How to Design Around Cognitive Offloading — from drphilippahardman.substack.com by Dr Philippa Hardman
Three new studies shed light on when offloading to AI harms learning, when it helps — and how to design for the difference

A cluster of new studies — most published in the last few weeks in the International Journal of Educational Technology in Higher Education — lets us answer two questions with more precision than ever before:

  1. When does cognitive offloading actually happen?
  2. When does using AI improve cognition?

The answers in turn help us to start to design learning which intentionally uses AI to drive – rather than diminish – learning.
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15 Best Instructional Design Conferences To Attend — from elearningindustry.com by Christopher Pappas

Overview: Looking for the best Instructional Design conference in 2026? Explore 15 leading learning, L&D, eLearning, and training conferences worldwide to build skills, discover learning technology, and expand your professional network.

 

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

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

 

Digital Accessibility Lawsuits in 2026: Five Trends Companies Should Know — from blog.usablenet.com

Here are five findings companies should understand, along with practical steps for reducing risk.

1. Digital accessibility lawsuits are on pace to reach 6,000
2. Where a company sells matters more than where it is headquartered
3. E-commerce remains the primary target
…and more

 

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 China’s Calligraphy Lessons Can Teach Us About AI — from linkedin.com by Rebecca Winthrop

He recalled visiting a primary school classroom in China several years ago where students were practicing calligraphy—the centuries-old art of writing Chinese characters with brush and ink. While the scene appeared entirely traditional, there was something innovative happening beneath the surface. Embedded in students’ desks was an AI system capable of providing immediate feedback on their brushwork, noting misplaced strokes and suggesting corrections.

The image is striking. Students were learning in much the same way generations before them had learned—brush in hand, immersed in a deeply human and cultural practice. Yet AI was quietly enhancing the experience by providing immediate, personalized feedback that would have been difficult for any teacher to provide to her whole class.

That example captures something important for me. The most promising uses of AI may not be the applications that place technology front and center, but those that support learners to do what they have always done: connect with educators, practice with concentration, and learn and grow.


AI Can Build Your Course, but Can it Design the Learning? — from drphilippahardman.substack.com by Dr. Philippa Hardman
Aka, the current state of AI’s instructional design ability & what it means for L&D

So these models have learned design artefacts in extraordinary volume and design method barely at all. They know what e-learning looks like. They have very little access to why any of it looks that way and whether it actually works or not.

That produces a completely consistent behaviour: ask an LLM for an e-learning module and it generates the statistical centre of every e-learning module it has ever seen. What AI produces isn’t the output of a design process. It’s the output of a sampling process — the statistical centre of every e-learning module it has ever seen.

So the honest conclusion isn’t that AI can design learning; it’s that AI executes design well when someone who already knows what to ask for is doing the asking and the checking.

This finding gives us a clearer division of labour than we’ve had before and with it a clearer picture of what the AI-enhanced workflow might look like:


The Pedagogy of Trading Places: Lessons from an Unexpected Role Reversal with AI — from facultyfocus.com by Sherrie Myers Bartell, PhD

These disruptions matter. They remind us that teaching is not a static identity but a dynamic posture. They show us that our pedagogical selves are not fixed; they are responsive to context, energy, and attention. They reveal that the qualities we value most in our teaching—curiosity, metaphor, play, and expansiveness—are not automatic. They require care and cultivation.

The AI didn’t “teach” me in the traditional sense. But it did something pedagogically adjacent: it surprised me back into myself.

 

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

The following strategies focus on how instructional designers can design for accessibility by embedding or enabling AI-supported tools within learning experiences. These approaches move beyond access to content and begin to support access to understanding, expression, and participation.

Personalized Clarification Through AI Copilots
Learners often need additional explanation, but may hesitate to ask questions in live sessions or require more individualized support.

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

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

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

Explain the following concept in a clear, simple way:

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

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


Jeff’s posting on LinkedIn.


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

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


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

In this episode, you’ll discover:

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

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

As Rebecca told me:

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

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

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

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

 

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

Table of contents

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


Also from elearningindustry.com, see:

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

Table of contents

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

 

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

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

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

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

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

 

Check Your Mic Before You Wreck Your Project — from learningguild.com by Kendal Rasnake

While a lot of our narration may be produced by AI nowadays, there are times when you need to record audio, such as when you need someone in-house to do a voiceover, or you are recording an interview, job shadow video, demonstration video, etc. Now, the responsibility of recording high-quality audio falls on you.

