BREAKING: Google introduces Guided Learning — from aieducation.substack.com by Claire Zau
Some thoughts on what could make Google’s AI tutor stand out

Another major AI lab just launched “education mode.”

Google introduced Guided Learning in Gemini, transforming it into a personalized learning companion designed to help you move from quick answers to real understanding.

Instead of immediately spitting out solutions, it:

  • Asks probing, open-ended questions
  • Walks learners through step-by-step reasoning
  • Adapts explanations to the learner’s level
  • Uses visuals, videos, diagrams, and quizzes to reinforce concepts

This Socratic style tutor rollout follows closely behind similar announcements like OpenAI’s Study Mode (last week) and Anthropic’s Claude for Education (April 2025).


How Sci-Fi Taught Me to Embrace AI in My Classroom — from edsurge.com by Dan Clark

I’m not too naive to understand that, no matter how we present it, some students will always be tempted by “the dark side” of AI. What I also believe is that the future of AI in education is not decided. It will be decided by how we, as educators, embrace or demonize it in our classrooms.

My argument is that setting guidelines and talking to our students honestly about the pitfalls and amazing benefits that AI offers us as researchers and learners will define it for the coming generations.

Can AI be the next calculator? Something that, yes, changes the way we teach and learn, but not necessarily for the worse? If we want it to be, yes.

How it is used, and more importantly, how AI is perceived by our students, can be influenced by educators. We have to first learn how AI can be used as a force for good. If we continue to let the dominant voice be that AI is the Terminator of education and critical thinking, then that will be the fate we have made for ourselves.


AI Tools for Strategy and Research – GT #32 — from goodtools.substack.com by Robin Good
Getting expert advice, how to do deep research with AI, prompt strategy, comparing different AIs side-by-side, creating mini-apps and an AI Agent that can critically analyze any social media channel

In this issue, discover AI tools for:

  • Getting Expert Advice
  • Doing Deep Research with AI
  • Improving Your AI Prompt Strategy
  • Comparing Results from Different AIs
  • Creating an AI Agent for Social Media Analysis
  • Summarizing YouTube Videos
  • Creating Mini-Apps with AI
  • Tasting an Award-Winning AI Short Film

GPT-Building, Agentic Workflow Design & Intelligent Content Curation — from drphilippahardman.substack.com by Dr. Philippa Hardman
What 3 recent job ads reveal about the changing nature of Instructional Design

In this week’s blog post, I’ll share my take on how the instructional design role is evolving and discuss what this means for our day-to-day work and the key skills it requires.

With this in mind, I’ve been keeping a close eye on open instructional design roles and, in the last 3 months, have noticed the emergence of a new flavour of instructional designer: the so-called “Generative AI Instructional Designer.”

Let’s deep dive into three explicitly AI-focused instructional design positions that have popped up in the last quarter. Each one illuminates a different aspect of how the role is changing—and together, they paint a picture of where our profession is likely heading.

Designers who evolve into prompt engineers, agent builders, and strategic AI advisors will capture the new premium. Those who cling to traditional tool-centric roles may find themselves increasingly sidelined—or automated out of relevance.


Google to Spend $1B on AI Training in Higher Ed — from insidehighered.com by Katherine Knott

Google’s parent company announced Wednesday (8/6/25) that it’s planning to spend $1 billion over the next three years to help colleges teach and train students about artificial intelligence.

Google is joining other AI companies, including OpenAI and Anthropic, in investing in AI training in higher education. All three companies have rolled out new tools aimed at supporting “deeper learning” among students and made their AI platforms available to certain students for free.


5 Predictions for How AI Will Impact Community Colleges — from pistis4edu.substack.com by Feng Hou

Based on current technology capabilities, adoption patterns, and the mission of community colleges, here are five well-supported predictions for AI’s impact in the coming years.

  1. Universal AI Tutor Access
  2. AI as Active Teacher
  3. Personalized Learning Pathways
  4. Interactive Multimodal Learning
  5. Value-Centric Education in an AI-Abundant World

 

Partnerships to make higher education work for the workforce — from timeshighereducation.com by Brooke Wilson
Fostering long-term industry partners can enhance student outcomes and prepare them for the workplace of the future. Here’s how to get the best out of them

As the pace of change accelerates across all industries, higher education institutions face increasing pressure to ensure their graduates are prepared for the workplace demands of today – and tomorrow. Cultivating meaningful partnerships with industry is no longer optional; it’s necessary.

