tools

New tests show that AI can design like an expert Instructional Designer: so what next? [Hardman]

On 10/16/2026, in 21st century, 24x7x365 access, adult learning, Artificial Intelligence/Agents/LLMs/and Related, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, education, education technology, emerging technologies, faculty/staff, future, future of higher education, game-changing environment, generational differences, Google, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, IT in HE, learning, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, Open AI, tools, United States, universities, vendors, vision/possibilities, workplace, by Daniel Christian

Here is Phillipa’s posting on LinkedIn.

Light Bulb Moments from 100 Episodes — from intentionalteaching.buzzsprout.com by Derek Bruff

Per Derek:

Welcome to the 100th episode of Intentional Teaching! I am very excited to reach this milestone, and I am deeply grateful to all my guests and all my listeners for making this possible. I learn so much from my guests, and I’m thrilled to know that folks out there appreciate the interviews and the show.

In this 100th episode, I take a look back at some of the light bulb moments I’ve had interviewing guests over the last four years. What quotes and ideas and examples have really stuck with me and informed my work?

My hope is that you’ll find these moments interesting and perhaps useful to your work in higher education, and that this clip show might interest you in digging into the podcast archives and listening to some older episodes.

Anthropic released a law student plugin. It’s designed to act as a tutor, but it will brief cases, build outlines, predict exam questions based on sample exams, and many other skills.
I’ll show you how to install it in the comments. You should expect your students are using this. You should probably use it for your footnotes.

— Paul Weitzel (@IThinkIAgree) October 13, 2026

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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5 Writing Tools to Get Unstuck [Caplan]

On 10/13/2026, in Artificial Intelligence/Agents/LLMs/and Related, education technology, experimentation, Google, ideas, journalism, tools, United States, vendors, vision/possibilities, writing, by Daniel Christian

5 Writing Tools to Get Unstuck — from wondertools.substack.com by Jeremy Caplan
Dictation, writing sprints, mind maps, AI interviews, and folded paper

The hardest part of writing is the first 10 minutes. Get past that, and momentum kicks in.

Having gotten stuck and unstuck a lot over the past 325 weeks of writing this newsletter, I’ve found a few tricks that help. Pick one to try, and leave a comment to share what you do to get unstuck.

As a little experiment, I’ve made an Unstuck Studio page to accompany this post and to help you get unstuck playfully.

As Daniel Pink explains, starting comes first.

“Action precedes motivation, not the other way around.”

The Top 100 Gen AI Consumer Apps — 7th Edition [Olivia Moore and Andressen Horowitz]

On 10/08/2026, in Artificial Intelligence/Agents/LLMs/and Related, business, corporate / business world, data related items, marketplaces, platforms, society, tools, trends, United States, vendors, by Daniel Christian

The Top 100 Gen AI Consumer Apps — 7th Edition — from a16z.com by Olivia Moore and Andressen Horowitz

The biggest takeaway from this new data? Consumer AI usage is wide, but not very deep…for almost everyone. While nearly half of U.S. consumers now report using AI, only 25% are engaged with it daily. And as of August, just 4.5% of U.S. consumers had an active paid personal subscription to ChatGPT, Gemini, or Claude. You can get more data on broad AI adoption in our State of Markets presentation we shared last week.

However, AI’s consumer power users are extremely engaged — and highly monetizable. The top 10% of spenders account for roughly half of all observed spending. These high spenders disproportionately buy coding, productivity, and creative tools.

In these users, consumer AI has found its first real market: people who pay — often a lot — for tools that help them build, create, and get work done. Reaching everyone else will likely take different products. We’re seeing glimmers of this now with the launch of personal assistants that, unlike their ancestor OpenClaw, are usable by non-developers — and free.

The State of AI Report 2026 — from press.airstreet.com by Nathan Benaich
AI is building AI, physical AI, booming inference, and escalating cyber risks.

For nearly a decade, this report has been a labor of love. My interest in AI began with my PhD in cancer research and computational biology in the early 2010s. Since 2013, I’ve invested in companies building and applying AI to accelerate technological progress. The report is my way of sharing what I’m learning and helping more people understand the research shaping our world.

Every day brings new papers, model releases, and developments in industry and politics. Much of the work goes into deciding what deserves your attention, checking what the evidence supports, debating it with researchers and builders, and explaining why it matters.

Some solid warnings about AI from Blake Montgomery’s recent newsletter:

There is an extensive and ongoing review related to our agents’ use of internet access during training and evaluation. We’ve been publishing summaries at the link below and will continue to.

