adult learning

Changes in the L&D / Corporate Learning World [as seen in article by Josh Bersin]

On 09/20/2025, in 21st century, 24x7x365 access, adult learning, Artificial Intelligence/Agents/LLMs/and Related, bots, business, cloud-based computing / apps / other cloud-related, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, elearning, emerging technologies, experimentation, Google, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, learning, learning agents, learning ecosystem, Learning Experience Design, microlearning, Microsoft, Open AI, platforms, productivity / tips and tricks, strategy, tools, training / L&D, trends, United States, workplace, by Daniel Christian

Workday Acquires Sana To Transform Its Learning Platform And Much More— from joshbersin.com by Josh Bersin

Well now, as the corporate learning market shifts to AI, (read the details in our study “The Revolution in Corporate Learning” ), Workday can jump ahead. This is because the $400 billion corporate training market is moving quickly to an AI-Native dynamic content approach (witness OpenAI’s launch of in-line learning in its chatbot). We’re just finishing a year-long study of this space and our detailed report and maturity model will be out in Q4.
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With Sana, and a few other AI-native vendors (Uplimit, Arist, Disperz, Docebo), companies can upload audios, videos, documents, and even interviews with experts and the system build learning programs in minutes. We use Sana for Galileo Learn (our AI-powered learning academy for Leadership and HR), and we now have 750+ courses and can build new programs in days instead of months.

And there’s more; this type of system gives every employee a personalized, chat-based experience to learn.

ChatGPT: the world’s most influential teacher [Hardman]

On 09/20/2025, in 21st century, 24x7x365 access, adult learning, Artificial Intelligence/Agents/LLMs/and Related, assessment, bots, cloud-based computing / apps / other cloud-related, colleges, communities of practice, community colleges, corporate / business world, corporate universities / corporate training, digital learning, education, education technology, emerging technologies, faculty/staff, future, future of higher education, game-changing environment, generational differences, heutagogy, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), instructional design, intelligent systems, intelligent tutoring, internet, 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, memory, metacognition / metacognitive skills, Open AI, pedagogy, personalized/customized learning, platforms, productivity / tips and tricks, society, student-related, teachers, teaching & learning, technologies for your home, tools, training / L&D, trends, United States, universities, vendors, web-based collaboration, by Daniel Christian

ChatGPT: the world’s most influential teacher — from drphilippahardman.substack.com by Dr. Philippa Hardman; emphasis DSC
New research shows that millions of us are “learning with AI” every week: what does this mean for how (and how well) humans learn?

This week, an important piece of research landed that confirms the gravity of AI’s role in the learning process. The TLDR is that learning is now a mainstream use case for ChatGPT; around 10.2% of all ChatGPT messages (that’s ~2BN messages sent by over 7 million users per week) are requests for help with learning.

The research shows that about 10.2% of all messages are tutoring/teaching, and within the “Practical Guidance” category, tutoring is 36%. “Asking” interactions are growing faster than “Doing” and are rated higher quality by users. Younger people contribute a huge share of messages, and growth is fastest in low- and middle-income countries (How People Use ChatGPT, 2025).

If AI is already acting as a global tutor, the question isn’t “will people learn with AI?”—they already are. The real question we need to ask is: what does great learning actually look like, and how should AI evolve to support it? That’s where decades of learning science help us separate “feels like learning” from “actually gaining new knowledge and skills”.

Let’s dive in.

“…students to use AI to help businesses solve ‘real world’ challenges” [McVicar] + other items re: AI in our learning ecosystems

On 09/09/2025, in adjunct faculty, adult learning, Artificial Intelligence/Agents/LLMs/and Related, bots, business, career development, change, cloud-based computing / apps / other cloud-related, collaboration, colleges, communities of practice, community colleges, content development, aggregation, repositories, copyright/ownership/NFTs, corporate / business world, corporate universities / corporate training, curriculum, data related items, digital audio, digital learning, digital storytelling, digital video, education technology, emerging technologies, experimentation, faculty/staff, future, future of higher education, game-changing environment, generational differences, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, leadership, learner profiles, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning preferences, liberal arts, multimedia, personalized/customized learning, platforms, productivity / tips and tricks, real-world assignments, reinvent, skills, society, staying relevant, student-related, teachers, teaching & learning, trends, United States, universities, vendors, vision/possibilities, workplace, by Daniel Christian

GRCC students to use AI to help businesses solve ‘real world’ challenges in new course — from www-mlive-com.cdn.ampproject.org by Brian McVicar; via Patrick Bailey on LinkedIn

GRAND RAPIDS, MI — A new course at Grand Rapids Community College aims to help students learn about artificial intelligence by using the technology to solve real-world business problems.
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In a release, the college said its grant application was supported by 20 local businesses, including Gentex, TwistThink and the Grand Rapids Public Museum. The businesses have pledged to work with students who will use business data to develop an AI project such as a chatbot that interacts with customers, or a program that automates social media posts or summarizes customer data.

