Philippa Hardman

Here’s what’s shaped the AI-education landscape in the last month:

The AI Speed Trap is [still] here: AI adoption in L&D is basically won (87%)—but it’s being used to ship faster, not learn better (84% prioritising speed), scaling “more of the same” at pace.
AI tutors risk a “pedagogy of passivity”: emerging evidence suggests tutoring bots can reduce cognitive friction and pull learners down the ICAP spectrum—away from interactive/constructive learning toward efficient consumption.
Singapore + India are building what the West lacks: they’re treating AI as national learning infrastructure—for resilience (Singapore) and access + language inclusion (India)—while Western systems remain fragmented and reactive.
Agentic AI is the next pivot: early signs show a shift from AI as a content engine to AI as a learning partner—with UConn using agents to remove barriers so learners can participate more fully in shared learning.
Moodle’s AI stance sends two big signals: the traditional learning ecosystem in fragmenting, and the concept of “user sovereignty” over by AI is emerging.

Four strategies for implementing custom AIs that help students learn, not outsource — from educational-innovation.sydney.edu.au by Kria Coleman, Matthew Clemson, Laura Crocco and Samantha Clarke; via Derek Bruff

For Cogniti to be taken seriously, it needs to be woven into the structure of your unit and its delivery, both in class and on Canvas, rather than left on the side. This article shares practical strategies for implementing Cogniti in your teaching so that students:

understand the context and purpose of the agent,
know how to interact with it effectively,
perceive its value as a learning tool over any other available AI chatbots, and
engage in reflection and feedback.

In this post, we discuss how to introduce and integrate Cogniti agents into the learning environment so students understand their context, interact effectively, and see their value as customised learning companions.

In this post, we share four strategies to help introduce and integrate Cogniti in your teaching so that students understand their context, interact effectively, and see their value as customised learning companions.

Collection: Teaching with Custom AI Chatbots — from teaching.virginia.edu; via Derek Bruff
The default behaviors of popular AI chatbots don’t always align with our teaching goals. This collection explores approaches to designing AI chatbots for particular pedagogical purposes.

Example/excerpt:

Not Your Default Chatbot: Five Teaching Applications of Custom AI Bots
Agile Learning
derekbruff.org/2025/10/01/five-teaching-applications-of-custom-ai-chatbots/

Higher education faces ‘deteriorating’ 2026 outlook, Fitch says — from highereddive.com by Laura Spitalniak
A shrinking pipeline of students, uncertainty about state and federal support, and rising expenses could all hurt college finances, according to analysts.

Dive Brief:

Fitch Ratings on Thursday issued a “deteriorating” outlook for the higher education sector in 2026, continuing the gloomy prediction the agency issued for 2025.
Analysts based their forecast on a shrinking prospective student base, “rising uncertainty related to state and federal support, continued expense escalation and shifting economic conditions.”
With its report, Fitch joins Moody’s Ratings and S&P Global Ratings in predicting a grim year for higher ed — Moody’s for the sector overall and S&P for nonprofit colleges specifically.

Yale expects layoffs as leaders brace for $300M in endowment taxes — from highereddive.com by Ben Unglesbee
The Ivy League institution’s tax bill starting next year will be higher than what it spends on student aid, university officials said.

Dive Brief:

Yale University is bracing for layoffs as it prepares to pay the government hundreds of millions of dollars in endowment income taxes.
In a public message, senior leaders at the Ivy League institution said that Yale’s schools plan to take steps such as delaying hiring and reducing travel spending to save money. But they warned workforce cuts were on the horizon.
“Layoffs may be necessary” in some units where cutting open positions and other reductions are insufficient, the university officials said. They expect to complete any downsizing by the end of 2026 barring “additional significant financial changes.”

Education Department adds ‘lower earnings’ warning to FAFSA — from highereddive.com by Natalie Schwartz
The agency will warn students when they’ve indicated interest in a college whose graduates have relatively low incomes.

The U.S. Department of Education has launched a new disclosure feature that warns students who fill out the Free Application for Federal Student Aid if they’re interested in colleges whose graduates have relatively low earnings, the agency said Monday.

