Paying vendors for student results — from hechingerreport.org by Jill Barshay
The first evaluation of outcomes-based contracting found student achievement sometimes improved under this approach

Instead of paying vendors simply for delivering these tools, school districts are experimenting with a new approach to purchasing, called outcomes-based contracting, in which part of a vendor’s payment depends on whether students actually use the service and meet agreed-upon academic goals. The idea is to share risk between schools and vendors — and create incentives for both sides to pay closer attention to whether an intervention is working.

From DSC:
This could be tough to do. But it’s an interesting posting/idea/approach/strategy. Are the goals reached due to the tools/products/services of the vendors or are those products and services just one piece of the overall learning pie?

 
 

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 — 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

 

The 2031 Crisis in Higher Education: a stark scenario — from bryanalexander.org by Bryan Alexander — with commentary on a posting by Matthew F. Wilson, Ph.D.

Today’s post is about a scenario for higher ed’s future.  It’s not from me, but created by one Matthew F. Wilson, director of Research Translation and AI Strategy at Baylor’s Institute for Global Human Flourishing.  “The 2031 Crisis in Higher Education” is a dark one, imagining an accelerating decline for American colleges and universities.

One key assumption of this scenario is that most colleges and universities will be unable to redesign themselves for the changing time.

All of that said, it’s a fascinating and daunting scenario.  It’s an interesting vision of my post-peak higher ed world.

A graphic from Matthew Wilson:


From DSC:
From what I can tell and have read, the things in the above graphic are already happening — and have been happening for some time now.

Also, I don’t think traditional institutions of higher education have the culture(s) it takes to change. So that part about colleges and U’s not being able to redesign themselves for the changing times could easily turn out to be the case.

 

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:
.


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 — 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.

 

From DSC:
Below is an item on futures thinking. Don’t blow this off. This topic — and skill/strategy — is important not only to traditional institutions of higher education, but also to businesses and organizations of all sizes. In fact, even students can practice developing a list of potential scenarios and implement their plans of action if one of those scenarios occurs.


Chris Mayer’s posting on LinkedIn.com

 

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.

 

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?

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.

  1. Virtual Conferences at Scale — Lucy Gray — Actionable Innovations Events / GLOW
  2. Micro-Mentorship — Tami Brewster
  3. Networked, Values-Driven PD — Julie Meltzer — Institute for Humane Education
  4. AI-Personalized PD Pathways — Marcus Borders
  5. Share Stories with Voice — Bethany LaDue Nugent
  6. 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:

 

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.

 

Why recruiters can’t find workers and new grads can’t find jobs (it’s not AI) — from washingtonpost.com by Jon Marcus
Experts say a major labor shortage looms because of population shifts and a mismatch between new graduates’ skills and employers’ needs.

Recent college graduates complain they can’t find entry-level jobs because artificial intelligence is taking over.

Yet, tech recruiter Matt Walsh and other experts say the growth of AI and the struggle to find entry-level work mask a bigger problem: The United States is facing what’s projected to become the largest labor shortage in its history.

In sectors such as semiconductor production, the problem isn’t AI or too few jobs, said Walsh, CEO of the Phoenix-based search firm Blue Signal.

“It’s ridiculous,” he said. “There just aren’t enough people.”

Economists warn that the worsening labor problem, due in part to a skills shortage and population shifts, will be vast and reach beyond tech.

Among the trends that have been leading to this moment: a mismatch between the careers college graduates are pursuing and the jobs employers are struggling to fill. Far fewer students are majoring in health care fields than are needed to meet demand, for instance.

“We have pumped so many young people into business and finance” when what’s really in demand are graduates in other fields, Hetrick said. “It’s like a factory producing these workers like widgets, even though society is saying, ‘We really don’t need them.’ And the factory just keeps pumping them out.”

 
© 2025 | Daniel Christian