“This rapidly emerging technology can transform the way businesses process data and information,” Kristi Haik, dean of GRCC’s School of Science, Technology, Engineering and Mathematics, said in a statement. “We want to help our local business partners understand and apply the technology. We also want to create real experiences for our students so they enter the workforce with demonstrated competence in AI applications.”

As Patrick Bailey said on LinkedIn about this article:

Nice to see a pedagogy that’s setting a forward movement rather than focusing on what could go wrong with AI in a curriculum.

Forecast for Learning and Earning in 2025-2026 report — from pages.asugsvsummit.com by Jennifer Lee and Claire Zau

In this look ahead at the future of learning and work, we aim to define:

Major thematic observations
What makes this moment an inflection point
Key predictions (and their precedent)
Short- and long-term projected impacts

The LMS at 30: From Course Management to Learning Management (At Last) — from onedtech.philhillaa.com; a guest post from Matthew Pittinsky, Ph.D.

As a 30 year observer and participant, it seems to me that previous technology platform shifts like SaaS and mobile did not fundamentally change the LMS. AI is different. We’re standing at the precipice of LMS 2.0, where the branding change from Course Management System to Learning Management System will finally live up to its name. Unlike SaaS or mobile, AI represents a technology platform shift that will transform the way participants interact with learning systems – and with it, the nature of the LMS itself.

Given the transformational potential of AI, it is useful to set the context and think about how we got here, especially on this 30th anniversary of the LMS.

LMS at 30 Part 2: Learning Management in the AI Era — from onedtech.philhillaa.com; a guest post from Matthew Pittinsky, Ph.D.

Where AI is disruptive is in its ability to introduce a whole new set of capabilities that are best described as personalized learning services. AI offers a new value proposition to the LMS, roughly the set of capabilities currently being developed in the AI Tutor / agentic TA segment. These new capabilities are so valuable given their impact on learning that I predict they will become the services with greatest engagement within a school or university’s “enterprise” instructional platform.

In this way, by LMS paradigm shift, I specifically mean a shift from buyers valuing the product on its course-centric and course management capabilities, to valuing it on its learner-centric and personalized learning capabilities.

AI and the future of education: disruptions, dilemmas and directions — from unesdoc.unesco.org

This anthology reveals how the integration of AI in education poses profound philosophical, pedagogical, ethical and political questions. As this global AI ecosystem evolves and becomes increasingly ubiquitous, UNESCO and its partners have a shared responsibility to lead the global discourse towards an equity- and justice-centred agenda. The volume highlights three areas in which UNESCO will continue to convene and lead a global commons for dialog and action particularly in areas on AI futures, policy and practice innovation, and experimentation.

As guardian of ethical, equitable human-centred AI in education.
As thought leader in reimagining curriculum and pedagogy
As a platform for engaging pluralistic and contested dialogues

AI, copyright and the classroom: what higher education needs to know — from timeshighereducation.com by Cayce Myers
As artificial intelligence reshapes teaching and research, one legal principle remains at the heart of our work: copyright. Understanding its implications isn’t just about compliance – it’s about protecting academic integrity, intellectual property and the future of knowledge creation. Cayce Myers explains

The School Year We Finally Notice “The Change” — from americanstogether.substack.com by Jason Palmer

Why It Matters
A decade from now, we won’t say “AI changed schools.” We’ll say: this was the year schools began to change what it means to be human, augmented by AI.

This transformation isn’t about efficiency alone. It’s about dignity, creativity, and discovery, and connecting education more directly to human flourishing. The industrial age gave us schools to produce cookie-cutter workers. The digital age gave us knowledge anywhere, anytime. The AI age—beginning now—gives us back what matters most: the chance for every learner to become infinitely capable.

This fall may look like any other—bells ringing, rows of desks—but beneath the surface, education has begun its greatest transformation since the one-room schoolhouse.