“Families deserve a clearer picture of how postsecondary education connects to real-world earnings, and this new indicator will provide that transparency,” U.S. Education Secretary Linda McMahon said in a Monday statement. “Not only will this new FAFSA feature make public earnings data more accessible, but it will empower prospective students to make data-driven decisions before they are saddled with debt.”

Also from highereddive.com, see:

College costs grew 3.6% in fiscal 2025, HEPI shows
Faculty salaries rose 4.3%, the highest recorded rate since the Higher Education Price Index began in 1998.
Martin University to ‘pause’ operations at the end of the month
The board of the private Indianapolis university is working to find a path toward economic viability, it said in a Tuesday press release.
Willamette University and Pacific University seek to merge
The two private nonprofits in Oregon said Thursday that they intend to create “the University of the Northwest,” with one state official voicing support.
University of Nebraska regents approve cutting 4 programs at flagship
The university’s governing board voted in favor of the plan despite sustained faculty objections over the eliminations and the process for determining them.

“My students use ChatGPT to attack their own thinking before I ever grade them.” [Winkel] + another item re: AI in our LE’s

On 12/10/2025, in adjunct faculty, adult learning, Artificial Intelligence/Agents/LLMs/and Related, bots, cloud-based computing / apps / other cloud-related, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, creativity, digital learning, education, education technology, emerging technologies, experimentation, faculty/staff, future of higher education, game-changing environment, generational differences, graphics, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, law schools, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning preferences, learning spaces, liberal arts, library / librarians, lifelong learning, multimedia, pedagogy, personalized/customized learning, platforms, productivity / tips and tricks, skills, society, student-related, teachers, teaching & learning, teaching online, technologies for your home, tools, training / L&D, trends, United States, universities, vendors, vision/possibilities, workplace, by Daniel Christian

Beyond Infographics: How to Use Nano Banana to *Actually* Support Learning — from drphilippahardman.substack.com by Dr Philippa Hardman
Six evidence-based use cases to try in Google’s latest image-generating AI tool

While it’s true that Nano Banana generates better infographics than other AI models, the conversation has so far massively under-sold what’s actually different and valuable about this tool for those of us who design learning experiences.

What this means for our workflow:

Instead of the traditional “commission ? wait ? tweak ? approve ? repeat” cycle, Nano Banana enables an iterative, rapid-cycle design process where you can:

Sketch an idea and see it refined in minutes.
Test multiple visual metaphors for the same concept without re-briefing a designer.
Build 10-image storyboards with perfect consistency by specifying the constraints once, not manually editing each frame.
Implement evidence-based strategies (contrasting cases, worked examples, observational learning) that are usually too labour-intensive to produce at scale.

This shift—from “image generation as decoration” to “image generation as instructional scaffolding”—is what makes Nano Banana uniquely useful for the 10 evidence-based strategies below.

Caring for Patients for 26 Years—and Still Not a Nurse — from workshift.org/ by Colleen Connolly

Arnett’s experience spending decades in a job she intended as a first step is common among CNAs, medical assistants, and other entry-level healthcare workers, many of them women of color from low-income backgrounds. Amid a nationwide nursing shortage, elevating those workers seems like an obvious solution, but the path from CNA to nurse isn’t so much a ladder as it is a huge leap.

And obstacle after obstacle is strewn in the way. The high cost of nursing school, lengthy prerequisite requirements, rigid schedules, and unpaid clinical hours make it difficult for many CNAs to advance in their careers, despite their willingness and ability and the dire need of healthcare facilities.

While there are no national statistics about the number of entry-level healthcare workers who move on to higher-paid positions, a study of federal grants for CNA training showed that only 3% of those who completed the training went on to pursue further education to become an LPN or RN. Only 1% obtained an associate degree or above. A similar study in California showed that 22% of people who completed CNA certificate programs at community colleges went on to get a higher-level educational credential in health, but only 13% became registered nurses within six years.

That reality perpetuates chronic shortages in nursing, and it also keeps hundreds of thousands of healthcare workers locked below a living wage, often for decades.