From curriculum co-design to experiential learning, universities can collaborate with businesses and industries in several ways to enhance student outcomes and strengthen regional economies.


The keys to strong university–non-profit partnerships — from timeshighereducation.com by Mariana Leyva, Martha Sáenz, and Itzel Eguiluz
Collaborative projects between universities and non-profits nurture empathy and allow students to make a real-world impact. Here, three educators share their tips for building meaningful partnerships that benefit students and communities alike

Collaborative projects between universities and non-profits nurture empathy and allow students to make a real-world impact. Here, three educators share their tips for building meaningful partnerships that benefit students and communities alike.

 

BREAKING: OpenAI Releases Study Mode — from aieducation.substack.com by Claire Zau
What’s New, What Works, and What’s Still Missing

What is Study Mode?
Study Mode is OpenAI’s take on a smarter study partner – a version of the ChatGPT experience designed to guide users through problems with Socratic prompts, scaffolded reasoning, and adaptive feedback (instead of just handing over the answer).

Built with input from learning scientists, pedagogy experts, and educators, it was also shaped by direct feedback from college students. While Study Mode is designed with college students in mind, it’s meant for anyone who wants a more learning-focused, hands-on experience across a wide range of subjects and skill levels.

Who can access it? And how?
Starting July 29, Study Mode is available to users on Free, Plus, Pro, and Team plans. It will roll out to ChatGPT Edu users in the coming weeks.


ChatGPT became your tutor — from theneurondaily.com by Grant Harvey
PLUS: NotebookLM has video now & GPT 4o-level AI runs on laptop

Here’s how it works: instead of asking “What’s 2+2?” and getting “4,” study mode asks questions like “What do you think happens when you add these numbers?” and “Can you walk me through your thinking?” It’s like having a patient tutor who won’t let you off the hook that easily.

The key features include:

  • Socratic questioning: It guides you with hints and follow-up questions rather than direct answers.
  • Scaffolded responses: Information broken into digestible chunks that build on each other.
  • Personalized support: Adjusts difficulty based on your skill level and previous conversations.
  • Knowledge checks: Built-in quizzes and feedback to make sure concepts actually stick.
  • Toggle flexibility: Switch study mode on and off mid-conversation depending on your goals.

Try study mode yourself by selecting “Study and learn” from tools in ChatGPT and asking a question.


Introducing study mode — from openai.com
A new way to learn in ChatGPT that offers step by step guidance instead of quick answers.

[On 7/29/25, we introduced] study mode in ChatGPT—a learning experience that helps you work through problems step by step instead of just getting an answer. Starting today, it’s available to logged in users on Free, Plus, Pro, Team, with availability in ChatGPT Edu coming in the next few weeks.

ChatGPT is becoming one of the most widely used learning tools in the world. Students turn to it to work through challenging homework problems, prepare for exams, and explore new concepts. But its use in education has also raised an important question: how do we ensure it is used to support real learning, and doesn’t just offer solutions without helping students make sense of them?

We’ve built study mode to help answer this question. When students engage with study mode, they’re met with guiding questions that calibrate responses to their objective and skill level to help them build deeper understanding. Study mode is designed to be engaging and interactive, and to help students learn something—not just finish something.


 

Recurring Themes In Bob Ambrogi’s 30 Years of Legal Tech Reporting (A Guest Post By ChatGPT) — from lawnext.com by ChatGPT
#legaltech #innovation #law #legal #innovation #vendors #lawyers #lawfirms #legaloperations

  • Evolution of Legal Technology: From Early Web to AI Revolution
  • Challenges in Legal Innovation and Adoption
  • Law Firm Innovation vs. Corporate Legal Demand: Shifting Dynamics
  • Tracking Key Technologies and Players in Legal Tech
  • Access to Justice, Ethics, and Regulatory Reform

Also re: legaltech, see:

How LegalTech is Changing the Client Experience in 2025 — from techbullion.com by Uzair Hasan

A Digital Shift in Law
In 2025, LegalTech isn’t a trend—it’s a standard. Tools like client dashboards, e-signatures, AI legal assistants, and automated case tracking are making law firms more efficient and more transparent. These systems also help reduce errors and save time. For clients, it means less confusion and more control.

