So, You Want to Open a Microschool — from educationnext.org by Kerry McDonald
For aspiring founders who have the will but lack the way to launch their schools, startup partners are there to help

In recent years, microschools—small, highly individualized, flexible learning models—have become a popular education option, now serving at least 750,000 U.S. schoolchildren. More than half of microschools nationwide operate as homeschooling centers, while 30 percent function as private schools, 5 percent are public charters, and the rest fit into unique, often overlapping categories, according to a 2025 sector analysis by the National Microschooling Center. While many founders achieve success on their own, joining an accelerator or network can offer the business coaching and community connection that make the inevitable challenges of entrepreneurship more manageable. Van Camp decided to join KaiPod Catalyst, a microschool accelerator program from KaiPod Learning.

I feature six of these microschool accelerators and networks in my new book, Joyful Learning: How to Find Freedom, Happiness, and Success Beyond Conventional Schooling. Some of them have been around for years, but they have attracted rising interest since 2020 as more parents and teachers consider starting schools. These programs vary widely in the startup services and supports they offer, but they share a commitment to building relationships among founders and facilitating the ongoing success of today’s creative schooling options.


MICROSCHOOL REPORT
A small shift with an outsized impact in K-12 education— from gettingsmart.com by Getting Smart

High quality, personalized instruction in an intimate setting that focuses on the whole child is growing in popularity—and it looks very different from traditional models both past and present. What may seem like a throwback to the pioneers’ one-room schoolhouse actually speaks volumes about what we as a society have outgrown.

What began as a response to a global crisis has led to a watershed moment.

Yet to categorize microschools simply as “pandemic pods” or private schools with a low headcount largely misses the mark. They are perhaps best described as intentionally-designed small learning environments that are bucking two centuries of inertia and industrial-era constraints.

Microschools are providing educators with an entrepreneurial opportunity that was unthinkable just a couple of decades ago, in tandem with the ability to deliver high student and family satisfaction. And they’re doing it by prioritizing learner agency, personalization, and mastery over compliance and standardization.

However, for microschools to truly scale and impact equitable outcomes, the K-12 sector must address critical policy challenges related to access, accountability and regulatory restrictions.

The following key findings from deeply researched case studies and strategic guides published by the Getting Smart team are intended to provide a comprehensive overview on the microschool movement. Each section offers an opportunity to dive deeper into resources on specific, timely topics.


Speaking of education reform and alternatives, also see:

Driving systems transformation for 21st-century educators, learners, and workers. — from jff.org

Today’s education ecosystem must meet the needs of today’s learners. This means learner-centered outcomes, pathways between education and careers, and policies and practices that support both degree and non-degree programs.

Jobs for the Future’s Education practice works to support systems change in the education ecosystem, influence policies that promote diverse pathways, and identify and apply data-informed, learner-centered solutions.

 

People Watched 700 Million Hours of YouTube Podcasts on TV in October — from bloomberg.com (this article is behind a paywall)

  • That’s up from 400 million hours a year ago as podcasts become the new late-night TV.
  • YouTube Wins Over TV Audience With Video Podcasts.
  • YouTube is dominating in the living room.
 

Coursera to Combine with Udemy to Empower the Global Workforce with Skills for the AI Era — from investor.coursera.com

Highly Complementary Capabilities Will Create a Leading Technology Platform, Redefining Skills Discovery, Development, and Mastery for Learners and Organizations at Scale

Unites Udemy’s Dynamic AI-Powered Skills Development Marketplace with World-Class University and Industry Brands Under the Coursera Ecosystem, Expanding Value, Impact, and Choice Globally

Strengthens Combined Company’s Financial Profile with Pro Forma Annual Revenue of More Than $1.5 Billion and Anticipated Annual Run-Rate Cost Synergies of $115 Million Within 24 Months

“We’re at a pivotal moment in which AI is rapidly redefining the skills required for every job across every industry. Organizations and individuals around the world need a platform that is as agile as the new and emerging skills learners must master,” said Greg Hart, CEO of Coursera. “By combining the highly complementary strengths of Coursera and Udemy, we will be in an even stronger position to address the global talent transformation opportunity, unlock a faster pace of innovation, and deliver valuable experiences and outcomes for our learners and customers. Together, we will ensure our millions of learners, thousands of enterprise, university, and government customers, and expert instructors have a platform to keep pace with technology acceleration.”

