teachers

New: Essential Resources for Special Education [edutopia.org]

On 10/13/2026, in assistive technologies, Bias | Diversity Equity & Inclusion (DE&I), education, engagement / engaging students, instructional design, K-12 related, learning, learning ecosystem, Learning Experience Design, parents/guardians, productivity / tips and tricks, professional development, student-related, teachers, tools, United States, vendors, youth, by Daniel Christian

New: Essential Resources for Special Education — from edutopia.org

We’ve gathered advice for teachers on managing student accommodations, navigating IEPs, and much more, as well as ideas for administrators on how to support teachers in this work.

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Several teaching-related articles and ideas from edutopia.org

On 10/08/2026, in art, creativity, culture, education, ideas, instructional design, K-12 related, learning, learning ecosystem, Learning Experience Design, library / librarians, metacognition / metacognitive skills, pedagogy, reading, skills, student-related, teachers, teaching & learning, United States, youth, by Daniel Christian

How Book Cover Keychains Boosted Our School’s Culture of Reading — from edutopia.org by Carsyn Smothers
This clever idea, which came from a librarian’s TikTok, is easy to carry out and encourages lively conversations about books.

Last year, I came across a TikTok that instantly caught my attention. School librarian Lauren Mobley explained how she managed to insert specially designed book covers into keychains, which students could attach to their backpacks and show off to their friends. Mobley created the book cover designs in Canva, she said, and then purchased a batch of keychains.

I loved the idea. I also wondered whether the keychains could be more than a fun craft or a decoration. Could they additionally serve as a reader advisory tool?

How Good Teachers Get Even Better — from edutopia.org by Youki Terada
Like elite athletes and musicians, even outstanding teachers have room to grow. Here are 6 research-based ways to keep sharpening your skills.

Effective teaching, then, is less about executing a set of prescribed strategies and more about developing the “informed judgment” necessary to “engage in complex decision-making and practice,” the researchers note. For example, watching how a master teacher delivers a lesson or handles difficult moments in the classroom, and then rehearsing those moves while getting feedback from coaches, allows for authentic “feedback in the moment” along with quick hints on “how to elevate instruction.”

That kind of expertise doesn’t happen automatically; it develops when teachers take the long view and engage, over many years, in a disciplined course of deliberate practice, identifying a set of skills they want to improve and then making the time to reflect on and practice them.

Arts-Integrated Outdoor Lessons for Elementary Students — from edutopia.org by Charlene Lutz
A pumpkin can become an entire unit if you let it: These engaging fall activities encourage students to slow down and learn from what’s around them.

October is one of my favorite times to take learning outside.

There is so much already happening in the environment that we really do not need to create an elaborate setup. Leaves are changing, seed pods are drying out, sticks and pine cones are everywhere, and pumpkins are suddenly easy to find. I have found that these ordinary seasonal materials can lead to some of the richest learning experiences because students are able to observe, move, touch, collect, build, draw, measure, and ask questions all within the same lesson.

Here are three October investigations I have found especially easy to adapt across K–5.

A 4-Step Plan for Promoting Metacognition in Middle School — from edutopia.org by Kasey Short
Thinking about how they think helps students develop an essential skill that supports their academic success and independence.

In middle school, as students gain independence and are given increased responsibility, it’s an essential time to explicitly teach metacognitive skills. Middle school is often the first opportunity for students to move from one class to another and interact each period with a new teacher who has their own style and set of expectations. Students also move from concrete to abstract thinking while managing long-term assignments, preparing for assessments, revising writing, and solving increasingly complex problems. When students are instructed to study, revise, prepare, and more, they need tools to make effective decisions about those tasks and useful strategies to manage their additional responsibilities.

Metacognition is an essential part of providing students with the tools and strategies they need to be successful in middle school. Work with metacognition is best used as a regular classroom practice that can be implemented by naming it, modeling, providing students with language to discuss their thinking, and creating consistent opportunities for students to engage with this skill and see its impact on their learning.

Tech & Learning Announces Winners of Best for Back to School 2026 — from techlearning.com by TL Editors
This annual award celebrates the products that offer schools versatility, value, and solutions to specific problems to support innovative, effective teaching and learning.