For example, immigration law—a field known for paperwork and long processing times—is being transformed through tech. Clients now track their case status online, receive instant updates, and even upload key documents from their phones. Lawyers, meanwhile, use AI tools to spot issues faster, prepare filings quicker, and manage growing caseloads without dropping the ball.

Loren Locke, Founder of Locke Immigration Law, explains how tech helps simplify high-stress cases:
“As a former consular officer, I know how overwhelming the visa process can feel. Now, we use digital tools to break down each step for our clients—timelines, checklists, updates—all in one place. One client recently told me it was the first time they didn’t feel lost during their visa process. That’s why I built my firm this way: to give people clarity when they need it most.”


While not so much legaltech this time, Jordan’s article below is an excellent, highly relevant posting for what we are going through — at least in the United States:

What are lawyers for? — from jordanfurlong.substack.com by Jordan Furlong
We all know lawyers’ commercial role, to be professional guides for human affairs. But we also need lawyers to bring the law’s guarantees to life for people and in society. And we need it right now.

The question “What are lawyers for?” raises another, prior and more foundational question: “What is the law for?”

But there’s more. The law also exists to regulate power in a society: to structure its distribution, create processes for its implementation, and place limits on its application. In a healthy society, power flows through the law, not around it. Certainly, we need to closely examine and evaluate those laws — the exercise of power through a biased or corrupted system will be illegitimate even if it’s “lawful.” But as a general rule, the law is available as a check on the arbitrary exercise of power, whether by a state authority or a private entity.

And above these two aspects of law’s societal role, I believe there’s also a third: to serve as a kind of “moral architecture” of society.

 

Blood in the Instructional Design Machine? — from drphilippahardman.substack.com by Dr. Philippa Hardman
The reality of AI, job degradation & the likely future of Instructional Design

This raises a very important, perhaps even existential question for our profession: do these tools free a designer from the mind-numbing drudgery of content conversion (the “augmented human”)? Or do they automate the core expertise of the learning professional’s role, e.g. selecting instructional startegies, structuring narratives and designing a learning flow, in the process reducing the ID’s role to simply finding the source file and pushing a button (the “inverted centaur”)?

The stated aspiration of these tool builders seems to be a future where AI means that the instructional designer’s value shifts decisively from production to strategy. Their stated goal is to handle the heavy lifting of content generation, allowing the human ID to provide the indispensable context, creativity, and pedagogical judgment that AI cannot replicate.

However, the risk of these tools lies in how we use them, and the “inverted centaur” model remains deeply potent and possible. In an organisation that prioritises cost above all, these same tools can be used to justify reducing the ID role to the functional drudgery of inputting a PDF and supervising the machine.

The key to this paradox lies in a crucial data point: spending on outside products and services has jumped a dramatic 23% to $12.4 billion. 

This signals a fundamental shift: companies are reallocating funds from large internal teams toward specialised consultants and advanced learning technologies like AI. L&D is not being de-funded; it is being re-engineered.

 

New Lightcast Report: AI Skills Command 28% Salary Premium as Demand Shifts Beyond Tech Industry — from lightcast.io; via Paul Fain
First-of-its-kind analysis reveals specific AI skills employers need most, enabling targeted workforce training strategies across all career areas

July 23, 2025 – Lightcast, the global leader in labor market intelligence, today released “Beyond the Buzz: Developing the AI Skills Employers Actually Need,” a comprehensive analysis revealing that artificial intelligence has fundamentally transformed hiring patterns across the world of work. The report, based on analysis of over 1.3 billion job postings, shows that job postings including AI skills offer 28% higher salaries—nearly $18,000 more per year—than those without such capabilities.

More importantly, the research analyzes specific skills based on their growth across job postings, their importance in the workforce, and their exposure to AI. This shows exactly which AI skills create value in which contexts, solving the critical challenge facing educators and workforce development leaders: moving beyond vague “AI literacy” to precise, targeted training that delivers measurable results.


Also via Paul Fain:


Despite growing awareness, however, participation in skill development is limited. In 2024, less than half of U.S. employees (45%) participated in training or education to build new skills for their current job. About one in three employees (32%) who are hoping to move into a new role within the next year strongly agree that they have the skills needed to be exceptional in that role.

 

Building a learning ecosystem that drives business results — from chieflearningofficer.com by Nick Romanowski
How SAX combined adaptive e-learning and experiential workshops to accelerate capability development and impact the bottom line.

At SAX, we know that to succeed in today’s market, we need professionals who can learn quickly, apply that learning effectively and continuously adapt as client needs evolve.