“Introducing AI assistants with memory” + other items re: AI in our learning ecosystems

On 12/01/2025, in accessibility / UDL, adjunct faculty, Artificial Intelligence/Agents/LLMs/and Related, bots, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate universities / corporate training, digital learning, digital video, education, education technology, emerging technologies, experimentation, faculty/staff, future of higher education, game-changing environment, generational differences, Google, higher education, human-computer interaction (HCI), innovation, instructional design, intelligent systems, IT in HE, 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, memory, multimedia, personalized/customized learning, platforms, productivity / tips and tricks, student-related, teachers, teaching & learning, tools, training / L&D, trends, United States, universities, vendors, by Daniel Christian

4 Simple & Easy Ways to Use AI to Differentiate Instruction — from mindfulaiedu.substack.com (Mindful AI for Education) by Dani Kachorsky, PhD
Designing for All Learners with AI and Universal Design Learning

So this year, I’ve been exploring new ways that AI can help support students with disabilities—students on IEPs, learning plans, or 504s—and, honestly, it’s changing the way I think about differentiation in general.

As a quick note, a lot of what I’m finding applies just as well to English language learners or really to any students. One of the big ideas behind Universal Design for Learning (UDL) is that accommodations and strategies designed for students with disabilities are often just good teaching practices. When we plan instruction that’s accessible to the widest possible range of learners, everyone benefits. For example, UDL encourages explaining things in multiple modes—written, visual, auditory, kinesthetic—because people access information differently. I hear students say they’re “visual learners,” but I think everyone is a visual learner, and an auditory learner, and a kinesthetic learner. The more ways we present information, the more likely it is to stick.

So, with that in mind, here are four ways I’ve been using AI to differentiate instruction for students with disabilities (and, really, everyone else too):

The Periodic Table of AI Tools In Education To Try Today — from ictevangelist.com by Mark Anderson

What I’ve tried to do is bring together genuinely useful AI tools that I know are already making a difference.

For colleagues wanting to explore further, I’m sharing the list exactly as it appears in the table, including website links, grouped by category below. Please do check it out, as along with links to all of the resources, I’ve also written a brief summary explaining what each of the different tools do and how they can help.

Seven Hard-Won Lessons from Building AI Learning Tools — from linkedin.com by Louise Worgan

Last week, I wrapped up Dr Philippa Hardman’s intensive bootcamp on AI in learning design. Four conversations, countless iterations, and more than a few humbling moments later – here’s what I am left thinking about.

Finally Catching Up to the New Models — from michellekassorla.substack.com by Michelle Kassorla
There are some amazing things happening out there!

An aside: Google is working on a new vision for textbooks that can be easily differentiated based on the beautiful success for NotebookLM. You can get on the waiting list for that tool by going to LearnYourWay.withgoogle.com.
…
Nano Banana Pro
Sticking with the Google tools for now, Nano Banana Pro (which you can use for free on Google’s AI Studio), is doing something that everyone has been waiting a long time for: it adds correct text to images.

Introducing AI assistants with memory — from perplexity.ai

The simple act of remembering is the crux of how we navigate the world: it shapes our experiences, informs our decisions, and helps us anticipate what comes next. For AI agents like Comet Assistant, that continuity leads to a more powerful, personalized experience.

Today we are announcing new personalization features to remember your preferences, interests, and conversations. Perplexity now synthesizes them automatically like memory, for valuable context on relevant tasks. Answers are smarter, faster, and more personalized, no matter how you work.

From DSC :
This should be important as we look at learning-related applications for AI.

For the last three days, my Substack has been in the top “Rising in Education” list. I realize this is based on a hugely flawed metric, but it still feels good. ?

– Michael G Wagner

Read on Substack

I’m a Professor. A.I. Has Changed My Classroom, but Not for the Worse. — from nytimes.com by Carlo Rotella [this should be a gifted article]
My students’ easy access to chatbots forced me to make humanities instruction even more human.