 

AI working competency is now a graduation requirement at Purdue [Pacton] + other items re: AI in our learning ecosystems


AI Has Landed in Education: Now What? — from learningfuturesdigest.substack.com by Dr. Philippa Hardman

Here’s what’s shaped the AI-education landscape in the last month:

  • The AI Speed Trap is [still] here: AI adoption in L&D is basically won (87%)—but it’s being used to ship faster, not learn better (84% prioritising speed), scaling “more of the same” at pace.
  • AI tutors risk a “pedagogy of passivity”: emerging evidence suggests tutoring bots can reduce cognitive friction and pull learners down the ICAP spectrum—away from interactive/constructive learning toward efficient consumption.
  • Singapore + India are building what the West lacks: they’re treating AI as national learning infrastructure—for resilience (Singapore) and access + language inclusion (India)—while Western systems remain fragmented and reactive.
  • Agentic AI is the next pivot: early signs show a shift from AI as a content engine to AI as a learning partner—with UConn using agents to remove barriers so learners can participate more fully in shared learning.
  • Moodle’s AI stance sends two big signals: the traditional learning ecosystem in fragmenting, and the concept of “user sovereignty” over by AI is emerging.

Four strategies for implementing custom AIs that help students learn, not outsource — from educational-innovation.sydney.edu.au by Kria Coleman, Matthew Clemson, Laura Crocco and Samantha Clarke; via Derek Bruff

For Cogniti to be taken seriously, it needs to be woven into the structure of your unit and its delivery, both in class and on Canvas, rather than left on the side. This article shares practical strategies for implementing Cogniti in your teaching so that students:

  • understand the context and purpose of the agent,
  • know how to interact with it effectively,
  • perceive its value as a learning tool over any other available AI chatbots, and
  • engage in reflection and feedback.

In this post, we discuss how to introduce and integrate Cogniti agents into the learning environment so students understand their context, interact effectively, and see their value as customised learning companions.

In this post, we share four strategies to help introduce and integrate Cogniti in your teaching so that students understand their context, interact effectively, and see their value as customised learning companions.


Collection: Teaching with Custom AI Chatbots — from teaching.virginia.edu; via Derek Bruff
The default behaviors of popular AI chatbots don’t always align with our teaching goals. This collection explores approaches to designing AI chatbots for particular pedagogical purposes.

Example/excerpt:



 


Higher education faces ‘deteriorating’ 2026 outlook, Fitch says — from highereddive.com by Laura Spitalniak
A shrinking pipeline of students, uncertainty about state and federal support, and rising expenses could all hurt college finances, according to analysts.

Dive Brief:

  • Fitch Ratings on Thursday issued a “deteriorating” outlook for the higher education sector in 2026, continuing the gloomy prediction the agency issued for 2025.
  • Analysts based their forecast on a shrinking prospective student base, “rising uncertainty related to state and federal support, continued expense escalation and shifting economic conditions.”
  • With its report, Fitch joins Moody’s Ratings and S&P Global Ratings in predicting a grim year for higher ed — Moody’s for the sector overall and S&P for nonprofit colleges specifically.

Yale expects layoffs as leaders brace for $300M in endowment taxes — from highereddive.com by Ben Unglesbee
The Ivy League institution’s tax bill starting next year will be higher than what it spends on student aid, university officials said.

Dive Brief:

  • Yale University is bracing for layoffs as it prepares to pay the government hundreds of millions of dollars in endowment income taxes.
  • In a public message, senior leaders at the Ivy League institution said that Yale’s schools plan to take steps such as delaying hiring and reducing travel spending to save money. But they warned workforce cuts were on the horizon.
  • “Layoffs may be necessary” in some units where cutting open positions and other reductions are insufficient, the university officials said. They expect to complete any downsizing by the end of 2026 barring “additional significant financial changes.”

Education Department adds ‘lower earnings’ warning to FAFSA — from highereddive.com by Natalie Schwartz
The agency will warn students when they’ve indicated interest in a college whose graduates have relatively low incomes.

The U.S. Department of Education has launched a new disclosure feature that warns students who fill out the Free Application for Federal Student Aid if they’re interested in colleges whose graduates have relatively low earnings, the agency said Monday. 

“Families deserve a clearer picture of how postsecondary education connects to real-world earnings, and this new indicator will provide that transparency,” U.S. Education Secretary Linda McMahon said in a Monday statement. “Not only will this new FAFSA feature make public earnings data more accessible, but it will empower prospective students to make data-driven decisions before they are saddled with debt.”