The 2026-27 school year is off and running, and it’s already shaping up to be another pivotal year for education. While AI remains a massive topic, the biggest headline this fall is the screentime debate, hands down. Communities nationwide—including the country’s two largest school districts—are advocating for strict limitations and outright bans to reclaim screen-free classrooms.

Yet, if there’s one constant in education, it’s resilience. We adapt, we evolve, and we keep going because at the heart of it all, we want what’s best for our students. Instead of a setback, this heightened scrutiny around screentime and AI has forced the edtech community to be better. It demands that the tools we bring into the classroom are safe and built to inspire active creation rather than passive consumption.
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How to Reduce Cognitive Load in Digital Lessons — from educationtechnologysolutions.com by etsmagazine

A digital lesson can be beautifully designed and still make learning unnecessarily hard.

Students may be asked to watch a video, remember an instruction, find a link, switch tabs, interpret unfamiliar icons and submit a response—all before they have dealt with the idea the lesson was meant to teach.

That friction is often mistaken for rigour. It is not. Productive difficulty comes from thinking about the content. Avoidable difficulty comes from navigating the lesson.

The goal is not to make learning effortless. It is to spend students’ limited attention on the knowledge and skill that matter.

The above article links to:

Managing cognitive load optimises learning — from edresearch.edu.au
Implications for policymakers

The Case for Prioritizing Play in Kindergarten [Swartz]

On 09/14/2026, in education, education reform, ideas, instructional design, K-12 related, learning, learning ecosystem, Learning Experience Design, play, relationships, student-related, teachers, Uncategorized, United States, vision/possibilities, youth, by Daniel Christian

The Case for Prioritizing Play in Kindergarten — from the74million.org by Mark Swartz
Laura Bornfreund on how schools, families and policymakers can transform kindergarten to better support young children.

In order for these years to lay a sturdy foundation for everything that follows, the kindergarten experience should prioritize play and relationship-building, including connections with peers and teachers. Over the years, however, kindergarten has become increasingly “schoolified,” according to Bornfreund…

The book laments the state of kindergarten today, where classroom experiences are overly scripted and funding is insufficient in many communities. At the same time, Bornfreund finds teachers who are providing meaningful experiences for young learners against the odds. In the conversation below, she shares her perspective on what a strong kindergarten experience looks like and offers insights on how schools, families and policymakers can reshape kindergarten to help children thrive.

Tips for teachers from edutopia.org

On 08/25/2026, in education, Emotion, engagement / engaging students, ideas, instructional design, K-12 related, learning, learning ecosystem, Learning Experience Design, pedagogy, productivity / tips and tricks, reading, research, science, skills, student-related, teachers, writing, youth, by Daniel Christian

Exceptional Videos of Authors Reading Their Books Aloud for Young Students — from edutopia.org by Kristin Rydholm
These 14 books can help teachers celebrate student writing by weaving literacy and social and emotional learning into the school day.

This classroom scenario is an example of how finishing a piece of writing is a dual celebration—an ending and a beginning. A published piece of writing means crossing a finish line as the culminating event within the writing process, but it is also a starting line, where a story begins a journey of its own—being read, seen, heard, and shared by others.

Who better to assist with modeling these transitional and celebratory moments than 14 professional authors of picture books?

Where to start
Featured below are links to exceptional authors and author/illustrators reading their picture books. Watching these videos, a child can see and hear the diverse faces and voices of authors who have prioritized stories about kids like them.

4 Ways to Encourage Great Questions in the Science Classroom — from edutopia.org by Katie Budrow
Here’s how a middle school teacher guides students to proactively ask and answer questions like ‘why does that happen?’

Narrow, prescribed tasks are known as convergent tasks. Define the parts of a cell has a specific answer. Sometimes, convergent tasks make the most sense. But whenever possible, I prefer to use broader divergent tasks, which allow for multiple ways to approach the learning. Describe the different ways that cell parts can work together to form a system is an example of a divergent task.

Divergent tasks inherently drive more student questions, since the answers aren’t just one-and-done. Divergence promotes “deep thinking, requiring students to analyze and evaluate concepts,” according to a study on the subject. Students are not just trying to find the “best” answer—they’re working toward a more complex concept.

A First-Week Routine That Gets Middle School Students Thinking Like Scientists — from edutopia.org by Bexaida Buzzie
Here’s a day-by-day plan for guiding your students to start the year by asking questions. Just resist the urge to answer them.

