content development, aggregation, repositories

Blood in the Instructional Design Machine? — from drphilippahardman.substack.com by Dr. Philippa Hardman
The reality of AI, job degradation & the likely future of Instructional Design

This raises a very important, perhaps even existential question for our profession: do these tools free a designer from the mind-numbing drudgery of content conversion (the “augmented human”)? Or do they automate the core expertise of the learning professional’s role, e.g. selecting instructional startegies, structuring narratives and designing a learning flow, in the process reducing the ID’s role to simply finding the source file and pushing a button (the “inverted centaur”)?

The stated aspiration of these tool builders seems to be a future where AI means that the instructional designer’s value shifts decisively from production to strategy. Their stated goal is to handle the heavy lifting of content generation, allowing the human ID to provide the indispensable context, creativity, and pedagogical judgment that AI cannot replicate.

However, the risk of these tools lies in how we use them, and the “inverted centaur” model remains deeply potent and possible. In an organisation that prioritises cost above all, these same tools can be used to justify reducing the ID role to the functional drudgery of inputting a PDF and supervising the machine.

The key to this paradox lies in a crucial data point: spending on outside products and services has jumped a dramatic 23% to $12.4 billion.

This signals a fundamental shift: companies are reallocating funds from large internal teams toward specialised consultants and advanced learning technologies like AI. L&D is not being de-funded; it is being re-engineered.

Firefly adds new video capabilities, industry leading AI models, and Generate Sound Effects feature — from blog.adobe.com

Today, we’re introducing powerful enhancements to our Firefly Video Model, including improved motion fidelity and advanced video controls that will accelerate your workflows and provide the precision and style you need to elevate your storytelling. We are also adding new generative AI partner models within Generate Video on Firefly, giving you the power to choose which model works best for your creative needs across image, video and sound.

Plus, our new workflow tools put you in control of your video’s composition and style. You can now layer in custom-generated sound effects right inside the Firefly web app — and start experimenting with AI-powered avatar-led videos.
…
Generate Sound Effects (beta)
Sound is a powerful storytelling tool that adds emotion and depth to your videos. Generate Sound Effects (beta) makes it easy to create custom sounds, like a lion’s roar or ambient nature sounds, that enhance your visuals. And like our other Firefly generative AI models, Generate Sound Effects (beta) is commercially safe, so you can create with confidence.

Just type a simple text prompt to generate the sound effect you need. Want even more control? Use your voice to guide the timing and intensity of the sound. Firefly listens to the energy and rhythm of your voice to place sound effects precisely where they belong — matching the action in your video with cinematic timing.

Teach business students to write like executives — from timeshighereducation.com by José Ignacio Sordo Galarza
Many business students struggle to communicate with impact. Teach them to pitch ideas on a single page to build clarity, confidence and work-ready communication skills

Many undergraduate business students transition into the workforce equipped with communication habits that, while effective in academic settings, prove ineffective in professional environments. At university, students are trained to write for professors, not executives. This becomes problematic in the workplace where lengthy reports and academic jargon often obscure rather than clarify intent. Employers seek ideas they can absorb in seconds. This is where the one-pager – a single-page, high-impact document that helps students develop clarity of thought, concise expression and strategic communication – proves effective.

Also from Times Higher Education, see:

Is the dissertation dead? If so, what are the alternatives? — from timeshighereducation.com by Rushana Khusainova, Sarah Sholl, & Patrick Harte
Dissertation alternatives, such as capstone projects and applied group-based projects, could better prepare graduates for their future careers. Discover what these might look like

The traditional dissertation, a longstanding pillar of higher education, is facing increasing scrutiny. Concerns about its relevance to contemporary career paths, limitations in fostering practical skills and the changing nature of knowledge production in the GenAI age have fuelled discussions about its continued efficacy. So, is the dissertation dead?

The dissertation is facing a number of challenges. It can be perceived as having little relevance to career aspirations in increasingly competitive job markets. According to The Future of Jobs Report 2025 by the World Economic Forum, employers demand and indeed prioritise skills such as collaborative problem-solving in diverse and complex contexts, which a dissertation might not demonstrate.

