From DSC: This one is for the youth out there. Learn these lessons NOW, before you go too much further in your journey here on Earth. If you do, you will reap the benefits of this learning for the rest of your days.
As I mentioned to our own kids when I forwarded this article to them:
My dad passed along a bit of wisdom to me when he told me what *his* dad (my Grandpa Christian) had told him:
“If a job is worth doing, it’s worth doing well.”
I’ve always remembered that and I *try* to do quality work.
The following article is worth your time. It touches upon a similar idea: .
I pass it along to help us *try* to do quality things and work…but NOT to load up unrealistic expectations on ourselves or create a harried, perfectionistic lifestyle.
Excerpt:
An old carpenter told his boss that he planned to retire. The boss was sad to lose the carpenter, but understood.
He asked if he’d stick around for one last job—to build one final house.
The carpenter reluctantly agreed, figuring he could get it done quickly. He cut corners, used cheap materials, and rushed through the work.
When the house was done, his boss arrived for the final inspection. But instead of walking the house, he reached into his pocket, and handed the carpenter the keys.
“This is your house,” his boss smiled, “My retirement gift to you.”
The carpenter was stunned. If he’d known he was building his own house, he would have done it differently. Now he’d have to live in a house he had built none too well.
The lesson: You’re always building your own house.
At least 85% of students with disabilities can learn and achieve on grade level.
14% of all U.S. students have a disability.
No belief is more damaging in education than the misperception that children with disabilities cannot really succeed and shouldn’t be challenged to reach the same high standards as all children.
Arne Duncan, former U.S. Secretary of Education
From DSC: One of our kids — actually, who is no longer a kid anymore — was born with Mosaic Down Syndrome. Looking back on her K-12 years, first through fifth grade went very well — which my wife and I were very grateful for. (We didn’t know what each year would bring and whether she would be able to move on to the next grade.)
But sixth and seventh grades were very rough. At the end of seventh grade, we decided to homeschool our daughter. The system she was in — like so many school systems across the nation — was meant to address the 80% of students who are neither gifted nor have special needs. The quickly-moving trains leave at such and such a time and then stop at such and such a time. One better keep up. This traditional system is a one-size-fits-all approach, and it’s something we do for administrative purposes — it’s not for the benefit of the kids within K-12 schools.
After a few years of both homeschooling and Christian education, it turned out that our daughter was able to learn almost all of the subjects in high school. But she needed to learn ON HER TIMELINE…AT HER OWN PACE of learning.
We’re proud of her. She has had a couple of jobs already and is doing quite well overall. Her motivation has been very low at times, which made homeschooling very tough. But, overall, I would agree with Karla Phillips-Krivicka’s key point that at least 85% of students with disabilities can learn and achieve at grade level. That’s been true for our daughter who has some special needs.
Adulting and Career Exploration — from the-job.beehiiv.com by Paul Fain Junior Achievement helps high school grads learn life skills and gain work experience while figuring out what comes next.
Bridging the Gap Between School and Careers Junior Achievement has stepped into the blur space between high school and what comes next. The nonprofit’s 5th Year program gives young adults a structured year to live on a college campus and explore careers, gain work experience, and build life skills.
An initial cohort of 24 students graduated this May from a trial run of the program based in Toledo, Ohio. Each participant held two internships—one in the fall and one in the spring. They also visited 60 employers across the metro area. Represented industries included law, engineering, construction, accounting, healthcare, higher education, and nonprofit organizations.
The program is focused on helping students find a clear path forward, by guiding them to match their interests and abilities with in-demand careers and local job opportunities.
“We’re giving them the space to just pause,” he says. “To discover, to explore, to grow personally, to grow socially.”
The microschooling sector’s robust diversity of educational approaches is often described by the families who choose it as among its most appealing attributes. The wide range of approaches offered, and the many ways different approaches are combined within different microschooling models, offer families options usually not currently available in the communities they live.
And while many of these approaches, like project-based learning, are popular across all of American education, within the smaller, more personalized and responsive context of a microschool, educators are able to take advantage of their flexibility to delve more deeply into the possibilities of each than they were in the more rigid structures of most traditional schools.
According to 2025 research published by the National Microschooling Center, microschool leaders reported that project-based learning is the most popular educational approach used (72 percent). Respondents were asked to indicate all that apply, so microschools typically indicated incorporating multiple approaches.
Get yourself unstuck: overthinking is boring and perfectionism is a trap — from timeshighereducation.com by David Thompson The work looks flawless, the student seems fine. But underneath, perfectionism is doing damage. David Thompson unpacks what educators can do to help high-performing students navigate the pressure to succeed and move from stuck to started
That’s why I encourage imperfection, messiness and play and build these ideas into how I teach.