I realized I was spending so much of my time going over my classroom rules that I forgot that the students were there to learn how to learn.

Once I took the pressure off myself, everything changed. Instead of focusing on perfection, I started to focus on curiosity and fun. Instead of cramming information and reaping frustration, I slowed down.

Here’s what my first five days look like, and how they build a foundation for scientific thinking.

15 Effective Ways to Manage Dysregulated Students — from edutopia.org by Andrew Boryga
Teachers are seeing more big emotions and disruptive behavior in early elementary classrooms. These practical strategies can help youngsters reflect, reset, and repair.

While many experts cite the pandemic’s role in creating skill deficiencies, it’s only a part of the story. Educators also point to major changes in the culture around child rearing, pointing to issues like rising screen time, less play, and fewer opportunities for face-to-face interaction—“developmental needs that no digital program, however sophisticated, can fully replicate,” writes elementary school teacher Cara Zelas.

Serious behavioral issues and developmental concerns require broad support from administrators, specialists, and families. But for everyday moments that derail lessons—a child melting down, refusing directions, or struggling to rejoin the group—many teachers find that simple practices, consistently applied, can help turn big feelings into moments of growth instead of lost instructional time.

“Using AI to create the practice opportunities online students need” [Miller Perkins] + other items re: AI in our learning ecosystems

On 08/19/2026, in 21st century, 24x7x365 access, adjunct faculty, adult learning, Artificial Intelligence/Agents/LLMs/and Related, assessment, business, career development, colleges, communications, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, education, education technology, emerging technologies, Emotion, engineering, experimentation, faculty/staff, game-changing environment, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, leadership, learning, learning agents, learning ecosystem, Learning Experience Design, learning spaces, liberal arts, mathematics, online learning, personalized/customized learning, productivity / tips and tricks, professional development, student-related, teachers, teaching & learning, technologies for your home, tools, training / L&D, UK, United States, universities, vendors, workplace, youth, by Daniel Christian

Using AI to create the practice opportunities online students need— from timeshighereducation.com by Kathy Miller Perkins
For disciplines that depend on interpersonal skills such as communication, leadership, negotiation and mediation, AI can provide elusive experiential learning, particularly in asynchronous environments

What if AI’s greatest educational value lies not in generating answers but in generating experiences?

The result surprised me. Students did not simply interact with the AI, they meaningfully engaged with it. Many reported that the experience felt valuable precisely because the simulated conversation partner pushed back. Unlike classmates who sometimes hesitate to challenge one another, the AI consistently maintained its position. Students had to work harder, listen more carefully and apply the communication strategies they had spent weeks learning. And, importantly, they practised.

Here’s how to show students what responsible AI use looks like — from timeshighereducation.com by Andrew Firr and Alex Fenton
Well-designed assessments can highlight generative AI’s limitations, where it can provide support and what responsible practice looks like. Andrew Firr and Alex Fenton offer strategies

We have been exploring ways to offer this in our Level 7 module for MSc engineering management students, many of whom come from the Global South. Assessment is built around a practical design problem: students examine how a real campus process operates, where delays occur, evidence they observe and how a feasible redesign might improve the system – in a 3,000-word essay.

They can use AI for planning and providing clarity, but not for generating the evidence on which the analysis rests. Invented observations, measurements, screenshots or unverifiable citations are prohibited. The assessment design reinforces this through a case study, diagram, fact-checking exercise and a short AI use statement.

Requiring an AI use statement encourages students to reflect on their processes. We ask which tool they used, how they used it, how they checked the output and which parts of the work depended on their own evidence and judgement. It reminds them that evidence must be theirs and that citations must be manually verified.

Slow math: Kids may learn more when AI makes them review mistakes — from hechingerreport.org by Jill Barshay and Kristin Fasiang
A randomized experiment involved more than 6,000 Tennessee middle school students learning fractions

In an experiment involving more than 6,000 middle schoolers in Tennessee, students learned slightly more math when an AI tutor walked them through their mistakes and then required them to demonstrate the same skill correctly three times in a row before moving on.
…
The winning combination wasn’t the addition of AI tutoring alone, but AI tutoring plus repetition, with the idea that students needed to stick with the skill to demonstrate some level of mastery. The students who practiced math with this AI-enhanced “mastery learning” approach scored about 3 percentage points higher than students receiving conventional computerized instruction. The advantage was small.