PODCAST: Did AI “break” school? Or will it “fix” it? …and if so, what can we do about it? [Noles & Harvey]

On 07/19/2025, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, change, content development, aggregation, repositories, digital learning, education, education reform, education technology, emerging technologies, experimentation, higher education, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, Open AI, pedagogy, platforms, podcasting, productivity / tips and tricks, skills, society, student-related, teachers, teaching & learning, technologies for your home, the downsides of how people use tech, tools, training / L&D, trends, United States, universities, by Daniel Christian

PODCAST: Did AI “break” school? Or will it “fix” it? …and if so, what can we do about it? — from theneurondaily.com by Grant Harvey, Corey Noles, Grant Harvey, & Matthew Robinson

In Episode 5 of The Neuron Podcast, Corey Noles and Grant Harvey tackle the education crisis head-on. We explore the viral UCLA “CheatGPT” controversy, MIT’s concerning brain study, and innovative solutions like Alpha School’s 2-hour learning model. Plus, we break down OpenAI’s new $10M teacher training initiative and share practical tips for using AI to enhance learning rather than shortcut it. Whether you’re a student, teacher, or parent, you’ll leave with actionable insights on the future of education.

On blogging (again) [Weller]

On 07/19/2025, in blogs / blogging / vlogging, collaboration, communications, communities of practice, content development, aggregation, repositories, digital learning, education technology, experimentation, ideas, internet, learning ecosystem, Learning Experience Design, lifelong learning, online media, productivity / tips and tricks, social learning / networks, writing, by Daniel Christian

On blogging (again) — from by Martin Weller

I also pondered what functions blogging has provided for me over the years.

Continuity – as an individual you persist across multiple organisations, roles and jobs. Although I stayed in one institution, I had many roles and the blog wasn’t associated with one specific project. Now I have left it continues.
Holistic – you can blog about one topic, but over time I think some personality will creep in. You are not just one thing, you have a personal life, tastes, interests etc which will all feed into what you do. A blog allows this more rounded representation.
Experimentation – there is relatively low cost and risk for much of it (this may not be the case for many people online, we need to acknowledge), so you can try things, and if they don’t work, so what? Also you can try formats that conventional outlets might not be appropriate for.
Development – the blog has been both an intentional and unintentional vehicle for working up ideas, documenting the process and getting feedback, which have led to more substantial outputs, such as books, project proposals and papers. Most importantly though it has been the means through which I have continually developed writing.
Connecting – particularly in those halcyon early days, it was a good way of finding others, working on ideas together, sharing something of yourself. A lot of my career related personal friendships have resulted from blogging.
Publicity – I became at one point (the OU crisis of 2018) something of a public voice of the OU, and have often used the blog for projects such as GO-GN

That’s not a bad return for a lil’ ol’ blog. I couldn’t say the same for academic journals.

Building a fully interactive, scenario-based training video in 45 minutes + other items re: AI in our learning ecosystems

On 07/12/2025, in Artificial Intelligence/Agents/LLMs/and Related, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, education, education technology, faculty/staff, future of higher education, game-changing environment, generational differences, higher education, human-computer interaction (HCI), instructional design, intelligent systems, IT in HE, learning ecosystem, Learning Experience Design, liberal arts, Microsoft, Open AI, parents/guardians, pedagogy, productivity / tips and tricks, professional development, teachers, teaching & learning, tools, training / L&D, United States, universities, using teams, vendors, writing, by Daniel Christian

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Tech check: Innovation in motion: How AI is rewiring L&D workflows — from chieflearningofficer.com by Gabrielle Pike
AI isn’t here to replace us. It’s here to level us up.

For today’s chief learning officer, the days of just rolling out compliance training are long gone. In 2025, learning and development leaders are architects of innovation, crafting ecosystems that are agile, automated and AI-infused. This quarter’s Tech Check invites us to pause, assess and get strategic about where tech is taking us. Because the goal isn’t more tools—it’s smarter, more human learning systems that scale with the business.

Sections include:

The state of AI in L&D: Hype vs. reality
AI in design: From static content to dynamic experiences
AI in development: Redefining production workflows
Strategic questions CLOs should be asking
Future forward: What’s next?
Closing thought

American Federation of Teachers (AFT) to Launch National Academy for AI Instruction with Microsoft, OpenAI, Anthropic and United Federation of Teachers — from aft.org

NEW YORK – The AFT, alongside the United Federation of Teachers and lead partner Microsoft Corp., founding partner OpenAI, and Anthropic, announced the launch of the National Academy for AI Instruction today. The groundbreaking $23 million education initiative will provide access to free AI training and curriculum for all 1.8 million members of the AFT, starting with K-12 educators. It will be based at a state-of-the-art bricks-and-mortar Manhattan facility designed to transform how artificial intelligence is taught and integrated into classrooms across the United States.

