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.




 

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.

 


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:


 

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:

 

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

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.

 

Entrepreneurship: The New Core Curriculum — from gettingsmart.com by Tom Vander Ark

Key Points

  • Entrepreneurship education fosters resilience, creativity, and financial literacy—skills critical for success in an unpredictable, tech-driven world.
  • Programs like NFTE, Junior Achievement, and Uncharted Learning empower students by offering real-world entrepreneurial experiences and mentorship.

“Entrepreneurship is the job of the future.”

— Charles Fadel, Education for the Age of AI

This shift requires a radical re-evaluation of what we teach. Education leaders across the country are realizing that the most valuable skill we can impart is not accounting or marketing, but the entrepreneurial mindset. This mindset—built on resilience, creative problem-solving, comfort with ambiguity, and the ability to pivot—is essential in startups, as an intrapreuer in big organizations, or as a citizen working for the common good.

 

Where are tomorrow’s teachers? Education degrees drop over 2 decades. — from k12dive.com by Anna Merod
Declines came in both bachelor’s and master’s degrees awarded between 2003-04 and 2022-23, an AACTE analysis of federal data shows.

The number of education degrees awarded in the U.S. steadily decreased in the nearly two decades between 2003-04 and 2022-23, according to a new analysis of federal data by the American Association of Colleges for Teacher Education.

Bachelor’s degrees in education dipped from 109,622 annually to 90,710 while master’s degrees declined from 162,632 to 143,669 in that time span, AACTE said in its report on data from the U.S. Department of Education.

 

Digest #182: How To Increase (Self-)Motivation — from lifehack.org by Carolina Kuepper-Tetzel

No matter whether you are a student or a teacher, sometimes it can be difficult to find motivation to start or complete a task. Instead, you may spend hours procrastinating with other activities and that opens an unhelpful cycle of stress and unhappiness. Stressful environments which are common in educational settings can increase the likelihood of maladaptive procrastination (1) and hamper motivation. This digest offers four resources on ways to think about and boost (self-)motivation.

Also see:

 

There is no God Tier video model — from downes.ca by Stephen Downes

From DSC:
Stephen has some solid reflections and asks some excellent questions in this posting, including:

The question is: how do we optimize an AI to support learning? Will one model be enough? Or do we need different models for different learners in different scenarios?


A More Human University: The Role of AI in Learning — from er.educause.edu by Robert Placido
Far from heralding the collapse of higher education, artificial intelligence offers a transformative opportunity to scale meaningful, individualized learning experiences across diverse classrooms.

The narrative surrounding artificial intelligence (AI) in higher education is often grim. We hear dire predictions of an “impending collapse,” fueled by fears of rampant cheating, the erosion of critical thinking, and the obsolescence of the human educator.Footnote1 This dystopian view, however, is a failure of imagination. It mistakes the death rattle of an outdated pedagogical model for the death of learning itself. The truth is far more hopeful: AI is not an asteroid coming for higher education. It is a catalyst that can finally empower us to solve our oldest, most intractable problem: the inability to scale deep, engaged, and truly personalized learning.


Claude for Life Sciences — from anthropic.com

Increasing the rate of scientific progress is a core part of Anthropic’s public benefit mission.

We are focused on building the tools to allow researchers to make new discoveries – and eventually, to allow AI models to make these discoveries autonomously.

Until recently, scientists typically used Claude for individual tasks, like writing code for statistical analysis or summarizing papers. Pharmaceutical companies and others in industry also use it for tasks across the rest of their business, like sales, to fund new research. Now, our goal is to make Claude capable of supporting the entire process, from early discovery through to translation and commercialization.

To do this, we’re rolling out several improvements that aim to make Claude a better partner for those who work in the life sciences, including researchers, clinical coordinators, and regulatory affairs managers.


AI as an access tool for neurodiverse and international staff — from timeshighereducation.com by Vanessa Mar-Molinero
Used transparently and ethically, GenAI can level the playing field and lower the cognitive load of repetitive tasks for admin staff, student support and teachers

Where AI helps without cutting academic corners
When framed as accessibility and quality enhancement, AI can support staff to complete standard tasks with less friction. However, while it supports clarity, consistency and inclusion, generative AI (GenAI) does not replace disciplinary expertise, ethical judgement or the teacher–student relationship. These are ways it can be put to effective use:

  • Drafting and tone calibration:
  • Language scaffolding:
  • Structure and templates: ..
  • Summarise and prioritise:
  • Accessibility by default:
  • Idea generation for pedagogy:
  • Translation and cultural mediation:

Beyond learning design: supporting pedagogical innovation in response to AI — from timeshighereducation.com by Charlotte von Essen
To avoid an unwinnable game of catch-up with technology, universities must rethink pedagogical improvement that goes beyond scaling online learning


The Sleep of Liberal Arts Produces AI — from aiedusimplified.substack.com by Lance Eaton, Ph.D.
A keynote at the AI and the Liberal Arts Symposium Conference

This past weekend, I had the honor to be the keynote speaker at a really fantstistic conferece, AI and the Liberal Arts Symposium at Connecticut College. I had shared a bit about this before with my interview with Lori Looney. It was an incredible conference, thoughtfully composed with a lot of things to chew on and think about.

It was also an entirely brand new talk in a slightly different context from many of my other talks and workshops. It was something I had to build entirely from the ground up. It reminded me in some ways of last year’s “What If GenAI Is a Nothingburger”.

It was a real challenge and one I’ve been working on and off for months, trying to figure out the right balance. It’s a work I feel proud of because of the balancing act I try to navigate. So, as always, it’s here for others to read and engage with. And, of course, here is the slide deck as well (with CC license).

 

The above posting on LinkedIn then links to this document


Designing Microsoft 365 Copilot to empower educators, students, and staff — from microsoft.com by Deirdre Quarnstrom

While over 80% of respondents in the 2025 AI in Education Report have already used AI for school, we believe there are significant opportunities to design AI that can better serve each of their needs and broaden access to the latest innovation.1

That’s why today [10/15/25], we’re announcing AI-powered experiences built for teaching and learning at no additional cost, new integrations in Microsoft 365 apps and Learning Management Systems, and an academic offering for Microsoft 365 Copilot.

Introducing AI-powered teaching and learning
Empowering educators with Teach

We’re introducing Teach to help streamline class prep and adapt AI to support educators’ teaching expertise with intuitive and customizable features. In one place, educators can easily access AI-powered teaching tools to create lesson plans, draft materials like quizzes and rubrics, and quickly make modifications to language, reading level, length, difficulty, alignment to relevant standards, and more.

 

 

10 Tips from Smart Teaching Stronger Learning — from Pooja K. Agarwal, Ph.D.

Per Dr. Pooja Agarwal:

Combining two strategies—spacing and retrieval practice—is key to success in learning, says Shana Carpenter.


On a somewhat related note (i.e., for Instructional Designers, teachers, faculty members, T&L staff members), also see:

 
© 2025 | Daniel Christian