Also from highereddive.com, see:

 

Fresh Off the Press: Parents’ Guide to Microschools — from gettingsmart.com

We’re excited to announce and share our new Parents Guide to Microschools, a clear and approachable introduction to one of the fastest growing learning models in the country. The guide unpacks what microschools are, how they work and why families are increasingly drawn to intimate, relationship centered environments. It highlights features like flexible schedules, small cohorts, personalized pathways and hands-on learning so parents can picture what these settings actually look and feel like.

It also equips families with practical tools to navigate the decision making process: key questions to ask during visits, indicators of strong culture and instruction, considerations around cost and accreditation and how to assess overall fit for each learner. Whether parents are simply curious or actively exploring new options, this guide offers clarity, confidence and a starting point for imagining what learning could look like next.

 

Beyond Infographics: How to Use Nano Banana to *Actually* Support Learning — from drphilippahardman.substack.com by Dr Philippa Hardman
Six evidence-based use cases to try in Google’s latest image-generating AI tool

While it’s true that Nano Banana generates better infographics than other AI models, the conversation has so far massively under-sold what’s actually different and valuable about this tool for those of us who design learning experiences.

What this means for our workflow:

Instead of the traditional “commission ? wait ? tweak ? approve ? repeat” cycle, Nano Banana enables an iterative, rapid-cycle design process where you can:

  • Sketch an idea and see it refined in minutes.
  • Test multiple visual metaphors for the same concept without re-briefing a designer.
  • Build 10-image storyboards with perfect consistency by specifying the constraints once, not manually editing each frame.
  • Implement evidence-based strategies (contrasting cases, worked examples, observational learning) that are usually too labour-intensive to produce at scale.

This shift—from “image generation as decoration” to “image generation as instructional scaffolding”—is what makes Nano Banana uniquely useful for the 10 evidence-based strategies below.

 


 


 

Why Parents Aren’t Reading to Kids, and What It Means for Young Students — from the74million.org by Jessika Harkay
A recent study found less than half of children are read to daily. The consequences are serious for early learners who enter school unprepared.

For children not getting the benefits of being read to at home, the opportunity gap has widened, with those young students entering school unprepared compared to those who have been read to.

“The gap really begins very, very early on. I think we underestimate how large a gap we’re already seeing in kindergarten,” said Susan Neuman, professor of childhood and literacy education at New York University, adding she recently visited a New York City kindergarten classroom and saw some children who only knew two letters compared to others who were prepared to read phrases.

A 2019 Ohio State University study found a 5-year-old child who is read to daily would be exposed to nearly 300,000 more words than one who isn’t read to regularly.

 

Caring for Patients for 26 Years—and Still Not a Nurse — from workshift.org/ by Colleen Connolly

Arnett’s experience spending decades in a job she intended as a first step is common among CNAs, medical assistants, and other entry-level healthcare workers, many of them women of color from low-income backgrounds. Amid a nationwide nursing shortage, elevating those workers seems like an obvious solution, but the path from CNA to nurse isn’t so much a ladder as it is a huge leap.

And obstacle after obstacle is strewn in the way. The high cost of nursing school, lengthy prerequisite requirements, rigid schedules, and unpaid clinical hours make it difficult for many CNAs to advance in their careers, despite their willingness and ability and the dire need of healthcare facilities.

While there are no national statistics about the number of entry-level healthcare workers who move on to higher-paid positions, a study of federal grants for CNA training showed that only 3% of those who completed the training went on to pursue further education to become an LPN or RN. Only 1% obtained an associate degree or above. A similar study in California showed that 22% of people who completed CNA certificate programs at community colleges went on to get a higher-level educational credential in health, but only 13% became registered nurses within six years.

That reality perpetuates chronic shortages in nursing, and it also keeps hundreds of thousands of healthcare workers locked below a living wage, often for decades.

 

4 Simple & Easy Ways to Use AI to Differentiate Instruction — from mindfulaiedu.substack.com (Mindful AI for Education) by Dani Kachorsky, PhD
Designing for All Learners with AI and Universal Design Learning

So this year, I’ve been exploring new ways that AI can help support students with disabilities—students on IEPs, learning plans, or 504s—and, honestly, it’s changing the way I think about differentiation in general.

