K-12 related

How Your Learners Actually Learn with AI [Hardman] + another item re: AI in our learning ecosystems

On 12/22/2025, in 21st century, 24x7x365 access, adjunct faculty, adult learning, Artificial Intelligence/Agents/LLMs/and Related, bots, cloud-based computing / apps / other cloud-related, colleges, communities of practice, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, education, education technology, emerging technologies, experimentation, faculty/staff, future of higher education, game-changing environment, generational differences, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, law schools, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning preferences, liberal arts, library / librarians, Microsoft, personalized/customized learning, platforms, productivity / tips and tricks, research, skills, student-related, teachers, teaching & learning, technologies for your home, tools, trends, United States, universities, vendors, workplace, youth, by Daniel Christian

How Your Learners *Actually* Learn with AI — from drphilippahardman.substack.com by Dr. Philippa Hardman
What 37.5 million AI chats show us about how learners use AI at the end of 2025 — and what this means for how we design & deliver learning experiences in 2026

Last week, Microsoft released a similar analysis of a whopping 37.5 million Copilot conversations. These conversation took place on the platform from January to September 2025, providing us with a window into if and how AI use in general — and AI use among learners specifically – has evolved in 2025.

Microsoft’s mass behavioural data gives us a detailed, global glimpse into what learners are actually doing across devices, times of day and contexts. The picture that emerges is pretty clear and largely consistent with what OpenAI’s told us back in the summer:

AI isn’t functioning primarily as an “answers machine”: the majority of us use AI as a tool to personalise and differentiate generic learning experiences and – ultimately – to augment human learning.

Let’s dive in!

Learners don’t “decide” to use AI anymore. They assume it’s there, like search, like spellcheck, like calculators. The question has shifted from “should I use this?” to “how do I use this effectively?”

8 AI Agents Every HR Leader Needs To Know In 2026 — from forbes.com by Bernard Marr

So where do you start? There are many agentic tools and platforms for AI tasks on the market, and the most effective approach is to focus on practical, high-impact workflows. So here, I’ll look at some of the most compelling use cases, as well as provide an overview of the tools that can help you quickly deliver tangible wins.
…
Some of the strongest opportunities in HR include:

Workforce management, administering job satisfaction surveys, monitoring and tracking performance targets, scheduling interventions, and managing staff benefits, medical leave, and holiday entitlement.
Recruitment screening, automatically generating and posting job descriptions, filtering candidates, ranking applicants against defined criteria, identifying the strongest matches, and scheduling interviews.
Employee onboarding, issuing new hires with contracts and paperwork, guiding them to onboarding and training resources, tracking compliance and completion rates, answering routine enquiries, and escalating complex cases to human HR specialists.
Training and development, identifying skills gaps, providing self-service access to upskilling and reskilling opportunities, creating personalized learning pathways aligned with roles and career goals, and tracking progress toward completion.

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.

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

On 12/16/2025, in 21st century, 24x7x365 access, adjunct faculty, adult learning, Alternatives, Artificial Intelligence/Agents/LLMs/and Related, Asia, Australia, bots, career development, change, changing business models, cloud-based computing / apps / other cloud-related, CMS/LMS, collaboration, colleges, communities of practice, community colleges, computer science, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, education technology, experimentation, faculty/staff, future of higher education, game-changing environment, generational differences, higher education, human-computer interaction (HCI), India, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, law schools, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning preferences, learning spaces, liberal arts, library / librarians, lifelong learning, microlearning, online media, personalized/customized learning, platforms, productivity / tips and tricks, student-related, teachers, teaching & learning, technologies for your home, the downsides of how people use tech, tools, training / L&D, trends, UK, United States, universities, vendors, vision/possibilities, youth, by Daniel Christian

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:

Not Your Default Chatbot: Five Teaching Applications of Custom AI Bots
Agile Learning
derekbruff.org/2025/10/01/five-teaching-applications-of-custom-ai-chatbots/

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.

“My students use ChatGPT to attack their own thinking before I ever grade them.” [Winkel] + another item re: AI in our LE’s

On 12/10/2025, in adjunct faculty, adult learning, Artificial Intelligence/Agents/LLMs/and Related, bots, cloud-based computing / apps / other cloud-related, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, creativity, digital learning, education, education technology, emerging technologies, experimentation, faculty/staff, future of higher education, game-changing environment, generational differences, graphics, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, law schools, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning preferences, learning spaces, liberal arts, library / librarians, lifelong learning, multimedia, pedagogy, personalized/customized learning, platforms, productivity / tips and tricks, skills, society, student-related, teachers, teaching & learning, teaching online, technologies for your home, tools, training / L&D, trends, United States, universities, vendors, vision/possibilities, workplace, by Daniel Christian

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 [Harkay]

On 12/10/2025, in education, K-12 related, learning, learning ecosystem, parents/guardians, participation, reading, research, student-related, teachers, trends, United States, writing, youth, by Daniel Christian

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.