“The AI opportunity in L&D isn’t one thing – it’s five different capability unlocks.” [Vinauskaite] + other items re: AI in our LE’s

On 11/21/2025, in Artificial Intelligence/Agents/LLMs/and Related, business, cloud-based computing / apps / other cloud-related, colleges, community colleges, corporate / business world, corporate universities / corporate training, digital learning, emerging technologies, faculty/staff, game-changing environment, higher education, innovation, instructional design, learning agents, learning ecosystem, Learning Experience Design, memory, online learning, Open AI, pedagogy, platforms, productivity / tips and tricks, professional development, simulations, skills, student-related, teachers, teaching & learning, tools, training / L&D, United States, universities, workplace, by Daniel Christian

AI’s Role in Online Learning > Take It or Leave It with Michelle Beavers, Leo Lo, and Sara McClellan — from intentionalteaching.buzzsprout.com by Derek Bruff

You’ll hear me briefly describe five recent op-eds on teaching and learning in higher ed. For each op-ed, I’ll ask each of our panelists if they “take it,” that is, generally agree with the main thesis of the essay, or “leave it.” This is an artificial binary that I’ve found to generate rich discussion of the issues at hand.

“Textbooks are no longer one-size-fits-all” [Fitzpatrick] + other items re: AI in our learning ecosystems

On 11/18/2025, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, bots, change, changing business models, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, education, education technology, emerging technologies, experimentation, faculty/staff, game-changing environment, generational differences, Google, higher education, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, K-12 related, law schools, learner profiles, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning preferences, learning spaces, liberal arts, lifelong learning, Open AI, platforms, productivity / tips and tricks, student-related, teachers, teaching & learning, technologies for your home, training / L&D, trends, United States, universities, vendors, by Daniel Christian

Three Years from GPT-3 to Gemini 3 — from oneusefulthing.org by Ethan Mollick
From chatbots to agents

Three years ago, we were impressed that a machine could write a poem about otters. Less than 1,000 days later, I am debating statistical methodology with an agent that built its own research environment. The era of the chatbot is turning into the era of the digital coworker. To be very clear, Gemini 3 isn’t perfect, and it still needs a manager who can guide and check it. But it suggests that “human in the loop” is evolving from “human who fixes AI mistakes” to “human who directs AI work.” And that may be the biggest change since the release of ChatGPT.

Results May Vary — from aiedusimplified.substack.com by Lance Eaton, PhD
On Custom Instructions with GenAI Tools….

I’m sharing today about custom instructions and my use of them across several AI tools (paid versions of ChatGPT, Gemini, and Claude). I want to highlight what I’m doing, how it’s going, and solicit from readers to share in the comments some of their custom instructions that they find helpful.

I’ve been in a few conversations lately that remind me that not everyone knows about them, even some of the seasoned folks around GenAI and how you might set them up to better support your work. And, of course, they are, like all things GenAI, highly imperfect!

I’ll include and discuss each one below, but if you want to keep abreast of my custom instructions, I’ll be placing them here as I adjust and update them so folks can see the changes over time.

Enrollment Growth Continues, Bolstered by Short-Term Credentials [Alonso]

On 11/13/2025, in Alternatives, business side of he, career development, colleges, community colleges, credentialing, expectations, faculty/staff, game-changing environment, higher education, parents/guardians, student-related, United States, by Daniel Christian

Enrollment Growth Continues, Bolstered by Short-Term Credentials — from insidehighered.com by Johanna Alonso
Enrollment is up across the board this fall, except for graduate student enrollment, which remained stagnant. The biggest increase was among those pursuing short-term credentials, followed by those earning associate degrees.

College enrollment continued to grow this fall, increasing by 2 percent compared to fall 2024, according to preliminary fall data released by the National Student Clearinghouse Research Center.

The biggest gains came from students studying for short-term credentials, whose ranks increased 6.6 percent, while the number of students enrolled in associate and bachelor’s degree programs rose 3.1 percent and 1.2 percent, respectively. Enrollment also grew faster at community colleges, which experienced a 4 percent increase, than at public (1.9 percent) and private (0.9 percent) four-year institutions.

