innovation

The AI-native university, AI literacy, AI and accessibility + other items re: AI in our learning ecosystems

On 07/22/2026, in 21st century, 24x7x365 access, accessibility / UDL, Artificial Intelligence/Agents/LLMs/and Related, colleges, communities of practice, community colleges, corporate / business world, corporate universities / corporate training, data related items, education technology, emerging technologies, experimentation, faculty/staff, game-changing environment, generational differences, higher education, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, learning, learning ecosystem, Learning Experience Design, liberal arts, lifelong learning, personalized/customized learning, productivity / tips and tricks, student-related, teachers, teaching & learning, training / L&D, trends, United States, universities, by Daniel Christian

AI & Accessibility: 5 Practical Ways to Use LLMs to Support Inclusive Learning — from learningguild.com by Dr. Athena Joyce Stanley (B.A., M.A.E., Ph.D.)

The following strategies focus on how instructional designers can design for accessibility by embedding or enabling AI-supported tools within learning experiences. These approaches move beyond access to content and begin to support access to understanding, expression, and participation.
…
Personalized Clarification Through AI Copilots
Learners often need additional explanation, but may hesitate to ask questions in live sessions or require more individualized support.

Instructional designers can integrate AI copilots, LLM-powered conversational interfaces, into learning environments to provide on-demand clarification. These tools can act as digital coaches, helping learners understand concepts through simplified explanations and relevant examples.

This approach supports learners who benefit from additional processing time and personalized guidance.

Sample Prompt (for IDs Configuring Copilot Behavior)
You are a workplace learning coach.

Explain the following concept in a clear, simple way:

- Use plain language
- Provide one practical, job-relevant example
- Avoid jargon unless necessary (and define it if used)

Then ask one follow-up question to check for understanding.

Jeff’s posting on LinkedIn.

Teaching AI Literacy with Susan Ray — from intentionalteaching.buzzsprout.com by Derek Bruff and Susan Ray

Per Derek Bruff:
In my conversation with Susan, we talk about that syllabus activity, as well as the AI transparency journals she asks her students to keep during her courses. We also talk about how her personal background prepared her to navigate the challenges and opportunities that AI has posed to her teaching, how she approaches assessing student learning in this age of AI—especially in her online asynchronous courses—and much more.

Building the AI-Native University: Student Success and Lifelong Learning — from coursera.org

In this episode, you’ll discover:

Why building an AI-native campus requires a data-first foundation
How to build an “achievement architecture” for lifelong success
How faculty-built AI tutors cut one program’s course attrition from 40% to 10%
What it means to be a lifelong learning companion

We’re Raising the First AI Generation. They’re Pushing Back. (Rebecca Winthrop, Brookings) — from humanistxyz.substack.com by Allison Dulin Salisbury
“Young people harbor real anger about AI because they’re already experiencing its consequences in their schools, relationships, job prospects, and feeds.”

As Rebecca told me:

“Kids harbor real anger. They’re pissed about climate impacts. They’re upset about job prospects. They’re outraged about AI being used to plagiarize writing and produce counterfeit artwork. Their relationships are being affected, and they’re seeing deepfakes in their feeds.”

Our conversation explores what follows from taking those concerns seriously. We discuss cognitive stunting, the case for small, purpose-built AI models over frontier models in education, why students should spend far more time in explorer mode, and how schools can cultivate agency, curiosity, and independent thinking in an age of AI.

The interview ends with one of Rebecca’s most practical recommendations: every school should have a student AI council, not as a symbolic gesture, but with real influence over the tools their schools adopt, the ways they’re used, and the data students are asked to hand over.

Every generation of technology seems to relearn the same lesson: build with people, not for them. AI should be no exception.