I Built a Team of AI Bots That Write Feedback Better than Me. Here’s How. — from drphilippahardman.substack.com by Dr Philippa Hardman
Aka, how to make learners love AI-assisted feedback, rather than loathe it.

This wasn’t hidden from the cohort. For reasons I’ll come to below, I always tell my cohorts at the very start that an AI assistant will be helping me draft their feedback. The aim wasn’t to remove me from the process, but to find out whether AI could help me to deliver feedback at a volume and quality that I simply couldn’t maintain without AI.

Spoiler: the experiment worked — but not for the reason I expected. In this post, I’ll share exactly what I built, tell you how to build a version for your course and reveal the three conditions that decide whether learners trust AI-assisted feedback or quietly stop reading it.

TL;DR: the spec for my feedback assistant is long not because the model needs persuading, but because it’s where my judgement lives. Every rule in it is a decision AI would otherwise make by itself, with limited expertise. A spec doesn’t make the model smarter — it makes expertise and judgement legible enough for the model to follow.

Of the five stages of AI grief, some managers are stuck in denial— from timeshighereducation.com by Shadi Mohamed
Acceptance is not surrender. It is about getting beyond a policing obsession and rethinking what assessment aims to measure, says Shadi Mohamed

In that moment of institutional blindness, it struck me: universities are not merely struggling with a technological adoption curve. They are grieving the demise of the modern university’s economic and institutional logic.

To understand the scale of this threat posed by AI, consider what the internet did to journalism. Newspapers thrived by bundling together classified advertising with quick news hits, sports scores and opinion columns, using that reliable revenue to fund the expensive social necessity of investigative reporting. The rise of internet advertising did not kill journalism outright but it shattered the bundle, leaving the expensive core product without its historical financial engine.

Universities operate on a similar logic, bundling content delivery, assessment, credentialling, research and professional formation. But generative AI is now commodifying the most visible parts of that package. When AI can deliver personalised explanations instantly and generate the essays and reports we use to measure student capability, the traditional degree loses its role in the labour market as a proxy for understanding. If the bundle breaks, the economic model that funds our deeper purposes is in peril.

As fewer young people choose college, this district wants to ensure they have career options — from hechingerreport.org by Ariel Gilreath
In Niagara Falls, New York, a town with shrinking job options, students are encouraged to consider their careers in ninth grade

At Niagara Falls High School, students are encouraged to consider their careers upon arrival in ninth grade. By 11th grade, every student at the school must pick from one of five pathways, ranging from business and finance to design and engineering. The shift toward career education comes as about one-third of seniors at Niagara Falls High are rejecting college and instead choosing to enter the workforce after graduation, compared with roughly a quarter a decade ago, said Superintendent Mark Laurrie, who retired in June. In a town that’s struggled with population declines, where now-shuttered manufacturing plants once dominated the local labor market, there’s an urgency to prepare high school students for careers.

“It’s important to give them hope for the future with a career pathway — a career, not a job — to have something to aspire to and, hopefully, keep them in the city and in the state,” Laurrie said.

“Paying vendors for student results” [Barshay] From DSC: This could be tough to do. But it’s an interesting posting.

On 08/10/2026, in education, education reform, education technology, emerging technologies, learning, learning ecosystem, strategy, teachers, United States, vendors, by Daniel Christian

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

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

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

How to Design Around Cognitive Offloading [Hardman]

On 08/10/2026, in corporate universities / corporate training, emerging technologies, faculty/staff, instructional design, learning, Learning Experience Design, learning theories, productivity / tips and tricks, professional development, research, teachers, teaching & learning, training / L&D, by Daniel Christian

How to Design Around Cognitive Offloading — from drphilippahardman.substack.com by Dr Philippa Hardman
Three new studies shed light on when offloading to AI harms learning, when it helps — and how to design for the difference

A cluster of new studies — most published in the last few weeks in the International Journal of Educational Technology in Higher Education — lets us answer two questions with more precision than ever before:

When does cognitive offloading actually happen?
When does using AI improve cognition?

