Is the eLearning authoring tool dead? — from linkedin.com by Melissa Milloway & Tim Slade
…which links to the video below:
Is the eLearning authoring tool dead? — from linkedin.com by Melissa Milloway & Tim Slade
…which links to the video below:
Here is Chris Martin’s posting on LinkedIn.com:
Here is Dominik Mate Kovacs’ posting on LinkedIn.com:
The AI ‘hivemind’: Why so many student essays sound alike — from hechingerreport.org by Jill Barshay
A study of more than 70 large language models found similar answers to brainstorming and creative writing prompts
The answers were frequently indistinguishable across different models by different companies that have different architectures and use different training data. The metaphors, imagery, word choices, sentence structures — even punctuation — often converged. Jiang’s team called this phenomenon “inter-model homogeneity” and quantified the overlaps and similarities. To drive the point home, Jiang titled her paper, the “Artificial Hivemind.” The study won a best paper award at the annual conference on Neural Information Processing Systems in December 2025, one of the premier gatherings for AI research.
AI Has No Moral Compass. Do You? — from michelleweise.substack.com by Michelle Weise & Dana Walsh
Why the Age of AI Demands We Take Character Formation Seriously
Here’s something to chew on:
Anthropic, the company behind Claude — a chatbot used by 30 million users per month — has exactly one person (whom we know of) working on AI ethics. One. A young Scottish philosopher is doing the vital work of training a large language model to discern right from wrong.
I don’t say this to shame Anthropic. In fact, Anthropic appears to be the only company (that we know of) being explicit about the moral foundations and reasoning of its chatbot. Hundreds of millions of users worldwide are leveraging tools from other LLMs that do not appear to have an explicit moral compass being cultivated from within.
I raise this because this is yet another example of where we are: extraordinary technical power advancing without an equally strong moral infrastructure to support it.
Why do we keep producing people who are skilled but not wise?
Here is Pradnya’s posting out on LinkedIn.com:
From DSC…note these excerpts from Pradnya’s posting:
Pradnya links to a page out at ParadisoSolutions.com. Check out some of the functionality this AI-powered system provides:
Teach Smarter with AI — from wondertools.substack.com by Jeremy Caplan and Lance Eaton
10 tested strategies from two educators who actually use them
I recently talked with Lance Eaton, Senior Associate Director of AI and Teaching & Learning at Northeastern University and writer of AI + Education = Simplified. We traded ideas about what’s actually working. We came up with 10 specific, practical ways anyone who teaches, coaches, or leads can put AI to work.
Watch the full conversation above, or read highlights below.
Beyond Audio Summaries: How to Use NotebookLM to *Actually* Design Better Learning — from drphilippahardman.substack.com by Dr. Philippa Hardman
Five methods to maximise the value of NotebookLM’s features
In practice, what makes NotebookLM different for learning designers is four things:
…
5 Evidence-Based Methods NotebookLM Operationalises…
Shadow AI Isn’t a Threat: It’s a Signal — from campustechnology.com by Damien Eversmann
Unofficial AI use on campus reveals more about institutional gaps than misbehavior.
Key Takeaways
How L&D Can Lead in the Age of AI Even If Your Company’s Not Ready — from learningguild.com
How to lead even when your company doesn’t allow AI
Even if your corporation isn’t ready for AI, you can still research tools personally to stay ahead of the curve, so when organizational restrictions lift, you are ready to use AI for learning right away. Here are some tools you can test at home if they’re restricted in your workplace:
The Higher Ed Playbook for AI Affordability — from campustechnology.com by Jason Dunn-Potter
Key Takeaways
Report: No Foolproof Method Exists for Detecting AI-Generated Media — from campustechnology.com by Chris Paoli
Key Takeaways
L&D Global Sentiment Survey 2026 — from linkedin.com by Donald H. Taylor
“But what’s happening right now is exponential.” — from linkedin.com by Josh Cavalier
Excerpt:
I need to be honest with you. I’ve been running experiments this week with Claude Code and Opus 4.6, and we have reached the precipice in the collapse of time required to produce high-quality text-based ID outputs.
This includes performance consulting reports, learning needs analyses, action mapping, scripts, storyboards, facilitator guides, rubrics, and technical specs.
I just mapped the entire performance consulting process into a multimodal AI integration architecture (diagram image). Every phase. Entry and contracting. Performance analysis. Cause analysis. Solution design. Implementation. Evaluation. Thirty files. System specifications for each. The next step is to vet out each “skill” with an expert performance consultant.
Then I attempted a learning output: an 8-module course built with a cognitive scaffold that moves beyond content delivery to facilitate deliberate practice, meaning-making, and guided reflection within the learner’s own context.
The result:
AI and human-centered learning — from linkedin.com by Patrick Blessinger
Democratizing opportunities
AI adaptive learning can adapt learning in real-time. These tools have the potential to provide a more personalized learning experience, but only if used properly.
The California State University system uses ChatGPT Edu (OpenAI, 2025). Students use it for AI-assisted tutoring, study aids, and writing support. These resources provide 24/7 availability of subject-matter expertise tailored to students’ learning needs. It is not a replacement for professors. Rather, it extends the reach of mentorship by reducing access barriers.
However, we must proceed with intellectual humility and ethical responsibility. Even though AI can customize messages, it cannot replace the encouragement of a teacher or professor, or the social and emotional aspects of learning. It’s at the intersection of humanistic values and knowledge development that education must find its balance.
Claude Code Puts Tech Workers on Notice — from builtin.com by Matthew Urwin
Anthropic is flexing its new and improved Claude Code, which used vibe coding to build the company’s latest tool, Cowork. The feat has inspired both excitement and angst within the tech world as the future of work continues to grow more uncertain.