Yet traditional training methods were no longer enough. Our firm faced familiar challenges: helping staff meet continuing professional education requirements efficiently, uncovering knowledge gaps to guide development and building a more capable, more client-ready workforce.

We found our solution in a flipped learning model that blends adaptive e-learning with live, experiential workshops. The results were transformative. We accelerated CPE credit completion by more than 50 percent, reclaimed 173 billable hours and equipped our people with deeper capabilities.

Here’s how we did it, and what we learned along the way.

Blend technology and human touch: Adaptive e-learning addresses individual knowledge gaps efficiently. Live workshops enable skill development through practice and feedback. Together, they drive both learning efficiency and behavior change.

 

AI is rewiring how we learn, and it’s a game-changer for L&D— from chieflearningofficer.com by Josh Bersin
As AI becomes central to learner engagement, L&D leaders are being urged to fundamentally rethink corporate training, says global industry analyst Josh Bersin.

What are people really doing with ChatGPT? They’re learning. They’re asking questions, getting immediate answers, digging deeper, analyzing information and ultimately making themselves more productive. So, one could argue that simply by shifting to a “learn by inquiry” model, we may triple our value to the business.

From my experience, there are two main learning models in this industry. The first is “what you need to know”—linear or prescriptive things that every employee needs to understand about the company, its products and their role. This kind of content is well handled by existing L&D models.

The second, and far more important, is “what you’d like to know”—questions, curiosities and explorations about how the company works, what customers truly need and how we can each go further in our careers. Thanks to AI, this kind of learning is now explosive and transformative.

Imagine a sales rep who loses a deal. Naturally, they may ask, “What could I have done to be more successful?” A well-designed AI-powered learning system would take that question, give the employee an initial answer and chat with the individual to dig into the problem.

The system would then surface relevant sales training material and recommend videos, tips or case studies for help. And the employee, assuming they like the experience, would likely keep exploring until they feel they’ve learned what they need.

This “curiosity-based” learning is now possible, and its benefits extend far beyond traditional training.

 


Tech check: Innovation in motion: How AI is rewiring L&D workflows — from chieflearningofficer.com by Gabrielle Pike
AI isn’t here to replace us. It’s here to level us up.

For today’s chief learning officer, the days of just rolling out compliance training are long gone. In 2025, learning and development leaders are architects of innovation, crafting ecosystems that are agile, automated and AI-infused. This quarter’s Tech Check invites us to pause, assess and get strategic about where tech is taking us. Because the goal isn’t more tools—it’s smarter, more human learning systems that scale with the business.

Sections include:

  • The state of AI in L&D: Hype vs. reality
  • AI in design: From static content to dynamic experiences
  • AI in development: Redefining production workflows
  • Strategic questions CLOs should be asking
  • Future forward: What’s next?
  • Closing thought

American Federation of Teachers (AFT) to Launch National Academy for AI Instruction with Microsoft, OpenAI, Anthropic and United Federation of Teachers — from aft.org

NEW YORK – The AFT, alongside the United Federation of Teachers and lead partner Microsoft Corp., founding partner OpenAI, and Anthropic, announced the launch of the National Academy for AI Instruction today. The groundbreaking $23 million education initiative will provide access to free AI training and curriculum for all 1.8 million members of the AFT, starting with K-12 educators. It will be based at a state-of-the-art bricks-and-mortar Manhattan facility designed to transform how artificial intelligence is taught and integrated into classrooms across the United States.

The academy will help address the gap in structured, accessible AI training and provide a national model for AI-integrated curriculum and teaching that puts educators in the driver’s seat.


Students Are Anxious about the Future with A.I. Their Parents Are, Too. — from educationnext.org by Michael B. Horn
The fast-growing technology is pushing families to rethink the value of college

In an era when the college-going rate of high school graduates has dropped from an all-time high of 70 percent in 2016 to roughly 62 percent now, AI seems to be heightening the anxieties about the value of college.

According to the survey, two-thirds of parents say AI is impacting their view of the value of college. Thirty-seven percent of parents indicate they are now scrutinizing college’s “career-placement outcomes”; 36 percent say they are looking at a college’s “AI-skills curriculum,” while 35 percent respond that a “human-skills emphasis” is important to them.

This echoes what I increasingly hear from college leadership: Parents and students demand to see a difference between what they are getting from a college and what they could be “learning from AI.”