“Introducing AI assistants with memory” + other items re: AI in our learning ecosystems

On 12/01/2025, in accessibility / UDL, adjunct faculty, Artificial Intelligence/Agents/LLMs/and Related, bots, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate universities / corporate training, digital learning, digital video, education, education technology, emerging technologies, experimentation, faculty/staff, future of higher education, game-changing environment, generational differences, Google, higher education, human-computer interaction (HCI), innovation, instructional design, intelligent systems, IT in HE, 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, liberal arts, library / librarians, memory, multimedia, personalized/customized learning, platforms, productivity / tips and tricks, student-related, teachers, teaching & learning, tools, training / L&D, trends, United States, universities, vendors, by Daniel Christian

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.

Two cool items involving art and creativity

On 11/21/2025, in art, collaboration, creativity, Emotion, K-12 related, more voice more choice more control, relationships, student-related, teachers, by Daniel Christian

Simon Laveuve’s Scaled-Down Tableaux Reveal Post-Apocalyptic Lifestyles — from thisiscolossal.com by Simon Laveuve and Kate Mothes

Bringing High School Students and Kindergartners Together to Make Art — from edutopia.org by Cory Desmond
A look at how teachers can have students collaborate across grades on an art project that promotes creativity and teamwork.

What happens when high school students and kindergartners collaborate? Art. Innovation. Growth. And so much more.

Inspired by illustrator Mica Angela Hendricks’s collaborations with her 4-year-old daughter—in which Hendricks would begin by drawing a portrait and then have her daughter add to it—I formalized the concept into an inter-grade art lesson. It’s a replicable, three-stage project based on vertical collaboration. This model bridges the creative and social gap between students, weaving together technical skill and imagination through methods based in social and emotional learning (SEL).

It operates by passing a structured project back and forth, compelling older students to engage with empathy, relationship maintenance, and responsible decision-making. Simultaneously, it empowers younger students, giving them significant creative autonomy through their own responsible choices. By breaking down the separation between age groups, cross-grade collaborations cultivate essential skills in ways that isolated classrooms typically can’t.

In this article, I’ll provide a flexible framework for vertical collaboration—a blueprint that teachers can adapt for their own cross-grade collaborations.

“Textbooks are no longer one-size-fits-all” [Fitzpatrick] + other items re: AI in our learning ecosystems

On 11/18/2025, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, bots, change, changing business models, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, education, education technology, emerging technologies, experimentation, faculty/staff, game-changing environment, generational differences, Google, higher education, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, K-12 related, law schools, learner profiles, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning preferences, learning spaces, liberal arts, lifelong learning, Open AI, platforms, productivity / tips and tricks, student-related, teachers, teaching & learning, technologies for your home, training / L&D, trends, United States, universities, vendors, by Daniel Christian

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.

How is AI impacting the learning ecosystems out there (esp. L&D)? Check these postings out.

On 11/13/2025, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, assessment, bots, change, cloud-based computing / apps / other cloud-related, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate universities / corporate training, digital learning, education technology, emerging technologies, Europe, faculty/staff, future of higher education, game-changing environment, generational differences, global / globalization, Google, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, law schools, learner profiles, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning preferences, learning spaces, learning theories, liberal arts, library / librarians, lifelong learning, Microsoft, online learning, productivity / tips and tricks, skills, society, student-related, teachers, teaching & learning, tools, training / L&D, trends, UK, United States, universities, vendors, vision/possibilities, workplace, by Daniel Christian

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:

“They’re not necessarily trying to cheat; they’re just being efficient”

Seeing The Unseen Students: The Invisible Strength of Teachers [Tazkiya] + The Power of Play [Bray]

On 11/13/2025, in education, Emotion, ideas, K-12 related, learning, learning ecosystem, more voice more choice more control, motivation, parents/guardians, pedagogy, play, student-related, teachers, United States, youth, by Daniel Christian

Seeing The Unseen Students: The Invisible Strength of Teachers — from teachthought.com by Tasneem Tazkiya
One afternoon, I asked a different question: “What would make school feel worth showing up for again?”

A Moment That Changed My View of Teaching
I’ll never forget a student I’ll call Jalen. He was bright and quick with answers, sharp in debate, but he had built a wall around himself after a difficult year at home. He’d stopped turning in work and began sitting silently in the back of the room, disengaged and defiant.

One afternoon, instead of lecturing him about missing assignments, I asked a different question: “What would make school feel worth showing up for again?”

That simple question opened a door. Over the following weeks, Jalen began sharing ideas for projects connected to his interests, designing sneakers and exploring how geometry applies to shoe patterns. I adapted lessons to let him create, design, and analyze. Slowly, his confidence returned. Months later, he told me, “You made me feel like my ideas mattered.”

