instructional design

How to Design Around Cognitive Offloading [Hardman]

On 08/10/2026, in corporate universities / corporate training, emerging technologies, faculty/staff, instructional design, learning, Learning Experience Design, learning theories, productivity / tips and tricks, professional development, research, teachers, teaching & learning, training / L&D, by Daniel Christian

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:

When does cognitive offloading actually happen?
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.
.

15 Best Instructional Design Conferences To Attend [Pappas]

On 08/10/2026, in corporate universities / corporate training, elearning, emerging technologies, instructional design, intelligent systems, intelligent tutoring, learning, learning ecosystem, Learning Experience Design, productivity / tips and tricks, professional development, training / L&D, by Daniel Christian

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.

What Nobody Warns You About Teaching College for the First Time [Morales]

On 08/10/2026, in adjunct faculty, colleges, community colleges, education, faculty/staff, higher education, ideas, instructional design, K-12 related, learning ecosystem, Learning Experience Design, teachers, teaching & learning, United States, universities, vendors, by Daniel Christian

What Nobody Warns You About Teaching College for the First Time — from facultyfocus.com by Christopher Morales; this article is behind a firewall

What became clear throughout these conversations was that secondary and postsecondary education often prioritize very different instructional skill sets.

In K–12 education, teachers frequently receive formal preparation in:

classroom management,
scaffolding,
differentiation,
assessment design,
engagement strategies,
and developmental learning theory.

In higher education, disciplinary expertise is often treated as the primary qualification for teaching.

Yet many instructors pointed out that expertise alone does not automatically translate into effective instruction.

Also from Faculty Focus, see:

The Syllabus and the Scar Tissue: What Leadership Preparation Programs Leave Out and Why It Matters — from facultyfocus.com Andy Szeto, EdD; this article is also behind a firewall

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 / globalization, 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

Why AI Is Changing What It Means to Be Intelligent [Elliott]

On 07/31/2026, in adjunct faculty, Artificial Intelligence/Agents/LLMs/and Related, colleges, community colleges, education technology, experimentation, faculty/staff, higher education, human-computer interaction (HCI), instructional design, intelligent systems, learning ecosystem, Learning Experience Design, teaching & learning, United States, universities, by Daniel Christian

Why AI Is Changing What It Means to Be Intelligent — from facultyfocus.com by Lydia Elliott, EdD; article may be behind a paywall

Practical adjustments may include:

oral explanations of written work
case-based or scenario-based exercises
reflective reasoning assignments
feedback conversations
requiring students to justify decisions

These approaches do not eliminate AI. They place learning where AI cannot substitute: interpretation, reasoning, and responsibility.

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’s the Story Your Syllabus Tells?: Setting the Stage for Learning — from facultyfocus.com by Dr. Daniel Andrés Rivera Rosado

But as I was reading Everyday Christian Teaching by Dr. David Smith, in the chapter titled Speaking, Hearing, Hospitality, in just the first paragraph he writes: “Teachers do not simply list course content for learners. They sequence it in ways that imply a story about what fits together and where it is headed.” (2025, p.73). Automatically I asked myself, what is the story my syllabus is telling students? To be completely honest, is it even telling a story at all?

“Is your syllabus helping your students at all?”

From DSC:
To that last sentence, I might add the words engaging, raising curiosity or wonder, or is it interesting to your students at all? Is there a “hook” that gets them interested? It might be a central question or two — and/or use some beneficial and relevant graphics. I’ve heard faculty use digital/interactive syllabi as well to engage their students.

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.

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

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

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

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

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

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

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

Explain the following concept in a clear, simple way:

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

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

Jeff’s posting on LinkedIn.

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

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

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

In this episode, you’ll discover:

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

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

As Rebecca told me:

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

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

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

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

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

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

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

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

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

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

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

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

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

Flipped Classrooms and Academic Achievement — from learningscientists.org by Megan Sumeracki

There are actually many, many ways to design a flipped classroom, and it has been fascinating to learn about the ways my colleague typically structures her hybrid, flipped-classroom courses. As a result, we’ve been able to engage in really interesting conversations about the best approach for this particular course, and why. As a result of some of these discussions, I came across a few recent meta-analyses related to the effects of flipped classrooms, the results of which I thought were worth sharing here (1, 2, 3).

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

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

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

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

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

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

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

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

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

Table of contents

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

Also from elearningindustry.com, see:

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

Table of contents

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

Learning Ecosystems

How to Design Around Cognitive Offloading [Hardman]

15 Best Instructional Design Conferences To Attend [Pappas]

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

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

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