This next item on LinkedIn is compliments of Ray Schroeder:



How to Prepare Students for a Fast-Moving (AI)World — from rdene915.com by Dr. Rachelle Dené Poth

Preparing for a Future-Ready Classroom
Here are the core components I focus on to prepare students:

1. Unleash Creativity and Problem-Solving.
2. Weave in AI and Computational Thinking.
3. Cultivate Resilience and Adaptability.


AI Is Reshaping Learning Roles—Here’s How to Future-Proof Your Team — from onlinelearningconsortium.org by Jennifer Mathes, Ph.D., CEO, Online Learning Consortium; via Robert Gibson on LinkedIn

Culture matters here. Organizations that foster psychological safety—where experimentation is welcomed and mistakes are treated as learning—are making the most progress. When leaders model curiosity, share what they’re trying, and invite open dialogue, teams follow suit. Small tests become shared wins. Shared wins build momentum.

Career development must be part of this equation. As roles evolve, people will need pathways forward. Some will shift into new specialties. Others may leave familiar roles for entirely new ones. Making space for that evolution—through upskilling, mobility, and mentorship—shows your people that you’re not just investing in AI, you’re investing in them.

And above all, people need transparency. Teams don’t expect perfection. But they do need clarity. They need to understand what’s changing, why it matters, and how they’ll be supported through it. That kind of trust-building communication is the foundation for any successful change.

These shifts may play out differently across sectors—but the core leadership questions will likely be similar.

AI marks a turning point—not just for technology, but for how we prepare our people to lead through disruption and shape the future of learning.


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2025 Learning System Top Picks — from elearninfo247.com by Craig Weiss

Who is leading the pack? Who is setting themselves apart here in the mid-year?

Are they an LMS? LMS/LXP? Talent Development System? Mentoring? Learning Platform?

Something else?

Are they solely customer training/education, mentoring, or coaching? Are they focused only on employees? Are they an amalgamation of all or some?

Well, they cut across the board – hence, they slide under the “Learning Systems” umbrella, which is under the bigger umbrella term – “Learning Technology.”

Categories: L&D-specific, Combo (L&D and Training, think internal/external audiences), and Customer Training/Education (this means customer education, which some vendors use to mean the same as customer training).

 

“Using AI Right Now: A Quick Guide” [Molnick] + other items re: AI in our learning ecosystems

Thoughts on thinking — from dcurt.is by Dustin Curtis

Intellectual rigor comes from the journey: the dead ends, the uncertainty, and the internal debate. Skip that, and you might still get the insight–but you’ll have lost the infrastructure for meaningful understanding. Learning by reading LLM output is cheap. Real exercise for your mind comes from building the output yourself.

The irony is that I now know more than I ever would have before AI. But I feel slightly dumber. A bit more dull. LLMs give me finished thoughts, polished and convincing, but none of the intellectual growth that comes from developing them myself. 


Using AI Right Now: A Quick Guide — from oneusefulthing.org by Ethan Mollick
Which AIs to use, and how to use them

Every few months I put together a guide on which AI system to use. Since I last wrote my guide, however, there has been a subtle but important shift in how the major AI products work. Increasingly, it isn’t about the best model, it is about the best overall system for most people. The good news is that picking an AI is easier than ever and you have three excellent choices. The challenge is that these systems are getting really complex to understand. I am going to try and help a bit with both.

First, the easy stuff.

Which AI to Use
For most people who want to use AI seriously, you should pick one of three systems: Claude from Anthropic, Google’s Gemini, and OpenAI’s ChatGPT.

Also see:


Student Voice, Socratic AI, and the Art of Weaving a Quote — from elmartinsen.substack.com by Eric Lars Martinsen
How a custom bot helps students turn source quotes into personal insight—and share it with others

This summer, I tried something new in my fully online, asynchronous college writing course. These classes have no Zoom sessions. No in-person check-ins. Just students, Canvas, and a lot of thoughtful design behind the scenes.

One activity I created was called QuoteWeaver—a PlayLab bot that helps students do more than just insert a quote into their writing.

Try it here

It’s a structured, reflective activity that mimics something closer to an in-person 1:1 conference or a small group quote workshop—but in an asynchronous format, available anytime. In other words, it’s using AI not to speed students up, but to slow them down.