The World’s Largest Pop-Up Book

On 07/22/2026, in art, creativity, design, ideas, innovation, library / librarians, reading, by Daniel Christian

Los Angeles Public Library Unveils the World’s Largest Pop-Up Book — from thisiscolossal.com by Kate Mothes and Daniel González

Steward Stories: How Heart of Oregon Corps Turns Service into Careers — from gettingsmart.com by Karen Pittman and Merita Irby

Our “Steward Stories” series captures lessons learned from interviews with leaders of mature, purpose-built ecosystem intermediaries. An ecosystem steward is a boundary-spanning leader who goes beyond traditional out-of-school time (OST) system building to weave together the diverse people, places, and possibilities that shape a young person’s daily life. Rather than managing a single isolated network, stewards collaborate across K-12 schools, youth development programs, and workforce systems to build vibrant, equitable learning ecosystems. They drive systemic change from practice to policy by creating purpose-built intermediaries, developing scalable cross-system training tools, and championing “Future Features” of learning. These core priorities include promoting learner agency, institutionalizing “unwalled” schools that connect community resources to formal education, broadening the definition of educators to include informal mentors, and normalizing pathways for students to receive school credit or credentials for out-of-school learning.

The starting points, paths, and targets set by these stewards are as varied as the conditions and opportunities present within their communities. But they share similarities in vision and approach. Learn More Here.

Learning ecosystems may be found anywhere, but it takes careful stewardship to help them thrive.
— Shift, Remake Learning

Free K-12 Career Literacy Resources from agilities.org

On 07/16/2026, in business, career development, collaboration, colleges, community colleges, corporate / business world, education, engagement / engaging students, engineering, entrepreneurship, experimentation, innovation, K-12 related, learning, skills, society, student-related, teachers, United States, workplace, youth, by Daniel Christian

Agilities — from agilities.org by the DeBruce Foundation; via Paul Fain
Help students build confidence and prepare for bright careers!
.

Also from Paul Fain, see:

Unlocking Opportunity: Progress on Moving More Students Toward Good Jobs — from highered.aspeninstitute.org

Released in partnership with the Community College Research Center (CCRC), Unlocking Opportunity: Progress on Moving More Students Toward Good Jobs highlights early outcomes from the first 10 colleges in the Unlocking Opportunity network. The report demonstrates that community colleges can rapidly increase enrollment in high-value workforce and transfer pathways while reducing enrollment in or improving programs with weaker labor market and bachelor’s degree outcomes.
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LEGAL FUTURISMS: Consumer Legal Tech and the Soul of US Democracy

The “Dollar Legal” Thought Experiment

What if the salvation of our democratic enthusiasm doesn’t come from a political revolution, but a technological one? Enter the thought experiment of Dollar Legal.

Imagine a ubiquitous, consumer-facing legal tech platform—accessible from any smartphone—that commoditizes basic legal defense and assertion of rights. It is AI-driven legal agency for the masses, costing no more than a cup of coffee, or perhaps literally a single dollar.

Dollar Legal wouldn’t exist to litigate complex corporate mergers; it would exist to handle the agonizing friction of everyday survival. It instantly analyzes a notice to quit, drafts a legally sound response asserting warranty of habitability defenses, and files it electronically. It forces the bureaucratic machine to pause. It translates the raw, terrifying human experience of a legal threat into the cold rules and procedures that the justice system understands.

And the price, $1.00, at sufficient scale, would support the operation and maintenance of the service.

By deploying Dollar Legal, we fundamentally shift the balance of power. The democratization of legal leverage changes the calculus for bad actors who rely on the silent default judgments of the unrepresented.

The Law School Deans Driving AI Innovation in Legal Education — from natlawreview.com by Shivani Vedhere, AI & the Law Newsletter; via Colin S. Levy

Artificial intelligence is no longer a peripheral issue for legal education. It is quickly becoming one of the central questions facing law schools: how to prepare future lawyers for a profession in which AI will affect research, client counseling, litigation strategy, access to justice, and the business of law.

