adult learning

New tests show that AI can design like an expert Instructional Designer: so what next? [Hardman]

On 10/16/2026, in 21st century, 24x7x365 access, adult learning, Artificial Intelligence/Agents/LLMs/and Related, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, education, education technology, emerging technologies, faculty/staff, future, future of higher education, game-changing environment, generational differences, Google, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, IT in HE, learning, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, Open AI, tools, United States, universities, vendors, vision/possibilities, workplace, by Daniel Christian

Here is Phillipa’s posting on LinkedIn.

Anthropic released a law student plugin. It’s designed to act as a tutor, but it will brief cases, build outlines, predict exam questions based on sample exams, and many other skills.
I’ll show you how to install it in the comments. You should expect your students are using this. You should probably use it for your footnotes.

— Paul Weitzel (@IThinkIAgree) October 13, 2026

Social Learning in a Skills-Based Economy [Hall]

On 10/13/2026, in adult learning, career development, change, communications, communities of practice, corporate / business world, corporate universities / corporate training, Emotion, engagement / engaging students, skills, social learning / networks, training / L&D, workplace, by Daniel Christian

Social Learning in a Skills-Based Economy — from learningguild.com by George Hall

In a skills-based economy, social learning should not be understood merely as interaction around content. It should be understood as part of the learning architecture itself: the social and emotional structure that helps people ask questions, test ideas, practice judgment, receive feedback, and stay open when learning feels personally risky.

That distinction matters.

In a defensive culture, social learning creates the conditions in which people can stay engaged with difficult ideas long enough to learn from them.

People often need other people to help them think:

They need to hear others reason their way through complexity
They need to see peers ask questions they were afraid to ask
They need to practice disagreement without rupture
They need to discover that uncertainty is shared
They need to see that changing one’s thinking does not have to mean losing face

This is not soft. Far from it.

It is foundational.

Online Course Video Statistics — from markstudios.com by Mark Santos

“Every figure on this page links to the organization that produced it, and each was re-checked against that source before publishing. How many people take online courses, how big the platforms are, how long course videos actually hold attention, how many learners finish, what the money looks like, and which popular online course statistics do not survive being traced to their origin.”
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The AI Tools that L&D Teams Are Building (Rather than Buying) — from drphilippahardman.substack.com by Dr. Philippa Hardman
Aka, how build skills are changing how L&D thinks & works

More and more of my advisory work is no longer about helping organisations choose a vendor; it’s about helping their teams build their own AI tools, and build them well. Over the last couple of years I’ve watched several hundred L&D practitioners do it, and in this week’s post I share what they built, why, and what it tells us about what L&D actually needs from AI.

A Tool of One’s Own
So, what do these tools look like in practice? I did some analysis and the tools that L&D teams are building first fall into three categories:

1. Tools that support the work before and after the course
2. Tools that make the learning experience more dynamic
3. Tools that do L&D tasks to the team’s own methods, processes and standards

The Checklist That Didn’t Exist: A Field Guide to Cutting Extraneous Load [Mervine Kiser]

On 09/14/2026, in adult learning, communities of practice, corporate / business world, corporate universities / corporate training, ideas, instructional design, learning, Learning Experience Design, learning theories, memory, productivity / tips and tricks, training / L&D, by Daniel Christian

The Checklist That Didn’t Exist: A Field Guide to Cutting Extraneous Load — from learningguild.com by Cally Mervine Kiser

If the content is fine, what else could be getting in the way?

The answer, it turns out, has been sitting in educational psychology research for decades. Working memory is finite. When learners engage with training, they are managing three competing cognitive demands simultaneously:

The complexity of the subject matter
The effortful processing that builds understanding
The mental effort generated by how the content is presented, independent of the content itself

That third one is called extraneous cognitive load, and it is the one we almost never explicitly design against. We design for accuracy. We design for alignment. We design for engagement, or at least what we hope will feel like engagement. We almost never sit down and ask, “How much unnecessary mental effort is this design generating, and how do we reduce it?”

When Learning Feels Like a Vulnerability [Hall]

On 09/14/2026, in adult learning, business, career development, change, corporate / business world, corporate universities / corporate training, Emotion, ideas, instructional design, learning, learning ecosystem, Learning Experience Design, training / L&D, vendors, by Daniel Christian

When Learning Feels Like a Vulnerability — from learningguild.com by George Hall

Why do some adult learners interpret training as a judgment about their competence, status, or identity?

Learning and development professionals often focus on content, platforms, courses, tools, and performance support. Those matter. But they are not enough. Learning is never just cognitive. It is also emotional and social.