The bot begins with a single quote that the student has found through their own research. From there, it acts like a patient writing coach, asking open-ended, Socratic questions such as:

What made this quote stand out to you?
How would you explain it in your own words?
What assumptions or values does the author seem to hold?
How does this quote deepen your understanding of your topic?
It doesn’t move on too quickly. In fact, it often rephrases and repeats, nudging the student to go a layer deeper.


The Disappearance of the Unclear Question — from jeppestricker.substack.com Jeppe Klitgaard Stricker
New Piece for UNESCO Education Futures

On [6/13/25], UNESCO published a piece I co-authored with Victoria Livingstone at Johns Hopkins University Press. It’s called The Disappearance of the Unclear Question, and it’s part of the ongoing UNESCO Education Futures series – an initiative I appreciate for its thoughtfulness and depth on questions of generative AI and the future of learning.

Our piece raises a small but important red flag. Generative AI is changing how students approach academic questions, and one unexpected side effect is that unclear questions – for centuries a trademark of deep thinking – may be beginning to disappear. Not because they lack value, but because they don’t always work well with generative AI. Quietly and unintentionally, students (and teachers) may find themselves gradually avoiding them altogether.

Of course, that would be a mistake.

We’re not arguing against using generative AI in education. Quite the opposite. But we do propose that higher education needs a two-phase mindset when working with this technology: one that recognizes what AI is good at, and one that insists on preserving the ambiguity and friction that learning actually requires to be successful.




Leveraging GenAI to Transform a Traditional Instructional Video into Engaging Short Video Lectures — from er.educause.edu by Hua Zheng

By leveraging generative artificial intelligence to convert lengthy instructional videos into micro-lectures, educators can enhance efficiency while delivering more engaging and personalized learning experiences.


This AI Model Never Stops Learning — from link.wired.com by Will Knight

Researchers at Massachusetts Institute of Technology (MIT) have now devised a way for LLMs to keep improving by tweaking their own parameters in response to useful new information.

The work is a step toward building artificial intelligence models that learn continually—a long-standing goal of the field and something that will be crucial if machines are to ever more faithfully mimic human intelligence. In the meantime, it could give us chatbots and other AI tools that are better able to incorporate new information including a user’s interests and preferences.

The MIT scheme, called Self Adapting Language Models (SEAL), involves having an LLM learn to generate its own synthetic training data and update procedure based on the input it receives.


Edu-Snippets — from scienceoflearning.substack.com by Nidhi Sachdeva and Jim Hewitt
Why knowledge matters in the age of AI; What happens to learners’ neural activity with prolonged use of LLMs for writing

Highlights:

  • Offloading knowledge to Artificial Intelligence (AI) weakens memory, disrupts memory formation, and erodes the deep thinking our brains need to learn.
  • Prolonged use of ChatGPT in writing lowers neural engagement, impairs memory recall, and accumulates cognitive debt that isn’t easily reversed.
 

How Do You Build a Learner-Centered Ecosystem? — from gettingsmart.com by Bobbi Macdonald and Alin Bennett

Key Points

  • It’s not just about redesigning public education—it’s about rethinking how, where and with whom learning happens. Communities across the United States are shaping learner-centered ecosystems and gathering insights along the way.
  • What does it take to build a learner-centered ecosystem? A shared vision. Distributed leadership. Place-based experiences.  Repurposed resources. And more. This piece unpacks 10 real-world insights from pilots in action.
    .

We believe the path forward is through the cultivation of learner-centered ecosystems — adaptive, networked structures that offer a transformed way of organizing, supporting, and credentialing community-wide learning. These ecosystems break down barriers between schools, communities, and industries, creating flexible, real-world learning experiences that tap into the full range of opportunities a community has to offer.

Last year, we announced our Learner-Centered Ecosystem Lab, a collaborative effort to create a community of practice consisting of twelve diverse sites across the country — from the streets of Brooklyn to the mountains of Ojai — that are demonstrating or piloting ecosystemic approaches. Since then, we’ve been gathering together, learning from one another, and facing the challenges and opportunities of trying to transform public education. And while there is still much more work to be done, we’ve begun to observe a deeper pattern language — one that aligns with our ten-point Ecosystem Readiness Framework, and one that, we hope, can help all communities start to think more practically and creatively about how to transform their own systems of learning.