The academy will help address the gap in structured, accessible AI training and provide a national model for AI-integrated curriculum and teaching that puts educators in the driver’s seat.

Students Are Anxious about the Future with A.I. Their Parents Are, Too. — from educationnext.org by Michael B. Horn
The fast-growing technology is pushing families to rethink the value of college

In an era when the college-going rate of high school graduates has dropped from an all-time high of 70 percent in 2016 to roughly 62 percent now, AI seems to be heightening the anxieties about the value of college.

According to the survey, two-thirds of parents say AI is impacting their view of the value of college. Thirty-seven percent of parents indicate they are now scrutinizing college’s “career-placement outcomes”; 36 percent say they are looking at a college’s “AI-skills curriculum,” while 35 percent respond that a “human-skills emphasis” is important to them.

This echoes what I increasingly hear from college leadership: Parents and students demand to see a difference between what they are getting from a college and what they could be “learning from AI.”

This next item on LinkedIn is compliments of Ray Schroeder:

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How to Prepare Students for a Fast-Moving (AI)World — from rdene915.com by Dr. Rachelle Dené Poth

Preparing for a Future-Ready Classroom
Here are the core components I focus on to prepare students:

1. Unleash Creativity and Problem-Solving.
2. Weave in AI and Computational Thinking.
3. Cultivate Resilience and Adaptability.

AI Is Reshaping Learning Roles—Here’s How to Future-Proof Your Team — from onlinelearningconsortium.org by Jennifer Mathes, Ph.D., CEO, Online Learning Consortium; via Robert Gibson on LinkedIn

Culture matters here. Organizations that foster psychological safety—where experimentation is welcomed and mistakes are treated as learning—are making the most progress. When leaders model curiosity, share what they’re trying, and invite open dialogue, teams follow suit. Small tests become shared wins. Shared wins build momentum.

Career development must be part of this equation. As roles evolve, people will need pathways forward. Some will shift into new specialties. Others may leave familiar roles for entirely new ones. Making space for that evolution—through upskilling, mobility, and mentorship—shows your people that you’re not just investing in AI, you’re investing in them.

And above all, people need transparency. Teams don’t expect perfection. But they do need clarity. They need to understand what’s changing, why it matters, and how they’ll be supported through it. That kind of trust-building communication is the foundation for any successful change.

These shifts may play out differently across sectors—but the core leadership questions will likely be similar.

AI marks a turning point—not just for technology, but for how we prepare our people to lead through disruption and shape the future of learning.

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“Why do we treat the syllabus like a liability waiver instead of a roadmap?” [Poff]

On 07/12/2025, in adjunct faculty, colleges, community colleges, computer science, content development, aggregation, repositories, digital learning, digital video, education, education technology, engagement / engaging students, experimentation, faculty/staff, Google, higher education, history, homeschooling/homeschoolers, ideas, instructional design, K-12 related, languages and translation, learning, Learning Experience Design, learning hubs & pods & microschooling, learning preferences, learning spaces, mathematics, parents/guardians, pedagogy, platforms, productivity / tips and tricks, programming, science, STEAM-related, student-related, teachers, teaching & learning, technologies for your home, tools, United States, universities, writing, youth, by Daniel Christian

Speaking of items involving teaching and learning, also see:

2025 Learning System Top Picks — from elearninfo247.com by Craig Weiss

Who is leading the pack? Who is setting themselves apart here in the mid-year?

Are they an LMS? LMS/LXP? Talent Development System? Mentoring? Learning Platform?

Something else?

Are they solely customer training/education, mentoring, or coaching? Are they focused only on employees? Are they an amalgamation of all or some?

Well, they cut across the board – hence, they slide under the “Learning Systems” umbrella, which is under the bigger umbrella term – “Learning Technology.”
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Categories: L&D-specific, Combo (L&D and Training, think internal/external audiences), and Customer Training/Education (this means customer education, which some vendors use to mean the same as customer training).