A new skill can feel like evidence that old competence is no longer enough. Feedback can feel like judgment. A new model can feel like criticism of past practice. A request to change can feel like a loss of face.

It means learning can feel personally exposing. Adult learners do not only receive training. They interpret what needing training seems to say about their competence, status, identity, and future value. That interpretation can either open learning or shut it down.

“It’s critical to find ways to make an institution’s own continuing & professional education programming accessible to its students.” [Ahluwalia]

On 08/31/2026, in adult learning, Alternatives, Canada, career development, learning ecosystem, lifelong learning, universities, by Daniel Christian

“Using AI to create the practice opportunities online students need” [Miller Perkins] + other items re: AI in our learning ecosystems

On 08/19/2026, in 21st century, 24x7x365 access, adjunct faculty, adult learning, Artificial Intelligence/Agents/LLMs/and Related, assessment, business, career development, colleges, communications, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, education, education technology, emerging technologies, Emotion, engineering, experimentation, faculty/staff, game-changing environment, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, leadership, learning, learning agents, learning ecosystem, Learning Experience Design, learning spaces, liberal arts, mathematics, online learning, personalized/customized learning, productivity / tips and tricks, professional development, student-related, teachers, teaching & learning, technologies for your home, tools, training / L&D, UK, United States, universities, vendors, workplace, youth, by Daniel Christian

Using AI to create the practice opportunities online students need— from timeshighereducation.com by Kathy Miller Perkins
For disciplines that depend on interpersonal skills such as communication, leadership, negotiation and mediation, AI can provide elusive experiential learning, particularly in asynchronous environments

What if AI’s greatest educational value lies not in generating answers but in generating experiences?

The result surprised me. Students did not simply interact with the AI, they meaningfully engaged with it. Many reported that the experience felt valuable precisely because the simulated conversation partner pushed back. Unlike classmates who sometimes hesitate to challenge one another, the AI consistently maintained its position. Students had to work harder, listen more carefully and apply the communication strategies they had spent weeks learning. And, importantly, they practised.

Here’s how to show students what responsible AI use looks like — from timeshighereducation.com by Andrew Firr and Alex Fenton
Well-designed assessments can highlight generative AI’s limitations, where it can provide support and what responsible practice looks like. Andrew Firr and Alex Fenton offer strategies

We have been exploring ways to offer this in our Level 7 module for MSc engineering management students, many of whom come from the Global South. Assessment is built around a practical design problem: students examine how a real campus process operates, where delays occur, evidence they observe and how a feasible redesign might improve the system – in a 3,000-word essay.

They can use AI for planning and providing clarity, but not for generating the evidence on which the analysis rests. Invented observations, measurements, screenshots or unverifiable citations are prohibited. The assessment design reinforces this through a case study, diagram, fact-checking exercise and a short AI use statement.

Requiring an AI use statement encourages students to reflect on their processes. We ask which tool they used, how they used it, how they checked the output and which parts of the work depended on their own evidence and judgement. It reminds them that evidence must be theirs and that citations must be manually verified.

Slow math: Kids may learn more when AI makes them review mistakes — from hechingerreport.org by Jill Barshay and Kristin Fasiang
A randomized experiment involved more than 6,000 Tennessee middle school students learning fractions

In an experiment involving more than 6,000 middle schoolers in Tennessee, students learned slightly more math when an AI tutor walked them through their mistakes and then required them to demonstrate the same skill correctly three times in a row before moving on.
…
The winning combination wasn’t the addition of AI tutoring alone, but AI tutoring plus repetition, with the idea that students needed to stick with the skill to demonstrate some level of mastery. The students who practiced math with this AI-enhanced “mastery learning” approach scored about 3 percentage points higher than students receiving conventional computerized instruction. The advantage was small.

I Built a Team of AI Bots That Write Feedback Better than Me. Here’s How. — from drphilippahardman.substack.com by Dr Philippa Hardman
Aka, how to make learners love AI-assisted feedback, rather than loathe it.

This wasn’t hidden from the cohort. For reasons I’ll come to below, I always tell my cohorts at the very start that an AI assistant will be helping me draft their feedback. The aim wasn’t to remove me from the process, but to find out whether AI could help me to deliver feedback at a volume and quality that I simply couldn’t maintain without AI.

Spoiler: the experiment worked — but not for the reason I expected. In this post, I’ll share exactly what I built, tell you how to build a version for your course and reveal the three conditions that decide whether learners trust AI-assisted feedback or quietly stop reading it.