So while it’s still early, we suspect that the way to establish a healthy learner-centered ecosystem is by paying close attention to the following ten conditions:

 

 

The Memory Paradox: Why Our Brains Need Knowledge in an Age of AI — from papers.ssrn.com by Barbara Oakley, Michael Johnston, Kenzen Chen, Eulho Jung, and Terrence Sejnowski; via George Siemens

Abstract
In an era of generative AI and ubiquitous digital tools, human memory faces a paradox: the more we offload knowledge to external aids, the less we exercise and develop our own cognitive capacities.
This chapter offers the first neuroscience-based explanation for the observed reversal of the Flynn Effect—the recent decline in IQ scores in developed countries—linking this downturn to shifts in educational practices and the rise of cognitive offloading via AI and digital tools. Drawing on insights from neuroscience, cognitive psychology, and learning theory, we explain how underuse of the brain’s declarative and procedural memory systems undermines reasoning, impedes learning, and diminishes productivity. We critique contemporary pedagogical models that downplay memorization and basic knowledge, showing how these trends erode long-term fluency and mental flexibility. Finally, we outline policy implications for education, workforce development, and the responsible integration of AI, advocating strategies that harness technology as a complement to – rather than a replacement for – robust human knowledge.

Keywords
cognitive offloading, memory, neuroscience of learning, declarative memory, procedural memory, generative AI, Flynn Effect, education reform, schemata, digital tools, cognitive load, cognitive architecture, reinforcement learning, basal ganglia, working memory, retrieval practice, schema theory, manifolds

 

“The AI-enhanced learning ecosystem” [Jennings] + other items re: AI in our learning ecosystems

The AI-enhanced learning ecosystem: A case study in collaborative innovation — from chieflearningofficer.com by Kevin Jennings
How artificial intelligence can serve as a tool and collaborative partner in reimagining content development and management.

Learning and development professionals face unprecedented challenges in today’s rapidly evolving business landscape. According to LinkedIn’s 2025 Workplace Learning Report, 67 percent of L&D professionals report being “maxed out” on capacity, while 66 percent have experienced budget reductions in the past year.

Despite these constraints, 87 percent agree their organizations need to develop employees faster to keep pace with business demands. These statistics paint a clear picture of the pressure L&D teams face: do more, with less, faster.

This article explores how one L&D leader’s strategic partnership with artificial intelligence transformed these persistent challenges into opportunities, creating a responsive learning ecosystem that addresses the modern demands of rapid product evolution and diverse audience needs. With 71 percent of L&D professionals now identifying AI as a high or very high priority for their learning strategy, this case study demonstrates how AI can serve not merely as a tool but as a collaborative partner in reimagining content development and management.
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How we use GenAI and AR to improve students’ design skills — from timeshighereducation.com by Antonio Juarez, Lesly Pliego and Jordi Rábago who are professors of architecture at Monterrey Institute of Technology in Mexico; Tomas Pachajoa is a professor of architecture at the El Bosque University in Colombia; & Carlos Hinrichsen and Marietta Castro are educators at San Sebastián University in Chile.
Guidance on using generative AI and augmented reality to enhance student creativity, spatial awareness and interdisciplinary collaboration

Blend traditional skills development with AI use
For subjects that require students to develop drawing and modelling skills, have students create initial design sketches or models manually to ensure they practise these skills. Then, introduce GenAI tools such as Midjourney, Leonardo AI and ChatGPT to help students explore new ideas based on their original concepts. Using AI at this stage broadens their creative horizons and introduces innovative perspectives, which are crucial in a rapidly evolving creative industry.

Provide step-by-step tutorials, including both written guides and video demonstrations, to illustrate how initial sketches can be effectively translated into AI-generated concepts. Offer example prompts to demonstrate diverse design possibilities and help students build confidence using GenAI.

Integrating generative AI and AR consistently enhanced student engagement, creativity and spatial understanding on our course. 


How Texas is Preparing Higher Education for AI — from the74million.org by Kate McGee
TX colleges are thinking about how to prepare students for a changing workforce and an already overburdened faculty for new challenges in classrooms.

“It doesn’t matter if you enter the health industry, banking, oil and gas, or national security enterprises like we have here in San Antonio,” Eighmy told The Texas Tribune. “Everybody’s asking for competency around AI.”

It’s one of the reasons the public university, which serves 34,000 students, announced earlier this year that it is creating a new college dedicated to AI, cyber security, computing and data science. The new college, which is still in the planning phase, would be one of the first of its kind in the country. UTSA wants to launch the new college by fall 2025.