The answers in turn help us to start to design learning which intentionally uses AI to drive – rather than diminish – learning.
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What Nobody Warns You About Teaching College for the First Time [Morales]

On 08/10/2026, in adjunct faculty, colleges, community colleges, education, faculty/staff, higher education, ideas, instructional design, K-12 related, learning ecosystem, Learning Experience Design, teachers, teaching & learning, United States, universities, vendors, by Daniel Christian

What Nobody Warns You About Teaching College for the First Time — from facultyfocus.com by Christopher Morales; this article is behind a firewall

What became clear throughout these conversations was that secondary and postsecondary education often prioritize very different instructional skill sets.

In K–12 education, teachers frequently receive formal preparation in:

classroom management,
scaffolding,
differentiation,
assessment design,
engagement strategies,
and developmental learning theory.

In higher education, disciplinary expertise is often treated as the primary qualification for teaching.

Yet many instructors pointed out that expertise alone does not automatically translate into effective instruction.

Also from Faculty Focus, see:

The Syllabus and the Scar Tissue: What Leadership Preparation Programs Leave Out and Why It Matters — from facultyfocus.com Andy Szeto, EdD; this article is also behind a firewall

Will this new company be the largest company on the Internet by 2030? [Christian]

On 08/01/2026, in 21st century, 24x7x365 access, adult learning, Artificial Intelligence/Agents/LLMs/and Related, Bias | Diversity Equity & Inclusion (DE&I), career development, cloud-based computing / apps / other cloud-related, communities of practice, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, cost of getting a degree, credentialing, curriculum, Daniel S. Christian, digital learning, disruption, education, education technology, elearning, emerging technologies, engagement / engaging students, future, future of higher education, game-changing environment, generational differences, global, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, informal learning, innovation, instructional design, intelligent systems, intelligent tutoring, internet, 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, lifelong learning, love of learning, more voice more choice more control, motivation, online learning, online media, online tutoring, pathways, personalized/customized learning, platforms, productivity / tips and tricks, professional development, reinvent, society, staying relevant, student-related, teachers, teaching & learning, training / L&D, United States, vision/possibilities, web-based collaboration, youth, by Daniel Christian

From DSC:
The vision that I’ve been tracking for well over a decade begins with this graphic:
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Could LearnVector be this next-generation company/platform? Perhaps. Time will tell.

Per Matt Tower via The EdSheet Vol. 38 dated 7/31/26:

Coursera bets $100M on its own co-founder: Andrew Ng’s new venture LearnVector lands one of the largest single checks in edtech this year — from Coursera, the company he founded 14 years ago.
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LearnVector.ai

What China’s Calligraphy Lessons Can Teach Us About AI — from linkedin.com by Rebecca Winthrop

He recalled visiting a primary school classroom in China several years ago where students were practicing calligraphy—the centuries-old art of writing Chinese characters with brush and ink. While the scene appeared entirely traditional, there was something innovative happening beneath the surface. Embedded in students’ desks was an AI system capable of providing immediate feedback on their brushwork, noting misplaced strokes and suggesting corrections.

The image is striking. Students were learning in much the same way generations before them had learned—brush in hand, immersed in a deeply human and cultural practice. Yet AI was quietly enhancing the experience by providing immediate, personalized feedback that would have been difficult for any teacher to provide to her whole class.

That example captures something important for me. The most promising uses of AI may not be the applications that place technology front and center, but those that support learners to do what they have always done: connect with educators, practice with concentration, and learn and grow.

AI Can Build Your Course, but Can it Design the Learning? — from drphilippahardman.substack.com by Dr. Philippa Hardman
Aka, the current state of AI’s instructional design ability & what it means for L&D

So these models have learned design artefacts in extraordinary volume and design method barely at all. They know what e-learning looks like. They have very little access to why any of it looks that way and whether it actually works or not.

That produces a completely consistent behaviour: ask an LLM for an e-learning module and it generates the statistical centre of every e-learning module it has ever seen. What AI produces isn’t the output of a design process. It’s the output of a sampling process — the statistical centre of every e-learning module it has ever seen.
…
So the honest conclusion isn’t that AI can design learning; it’s that AI executes design well when someone who already knows what to ask for is doing the asking and the checking.