For decades, law schools treated legal technology as an elective or a niche interest for students already inclined toward innovation. That era is ending. Law firms are adopting AI tools at scale and even investing in developing their own tools. Clients are asking harder questions about efficiency, cost, and competence. Courts are sanctioning lawyers and litigants for AI-generated hallucinations, with the number of identified cases in the United States now exceeding 1,000. Students entering the profession will be expected to keep up with this rapidly changing landscape.

The most forward-looking law schools are responding accordingly. That transformation is being driven in large part by a group of innovative law school deans who are treating AI not as a passing trend, but as a structural change in legal education.

These initiatives signal a broader shift in legal academia where law schools are no longer merely debating whether AI belongs in the curriculum. The more pressing question is how deeply, how early, and how responsibly AI should be integrated into legal education.

Higher Education Can’t Wait for the Future to Arrive (Lev Gonick, Arizona State University) [Salisbury]

On 07/07/2026, in 21st century, 24x7x365 access, career development, change, changing business models, collaboration, colleges, community colleges, competency-based learning/education, faculty/staff, future, future of higher education, game-changing environment, heutagogy, higher education, innovation, instructional design, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning preferences, liberal arts, more voice more choice more control, skills, society, student-related, teaching & learning, trends, United States, universities, vision/possibilities, by Daniel Christian

Higher Education Can’t Wait for the Future to Arrive (Lev Gonick, Arizona State University) — from humanistxyz.substack.com by Allison Dulin Salisbury
“The biggest risk we face as a sector is assuming we can wait out AI.”

We have an opportunity right now to reorient the university around student experience—not as an aspiration, but as a necessity. I’m calling this shift TechEd, which I explore in detail in my LinkedIn series The TechEd Revolution.

AI poses a fundamental shift in how technology might empower students to own their discovery and educational journey, and to drastically reduce the friction that makes college so unappealing to so many.

To that end, we need to urgently redesign systems and opportunities around skills and competencies. That work should be far more advanced than it currently is. And one of the hardest challenges is rethinking how we operate as a workforce in academia.

Instructional Design Trends: What’s Shaping The Future Of Learning? [Pappas] + “The Future Of Personalized Learning And The Leaders Being Trained To Deliver It” [Ayers]

On 07/06/2026, in analytics, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, educational games / serious games, elearning, emerging technologies, engagement / engaging students, future, game-changing environment, human-computer interaction (HCI), ideas, immersion, innovation, instructional design, intelligent systems, intelligent tutoring, leadership, organizational change, personalized/customized learning, skills, strategy, traditional / tradition, training / L&D, trends, user experience (UX), by Daniel Christian

Instructional Design Trends: What’s Shaping The Future Of Learning? — from elearningindustry.com by Christopher Pappas

Table of contents

1. Why Instructional Design Is Entering A New Era
2. The State Of Instructional Design Today
3. Top Instructional Design Trends Shaping 2026
4. The Future Of Instructional Design And Technology

Also from elearningindustry.com, see:

The Future Of Personalized Learning And The Leaders Being Trained To Deliver It — by Ryan Ayers

Table of contents

1. Personalized Learning For Future Leaders
2. Where Personalized Learning Is Heading
3. What Implementing Personalized Learning At Scale Actually Requires
4. The Educational Leaders Being Trained To Deliver This Future
5. Conclusion

Will learning curated by employers replace degrees? — from universityworldnews.com by Louise Nicol

If universities do not future-proof their offer through deeper and more credible partnerships with employers and industry, what exactly prevents employers from educating and training people themselves?

This is why the future of higher education depends on far deeper and more operational partnerships with industry. Not symbolic advisory boards or occasional guest lectures but genuine co-design of curricula, shared ownership of applied projects and clear accountability for graduate capability.

Universities that integrate live industry problems, cross-faculty collaboration and work-based learning into the core of their programmes make themselves harder to replace. Those that acknowledge the existence of external learning platforms and deliberately build them into a broader educational journey strengthen rather than weaken their position.

