vendors

Escaping The Backrooms Of Workforce Development — by Ryan Craig

Which makes sense. Because far too many find themselves in a liminal space, neither in school nor a career. Needing to make a living in an era of digital transformation and AI, they’re having a horrific time finding their way into and around work. So it’s not just education and training wonks who think workforce is the defining issue of our time. The success of Backrooms demonstrates Gen Z thinks so, too.

It’s happening everywhere. Young people around the world are angry at how hard it’s become to launch careers. This summer an entire protest movement arose in India – the world’s largest Gen Z population – around entrance exams for medical school, one of the few remaining sure bets. In the UK, youth unemployment is over 16%; it’s 15% across the EU and over 25% in Sweden. Back home, nearly 400,000 young Americans stopped looking for work in June alone. So it’s urgent that we identify what actually works to help young people get good first jobs.

The answer lies between apprenticeship perfection and train-and-pray scale. We desperately need a scalable training-first model that’s as proximate as possible to employment opportunities, employers, and actual employment. That can only mean work-based learning: real work experience completed during or connected with a training, certificate, or degree program. Work-based learning can take many forms: rotations, clinics, co-ops, internships, short projects. It can be integrated into coursework or independent. But what all forms require are bona fide employers, which regulate scale. Such programs can enroll only as many as can fit within the constraint of available work-based learning opportunities.

Also see:

Is Your College A Zombie? — from forbes.com by Ann Kirschner; via Ryan Craig

I want to be careful here, because this is not an argument that universities are doing nothing. They are doing an enormous amount. New programs, AI task forces, employability frameworks, microcredentials, and shifts in how they enable lifelong learning.

Activity is not the problem; what has not changed is the machinery that decides what counts. Too many institutions move in herds rather than forging an independent path. When one college launches a new program, say, data science and AI, fifty will follow without asking whether their version serves their students or simply checks a competitive box.

Meanwhile, 88% of American professionals believe colleges and universities should be the ones providing AI training, and nearly half say their employers have offered no AI resources whatsoever.¹

We are at a tipping point. In the next 25 years, technologies like AI, clean energy, and bioengineering are poised to reshape society on a scale few can imagine.

Peter Leyden draws on decades of observing technological revolutions and historical patterns to show how old systems collapse, new ones rise, and humanity faces both extraordinary risk and unprecedented opportunity.

0:00 We’re on the cusp of an era of progress
0:37 The Great Progression
1:08 What was the ‘Long Boom?’
4:56 How often do these epoch resets happen?
6:12 3 Tipping points
6:39 Artificial Intelligence
7:13 Clean energy technologies
7:32 Biotechnology
9:00 The 80-year cycle
13:27 The Gilded Age
17:50 The Founding Era
22:46 The new enlightenment
32:18 The clean energy revolution
37:13 Bioengineering the genome
39:43 Industrial production vs biological engineering
47:40 What will the future think?

“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.

Student Voices: Technology as a Future Learning Partner — from campustechnology.com by Mary Grush
A Q&A with Eli Blouin and Mark Frydenberg

Key Takeaways

With advanced technologies, we’re moving from accessing learning resources to participating in technology learning partnerships.
Technology learning partners participate in the learning process by asking questions and giving feedback, not just information search results.
Tomorrow’s technology learning partners will understand the whole learner — including knowledge gaps and personal learning style.
Student experiences with AI and other technologies today will inform the next generation of human/machine learning partners.

Grush: What do you think may be among the most meaningful changes in, say, the next five years?

Blouin: When I think of what will improve in the next five years — and I truly believe it’s where we’re ultimately heading — I think it will be the technology learning partner’s ability to gain a full picture of the learner. The technology will be able to take absurd amounts of context — and data — and understand the learner as a whole: where their gaps are, what they need to learn, how they learn, and how to create content tailored to a particular student. In an instant it would be able to assess, to test knowledge, and know the student as a whole person. That would be an ideal learning partner.

“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?

Pathways Phase 2: The Future of Law [LegalTech Fund, Harvey, & Law.com]

On 08/10/2026, in future, ideas, law schools, Legal operations, legal reform, legal technologies, legislatures / government / legal, pathways, vendors, by Daniel Christian

From the LegalTech Fund’s Q2 2026 Update:

Industry Foresight: Following the successful completion of Pathways Phase 1, we launched Pathways Phase 2: The Future of Law in partnership with Harvey and Law.com. Phase 2 brings together a curated cohort of legal industry leaders, innovators, academics, and operators to develop future scenarios and identify the critical legal, regulatory, business, capital, and technology inflection points that may shape the industry through 2040. The resulting framework will serve as a shared strategic tool to help the legal ecosystem navigate uncertainty and prepare for multiple possible futures.

This quote/insight is also for the Instructional Technologists out there

On 08/10/2026, in change, colleges, community colleges, education technology, faculty/staff, higher education, innovation, journalism, United States, universities, vendors, by Daniel Christian

From MLive.com’s John Hiner — in his Letter from the Editor dated 8/6/26:
40 years of change taught me this: It’s never really been about the technology

What I’ve learned over 40 years is that people rarely resist change because they dislike innovation. More often, it’s because they’re worried they’ll lose something they value.

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

A Writer’s Toolkit [Tenore Tarpley & Caplan]

On 08/10/2026, in Artificial Intelligence/Agents/LLMs/and Related, faculty/staff, Google, human-computer interaction (HCI), journalism, Open AI, research, tools, United States, vendors, writing, by Daniel Christian

A Writer’s Toolkit — from wondertools.substack.com by Mallary Tenore Tarpley and Jeremy Caplan
Useful tools for every stage

Per Jeremy Caplan: My friend and colleague Mallary Tenore Tarpley writes an excellent newsletter, Write at the Edge, with helpful writing tips and best practices. She’s a professor, journalist, and author who has written for The New York Times, The Washington Post, and other outlets. She recently published an important debut book, Slip: Life in the Middle of Eating Disorder Recovery.