How should universities teach leadership now that teams include humans and autonomous AI agents? — from timeshighereducation.com by Alex Zarifis
Trust and leadership style are emerging as key aspects of teambuilding in the age of AI. Here are ways to integrate these considerations with technology in teaching

Transactional and transformational leaderships’ combined impact on AI and trust
Given the volatile times we live in, a leader may find themselves in a situation where they know how they will use AI, but they are not entirely clear on the goals and journey. In a teaching context, students can be given scenarios where they must lead a team, including autonomous AI agents, to achieve goals. They can then analyse the situations and decide what leadership styles to apply and how to build trust in their human team members. Educators can illustrate this decision-making process using a table (see above).

They may need to combine transactional leadership with transformational leadership, for example. Transactional leadership focuses on planning, communicating tasks clearly and an exchange of value. This works well with both humans and automated AI agents.

The Rise Of AI Agents: Teaching At Scale [Sivalingam]

On 09/05/2025, in 21st century, 24x7x365 access, adult learning, Artificial Intelligence/Agents/LLMs/and Related, bots, business, cloud-based computing / apps / other cloud-related, corporate / business world, corporate universities / corporate training, curriculum, digital learning, emerging technologies, engagement / engaging students, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, lifelong learning, personalized/customized learning, productivity / tips and tricks, professional development, reinvent, skills, staying relevant, tools, training / L&D, United States, vision/possibilities, workplace, by Daniel Christian

From Content To Capability: How AI Agents Are Redefining Workplace Learning — from forbes.com by Nelson Sivalingam

Real, capability-building learning requires three key elements: content, context and conversation.

The Rise Of AI Agents: Teaching At Scale
The generative AI revolution is often framed in terms of efficiency: faster content creation, automated processes and streamlined workflows. But in the world of L&D, its most transformative potential lies elsewhere: the ability to scale great teaching.

AI gives us the means to replicate the role of an effective teacher across an entire organization. Specifically, AI agents—purpose-built systems that understand, adapt and interact in meaningful, context-aware ways—can make this possible. These tools understand a learner’s role, skill level and goals, then tailor guidance to their specific challenges and adapt dynamically over time. They also reinforce learning continuously, nudging progress and supporting application in the flow of work.

More than simply sharing knowledge, an AI agent can help learners apply it and improve with every interaction. For example, a sales manager can use a learning agent to simulate tough customer scenarios, receive instant feedback based on company best practices and reinforce key techniques. A new hire in the product department could get guidance on the features and on how to communicate value clearly in a roadmap meeting.

In short, AI agents bring together the three essential elements of capability building, not in a one-size-fits-all curriculum but on demand and personalized for every learner. While, obviously, this technology shouldn’t replace human expertise, it can be an effective tool for removing bottlenecks and unlocking effective learning at scale.

Jane Hart’s “Top 100 Tools for Learning 2025” is now available

Google introduces Guided Learning [Zau] + other items re: AI in our learning ecosystems

On 08/09/2025, in 21st century, 24x7x365 access, adjunct faculty, adult learning, Apple, Artificial Intelligence/Agents/LLMs/and Related, bots, career development, cloud-based computing / apps / other cloud-related, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, education, education technology, emerging technologies, experimentation, faculty/staff, game-changing environment, Google, heutagogy, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, law schools, learning, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning spaces, liberal arts, lifelong learning, online tutoring, personalized/customized learning, platforms, productivity / tips and tricks, research, skills, student-related, teachers, teaching & learning, teaching online, tools, training / L&D, trends, United States, universities, user experience (UX), vendors, vision/possibilities, by Daniel Christian

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.
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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.

Universal AI Tutor Access
AI as Active Teacher
Personalized Learning Pathways
Interactive Multimodal Learning
Value-Centric Education in an AI-Abundant World

Several items re: the new Study Mode from OpenAI

On 07/30/2025, in 21st century, 24x7x365 access, adult learning, Artificial Intelligence/Agents/LLMs/and Related, bots, cloud-based computing / apps / other cloud-related, colleges, communities of practice, community colleges, corporate / business world, corporate universities / corporate training, digital learning, education, education technology, emerging technologies, experimentation, faculty/staff, future, future of higher education, game-changing environment, heutagogy, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, informal learning, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, liberal arts, library / librarians, online tutoring, Open AI, personalized/customized learning, platforms, productivity / tips and tricks, student-related, teachers, teaching & learning, technologies for your home, tools, training / L&D, United States, universities, user experience (UX), vendors, vision/possibilities, by Daniel Christian

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.