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These moments don’t come from big breakthroughs. They come from removing pressure and replacing it with permission.
Yoodli is an AI tool designed to help users improve their public speaking skills. It analyzes your speech in real-time or after a recording and gives you feedback on things like:
Filler words (“um,” “like,” “you know”)
Pacing (Are you sprinting or sedating your audience?)
Word choice and sentence complexity
Eye contact and body language (with video)
And yes, even your “uhhh” to actual word ratio
Yoodli gives you a transcript and a confidence score, plus suggestions that range from helpful to brutally honest. It’s basically Simon Cowell with AI ethics and a smiley face interface.
[What’s] going on with AI and education? — from theneuron.ai by Grant Harvey With students and teachers alike using AI, schools are facing an “assessment crisis” where the line between tool and cheating has blurred, forcing a shift away from a broken knowledge economy toward a new focus on building human judgment through strategic struggle.
What to do about it: The future belongs to the “judgment economy,” where knowledge is commoditized but taste, agency, and learning velocity become the new human moats. Use the “Struggle-First” principle: wrestle with problems for 20-30 minutes before turning to AI, then use AI as a sparring partner (not a ghostwriter) to deepen understanding. The goal isn’t to avoid AI, but to strategically choose when to embrace “desirable difficulties” that build genuine expertise versus when to leverage AI for efficiency.
… The Alpha-School Program in brief:
Students complete core academics in just 2 hours using AI tutors, freeing up 4+ hours for life skills, passion projects, and real-world experiences.
The school claims students learn at least 2x faster than their peers in traditional school.
The top 20% of students show 6.5x growth. Classes score in the top 1-2% nationally across the board.
Claims are based on NWEA’s Measures of Academic Progress (MAP) assessments… with data only available to the school. Hmm…
Austen Allred shared a story about the school, which put it on our radar.
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In the latest installment of Gallup and the Walton Family Foundation’s research on education, K-12 teachers reveal how AI tools are transforming their workloads, instructional quality and classroom optimism. The report finds that 60% of teachers used an AI tool during the 2024–25 school year. Weekly AI users report reclaiming nearly six hours per week — equivalent to six weeks per year — which they reinvest in more personalized instruction, deeper student feedback and better parent communication.
Despite this emerging “AI dividend,” adoption is uneven: 40% of teachers aren’t using AI at all, and only 19% report their school has a formal AI policy. Teachers with access to policies and support save significantly more time.
Educators also say AI improves their work. Most report higher-quality lesson plans, assessments and student feedback. And teachers who regularly use AI are more optimistic about its benefits for student engagement and accessibility — mirroring themes from the Voices of Gen Z: How American Youth View and Use Artificial Intelligence report, which found students hesitant but curious about AI’s classroom role. As AI tools grow more embedded in education, both teachers and students will need the training and support to use them effectively.
What Is Amira Learning?
Amira Learning’s system is built upon research led by Jack Mostow, a professor at Carnegie Mellon who helped pioneer AI literacy education. Amira uses Claude AI to power its AI features, but these features are different than many other AI tools on the market. Instead of focusing on chat and generative response, Amira’s key feature is its advanced speech recognition and natural language processing capabilities, which allow the app to “hear” when a student is struggling and tailor suggestions to that student’s particular mistakes.
Though it’s not meant to replace a teacher, Amira provides real-time feedback and also helps teachers pinpoint where a student is struggling. For these reasons, Amira Learning is a favorite of education scientists and advocates for science of reading-based literacy instruction. The tool currently is used by more than 4 million students worldwide and across the U.S.
Getting (and Keeping) Early Learners’ Attention — from edutopia.org by Heather Sanderell These ideas for lesson hooks—like using songs, video clips, and picture walks—can motivate young students to focus on learning.
How do you grasp and maintain the attention of a room full of wide-eyed students with varying interests and abilities? Do you use visuals and games or interactive activities? Do you use art and sports and music or sounds? The answer is yes, to all!
When trying to keep the attention of your learners, it’s important to stimulate their senses and pique their diverse interests. Educational theorist and researcher Robert Gagné devised his nine events of instructional design, which include grabbing learners’ attention with a lesson hook. This is done first to set the tone for the remainder of the lesson.
3 Ways to Help Students Overcome the Forgetting Curve — from edutopia.org by Cathleen Beachboard Our brains are wired to forget things unless we take active steps to remember. Here’s how you can help students hold on to what they learn.