That moment reminded me that teaching isn’t just about delivering content; it’s about restoring belief in learning, and in oneself.

Also see:

The Power of Play — from barbarabray.net by Barbara Bray

Play brings joy and happiness to learning. Infusing play in schools prepares kids as future citizens.
When you play a game with your friends, how do you feel?

When you see children playing with other children, what do you notice?

Ask a child if they remember the worksheet they filled out last week.
Did they have fun?

Do they remember what they learned?

Let’s play more and discover how learning unfolds.
Schools can invest in more play through games, interactive experiences, and just making learning fun. Providing engaging activities through play creates learners who become critical thinkers, researchers, and designers.

Also re: teaching and learning:

Using Classic Texts From the Past to Foster Future-Ready Skills — from edutopia.org by Lauren Kaufman
High school teachers can use texts from the canon to promote the skills their schools or states have identified as essential for graduates.
Empowering Students Through a Focus on Incremental Progress — from edutopia.org by Kathy Collier
Elementary teachers can help students feel confident tackling big goals by encouraging them to focus on getting a little bit better every day.
Discovering Global Sounds Through the Recorder — from edutopia.org by Nina Stern, JoDee Scissors
Music teachers can guide exploration of musical styles from around the world to spark elementary students’ curiosity and build community.
Entrepreneurial Mindset in Middle School — from rdene915.com by Dr. Rachelle Dené Poth

A New AI Career Ladder — from ssir.org (Stanford Social Innovation Review) by Bruno V. Manno; via Matt Tower
The changing nature of jobs means workers need new education and training infrastructure to match.

AI has cannibalized the routine, low-risk work tasks that used to teach newcomers how to operate in complex organizations. Without those task rungs, the climb up the opportunity ladder into better employment options becomes steeper—and for many, impossible. This is not a temporary glitch. AI is reorganizing work, reshaping what knowledge and skills matter, and redefining how people are expected to acquire them.

The consequences ripple from individual career starts to the broader American promise of economic and social mobility, which includes both financial wealth and social wealth that comes from the networks and relationships we build. Yet the same technology that complicates the first job can help us reinvent how experience is earned, validated, and scaled. If we use AI to widen—not narrow—access to education, training, and proof of knowledge and skill, we can build a stronger career ladder to the middle class and beyond. A key part of doing this is a redesign of education, training, and hiring infrastructure.

…

What’s needed is a redesigned model that treats work as a primary venue for learning, validates capability with evidence, and helps people keep climbing after their first job. Here are ten design principles for a reinvented education and training infrastructure for the AI era.

Create hybrid institutions that erase boundaries. …
Make work-based learning the default, not the exception. …
Create skill adjacencies to speed transitions. …
Place performance-based hiring at the core. …
Ongoing supports and post-placement mobility. …
Portable, machine-readable credentials with proof attached. …
…plus several more…

“…a new operating system for L&D in the age of AI?” [Hardman] + other items re: AI in our learning ecosystems

On 10/30/2025, in 21st century, 24x7x365 access, adult learning, Artificial Intelligence/Agents/LLMs/and Related, bots, business, content development, aggregation, repositories, corporate universities / corporate training, digital learning, education technology, emerging technologies, experimentation, higher education, human-computer interaction (HCI), India, innovation, instructional design, intelligent systems, intelligent tutoring, K-12 related, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, liberal arts, training / L&D, by Daniel Christian

Custom AI Development: Evolving from Static AI Systems to Dynamic Learning Agents in 2025 — community.nasscom.in

This blog explores how custom AI development accelerates the evolution from static AI to dynamic learning agents and why this transformation is critical for driving innovation, efficiency, and competitive advantage.
…
Dynamic Learning Agents: The Next Generation
Dynamic learning agents, sometimes referred to as adaptive or agentic AI, represent a leap forward. They combine continuous learning, autonomous action, and context-aware adaptability.

Custom AI development plays a crucial role here: it ensures that these agents are designed specifically for an enterprise’s unique needs rather than relying on generic, one-size-fits-all AI platforms. Tailored dynamic agents can:

Continuously learn from incoming data streams
Make autonomous, goal-directed decisions aligned with business objectives
Adapt behavior in real time based on context and feedback
Collaborate with other AI agents and human teams to solve complex challenges

The result is an AI ecosystem that evolves with the business, providing sustained competitive advantage.

Also from community.nasscom.in, see:

Building AI Agents with Multimodal Models: From Perception to Action

Perception: The Foundation of Intelligent Agents
Perception is the first step in building AI agents. It involves capturing and interpreting data from multiple modalities, including text, images, audio, and structured inputs. A multimodal AI agent relies on this comprehensive understanding to make informed decisions.