Summary:
Anthropic is becoming the leader in enterprise artificial intelligence, thanks to upgrades made to Claude Code. The coding tool practically built Anthropic’s Cowork product — sparking both excitement around the possibilities of vibe coding and fears around the job outlook of tech workers.
Kling 3.0 just launched. The best video model yet. — from heatherbcooper.substack.com by Heather Cooper
& workflows from Imagine Art 1.5 pro, Pixverse Real-Time Video & Genspark
In today’s edition:
Kling 3.0: Everyone a Director
Kling just dropped version 3.0, and it’s a legitimate leap forward for AI video production (Kling is the GOAT). After spending early access time testing the new capabilities, I can confirm this is the most significant update to video generation tools I’ve seen in months.
Key highlights:
Farewell to Traditional Universities | What AI Has in Store for Education
Premiered Jan 16, 2026
Description:
What if the biggest change in education isn’t a new app… but the end of the university monopoly on credibility?
Jensen Huang has framed AI as a platform shift—an industrial revolution that turns intelligence into infrastructure. And when intelligence becomes cheap, personal, and always available, education stops being a place you go… and becomes a system that follows you. The question isn’t whether universities will disappear. The question is whether the old model—high cost, slow updates, one-size-fits-all—can survive a world where every student can have a private tutor, a lab partner, and a curriculum designer on demand.
This video explores what AI has in store for education—and why traditional universities may need to reinvent themselves fast.
In this video you’ll discover:
From DSC:
There appears to be another, similar video, but with a different date and length of the video. So I’m including this other recording as well here:
The End of Universities as We Know Them: What AI Is Bringing
Premiered Jan 27, 2026
What if universities don’t “disappear”… but lose their monopoly on learning, credentials, and opportunity?
AI is turning education into something radically different: personal, instant, adaptive, and always available. When every student can have a 24/7 tutor, a writing coach, a coding partner, and a study plan designed specifically for them, the old model—one professor, one curriculum, one pace for everyone—starts to look outdated. And the biggest disruption isn’t the classroom. It’s the credential. Because in an AI world, proof of skill can become more valuable than a piece of paper.
This video explores the end of universities as we know them: what AI is bringing, what will break, what will survive, and what replaces the traditional path.
In this video you’ll discover:
The Learning and Employment Records (LER) Report for 2026: Building the infrastructure between learning and work — from smartresume.com; with thanks to Paul Fain for this resource
Executive Summary (excerpt)
This report documents a clear transition now underway: LERs are moving from small experiments to systems people and organizations expect to rely on. Adoption remains early and uneven, but the forces reshaping the ecosystem are no longer speculative. Federal policy signals, state planning cycles, standards maturation, and employer behavior are aligning in ways that suggest 2026 will mark a shift from exploration to execution.
Across interviews with federal leaders, state CIOs, standards bodies, and ecosystem builders, a consistent theme emerged: the traditional model—where institutions control learning and employment records—no longer fits how people move through education and work. In its place, a new model is being actively designed—one in which individuals hold portable, verifiable records that systems can trust without centralizing control.
Most states are not yet operating this way. But planning timelines, RFP language, and federal signals indicate that many will begin building toward this model in early 2026.
As the ecosystem matures, another insight becomes unavoidable: records alone are not enough. Value emerges only when trusted records can be interpreted through shared skill languages, reused across contexts, and embedded into the systems and marketplaces where decisions are made.
Learning and Employment Records are not a product category. They are a data layer—one that reshapes how learning, work, and opportunity connect over time.
This report is written for anyone seeking to understand how LERs are beginning to move from concept to practice. Whether readers are new to the space or actively exploring implementation, the report focuses on observable signals, emerging patterns, and the practical conditions required to move from experimentation toward durable infrastructure.
…
…
“The building blocks for a global, interoperable skills ecosystem are already in place. As education and workforce alignment accelerates, the path toward trusted, machine-readable credentials is clear. The next phase depends on credentials that carry value across institutions, industries, states, and borders; credentials that move with learners wherever their education and careers take them. The question now isn’t whether to act, but how quickly we move.”
– Curtiss Barnes, Chief Executive Officer, 1EdTech
The above item was from Paul Fain’s recent posting, which includes the following excerpt:
SmartResume just published a guide for making sense of this rapidly expanding landscape. The LER Ecosystem Report was produced in partnership with AACRAO, Credential Engine, 1EdTech, HR Open Standards, and the U.S. Chamber of Commerce Foundation. It was based on interviews and feedback gathered over three years from 100+ leaders across education, workforce, government, standards bodies, and tech providers.
The tools are available now to create the sort of interoperable ecosystem that can make talent marketplaces a reality, the report argues. Meanwhile, federal policy moves and bipartisan attention to LERs are accelerating action at the state level.
“For state leaders, this creates a practical inflection point,” says the report. “LERs are shifting from an innovation discussion to an infrastructure planning conversation.”
Philippa provides a link to:
Global list of over 100 L&D conferences in 2026 — from donaldhtaylor.co.uk by Don Taylor
I’m a firm believer in conferences. This isn’t just because I have chaired the Learning Technologies Conference in London since 2000. It’s because they are invaluable in sustaining our community. So many in Learning and Development work alone or in small teams, that building and maintaining personal contacts is crucial.For a number of years, I have kept a personal list of the Learning and Development conferences running internationally. This year, I thought it would be helpful to share it.
AI and the Work of Centers for Teaching and Learning — from derekbruff.org by Derek Bruff
In the same way, when I approach any kind of educational technology, I’m looking for tools that can be responsive to my pedagogical aims. The pedagogy should drive the technology use, not the other way around.
How to Design with AI in 2026 (based on the most compelling research published in 2025). — from linkedin.com by Dr. Philippa Hardman