You teach a lesson that lights up the room. Students are nodding and hands are flying up, and afterward you walk out thinking, “They got it. They really got it.”
And then, the next week, you ask a simple review question—and the room falls silent.
If that situation has ever made you question your ability to teach, take heart: You’re not failing, you’re simply facing the forgetting curve. Understanding why students forget—and how we can help them remember—can transform not just our lessons but our students’ futures.
The good news? You don’t have to overhaul your curriculum to beat the forgetting curve. You just need three small, powerful shifts in how you teach.
7 Nature Experiments to Spark Student Curiosity — from edutopia.org by Donna Phillips Encourage your students to ask questions about and explore the world around them with these hands-on lessons.
Children are natural scientists—they ask big questions, notice tiny details, and learn best through hands-on exploration. That’s why nature experiments are a classroom staple for me. From growing seeds to using the sun’s energy, students don’t just learn science, they experience it. Here are my favorite go-to nature experiments that spark curiosity.
Intellectual rigor comes from the journey: the dead ends, the uncertainty, and the internal debate. Skip that, and you might still get the insight–but you’ll have lost the infrastructure for meaningful understanding. Learning by reading LLM output is cheap. Real exercise for your mind comes from building the output yourself.
The irony is that I now know more than I ever would have before AI. But I feel slightly dumber. A bit more dull. LLMs give me finished thoughts, polished and convincing, but none of the intellectual growth that comes from developing them myself.
Every few months I put together a guide on which AI system to use. Since I last wrote my guide, however, there has been a subtle but important shift in how the major AI products work. Increasingly, it isn’t about the best model, it is about the best overall system for most people. The good news is that picking an AI is easier than ever and you have three excellent choices. The challenge is that these systems are getting really complex to understand. I am going to try and help a bit with both.
First, the easy stuff.
Which AI to Use For most people who want to use AI seriously, you should pick one of three systems: Claude from Anthropic, Google’s Gemini, and OpenAI’s ChatGPT.
This summer, I tried something new in my fully online, asynchronous college writing course. These classes have no Zoom sessions. No in-person check-ins. Just students, Canvas, and a lot of thoughtful design behind the scenes.
One activity I created was called QuoteWeaver—a PlayLab bot that helps students do more than just insert a quote into their writing.
It’s a structured, reflective activity that mimics something closer to an in-person 1:1 conference or a small group quote workshop—but in an asynchronous format, available anytime. In other words, it’s using AI not to speed students up, but to slow them down.
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The bot begins with a single quote that the student has found through their own research. From there, it acts like a patient writing coach, asking open-ended, Socratic questions such as:
What made this quote stand out to you?
How would you explain it in your own words?
What assumptions or values does the author seem to hold?
How does this quote deepen your understanding of your topic?
It doesn’t move on too quickly. In fact, it often rephrases and repeats, nudging the student to go a layer deeper.
On [6/13/25], UNESCO published a piece I co-authored with Victoria Livingstone at Johns Hopkins University Press. It’s called The Disappearance of the Unclear Question, and it’s part of the ongoing UNESCO Education Futures series – an initiative I appreciate for its thoughtfulness and depth on questions of generative AI and the future of learning.
Our piece raises a small but important red flag. Generative AI is changing how students approach academic questions, and one unexpected side effect is that unclear questions – for centuries a trademark of deep thinking – may be beginning to disappear. Not because they lack value, but because they don’t always work well with generative AI. Quietly and unintentionally, students (and teachers) may find themselves gradually avoiding them altogether.
Of course, that would be a mistake.
We’re not arguing against using generative AI in education. Quite the opposite. But we do propose that higher education needs a two-phase mindset when working with this technology: one that recognizes what AI is good at, and one that insists on preserving the ambiguity and friction that learning actually requires to be successful.
By leveraging generative artificial intelligence to convert lengthy instructional videos into micro-lectures, educators can enhance efficiency while delivering more engaging and personalized learning experiences.
Researchers at Massachusetts Institute of Technology (MIT) have now devised a way for LLMs to keep improving by tweaking their own parameters in response to useful new information.
The work is a step toward building artificial intelligence models that learn continually—a long-standing goal of the field and something that will be crucial if machines are to ever more faithfully mimic human intelligence. In the meantime, it could give us chatbots and other AI tools that are better able to incorporate new information including a user’s interests and preferences.
The MIT scheme, called Self Adapting Language Models (SEAL), involves having an LLM learn to generate its own synthetic training data and update procedure based on the input it receives.