Total graduate enrollment was stagnant, however, and the number of master’s students actually decreased by 0.6 percent.

Speaking of higher education, also see:

OPINION: Too many college graduates are stranded before their careers can even begin. We can’t let that happen — from hechingerreport.org by Bruno V. Manno

This fall, some 19 million undergraduates returned to U.S. campuses with a long-held expectation: Graduate, land an entry-level job, climb the career ladder. That formula is breaking down.

Once reliable gateway jobs for college graduates in industries like finance, consulting and journalism have tightened requirements. Many entry-level job postings that previously provided initial working experience for college graduates now require two to three years of prior experience, while AI, a recent analysis concluded, “snaps up good entry-level tasks,” especially routine work like drafting memos, preparing spreadsheets and summarizing research.

Without these proving grounds, new hires lose chances to build skills by doing. And the demand for work experience that potential workers don’t have creates an experience gap for new job seekers. Once stepping-stones, entry-level positions increasingly resemble mid-career jobs.

How is AI impacting the learning ecosystems out there (esp. L&D)? Check these postings out.

On 11/13/2025, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, assessment, bots, change, cloud-based computing / apps / other cloud-related, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate universities / corporate training, digital learning, education technology, emerging technologies, Europe, faculty/staff, future of higher education, game-changing environment, generational differences, global / globalization, Google, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, law schools, learner profiles, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning preferences, learning spaces, learning theories, liberal arts, library / librarians, lifelong learning, Microsoft, online learning, productivity / tips and tricks, skills, society, student-related, teachers, teaching & learning, tools, training / L&D, trends, UK, United States, universities, vendors, vision/possibilities, workplace, by Daniel Christian

?

Gen AI Is Going Mainstream: Here’s What’s Coming Next — from joshbersin.com by Josh Bersin

I just completed nearly 60,000 miles of travel across Europe, Asia, and the Middle East meeting with hundred of companies to discuss their AI strategies. While every company’s maturity is different, one thing is clear: AI as a business tool has arrived: it’s real and the use-cases are growing.

A new survey by Wharton shows that 46% of business leaders use Gen AI daily and 80% use it weekly. And among these users, 72% are measuring ROI and 74% report a positive return. HR, by the way, is the #3 department in use cases, only slightly behind IT and Finance.

What are companies getting out of all this? Productivity. The #1 use case, by far, is what we call “stage 1” usage – individual productivity.

.

From DSC:
Josh writes: “Many of our large clients are now implementing AI-native learning systems and seeing 30-40% reduction in staff with vast improvements in workforce enablement.”

While I get the appeal (and ROI) from management’s and shareholders’ perspective, this represents a growing concern for employment and people’s ability to earn a living.

And while I highly respect Josh and his work through the years, I disagree that we’re over the problems with AI and how people are using it:

Two years ago the NYT was trying to frighten us with stories of AI acting as a romance partner. Well those stories are over, and thanks to a $Trillion (literally) of capital investment in infrastructure, engineering, and power plants, this stuff is reasonably safe.

Those stories are just beginning…they’re not close to being over.

“… imagine a world where there’s no separation between learning and assessment…” — from aiedusimplified.substack.com by Lance Eaton, Ph.D. and Tawnya Means
An interview with Tawnya Means

So let’s imagine a world where there’s no separation between learning and assessment: it’s ongoing. There’s always assessment, always learning, and they’re tied together. Then we can ask: what is the role of the human in that world? What is it that AI can’t do?
…
Imagine something like that in higher ed. There could be tutoring or skill-based work happening outside of class, and then relationship-based work happening inside of class, whether online, in person, or some hybrid mix.

The aspects of learning that don’t require relational context could be handled by AI, while the human parts remain intact. For example, I teach strategy and strategic management. I teach people how to talk with one another about the operation and function of a business. I can help students learn to be open to new ideas, recognize when someone pushes back out of fear of losing power, or draw from my own experience in leading a business and making future-oriented decisions.

But the technical parts such as the frameworks like SWOT analysis, the mechanics of comparing alternative viewpoints in a boardroom—those could be managed through simulations or reports that receive immediate feedback from AI. The relational aspects, the human mentoring, would still happen with me as their instructor.