We have not been as fast as we would have liked but we are trying to balance our desire… https://t.co/8zoMxas5Eq

— Sam Altman (@sama) September 25, 2026

Scoop: Top AI companies probing tens of thousands of security incidents — from axios.com by Madison Mills

OpenAI, Anthropic and security researchers are investigating tens of thousands of incidents in which their frontier models took steps that outside evaluators would consider problematic, sources told Axios.

Why it matters: The sheer number of incidents, which occurred in recent months in internal testing and the real world, indicates that the problem is orders of magnitude more complex than what is publicly known.

The findings, which are surfacing as part of internal work to assess models and in investigations at both companies into model behavior, raise questions about whether either company — or any top model-maker — is currently capable of establishing complete control over its technology.

Key Risk Factors for AI Loss of Control Came Together in 2026 Incident, Independent UN Scientific Panel Finds
Halting this incident is no assurance that humans will keep control of more capable systems

NEW YORK, 21 September 2026 – The Independent International Scientific Panel on AI, established by the UN General Assembly, released its first thematic brief, an assessment of the breach of Hugging Face’s systems by AI agents under evaluation at OpenAI this summer. The Panel, made up of 40 independent experts from all regions, is publishing it as an advance unedited version as world leaders gather in New York for the Assembly’s High-Level Week.

“Researchers have long warned that three conditions could lead to loss of control: a misaligned goal, the capability to pursue it, and an environment that allows it. This summer, all three came together in a real system, not a laboratory. Since this is not an isolated observation of misaligned goals, this raises serious questions about the way AI agents are currently trained.” – Yoshua Bengio, Co-Chair of the Panel and Turing Award laureate

Meta’s New Muse AI Agent Read My Private Messages. I Never Asked It To — from inc.com by Jason Aten
Permission isn’t the same and what a user actually expects your AI product will do with their personal information.

That obviously requires a certain amount of trust. An AI agent isn’t especially useful if it can’t see your files, interact with your apps, or understand what you’re working on. Meta says Muse is designed around that reality, while still putting users in control of what it can access.

At least, that’s what I thought.

Not only had I not asked it to do that sort of thing, I never gave it permission to read my messages. In fact, I remember explicitly choosing not to let it have access to my messages, calendar, and other personal information.

Although not from Blake, also see this free/gifted article out at the Washington Post:

ChatGPT-maker’s AI inappropriately probed federal government websites — from washingtonpost.com by Gerrit De Vynck and Nitasha Tiku
OpenAI said that its artificial intelligence agents inappropriately accessed sites for the Commerce Department and the Securities and Exchange Commission.

SAN FRANCISCO — Artificial intelligence technology from ChatGPT maker OpenAI probed U.S. government websites including the Departments of Education and Commerce, researchers said Friday, adding to the growing list of incidents in which OpenAI’s AI agents acted without the company’s knowledge.

The company’s AI agents attempted to hack into the website for the Education Department’s Office for Civil Rights but were not successful, according to a statement Friday from AI research firm Transluce. OpenAI’s software also accessed data from the U.S. Census Bureau using log-in information discovered on the web and copied public information from the Securities and Exchange Commission, a spokesperson for OpenAI said after the Transluce statement.

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 Improve Your AI Skills [Andrade & Caplan]

On 09/19/2026, in Artificial Intelligence/Agents/LLMs/and Related, Google, human-computer interaction (HCI), Open AI, platforms, productivity / tips and tricks, professional development, skills, tools, United States, vendors, by Daniel Christian

How to Improve Your AI Skills — from wondertools.substack.com by Frank Andrade and Jeremy Caplan
What to learn next, from prompts to workflows
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Today I’m sharing a guest post on how to strengthen your AI skills. It’s by Frank Andrade, an AI instructor who has helped thousands of people on Substack master ChatGPT and Claude with beginner-friendly guides and in-depth tutorials.

OpenAI Releases Astra for Law

On 09/19/2026, in 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, emerging technologies, law schools, Legal operations, legal technologies, legislatures / government / legal, Open AI, platforms, tools, United States, vendors, by Daniel Christian

Another day, another frontier AI company moving into legal. First it was @AnthropicAI with Claude for Legal, and now it is @OpenAI, which today announced Astra for Law, a version of its latest GPT-6 Astra model configured for legal work. https://t.co/TqJbfU9tfO

— Bob Ambrogi (@bobambrogi) September 17, 2026

Astra for Law: Frontier intelligence built for your practice.