The real risk for universities is not replacement but marginalisation. Employers will not abandon universities out of hostility or ideology. They will do so pragmatically if universities fail to add distinctive value beyond what employers can now deliver themselves.

The Current State of Play: AI in Higher Education and the Road Ahead [Gamby, Kil, Koblic, LeBlanc, Moldoveanu & Siemens]

On 06/29/2026, in 21st century, Artificial Intelligence/Agents/LLMs/and Related, business side of he, career development, change, colleges, community colleges, corporate / business world, culture, emerging technologies, ethics, expectations, experimentation, faculty/staff, game-changing environment, generational differences, higher education, ideas, innovation, instructional design, intelligent systems, IT in HE, leadership, learning, learning agents, learning ecosystem, Learning Experience Design, liberal arts, morals/values, organizational change, pace of change, parents/guardians, personalized/customized learning, policy, reinvent, relationships, skills, society, strategy, student-related, teaching & learning, trends, United States, universities, vision/possibilities, by Daniel Christian

The Current State of Play: AI in Higher Education and the Road Ahead — from er.educause.edu by Tanya Gamby, David Kil, Rachel Koblic, Paul LeBlanc, Mihnea Moldoveanu and George Siemens

The conventional explanation for this strategic vacuum points to the speed of technological change; it is moving too fast for institutions built for deliberation. That is true. . . and incomplete. The deeper issue is cultural. In fairness to higher education, many industries are struggling to keep up with the pace of AI advances. Higher education, however, moves even more slowly and is not built for the kind of transformational speed now underway. Getting institutional stakeholders to engage, rethink the work, and move faster may be the central challenge facing presidents and chancellors today, and that’s saying a lot in such volatile times.

From DSC:
I highlighted this paragraph because it hits upon the key item involved here — culture. “The deeper issue is cultural.” I think that’s a very true statement.

Part of the culture and setup of many institutions includes giving faculty members full rein of their classes and their departments. Faculty members have a great deal of leeway and power in how they do things. So trying to get X faculty members to get on board — including the Department Chairs — is not an easy task.

Another part of culture involves being willing — or not — to change in the first place. Some institutions are like Google and are used to making changes and being more innovative. But those institutions are not the norm, at least in my experience. And this doesn’t even address another topic the article mentioned — the pace of these changes. As the authors point out, most institutions of traditional higher education are not equipped to deal with the current pace of change (nor are most of our other types of institutions and our corporations as well).

I’m going to end this posting with another brief excerpt from the article:

Institutions rooted in human relationships, committed to truth-seeking, and oriented toward the full development of persons play a central role. AI cannot manufacture the experience of mattering to another human being. It cannot model intellectual courage or ethical discernment. It cannot build the kind of community in which students discover who they are and what they believe.

These are not small things. They are, in fact, the things most worth doing. At their best, colleges and universities are not only preparing better workers but shaping individuals and strengthening society.

AI’s getting expensive for us these days

On 06/23/2026, in Adobe, Artificial Intelligence/Agents/LLMs/and Related, business side of he, change, changing business models, cloud-based computing / apps / other cloud-related, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, cost of getting a degree, Daniel S. Christian, education technology, emerging technologies, experimentation, faculty/staff, funding / grants, game-changing environment, graphics, higher education, human-computer interaction (HCI), innovation, intelligent systems, IT in HE, learning ecosystem, liberal arts, library / librarians, new business models, Open AI, platforms, student-related, teaching & learning, technologies for your home, tools, trends, United States, universities, by Daniel Christian

From DSC:
I used to be able to bring up Firefly on the web and use it “free” of charge — I didn’t have to go purchase tokens or credits. (I was actually paying for the Adobe Creative Cloud Pro suite of tools…so it wasn’t really free.)