As a quick note, a lot of what I’m finding applies just as well to English language learners or really to any students. One of the big ideas behind Universal Design for Learning (UDL) is that accommodations and strategies designed for students with disabilities are often just good teaching practices. When we plan instruction that’s accessible to the widest possible range of learners, everyone benefits. For example, UDL encourages explaining things in multiple modes—written, visual, auditory, kinesthetic—because people access information differently. I hear students say they’re “visual learners,” but I think everyone is a visual learner, and an auditory learner, and a kinesthetic learner. The more ways we present information, the more likely it is to stick.

So, with that in mind, here are four ways I’ve been using AI to differentiate instruction for students with disabilities (and, really, everyone else too):


The Periodic Table of AI Tools In Education To Try Today — from ictevangelist.com by Mark Anderson

What I’ve tried to do is bring together genuinely useful AI tools that I know are already making a difference.

For colleagues wanting to explore further, I’m sharing the list exactly as it appears in the table, including website links, grouped by category below. Please do check it out, as along with links to all of the resources, I’ve also written a brief summary explaining what each of the different tools do and how they can help.





Seven Hard-Won Lessons from Building AI Learning Tools — from linkedin.com by Louise Worgan

Last week, I wrapped up Dr Philippa Hardman’s intensive bootcamp on AI in learning design. Four conversations, countless iterations, and more than a few humbling moments later – here’s what I am left thinking about.


Finally Catching Up to the New Models — from michellekassorla.substack.com by Michelle Kassorla
There are some amazing things happening out there!

An aside: Google is working on a new vision for textbooks that can be easily differentiated based on the beautiful success for NotebookLM. You can get on the waiting list for that tool by going to LearnYourWay.withgoogle.com.

Nano Banana Pro
Sticking with the Google tools for now, Nano Banana Pro (which you can use for free on Google’s AI Studio), is doing something that everyone has been waiting a long time for: it adds correct text to images.


Introducing AI assistants with memory — from perplexity.ai

The simple act of remembering is the crux of how we navigate the world: it shapes our experiences, informs our decisions, and helps us anticipate what comes next. For AI agents like Comet Assistant, that continuity leads to a more powerful, personalized experience.

Today we are announcing new personalization features to remember your preferences, interests, and conversations. Perplexity now synthesizes them automatically like memory, for valuable context on relevant tasks. Answers are smarter, faster, and more personalized, no matter how you work.

From DSC :
This should be important as we look at learning-related applications for AI.


For the last three days, my Substack has been in the top “Rising in Education” list. I realize this is based on a hugely flawed metric, but it still feels good. ?

– Michael G Wagner

Read on Substack


I’m a Professor. A.I. Has Changed My Classroom, but Not for the Worse. — from nytimes.com by Carlo Rotella [this should be a gifted article]
My students’ easy access to chatbots forced me to make humanities instruction even more human.


 

 

AI’s Role in Online Learning > Take It or Leave It with Michelle Beavers, Leo Lo, and Sara McClellan — from intentionalteaching.buzzsprout.com by Derek Bruff

You’ll hear me briefly describe five recent op-eds on teaching and learning in higher ed. For each op-ed, I’ll ask each of our panelists if they “take it,” that is, generally agree with the main thesis of the essay, or “leave it.” This is an artificial binary that I’ve found to generate rich discussion of the issues at hand.




 

New Study: Business As Usual Could Doom Dozens Of New England Colleges — from forbes.com by Michael B. Horn

The cause of the challenges isn’t one single factor, but a series of pressures from demographic changes, shifts in the public’s perception of higher education’s value, rising operating costs, emerging alternatives to traditional colleges, and, of late, changes in federal policies and programs. The net effect is that many institutions are much closer to the brink of closure than ever before.

What’s daunting is that flat enrollment is almost certainly an overly optimistic scenario.

If enrollment at the 44 schools falls by 15 percent over the next four years and business proceeds as usual, then 28 of the schools will have less than 10 years of cash and unrestricted quasi-endowments before they would become insolvent—assuming no major cuts, additional philanthropy, new debt, or asset sales. Fourteen would have less than five years before insolvency.

Also see:

From DSC:
The cultures at many institutions of traditional higher education will make some of the necessary changes and strategies (that Michael and Steven discuss) very hard to make. For example, to merge with another institution or institutions. Such a strategy could be very challenging to implement, even as alternatives continue to emerge.