A new offering powered by GPT-6 Astra with tools, settings, and context to support the expertise and judgment of lawyers and legal technology firms. pic.twitter.com/qxVRXkvp4o

— OpenAI (@OpenAI) September 17, 2026

Will smart glasses make it too risky to speak up in class? — from timeshighereducation.com by Georgia Luckhurst & Kieran Phelan
AI-powered glasses may boost learning but they also pose obvious threats to privacy, academic integrity and the sanctity of the seminar room as a safe space to explore ideas. Are universities doing enough to head off the risks, asks Georgia Luckhurst – while Kieran Phelan suggests they are not

Smart glasses can superimpose information on to a viewer’s field of vision, and they can access apps and communicate with your phone. Some are hands-free while some require touch, and some also respond to voice automation. Most controversially, they can take pictures and record footage, potentially without anyone else knowing that it is happening. And they are becoming ever more common.

But, for academia, the biggest issue associated with smart glasses may be a decline in intellectual risk-taking and freedom of expression, Murray said.

How useful are smart glasses in improving accessibility in higher education? — from timeshighereducation.com by Helen Nicholson-Benn
Smart glasses have the potential to support learning for disabled students, but this technology also comes with significant privacy concerns. Helen Nicholson-Benn looks at how to balance functional benefits with data security and safeguarding

Consider how different models of smart glasses might be used to improve accessibility in higher education. A deaf student might use XRai’s ar2 captioning glasses during a lecture to view live captions in their eyeline, allowing them to follow the content without looking down at a separate screen. A visually impaired student might use Envision’s Ally Solos glasses to generate a description of images on printed material or read text during a class. The glasses provide a hands-free option rather than scanning the materials with their smartphone.

These examples are hypothetical, and smart glasses are far from an everyday teaching tool, but that may be about to change. Smart glasses available today are far more capable than their predecessors, particularly boosted by developments in artificial intelligence (AI) technology.

Which brings up the topic of how to handle these technologies in the classroom:

Are device-free classrooms the way forward? — from timeshighereducation.com by Georgia Luckhurst
US universities embrace laptop and phone bans, but professor suggests policies may be more about political positioning than pedagogy

Growing numbers of US universities are making some of their courses “device free”, drawing mixed enthusiasm from edtech experts.

In the latest move the University of Chicago is introducing a no-laptops and no-phones policy on three of its 15 required undergraduate modules, aiming to “reduce distractions and encourage face-to-face discussions”. Exceptions remain, including for students with disabilities.
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Device-free policies appear in other countries, experts suggested, despite the trend picking up pace in the US.

MIT’s Ad Hoc Committee on AI Use in Teaching, Learning, and Research Training — from aiandeducation.mit.edu

However, what we learned as a group quickly convinced us that the Institute community, particularly the faculty, must tackle a set of deeper questions about the structure, meaning, and value of an MIT education in an era in which AI is one of several factors complicating the Institute’s mission.
…

In this report, we:

Highlight key aspects of the current educational landscape at MIT.
Share eight principles we relied on and that we hope will guide the Institute in the work ahead.
Recommend immediate and long-term actions for both instructors and the administration.

On somewhat related notes:

Your AI Teaching Toolkit — from wondertools.substack.com by Jeremy Caplan
11 prompts to save time and spark ideas
AI Should Accelerate How We Learn About Learning (Rajen Sheth, Kyron Learning) — from humanistxyz.substack.com by Allison Dulin Salisbury
“We shouldn’t have to wait years to find out if an approach works. We can test and learn in weeks.”

How a studio-based format transforms online teaching [via multiple authors from Cranfield University]

On 09/10/2026, in adjunct faculty, collaboration, colleges, communities of practice, community colleges, content development, aggregation, repositories, digital audio, digital learning, digital video, distance education, education technology, engagement / engaging students, experimentation, faculty/staff, higher education, ideas, instructional design, IT in HE, law schools, learning, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, multimedia, online learning, online media, pedagogy, teaching & learning, tools, UK, universities, using teams, vendors, vision/possibilities, by Daniel Christian

How a studio-based format transforms online teaching — from timeshighereducation.com by multiple authors from Cranfield University in England
Online teaching works best when teaching, facilitation and technical delivery are treated as complementary professional roles. Read guidance on studio-based delivery

Our experience of studio-based delivery suggests the need for a different approach. In this model, teaching is delivered as a live, facilitated learning experience in which academics focus on teaching and interaction, while facilitators and production staff manage interaction, session flow and technology.

Responsibilities are intentionally divided to enable more effective online pedagogy: academics concentrate on explaining concepts, facilitating discussion and responding to students while production staff manage the technical environment, transition between activities, recordings, multimedia integration, chat moderation, breakout rooms and troubleshooting, enabling a more engaging and authentic learning experience.

The most transferable lesson is that online teaching works best when teaching, facilitation and technical delivery are treated as complementary professional roles and when it is underpinned by pedagogical design.

“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.

Learning Ecosystems

How a studio-based format transforms online teaching [via multiple authors from Cranfield University]

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