Part 2 of their interview is here:

“They’re not necessarily trying to cheat; they’re just being efficient”

A New AI Career Ladder — from ssir.org (Stanford Social Innovation Review) by Bruno V. Manno; via Matt Tower
The changing nature of jobs means workers need new education and training infrastructure to match.

AI has cannibalized the routine, low-risk work tasks that used to teach newcomers how to operate in complex organizations. Without those task rungs, the climb up the opportunity ladder into better employment options becomes steeper—and for many, impossible. This is not a temporary glitch. AI is reorganizing work, reshaping what knowledge and skills matter, and redefining how people are expected to acquire them.

The consequences ripple from individual career starts to the broader American promise of economic and social mobility, which includes both financial wealth and social wealth that comes from the networks and relationships we build. Yet the same technology that complicates the first job can help us reinvent how experience is earned, validated, and scaled. If we use AI to widen—not narrow—access to education, training, and proof of knowledge and skill, we can build a stronger career ladder to the middle class and beyond. A key part of doing this is a redesign of education, training, and hiring infrastructure.

…

What’s needed is a redesigned model that treats work as a primary venue for learning, validates capability with evidence, and helps people keep climbing after their first job. Here are ten design principles for a reinvented education and training infrastructure for the AI era.

Create hybrid institutions that erase boundaries. …
Make work-based learning the default, not the exception. …
Create skill adjacencies to speed transitions. …
Place performance-based hiring at the core. …
Ongoing supports and post-placement mobility. …
Portable, machine-readable credentials with proof attached. …
…plus several more…

Class of 2025 says they see the effects of a tough job market [Moody] + item re: prices for obtaining a degree

On 11/07/2025, in business, business side of he, career development, colleges, community colleges, cost of getting a degree, faculty/staff, funding / grants, higher education, parents/guardians, student-related, teaching & learning, United States, universities, workplace, by Daniel Christian

Net tuition rises at colleges, but costs are far below their peaks — from highereddive.com by Ben Unglesbee
The prices students and their families paid after aid at four-year public colleges and private nonprofits ticked up in 2025-26, per College Board estimates.

Dive Brief:

The average tuition and fees paid by students and their families after aid rose slightly for the 2025-26 academic year but remain well below historic peaks, according to the latest higher education pricing study from the College Board.
At public four-year colleges, net tuition and fees for first-time, full-time students increased just 1.3% to $2,300 from last year, when adjusted for inflation, according to the College Board’s estimates. That figure is down 48.3% from the peak in 2012-2013.
At private nonprofits, net tuition and fees for first-time, full-time students rose 3.7% annually to $16,910 in the 2025-26 year, when adjusted for inflation. By comparison, that’s down 14.6% from the peak for private colleges in 2006-07.

Class of 2025 says they see the effects of a tough job market — from hrdive.com by Kathryn Moody
Young workers have been particularly exposed to the changes brought by artificial intelligence tools, some research has indicated.

The Class of 2025 faced a particularly tough job market, searching for jobs earlier, submitting more applications — averaging 10 applications to the Class of 2024’s six — and receiving fewer offers on average, a National Association of Colleges and Employers study said in a recent report, in partnership with Indeed.

Graduates were more likely to accept those offers, however, even amid uncertainty; 86.7% of those offered a job had accepted in 2025, compared to 81.2% of 2024 graduates.

“Compared to earlier classes, they were more likely to say they were unsure about their plans, and more were planning to enter the military, suggesting they were unsure about private-sector employment,” NACE said in an Oct. 30 announcement regarding the report.

An addendum from DSC:
While we’re talking the workplace, careers, jobs, and such involving higher education, also see:

Careers in Educational Development with Leslie Cramblet Alvarez and Chris Hakala — from intentionalteaching.buzzsprout.com by Derek Bruff

On the show today I talk with Leslie Cramblet Alvarez and Chris Hakala, authors of the new book Understanding Educational Developers: Tales from the Center from Routledge Press. The book blends scholarship and personal narratives to explore the career trajectories of the professionals who work at CTLs (Centers for Teaching & Learning). How do academics move into these careers? And what can these careers look like over time?