Edu-Snippets — from scienceoflearning.substack.com by Nidhi Sachdeva and Jim Hewitt Why knowledge matters in the age of AI; What happens to learners’ neural activity with prolonged use of LLMs for writing
Highlights:
Offloading knowledge to Artificial Intelligence (AI) weakens memory, disrupts memory formation, and erodes the deep thinking our brains need to learn.
Prolonged use of ChatGPT in writing lowers neural engagement, impairs memory recall, and accumulates cognitive debt that isn’t easily reversed.
It’s not just about redesigning public education—it’s about rethinking how, where and with whom learning happens.Communities across the United States are shaping learner-centered ecosystems and gathering insights along the way.
What does it take to build a learner-centered ecosystem? A shared vision. Distributed leadership. Place-based experiences. Repurposed resources. And more. This piece unpacks 10 real-world insights from pilots in action. .
We believe the path forward is through the cultivation of learner-centered ecosystems — adaptive, networked structures that offer a transformed way of organizing, supporting, and credentialing community-wide learning. These ecosystems break down barriers between schools, communities, and industries, creating flexible, real-world learning experiences that tap into the full range of opportunities a community has to offer.
Last year, we announced our Learner-Centered Ecosystem Lab, a collaborative effort to create a community of practice consisting of twelve diverse sites across the country — from the streets of Brooklyn to the mountains of Ojai — that are demonstrating or piloting ecosystemic approaches. Since then, we’ve been gathering together, learning from one another, and facing the challenges and opportunities of trying to transform public education. And while there is still much more work to be done, we’ve begun to observe a deeper pattern language — one that aligns with our ten-point Ecosystem Readiness Framework, and one that, we hope, can help all communities start to think more practically and creatively about how to transform their own systems of learning.
So while it’s still early, we suspect that the way to establish a healthy learner-centered ecosystem is by paying close attention to the following ten conditions:
Abstract In an era of generative AI and ubiquitous digital tools, human memory faces a paradox: the more we offload knowledge to external aids, the less we exercise and develop our own cognitive capacities. This chapter offers the first neuroscience-based explanation for the observed reversal of the Flynn Effect—the recent decline in IQ scores in developed countries—linking this downturn to shifts in educational practices and the rise of cognitive offloading via AI and digital tools. Drawing on insights from neuroscience, cognitive psychology, and learning theory, we explain how underuse of the brain’s declarative and procedural memory systems undermines reasoning, impedes learning, and diminishes productivity. We critique contemporary pedagogical models that downplay memorization and basic knowledge, showing how these trends erode long-term fluency and mental flexibility. Finally, we outline policy implications for education, workforce development, and the responsible integration of AI, advocating strategies that harness technology as a complement to – rather than a replacement for – robust human knowledge.
Here are some incredibly powerful numbers from Mary Meeker’s AI Trends report, which showcase how artificial intelligence as a tech is unlike any other the world has ever seen.
AI took only three years to reach 50% user adoption in the US; mobile internet took six years, desktop internet took 12 years, while PCs took 20 years.
ChatGPT reached 800 million users in 17 months and 100 million in only two months, vis-à-vis Netflix’s 100 million (10 years), Instagram (2.5 years) and TikTok (nine months).
ChatGPT hit 365 billion annual searches in two years (2024) vs. Google’s 11 years (2009)—ChatGPT 5.5x faster than Google.
Above via Mary Meeker’s AI Trend-Analysis — from getsuperintel.com by Kim “Chubby” Isenberg How AI’s rapid rise, efficiency race, and talent shifts are reshaping the future.
The TLDR
Mary Meeker’s new AI trends report highlights an explosive rise in global AI usage, surging model efficiency, and mounting pressure on infrastructure and talent. The shift is clear: AI is no longer experimental—it’s becoming foundational, and those who optimize for speed, scale, and specialization will lead the next wave of innovation.
The Rundown: Meta aims to release tools that eliminate humans from the advertising process by 2026, according to a report from the WSJ — developing an AI that can create ads for Facebook and Instagram using just a product image and budget.
The details:
Companies would submit product images and budgets, letting AI craft the text and visuals, select target audiences, and manage campaign placement.
The system will be able to create personalized ads that can adapt in real-time, like a car spot featuring mountains vs. an urban street based on user location.
The push would target smaller companies lacking dedicated marketing staff, promising professional-grade advertising without agency fees or skillset.
Advertising is a core part of Mark Zuckerberg’s AI strategy and already accounts for 97% of Meta’s annual revenue.
Why it matters: We’re already seeing AI transform advertising through image, video, and text, but Zuck’s vision takes the process entirely out of human hands. With so much marketing flowing through FB and IG, a successful system would be a major disruptor — particularly for small brands that just want results without the hassle.