TL;DR: the spec for my feedback assistant is long not because the model needs persuading, but because it’s where my judgement lives. Every rule in it is a decision AI would otherwise make by itself, with limited expertise. A spec doesn’t make the model smarter — it makes expertise and judgement legible enough for the model to follow.

Of the five stages of AI grief, some managers are stuck in denial— from timeshighereducation.com by Shadi Mohamed
Acceptance is not surrender. It is about getting beyond a policing obsession and rethinking what assessment aims to measure, says Shadi Mohamed

In that moment of institutional blindness, it struck me: universities are not merely struggling with a technological adoption curve. They are grieving the demise of the modern university’s economic and institutional logic.

To understand the scale of this threat posed by AI, consider what the internet did to journalism. Newspapers thrived by bundling together classified advertising with quick news hits, sports scores and opinion columns, using that reliable revenue to fund the expensive social necessity of investigative reporting. The rise of internet advertising did not kill journalism outright but it shattered the bundle, leaving the expensive core product without its historical financial engine.

Universities operate on a similar logic, bundling content delivery, assessment, credentialling, research and professional formation. But generative AI is now commodifying the most visible parts of that package. When AI can deliver personalised explanations instantly and generate the essays and reports we use to measure student capability, the traditional degree loses its role in the labour market as a proxy for understanding. If the bundle breaks, the economic model that funds our deeper purposes is in peril.

Will this new company be the largest company on the Internet by 2030? [Christian]

On 08/01/2026, in 21st century, 24x7x365 access, adult learning, Artificial Intelligence/Agents/LLMs/and Related, Bias | Diversity Equity & Inclusion (DE&I), career development, cloud-based computing / apps / other cloud-related, communities of practice, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, cost of getting a degree, credentialing, curriculum, Daniel S. Christian, digital learning, disruption, education, education technology, elearning, emerging technologies, engagement / engaging students, future, future of higher education, game-changing environment, generational differences, global, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, informal learning, innovation, instructional design, intelligent systems, intelligent tutoring, internet, K-12 related, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning preferences, learning spaces, lifelong learning, love of learning, more voice more choice more control, motivation, online learning, online media, online tutoring, pathways, personalized/customized learning, platforms, productivity / tips and tricks, professional development, reinvent, society, staying relevant, student-related, teachers, teaching & learning, training / L&D, United States, vision/possibilities, web-based collaboration, youth, by Daniel Christian

From DSC:
The vision that I’ve been tracking for well over a decade begins with this graphic:
.

Could LearnVector be this next-generation company/platform? Perhaps. Time will tell.

Per Matt Tower via The EdSheet Vol. 38 dated 7/31/26:

Coursera bets $100M on its own co-founder: Andrew Ng’s new venture LearnVector lands one of the largest single checks in edtech this year — from Coursera, the company he founded 14 years ago.
.

LearnVector.ai

How Explainer Video Production Turns Ideas Into Clear Stories [Williamson]

On 07/31/2026, in adult learning, business, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, digital storytelling, digital video, ideas, instructional design, learning, Learning Experience Design, productivity / tips and tricks, training / L&D, by Daniel Christian

How Explainer Video Production Turns Ideas Into Clear Stories — from bitrebels.com by Lauren Williamson

Ideas rarely arrive in a neat order. They show up as notes, claims, diagrams, feature lists, and customer questions. Explainer video production turns that raw material into a story people can process quickly. It clarifies the problem, frames the change, and shows why the answer matters. When the script, visuals, voice, and pacing work together, viewers spend less energy decoding the message and more attention on absorbing it.

Explainer video production works because it gives ideas a usable order. It turns scattered information into a story with purpose, pace, and visual evidence. The strongest results come from careful message decisions before animation starts. When script, design, voice, and timing support one central point, viewers can follow with less effort. That clarity helps organizations teach, persuade, and make it easier to remember.

What Teaching Faculty Want From Professional Development (That’s Not Just Workshops) [Dodson]

On 07/15/2026, in adult learning, K-12 related, leadership, learning ecosystem, Learning Experience Design, productivity / tips and tricks, professional development, strategy, teachers, United States, by Daniel Christian

What Teaching Faculty Want From Professional Development (That’s Not Just Workshops) — from rdene915.com by guest author Tessa Dodson

The journey toward a more meaningful, empowering, and effective model of professional development for teachers begins with dialogue. By asking educators what they need to grow and trusting their answers, school leaders can take the first crucial step toward building a culture where both teachers and students can thrive.