Leslie Cramblet Alvarez is assistant vice provost and director of the Office of Teaching and Learning at the University of Denver. Chris Hakala is director for the Center for Excellence in Teaching, Learning, and Scholarship and professor of psychology at Springfield College.

I wanted to talk with Chris and Leslie about what they discovered while writing their book. I also wanted to know what advice they had for navigating educational development careers here in the U.S. in 2025, with higher education under attack from the federal government, a looming demographic cliff affecting enrollment and tuition, and a budget situation that for more institutions is not rosy. Leslie and Chris offer advice for faculty considering a move into a faculty development role, as well as for those of us current working at CTLs trying to plan our careers.

The Other Regulatory Time Bomb — from onedtech.philhillaa.com by Phil Hill
Higher ed in the US is not prepared for what’s about to hit in April for new accessibility rules

Most higher-ed leaders have at least heard that new federal accessibility rules are coming in 2026 under Title II of the ADA, but it is apparent from conversations at the WCET and Educause annual conferences that very few understand what that actually means for digital learning and broad institutional risk. The rule isn’t some abstract compliance update: it requires every public institution to ensure that all web and media content meets WCAG 2.1 AA, including the use of audio descriptions for prerecorded video. Accessible PDF documents and video captions alone will no longer be enough. Yet on most campuses, the conversation has been understood only as a buzzword, delegated to accessibility coordinators and media specialists who lack the budget or authority to make systemic changes.

And no, relying on faculty to add audio descriptions en masse is not going to happen.

The result is a looming institutional risk that few presidents, CFOs, or CIOs have even quantified.

“This isn’t a cheating crisis. It’s an identify crisis [for higher education].” + numerous other items re: AI in our LE’s

On 11/05/2025, in active learning, apprenticeships, Artificial Intelligence/Agents/LLMs/and Related, bots, business side of he, colleges, community colleges, content development, aggregation, repositories, dangers of the status quo, education technology, emerging technologies, face-to-face, faculty/staff, future of higher education, game-changing environment, higher education, ideas, innovation, instructional design, intelligent systems, learning, learning ecosystem, Learning Experience Design, liberal arts, pedagogy, reinvent, society, staying relevant, student-related, surviving, teaching & learning, trends, UK, United States, universities, vision/possibilities, by Daniel Christian

??

…the above posting links to:

Higher Ed Is Sleepwalking Toward Obsolescence— And AI Won’t Be the Cause, Just the Accelerant — from substack.com by Steven Mintz
AI Has Exposed Higher Ed’s Hollow Core — The University Must Reinvent Itself or Fade

It begins with a basic reversal of mindset: Stop treating AI as a threat to be policed. Start treating it as the accelerant that finally forces us to build the education we should have created decades ago.

A serious institutional response would demand — at minimum — six structural commitments:

Make high-intensity human learning the norm. …
Put active learning at the center, not the margins. …
Replace content transmission with a focus on process. …
Mainstream high-impact practices — stop hoarding them for honors students. …
Redesign assessment to make learning undeniable. …

And above all: Instructional design can no longer be a private hobby.

Teaching with AI: From Prohibition to Partnership for Critical Thinking — from facultyfocus.com by Michael Kiener, PhD, CRC

How to Integrate AI Developmentally into Your Courses

Lower-Level Courses: Focus on building foundational skills, which includes guided instruction on how to use AI responsibly. This moves the strategy beyond mere prohibition.
Mid-Level Courses: Use AI as a scaffold where faculty provide specific guidelines on when and how to use the tool, preparing students for greater independence.
Upper-Level/Graduate Courses: Empower students to evaluate AI’s role in their learning. This enables them to become self-regulated learners who make informed decisions about their tools.
Balanced Approach: Make decisions about AI use based on the content being learned and students’ developmental needs.

Now that you have a framework for how to conceptualize including AI into your courses here are a few ideas on scaffolding AI to allow students to practice using technology and develop cognitive skills.