For example, in healthcare, an AI agent may process electronic health records (text), MRI scans (vision), and patient audio consultations (speech) to build a complete understanding of a patient’s condition. Similarly, in retail, AI agents can analyze purchase histories (structured data), product images (vision), and customer reviews (text) to inform recommendations and marketing strategies.

Effective perception ensures that AI agents have contextual awareness, which is essential for accurate reasoning and appropriate action.

From 70-20-10 to 90-10: a new operating system for L&D in the age of AI? — from linkedin.com by Dr. Philippa Hardman

Also from Philippa, see:

Defining & Navigating the Jagged Frontier in Instructional Design (October, 2025)
What we know about where AI helps (and where it hinders) Instructional Design, and how to manage it

Your New ChatGPT Guide — from wondertools.substack.com by Jeremy Caplan and The PyCoach
25 AI Tips & Tricks from a guest expert

ChatGPT can make you more productive or dumber. An MIT study found that while AI can significantly boost productivity, it may also weaken your critical thinking. Use it as an assistant, not a substitute for your brain.
If you’re a student, use study mode in ChatGPT, Gemini, or Claude. When this feature is enabled, the chatbots will guide you through problems rather than just giving full answers, so you’ll be doing the critical thinking.
ChatGPT and other chatbots can confidently make stuff up (aka AI hallucinations). If you suspect something isn’t right, double-check its answers.
NotebookLM hallucinates less than most AI tools, but it requires you to upload sources (PDFs, audio, video) and won’t answer questions beyond those materials. That said, it’s great for students and anyone with materials to upload.
Probably the most underrated AI feature is deep research. It automates web searching for you and returns a fully cited report with minimal hallucinations in five to 30 minutes. It’s available in ChatGPT, Perplexity, and Gemini, so give it a try.

“OpenAI’s Atlas: the End of Online Learning—or Just the Beginning?” [Hardman] + other items re: AI in our LE’s

On 10/28/2025, in 21st century, 24x7x365 access, adult learning, Artificial Intelligence/Agents/LLMs/and Related, assessment, assistive technologies, change, collaboration, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate universities / corporate training, digital learning, education technology, emerging technologies, experimentation, faculty/staff, game-changing environment, generational differences, heutagogy, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, internet, IT in HE, K-12 related, law schools, learner profiles, learning, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning preferences, learning spaces, learning theories, liberal arts, library / librarians, lifelong learning, memory, online learning, online media, online tutoring, Open AI, pedagogy, personalized/customized learning, platforms, productivity / tips and tricks, reading, student-related, teachers, teaching & learning, teaching online, technologies for your home, tools, training / L&D, trends, United States, universities, usability, user experience (UX), vendors, virtual tutoring, vision/possibilities, web-based collaboration, by Daniel Christian

OpenAI’s Atlas: the End of Online Learning—or Just the Beginning? — from drphilippahardman.substack.com by Dr. Philippa Hardman

My take is this: in all of the anxiety lies a crucial and long-overdue opportunity to deliver better learning experiences. Precisely because Atlas perceives the same context in the same moment as you, it can transform learning into a process aligned with core neuro-scientific principles—including active retrieval, guided attention, adaptive feedback and context-dependent memory formation.

Perhaps in Atlas we have a browser that for the first time isn’t just a portal to information, but one which can become a co-participant in active cognitive engagement—enabling iterative practice, reflective thinking, and real-time scaffolding as you move through challenges and ideas online.

With this in mind, I put together 10 use cases for Atlas for you to try for yourself.
…

6. Retrieval Practice
What: Pulling information from memory drives retention better than re-reading.
Why: Practice testing delivers medium-to-large effects (Adesope et al., 2017).
Try: Open a document with your previous notes. Ask Atlas for a mixed activity set: “Quiz me on the Krebs cycle—give me a near-miss, high-stretch MCQ, then a fill-in-the-blank, then ask me to explain it to a teen.”
Atlas uses its browser memory to generate targeted questions from your actual study materials, supporting spaced, varied retrieval.

From DSC:
A quick comment. I appreciate these ideas and approaches from Katarzyna and Rita. I do think that someone is going to want to be sure that the AI models/platforms/tools are given up-to-date information and updated instructions — i.e., any new procedures, steps to take, etc. Perhaps I’m missing the boat here, but an internal AI platform is going to need to have access to up-to-date information and instructions.

Chegg CEO steps down amid major AI-driven restructure — from linkedin.com by Megan McDonough

Edtech firm Chegg confirmed Monday it is reducing its workforce by 45%, or 388 employees globally, and its chief executive officer is stepping down. Current CEO Nathan Schultz will be replaced effective immediately by executive chairman (and former CEO) Dan Rosensweig. The rise of AI-powered tools has dealt a massive blow to the online homework helper and led to “substantial” declines in revenue and traffic. Company shares have slipped over 10% this year. Chegg recently explored a possible sale, but ultimately decided to keep the company intact.

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