This finding gives us a clearer division of labour than we’ve had before and with it a clearer picture of what the AI-enhanced workflow might look like:

The Pedagogy of Trading Places: Lessons from an Unexpected Role Reversal with AI — from facultyfocus.com by Sherrie Myers Bartell, PhD

These disruptions matter. They remind us that teaching is not a static identity but a dynamic posture. They show us that our pedagogical selves are not fixed; they are responsive to context, energy, and attention. They reveal that the qualities we value most in our teaching—curiosity, metaphor, play, and expansiveness—are not automatic. They require care and cultivation.

The AI didn’t “teach” me in the traditional sense. But it did something pedagogically adjacent: it surprised me back into myself.

The AI-native university, AI literacy, AI and accessibility + other items re: AI in our learning ecosystems

On 07/22/2026, in 21st century, 24x7x365 access, accessibility / UDL, Artificial Intelligence/Agents/LLMs/and Related, colleges, communities of practice, community colleges, corporate / business world, corporate universities / corporate training, data related items, education technology, emerging technologies, experimentation, faculty/staff, game-changing environment, generational differences, higher education, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, learning, learning ecosystem, Learning Experience Design, liberal arts, lifelong learning, personalized/customized learning, productivity / tips and tricks, student-related, teachers, teaching & learning, training / L&D, trends, United States, universities, by Daniel Christian

AI & Accessibility: 5 Practical Ways to Use LLMs to Support Inclusive Learning — from learningguild.com by Dr. Athena Joyce Stanley (B.A., M.A.E., Ph.D.)

The following strategies focus on how instructional designers can design for accessibility by embedding or enabling AI-supported tools within learning experiences. These approaches move beyond access to content and begin to support access to understanding, expression, and participation.
…
Personalized Clarification Through AI Copilots
Learners often need additional explanation, but may hesitate to ask questions in live sessions or require more individualized support.

Instructional designers can integrate AI copilots, LLM-powered conversational interfaces, into learning environments to provide on-demand clarification. These tools can act as digital coaches, helping learners understand concepts through simplified explanations and relevant examples.

This approach supports learners who benefit from additional processing time and personalized guidance.

Sample Prompt (for IDs Configuring Copilot Behavior)
You are a workplace learning coach.

Explain the following concept in a clear, simple way:

- Use plain language
- Provide one practical, job-relevant example
- Avoid jargon unless necessary (and define it if used)

Then ask one follow-up question to check for understanding.

Jeff’s posting on LinkedIn.

Teaching AI Literacy with Susan Ray — from intentionalteaching.buzzsprout.com by Derek Bruff and Susan Ray

Per Derek Bruff:
In my conversation with Susan, we talk about that syllabus activity, as well as the AI transparency journals she asks her students to keep during her courses. We also talk about how her personal background prepared her to navigate the challenges and opportunities that AI has posed to her teaching, how she approaches assessing student learning in this age of AI—especially in her online asynchronous courses—and much more.

Building the AI-Native University: Student Success and Lifelong Learning — from coursera.org

In this episode, you’ll discover:

Why building an AI-native campus requires a data-first foundation
How to build an “achievement architecture” for lifelong success
How faculty-built AI tutors cut one program’s course attrition from 40% to 10%
What it means to be a lifelong learning companion

We’re Raising the First AI Generation. They’re Pushing Back. (Rebecca Winthrop, Brookings) — from humanistxyz.substack.com by Allison Dulin Salisbury
“Young people harbor real anger about AI because they’re already experiencing its consequences in their schools, relationships, job prospects, and feeds.”

As Rebecca told me:

“Kids harbor real anger. They’re pissed about climate impacts. They’re upset about job prospects. They’re outraged about AI being used to plagiarize writing and produce counterfeit artwork. Their relationships are being affected, and they’re seeing deepfakes in their feeds.”

Our conversation explores what follows from taking those concerns seriously. We discuss cognitive stunting, the case for small, purpose-built AI models over frontier models in education, why students should spend far more time in explorer mode, and how schools can cultivate agency, curiosity, and independent thinking in an age of AI.

The interview ends with one of Rebecca’s most practical recommendations: every school should have a student AI council, not as a symbolic gesture, but with real influence over the tools their schools adopt, the ways they’re used, and the data students are asked to hand over.

Every generation of technology seems to relearn the same lesson: build with people, not for them. AI should be no exception.

Learning Ecosystems

“Paying vendors for student results” [Barshay] From DSC: This could be tough to do. But it’s an interesting posting.

How to Design Around Cognitive Offloading [Hardman]

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