80 per cent of young people in the UK are using AI for their schoolwork — from aipioneers.org by Graham Attwell

What was encouraging, though, is that students aren’t just passively accepting this new reality. They are actively asking for help. Almost half want their teachers to help them figure out what AI-generated content is trustworthy, and over half want clearer guidelines on when it’s appropriate to use AI in their work. This isn’t a story about students trying to cheat the system; it’s a story about a generation grappling with a powerful new technology and looking to their educators for guidance. It echoes a sentiment I heard at the recent AI Pioneers’ Conference – the issue of AI in education is fundamentally pedagogical and ethical, not just technological.

“OpenAI’s Atlas: the End of Online Learning—or Just the Beginning?” [Hardman] + other items re: AI in our LE’s

On 10/28/2025, in 21st century, 24x7x365 access, adult learning, Artificial Intelligence/Agents/LLMs/and Related, assessment, assistive technologies, change, collaboration, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate universities / corporate training, digital learning, education technology, emerging technologies, experimentation, faculty/staff, game-changing environment, generational differences, heutagogy, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, internet, IT in HE, K-12 related, law schools, learner profiles, learning, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning preferences, learning spaces, learning theories, liberal arts, library / librarians, lifelong learning, memory, online learning, online media, online tutoring, Open AI, pedagogy, personalized/customized learning, platforms, productivity / tips and tricks, reading, student-related, teachers, teaching & learning, teaching online, technologies for your home, tools, training / L&D, trends, United States, universities, usability, user experience (UX), vendors, virtual tutoring, vision/possibilities, web-based collaboration, by Daniel Christian

OpenAI’s Atlas: the End of Online Learning—or Just the Beginning? — from drphilippahardman.substack.com by Dr. Philippa Hardman

My take is this: in all of the anxiety lies a crucial and long-overdue opportunity to deliver better learning experiences. Precisely because Atlas perceives the same context in the same moment as you, it can transform learning into a process aligned with core neuro-scientific principles—including active retrieval, guided attention, adaptive feedback and context-dependent memory formation.

Perhaps in Atlas we have a browser that for the first time isn’t just a portal to information, but one which can become a co-participant in active cognitive engagement—enabling iterative practice, reflective thinking, and real-time scaffolding as you move through challenges and ideas online.

With this in mind, I put together 10 use cases for Atlas for you to try for yourself.
…

6. Retrieval Practice
What: Pulling information from memory drives retention better than re-reading.
Why: Practice testing delivers medium-to-large effects (Adesope et al., 2017).
Try: Open a document with your previous notes. Ask Atlas for a mixed activity set: “Quiz me on the Krebs cycle—give me a near-miss, high-stretch MCQ, then a fill-in-the-blank, then ask me to explain it to a teen.”
Atlas uses its browser memory to generate targeted questions from your actual study materials, supporting spaced, varied retrieval.

From DSC:
A quick comment. I appreciate these ideas and approaches from Katarzyna and Rita. I do think that someone is going to want to be sure that the AI models/platforms/tools are given up-to-date information and updated instructions — i.e., any new procedures, steps to take, etc. Perhaps I’m missing the boat here, but an internal AI platform is going to need to have access to up-to-date information and instructions.

Is An Internship In College More Important Than The Degree Itself? — from forbes.com by Brandon Busteed

While confidence in higher education has eroded and more Americans are questioning the importance of a degree, the demand for internships among college students is skyrocketing and the odds of getting an internship at a major company are now lower than getting into the Ivy League. This begs the question: are we at a point where an internship is as valuable – or perhaps more so – than a degree itself?

While concerns about degree ROI were on the rise, the value of internships and other work-integrated learning opportunities was becoming increasingly apparent. New research and analysis have shown us how valuable it is for a student to have an internship during college: it doubles the odds they have a good job waiting for them upon graduation and doubles their odds of being engaged in their work over their lifetime. Although there are some variations in those outcomes by choice of college or academic major, those variations pale in comparison to the impact of having an internship. In short, a collegiate internship experience is a more important indicator of these outcomes than alma mater or major.

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