Mallary recently interviewed me about writing tools. She wrote up a summary of our conversation, highlighting the tools I talked about. I’m turning the rest of this post over to her summary.

Digital Accessibility Lawsuits in 2026: Five Trends Companies Should Know [blog.usablenet.com]

On 07/31/2026, in 21st century, accessibility / UDL, business, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, legislatures / government / legal, marketing/social marketing, policy, United States, universities, vendors, by Daniel Christian

Digital Accessibility Lawsuits in 2026: Five Trends Companies Should Know — from blog.usablenet.com

Here are five findings companies should understand, along with practical steps for reducing risk.

1. Digital accessibility lawsuits are on pace to reach 6,000
2. Where a company sells matters more than where it is headquartered
3. E-commerce remains the primary target
…and more

What’s the Story Your Syllabus Tells?: Setting the Stage for Learning — from facultyfocus.com by Dr. Daniel Andrés Rivera Rosado

But as I was reading Everyday Christian Teaching by Dr. David Smith, in the chapter titled Speaking, Hearing, Hospitality, in just the first paragraph he writes: “Teachers do not simply list course content for learners. They sequence it in ways that imply a story about what fits together and where it is headed.” (2025, p.73). Automatically I asked myself, what is the story my syllabus is telling students? To be completely honest, is it even telling a story at all?

“Is your syllabus helping your students at all?”

From DSC:
To that last sentence, I might add the words engaging, raising curiosity or wonder, or is it interesting to your students at all? Is there a “hook” that gets them interested? It might be a central question or two — and/or use some beneficial and relevant graphics. I’ve heard faculty use digital/interactive syllabi as well to engage their students.

The image model race just split into four lanes –> find which model fits your work [Cooper]

On 07/22/2026, in art, Artificial Intelligence/Agents/LLMs/and Related, creativity, design, digital video, emerging technologies, experimentation, Google, graphics, platforms, tools, United States, vendors, by Daniel Christian

The image model race just split into four lanes –> find which model fits your work — from heatherbcooper.substack.com by Heather B. Cooper

In today’s edition:

Stop asking which image model is “best” – the top 4
Seedream 5.0 Pro’s layer trick
Image & Video Prompts

Steward Stories: How Heart of Oregon Corps Turns Service into Careers — from gettingsmart.com by Karen Pittman and Merita Irby

Our “Steward Stories” series captures lessons learned from interviews with leaders of mature, purpose-built ecosystem intermediaries. An ecosystem steward is a boundary-spanning leader who goes beyond traditional out-of-school time (OST) system building to weave together the diverse people, places, and possibilities that shape a young person’s daily life. Rather than managing a single isolated network, stewards collaborate across K-12 schools, youth development programs, and workforce systems to build vibrant, equitable learning ecosystems. They drive systemic change from practice to policy by creating purpose-built intermediaries, developing scalable cross-system training tools, and championing “Future Features” of learning. These core priorities include promoting learner agency, institutionalizing “unwalled” schools that connect community resources to formal education, broadening the definition of educators to include informal mentors, and normalizing pathways for students to receive school credit or credentials for out-of-school learning.

The starting points, paths, and targets set by these stewards are as varied as the conditions and opportunities present within their communities. But they share similarities in vision and approach. Learn More Here.

Learning ecosystems may be found anywhere, but it takes careful stewardship to help them thrive.
— Shift, Remake Learning

Microsoft Discovery Platform Brings Agentic AI to Scientific Research [Paoli]

On 07/14/2026, in Artificial Intelligence/Agents/LLMs/and Related, colleges, community colleges, emerging technologies, faculty/staff, higher education, intelligent systems, Microsoft, platforms, research, science, STEAM-related, tools, United States, universities, vendors, by Daniel Christian

Microsoft Discovery Platform Brings Agentic AI to Scientific Research — from campustechnology.com by Chris Paoli

Key Takeaways

Microsoft Discovery reaches general availability, bringing agentic AI to scientific research and development workflows.
AI agents support hypothesis generation, experimentation, data analysis, and knowledge management at scale.
New Discovery app preview enables researchers to explore AI-driven scientific discovery with lower adoption barriers.

LEGAL FUTURISMS: Consumer Legal Tech and the Soul of US Democracy

The “Dollar Legal” Thought Experiment

What if the salvation of our democratic enthusiasm doesn’t come from a political revolution, but a technological one? Enter the thought experiment of Dollar Legal.

Imagine a ubiquitous, consumer-facing legal tech platform—accessible from any smartphone—that commoditizes basic legal defense and assertion of rights. It is AI-driven legal agency for the masses, costing no more than a cup of coffee, or perhaps literally a single dollar.

Dollar Legal wouldn’t exist to litigate complex corporate mergers; it would exist to handle the agonizing friction of everyday survival. It instantly analyzes a notice to quit, drafts a legally sound response asserting warranty of habitability defenses, and files it electronically. It forces the bureaucratic machine to pause. It translates the raw, terrifying human experience of a legal threat into the cold rules and procedures that the justice system understands.

And the price, $1.00, at sufficient scale, would support the operation and maintenance of the service.

By deploying Dollar Legal, we fundamentally shift the balance of power. The democratization of legal leverage changes the calculus for bad actors who rely on the silent default judgments of the unrepresented.

Learning Ecosystems

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

Pathways Phase 2: The Future of Law [LegalTech Fund, Harvey, & Law.com]

This quote/insight is also for the Instructional Technologists out there

Digital Accessibility Lawsuits in 2026: Five Trends Companies Should Know [blog.usablenet.com]

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