 


Three Years from GPT-3 to Gemini 3 — from oneusefulthing.org by Ethan Mollick
From chatbots to agents

Three years ago, we were impressed that a machine could write a poem about otters. Less than 1,000 days later, I am debating statistical methodology with an agent that built its own research environment. The era of the chatbot is turning into the era of the digital coworker. To be very clear, Gemini 3 isn’t perfect, and it still needs a manager who can guide and check it. But it suggests that “human in the loop” is evolving from “human who fixes AI mistakes” to “human who directs AI work.” And that may be the biggest change since the release of ChatGPT.




Results May Vary — from aiedusimplified.substack.com by Lance Eaton, PhD
On Custom Instructions with GenAI Tools….

I’m sharing today about custom instructions and my use of them across several AI tools (paid versions of ChatGPT, Gemini, and Claude). I want to highlight what I’m doing, how it’s going, and solicit from readers to share in the comments some of their custom instructions that they find helpful.

I’ve been in a few conversations lately that remind me that not everyone knows about them, even some of the seasoned folks around GenAI and how you might set them up to better support your work. And, of course, they are, like all things GenAI, highly imperfect!

I’ll include and discuss each one below, but if you want to keep abreast of my custom instructions, I’ll be placing them here as I adjust and update them so folks can see the changes over time.

 

Free Music Discovery Tools — from wondertools.substack.com by Jeremy Caplan and Chris Dalla Riva
Travel through time and around the world with sound

I love apps like Metronaut and Tomplay, which let me carry a collection of classical (sheet) music on my phone. They also provide piano or orchestral accompaniment for any violin piece I want to play.

Today’s post shares 10 other recommended tools for music lovers from my fellow writer and friend, Chris Dalla Riva, who writes Can’t Get Much Higher, a popular Substack focused on the intersection of music and data. I invited Chris to share with you his favorite resources for discovering, learning, and creating music.

Sections include:

  • Learn about Music
  • Discover New Music
  • Learn an Instrument
  • Tools for Artists
 


Gen AI Is Going Mainstream: Here’s What’s Coming Next — from joshbersin.com by Josh Bersin

I just completed nearly 60,000 miles of travel across Europe, Asia, and the Middle East meeting with hundred of companies to discuss their AI strategies. While every company’s maturity is different, one thing is clear: AI as a business tool has arrived: it’s real and the use-cases are growing.

A new survey by Wharton shows that 46% of business leaders use Gen AI daily and 80% use it weekly. And among these users, 72% are measuring ROI and 74% report a positive return. HR, by the way, is the #3 department in use cases, only slightly behind IT and Finance.

What are companies getting out of all this? Productivity. The #1 use case, by far, is what we call “stage 1” usage – individual productivity. 

.


From DSC:
Josh writes: “Many of our large clients are now implementing AI-native learning systems and seeing 30-40% reduction in staff with vast improvements in workforce enablement.

While I get the appeal (and ROI) from management’s and shareholders’ perspective, this represents a growing concern for employment and people’s ability to earn a living. 

And while I highly respect Josh and his work through the years, I disagree that we’re over the problems with AI and how people are using it: 

Two years ago the NYT was trying to frighten us with stories of AI acting as a romance partner. Well those stories are over, and thanks to a $Trillion (literally) of capital investment in infrastructure, engineering, and power plants, this stuff is reasonably safe.

Those stories are just beginning…they’re not close to being over. 


“… imagine a world where there’s no separation between learning and assessment…” — from aiedusimplified.substack.com by Lance Eaton, Ph.D. and Tawnya Means
An interview with Tawnya Means

So let’s imagine a world where there’s no separation between learning and assessment: it’s ongoing. There’s always assessment, always learning, and they’re tied together. Then we can ask: what is the role of the human in that world? What is it that AI can’t do?

Imagine something like that in higher ed. There could be tutoring or skill-based work happening outside of class, and then relationship-based work happening inside of class, whether online, in person, or some hybrid mix.

The aspects of learning that don’t require relational context could be handled by AI, while the human parts remain intact. For example, I teach strategy and strategic management. I teach people how to talk with one another about the operation and function of a business. I can help students learn to be open to new ideas, recognize when someone pushes back out of fear of losing power, or draw from my own experience in leading a business and making future-oriented decisions.

But the technical parts such as the frameworks like SWOT analysis, the mechanics of comparing alternative viewpoints in a boardroom—those could be managed through simulations or reports that receive immediate feedback from AI. The relational aspects, the human mentoring, would still happen with me as their instructor.

Part 2 of their interview is here:


 
© 2025 | Daniel Christian