But the other day I was trying to figure out what the latest pricing is at Adobe with that suite of tools and the use of credits for AI-based features. They say Adobe Creative Cloud Pro users get 4000 credits a month. Well, I have that suite and I’m still getting prompted to purchase credits. Firefly for individuals runs from $9.99 (2,000 credits/month) to $139.91 per month (50,000 credits per month). Not inexpensive, right? Below are other items along these lines.

The Era of Affordable AI Is Over. What Comes Next? — from builtin.com by Ameya Kanitkar
AI providers are shifting to usage-based billing for their services. AI fluency is more important now than ever to make the most of your tools to avoid unnecessary spending.

Summary: The era of cheap, flat-rate AI is ending as providers shift to usage-based billing. Every prompt now carries a direct cost, turning casual use into major budget risks, as seen when Uber depleted its 2026 AI budget in four months. Leaders must now track real-time value and token efficiency.

For a brief window, companies had access to the most transformative technology in a generation at the cost of a streaming subscription. Tools like ChatGPT put AI within reach of anyone with a browser and time for experimentation, while GitHub Copilot came in at just $10 a month, with token costs remaining relatively low. In the beginning, experimentation felt cost-effective, easy and relatively low-risk.

But that era is ending, and the bill is coming due faster than a lot of enterprise leaders anticipated.

The Fable of AI in Education — from downes.ca by Stephen Downes
Marc Watkins, Rhetorica, Jun 17, 2026

Tokenomics will be a hot topic of discussion on university campuses because, as Marc Watkins notes in this article, there is no realistic path forward to providing all students with access to advanced AI.

From this posting on LinkedIn.com from Dr. Nick Jackson:

And now there is a third layer emerging. Institutions are waking up to a systems-level question they are likely not remotely prepared for. Who pays for AI? How are budgets managed when there are unclear token consumption pricing models? How is AI procured? Who decides what tools get used and by whom and who gets access and at what level?

.

The Evolving L&D Roles in 2026 Exploring who you might become next — from liftedlnd.substack.com by Lifted L&D

1. The Learning Experience Architect
This is really the evolution of the instructional designer. The difference is that the focus is no longer on building individual courses. Instead, the focus shifts towards designing capability ecosystems.

In modern learning platforms, learning is dynamic and increasingly personalised. AI engines infer skill levels, recommend resources, generate practice scenarios and adapt content based on how people engage. The role of the Learning Experience Architect is to orchestrate that environment so it genuinely supports capability development.
…

Across all of these emerging roles, three themes keep appearing.

The first is data fluency. …
The second is systems thinking. …
The third is human judgement.

Also relevant/see:

The Tyranny of College Admissions: Why It’s So Challenging to Have Real Change in K-12 Education — from gettingsmart.com by Jon Alfuth

Key Points

College admissions policy shapes K-12 practice. If colleges continue to privilege course sequences, seat time, and grades, high schools will remain constrained in how far they can move toward competency-based learning.
States and institutions already offer models for change. Wisconsin, Colorado, Indiana, and pilots like CUNY and Michigan Ross show that admissions can incorporate portfolios, demonstrations of learning, and durable skills.

If we could instead orient K-12 education around skill development and application rather than Carnegie Units and grades, we could create a new paradigm for where, when and how students demonstrate college and career readiness. Competency-based education moves schools and systems towards this desirable future that balances knowledge with skills.

Despite tremendous evidence of its potential, efforts to accelerate this shift have been stymied by the tyranny of college admissions requirements and processes. Parents, teachers, administrators and policymakers end up in a quandary. Anyone attempting to shift away from this traditional course sequence is criticized as trying to lock kids out of higher education and we snap back to the way things have always been done.

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
.

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.

Learning Ecosystems

The World’s Largest Pop-Up Book

Instructional Design Trends: What’s Shaping The Future Of Learning? [Pappas] + “The Future Of Personalized Learning And The Leaders Being Trained To Deliver It” [Ayers]

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