But many state higher education leaders are thinking beyond that. As AI becomes a part of everyday life in new, unpredictable ways, universities across Texas and the country are also starting to consider how to ensure faculty are keeping up with the new technology and students are ready to use it when they enter the workforce.


In the Room Where It Happens: Generative AI Policy Creation in Higher Education — from er.educause.edu by Esther Brandon, Lance Eaton, Dana Gavin, and Allison Papini

To develop a robust policy for generative artificial intelligence use in higher education, institutional leaders must first create “a room” where diverse perspectives are welcome and included in the process.


Q&A: Artificial Intelligence in Education and What Lies Ahead — from usnews.com by Sarah Wood
Research indicates that AI is becoming an essential skill to learn for students to succeed in the workplace.

Q: How do you expect to see AI embraced more in the future in college and the workplace?
I do believe it’s going to become a permanent fixture for multiple reasons. I think the national security imperative associated with AI as a result of competing against other nations is going to drive a lot of energy and support for AI education. We also see shifts across every field and discipline regarding the usage of AI beyond college. We see this in a broad array of fields, including health care and the field of law. I think it’s here to stay and I think that means we’re going to see AI literacy being taught at most colleges and universities, and more faculty leveraging AI to help improve the quality of their instruction. I feel like we’re just at the beginning of a transition. In fact, I often describe our current moment as the ‘Ask Jeeves’ phase of the growth of AI. There’s a lot of change still ahead of us. AI, for better or worse, it’s here to stay.




AI-Generated Podcasts Outperform Textbooks in Landmark Education Study — form linkedin.com by David Borish

A new study from Drexel University and Google has demonstrated that AI-generated educational podcasts can significantly enhance both student engagement and learning outcomes compared to traditional textbooks. The research, involving 180 college students across the United States, represents one of the first systematic investigations into how artificial intelligence can transform educational content delivery in real-time.


What can we do about generative AI in our teaching?  — from linkedin.com by Kristina Peterson

So what can we do?

  • Interrogate the Process: We can ask ourselves if we I built in enough checkpoints. Steps that can’t be faked. Things like quick writes, question floods, in-person feedback, revision logs.
  • Reframe AI: We can let students use AI as a partner. We can show them how to prompt better, revise harder, and build from it rather than submit it. Show them the difference between using a tool and being used by one.
  • Design Assignments for Curiosity, Not Compliance: Even the best of our assignments need to adapt. Mine needs more checkpoints, more reflective questions along the way, more explanation of why my students made the choices they did.

Teachers Are Not OK — from 404media.co by Jason Koebler

The response from teachers and university professors was overwhelming. In my entire career, I’ve rarely gotten so many email responses to a single article, and I have never gotten so many thoughtful and comprehensive responses.

One thing is clear: teachers are not OK.

In addition, universities are contracting with companies like Microsoft, Adobe, and Google for digital services, and those companies are constantly pushing their AI tools. So a student might hear “don’t use generative AI” from a prof but then log on to the university’s Microsoft suite, which then suggests using Copilot to sum up readings or help draft writing. It’s inconsistent and confusing.

I am sick to my stomach as I write this because I’ve spent 20 years developing a pedagogy that’s about wrestling with big ideas through writing and discussion, and that whole project has been evaporated by for-profit corporations who built their systems on stolen work. It’s demoralizing.

 

Skilling Up for AI Transformation — from learningguild.com by Lauren Milstid and Megan Torrance

Lately, I’ve been in a lot of conversations—some casual, some strategy-deep—about what it takes to skill up teams for AI. One pattern keeps emerging: The organizations getting the most out of generative AI are the ones doing the most to support their people. They’re not just training on a single tool. They’re building the capacity to work with AI as a class of technology.

So let’s talk about that. Not the hype, but the real work of helping humans thrive in an AI-enabled workplace.


If Leadership Training Isn’t Applied, It Hasn’t Happened — from learningguild.com by Tim Samuels

L&D leadership training sessions often “feel” successful. A program is designed, a workshop is delivered, and employees leave feeling informed and engaged. But if that training isn’t applied in the workplace, did it actually happen? If we focus entirely on the “learning” but not the “development,” we’re wasting huge amounts of time and money. So let’s take a look at the current situation first.

The reality is stark; according to Harvard Business Review:

  • Only 12% of employees apply new skills learned in L&D programs
  • Just 25% believe their training measurably improved performance
  • We forget 75% of what we learn within six days unless we use it
 
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