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.

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.

The type of functionality found in MyNextChapter.ai could work very well in a next-gen learning platform [Christian]

On 07/24/2025, in 21st century, 24x7x365 access, adult learning, Alternatives, apprenticeships, Artificial Intelligence/Agents/LLMs/and Related, bots, business, career development, change, cloud-based computing / apps / other cloud-related, colleges, communications, community colleges, corporate / business world, Daniel S. Christian, emerging technologies, experimentation, higher education, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, lifelong learning, passions, pathways, personalized/customized learning, platforms, professional development, reinvent, skills, social learning / networks, society, staying relevant, surviving, teachers, teaching & learning, teaching online, technologies for your home, tools, United States, universities, vendors, vision/possibilities, vocational / trades, by Daniel Christian

From DSC:
In looking at MyNextChapter.ai — THIS TYPE OF FUNCTIONALITY of an AI-based chatbot talking to you re: good fits for a future job — is the kind of thing that could work well in this type of vision/learning platform. The AI asks you relevant career-oriented questions, comes up with some potential job fits, and then gives you resources about how to gain those skills, who to talk with, organizations to join, next steps to get your foot in the door somewhere, etc.

The next gen learning platform would provide links to online-based courses, blogs, peoples’ names on LinkedIn, courses from L&D organizations or from institutions of higher education or from other entities/places to obtain those skills (similar to the ” Action Plan” below from MyNextChapter.ai).

A great example of a learning ecosystem!!! [Christian]

On 07/19/2025, in adult learning, career development, collaboration, communications, communities of practice, experimentation, heutagogy, ideas, instructional design, learning, learning ecosystem, Learning Experience Design, learning preferences, play, by Daniel Christian

From DSC:
Read through the article below. It’s an excellent example of a learning ecosystem, one that has been developed and practiced by Tiago Forte.

My 4-Stage System for Learning Anything New — from fortelabs.com by Tiago Forte

Stage 1: Immersion – Get Maximum Exposure
Stage 2: Building – Make Something Real
Stage 3: Structured Learning – Find Your Mentors
Stage 4: Connection – Build Real Relationships
The Secret Ingredient: Cultivating Play in Learning

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.

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.”
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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

On 06/23/2025, in 21st century, 24x7x365 access, adjunct faculty, adult learning, Artificial Intelligence/Agents/LLMs/and Related, bots, change, cloud-based computing / apps / other cloud-related, CMS/LMS, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, digital video, education, education technology, emerging technologies, engagement / engaging students, experimentation, face-to-face, faculty/staff, game-changing environment, Google, heutagogy, higher education, homeschooling/homeschoolers, 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, liberal arts, library / librarians, lifelong learning, memory, metacognition / metacognitive skills, multimedia, Natural Language Processing (NLP), new media literacies, online learning, online media, Open AI, personalized/customized learning, platforms, productivity / tips and tricks, professional development, student-related, teachers, teaching & learning, teaching online, technologies for your home, tools, traditional / tradition, training / L&D, trends, United States, universities, user experience (UX), vendors, vision/possibilities, writing, by Daniel Christian

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.
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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.

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

On 06/09/2025, in 21st century, 24x7x365 access, 3D, A/V -- audio/visual, active learning, adjunct faculty, adult learning, architecture, Augmented Reality (AR), bots, business, career development, change, colleges, communities of practice, community colleges, computer science, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, creativity, curriculum, data related items, design, digital learning, education technology, emerging technologies, engagement / engaging students, experimentation, faculty/staff, future, future of higher education, game-changing environment, generational differences, global / globalization, Google, health, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, K-12 related, law schools, leadership, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, legal technologies, legislatures / government / legal, library / librarians, lifelong learning, online learning, online media, online tutoring, pedagogy, personalized/customized learning, platforms, podcasting, policy, productivity / tips and tricks, professional development, skills, society, student-related, teachers, teaching & learning, teaching online, technologies for your home, tools, traditional / tradition, training / L&D, trends, United States, universities, vendors, vision/possibilities, visualizing information, workplace, XR - extended reality, by Daniel Christian

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.
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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.

Learning Ecosystems

Building a learning ecosystem that drives business results [Romanowski]

A great example of a learning ecosystem!!! [Christian]

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