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:
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:
These approaches do not eliminate AI. They place learning where AI cannot substitute:
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.
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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.
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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:
Then ask one follow-up question to check for understanding.
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:
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
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 — 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?
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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.
Also from Lucy Gray, see the following for some nice tips and resources:
This is the Future of High School
The Tennessee School Rewriting the Rules of High School — from xqsuperschool.org
At Elizabethton High School, students wanted more from their education. So they helped rebuild it—class by class, project by project. Their idea: give students real, meaningful work, and they’ll rise to the challenge.
A cold case became a Prime Video series. A robotics club became an international competitor. And an ordinary high school became something else entirely. Elizabethton is reinventing high school—and showing what’s possible for the rest of the country.
Watch the Elizabethton+XQ story
Ten years, one school, and a redesign still unfolding. It took courage to break with tradition—and that risk is paying off for an entire community.
“Teachers ban it. Employers demand it.”
Also relevant/see:
The Shifting Career Ladder — from nafez.substack.com by Nafez Dakkak
AI is changing how work works and quietly removing the pathways through which young people learn to become experts.
AI is reshaping how people build skills, enter professions, and move along the career ladder and through the labour market.
In this conversation, I sit down with Matt Sigelmen founder of LightCast and now the President of Burning Glass Institute. Matt has dedicated his career to understanding the labor market and helping society improve the connections within in it.
Matt and I explore why people and opportunities are often only “a few skills apart,” why entry-level work may be losing its traditional role as the first rung of expertise, and why schools, universities, and employers now need to rethink the pathways that turn potential into mastery.
Educators need to be deeply aligned with what these changes are, and they need to shift the AI discourse from “how” questions to “what” questions. What do we need to teach? What do we need to keep in the curriculum?
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) — 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.
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.
Stanford Online Launches Immersive Learning Studio — from campustechnology.com by Matt Jones
Key Takeaways