What Teachers Really Want From Professional Development
The most effective frameworks for teachers’ professional development are built on a foundation of empowerment. This involves a profound shift in mindset, from viewing teachers as recipients of training to recognizing them as professionals who can and should guide their own learning. When school structures are designed to foster teacher autonomy, the impact on professional growth is significant.

A 2023 study found that teachers’ autonomous behavior predicted professional development at work. The study identified key structural factors, such as “empowering teachers” and the “decentralization of responsibilities,” as crucial to creating an environment in which this autonomy could flourish. By trusting teachers to take ownership of their professional growth, leaders can unlock their intrinsic teacher motivation and capacity for innovation.

Reconnecting Professional Learning — Reflections from [Lucy Gray’s] ISTE Panel

On 07/14/2026, in adult learning, Apple, Artificial Intelligence/Agents/LLMs/and Related, collaboration, communities of practice, education, education technology, ideas, instructional design, leadership, learning, learning ecosystem, Learning Experience Design, pathways, professional development, reinvent, relationships, teachers, by Daniel Christian

Reconnecting Professional Learning — from elemenous.substack.com by Lucy Gray
Reflections from My Wednesday ISTE Panel

At ISTE this year, I facilitated a Wednesday morning panel on professional learning. The session I organized was titled, The Future of Professional Learning: Connecting Educators Across Borders. I was joined by fellow Apple Distinguished Educators Tami Brewster, Bethany LaDue Nugent, Marcus Borders, Jason Krug and global educator Julie Meltzer. Our focus: How do we move professional development away from isolated, one-time experiences and toward something more connected, meaningful, and human?
…
The panel was grounded in a few simple but powerful ideas: professional learning should nurture, guide, and empower. It should be relevant, contextual, reflective, and sustained. It should recognize educators as capable professionals, not as people who are broken and need to be fixed. Too often, professional development is still designed around deficit thinking. Too often, teachers’ needs are not the starting point, and sessions become dry, one-directional experiences where information is delivered at them rather than built through conversation and collaboration, with little choice, little personalization, and little connection to the realities of their classrooms. Our panel served as a call to action to re-think professional learning.

We explored six different approaches to professional learning, and while each model was distinct, a clear through line emerged: relationships matter most.

Virtual Conferences at Scale — Lucy Gray — Actionable Innovations Events / GLOW
Micro-Mentorship — Tami Brewster
Networked, Values-Driven PD — Julie Meltzer — Institute for Humane Education
AI-Personalized PD Pathways — Marcus Borders
Share Stories with Voice — Bethany LaDue Nugent
Speak Your Crazy — Jason Krug

Our Padlet – Share resources and introduce yourself
Our Slides – Meet our panelists and learn about our work
Our Google NotebookLM – This notebook contains dozens of resources related to research and best practices in educator professional learning
The Connected PD App – This is an app I’m building in Base 44 to help people plan great professional learning experiences

Also from Lucy Gray, see the following for some nice tips and resources:

How I Spent My Time at #ISTElive26: Learning, Connecting, and Looking for What’s Next
A few reflections on AI, global learning, libraries, coaching, creativity, and the conversations that made ISTE meaningful.

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

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

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

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

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

Also relevant/see:

Majority of law school faculty self-censor, think legal education headed in wrong direction, new survey finds [Hill]

On 06/10/2026, in adult learning, faculty/staff, higher education, law schools, learning ecosystem, teaching & learning, United States, universities, by Daniel Christian

Majority of law school faculty self-censor, think legal education headed in wrong direction, new survey finds — from abajournal.com by Julianne Hill

A majority of law school faculty said legal education is headed in the wrong direction and feel unable to freely express their opinions for fear of how students, colleagues or administrators would respond.

That’s according to the finding of a new survey of nearly 2,000 law school faculty at 192 ABA-accredited law schools by the Foundation for Individual Rights and Expression, a nonprofit organization that defends free speech.

Released Tuesday, 57% identified as liberal leaning, 18% identified as conservative leaning, 16% identified as moderate, and 10% identified as something else, according to the survey.

Learning Ecosystems

The Checklist That Didn’t Exist: A Field Guide to Cutting Extraneous Load [Mervine Kiser]

When Learning Feels Like a Vulnerability [Hall]

“It’s critical to find ways to make an institution’s own continuing & professional education programming accessible to its students.” [Ahluwalia]

How Explainer Video Production Turns Ideas Into Clear Stories [Williamson]

Majority of law school faculty self-censor, think legal education headed in wrong direction, new survey finds [Hill]

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