Well, all you have to do is grab a mic and point, right? Wrong!

The last thing you need is to record the CEO and have him/her sound horrible or look ridiculous because they are holding a fuzzy mic on a long wire up to their mouth. Instead, just learn a little about mics and you can purchase and/or choose the right one.

All Mics Are Not Built Equally
I had someone who was having audio trouble tell me that they used a “Brand Name” mic before and it sounded good, so maybe they would go back to using a “Brand Name” mic. As you can imagine, choosing a mic for a certain purpose based on the brand name is equivalent to choosing a Chevy mini-hybrid car to tow an RV because your truck used to tow the RV well and it was a Chevy. Brands make different types of microphones and understanding how mics are built can help you to choose the right one, no matter the brand.

 

If AI Eats the Entry-Level Job, Where Do Young People Learn to Work? (Ryan Craig, Achieve Partners) — from humanistxyz.substack.com by Allison Dulin Salisbury; via Ryan Craig
“The public should not be subsidizing colleges whose students lack relevant, paid, in-field work experience.”

That is the trap at the center of this conversation: everyone wants to hire someone with three years of experience, and almost no one wants to provide those three years.

And Ryan’s policy prescription is unusually concrete: pay employers to hire and train apprentices, following the countries that have scaled apprenticeship far faster than the U.S.; require colleges receiving federal student aid to provide relevant, paid, in-field work experience; and build a market of intermediaries that can make the whole thing operational.

Ryan’s view is that higher education remains critically important. But college without meaningful work experience may become a much worse bet, especially for students who cannot afford to guess wrong.

 

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:


 
 


Rethinking Learning Design in Elementary Schools — from edcircuit.com
Why K–5 leaders must redesign—not just adopt—technology to restore attention, deepen thinking, and align AI with how children actually learn

Rethinking learning design in elementary schools is critical as screen time and AI reshape attention, thinking, and student engagement.

Designing for Thinking, Not Just Doing
At its core, learning design must shift from task completion to thinking development.

This requires creating environments where students:

  • Spend time processing ideas
  • Work through confusion without immediate answers
  • Build persistence through challenge

It also requires clarity around the role of technology.

Technology should:

  • Extend thinking
  • Provide meaningful feedback
  • Support exploration

It should not:

  • Replace effort
  • Short-circuit reasoning
  • Eliminate productive struggle

The goal is not to reduce technology use.

It is to ensure that students remain the ones doing the thinking.


Should We Integrate AI into Our Teaching?: Evidence-Based Guidelines for Deciding When AI Belongs — from Faculty Focus by Norman Eng, EdD

Four Questions for Deciding Whether to Use AI

Question 1: Will this AI tool help students use, recall, and demonstrate understanding of core disciplinary content?
Question 2: Will this AI tool require students to apply their learning to a new context?
Question 3: Will this AI tool support—not replace—independent, evidence-based reasoning?
Question 4: Will this AI integration preserve meaningful human interaction?


 

Christian: Could this be a part of our future learning ecosystems?


From DSC:
Could this be a part of our future learning ecosystems? Education as a personalized content feed.


Coursera wants users to learn through shorter, faster content  — from digitaltrends.com by Moinak Pal
Coursera wants online learning to feel more like TikTok
.

Online learning platform Coursera is taking a page straight out of TikTok’s playbook. The company has launched a new AI-powered feed designed to serve short-form educational content in a scrollable, personalized format, signaling a major shift in how digital learning platforms may try to keep users engaged.

The feature introduces bite-sized video lessons, clips, and explainers curated through artificial intelligence based on a user’s interests, learning habits, career goals, and previous course activity. Instead of committing to hour-long lectures or full certification programs upfront, users can now discover short educational snippets designed to make learning feel more casual, accessible, and addictive.

Users scroll through a feed of short educational videos and AI-curated learning moments covering topics ranging from coding and business to AI, productivity, data science, and personal development.

 
© 2025 | Daniel Christian