“Using AI Right Now: A Quick Guide” [Molnick] + other items re: AI in our learning ecosystems

On 06/23/2025, in 21st century, 24x7x365 access, adjunct faculty, adult learning, Artificial Intelligence/Agents/LLMs/and Related, bots, change, cloud-based computing / apps / other cloud-related, CMS/LMS, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, digital video, education, education technology, emerging technologies, engagement / engaging students, experimentation, face-to-face, faculty/staff, game-changing environment, Google, heutagogy, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, law schools, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, liberal arts, library / librarians, lifelong learning, memory, metacognition / metacognitive skills, multimedia, Natural Language Processing (NLP), new media literacies, online learning, online media, Open AI, personalized/customized learning, platforms, productivity / tips and tricks, professional development, student-related, teachers, teaching & learning, teaching online, technologies for your home, tools, traditional / tradition, training / L&D, trends, United States, universities, user experience (UX), vendors, vision/possibilities, writing, by Daniel Christian

Thoughts on thinking — from dcurt.is by Dustin Curtis

Intellectual rigor comes from the journey: the dead ends, the uncertainty, and the internal debate. Skip that, and you might still get the insight–but you’ll have lost the infrastructure for meaningful understanding. Learning by reading LLM output is cheap. Real exercise for your mind comes from building the output yourself.

The irony is that I now know more than I ever would have before AI. But I feel slightly dumber. A bit more dull. LLMs give me finished thoughts, polished and convincing, but none of the intellectual growth that comes from developing them myself.

Using AI Right Now: A Quick Guide — from oneusefulthing.org by Ethan Mollick
Which AIs to use, and how to use them

Every few months I put together a guide on which AI system to use. Since I last wrote my guide, however, there has been a subtle but important shift in how the major AI products work. Increasingly, it isn’t about the best model, it is about the best overall system for most people. The good news is that picking an AI is easier than ever and you have three excellent choices. The challenge is that these systems are getting really complex to understand. I am going to try and help a bit with both.

First, the easy stuff.

Which AI to Use
For most people who want to use AI seriously, you should pick one of three systems: Claude from Anthropic, Google’s Gemini, and OpenAI’s ChatGPT.

Also see:

Student Voice, Socratic AI, and the Art of Weaving a Quote — from elmartinsen.substack.com by Eric Lars Martinsen
How a custom bot helps students turn source quotes into personal insight—and share it with others

This summer, I tried something new in my fully online, asynchronous college writing course. These classes have no Zoom sessions. No in-person check-ins. Just students, Canvas, and a lot of thoughtful design behind the scenes.

One activity I created was called QuoteWeaver—a PlayLab bot that helps students do more than just insert a quote into their writing.

Try it here

It’s a structured, reflective activity that mimics something closer to an in-person 1:1 conference or a small group quote workshop—but in an asynchronous format, available anytime. In other words, it’s using AI not to speed students up, but to slow them down.
…
The bot begins with a single quote that the student has found through their own research. From there, it acts like a patient writing coach, asking open-ended, Socratic questions such as:

What made this quote stand out to you?
How would you explain it in your own words?
What assumptions or values does the author seem to hold?
How does this quote deepen your understanding of your topic?
It doesn’t move on too quickly. In fact, it often rephrases and repeats, nudging the student to go a layer deeper.

The Disappearance of the Unclear Question — from jeppestricker.substack.com Jeppe Klitgaard Stricker
New Piece for UNESCO Education Futures

On [6/13/25], UNESCO published a piece I co-authored with Victoria Livingstone at Johns Hopkins University Press. It’s called The Disappearance of the Unclear Question, and it’s part of the ongoing UNESCO Education Futures series – an initiative I appreciate for its thoughtfulness and depth on questions of generative AI and the future of learning.

Our piece raises a small but important red flag. Generative AI is changing how students approach academic questions, and one unexpected side effect is that unclear questions – for centuries a trademark of deep thinking – may be beginning to disappear. Not because they lack value, but because they don’t always work well with generative AI. Quietly and unintentionally, students (and teachers) may find themselves gradually avoiding them altogether.

Of course, that would be a mistake.

We’re not arguing against using generative AI in education. Quite the opposite. But we do propose that higher education needs a two-phase mindset when working with this technology: one that recognizes what AI is good at, and one that insists on preserving the ambiguity and friction that learning actually requires to be successful.

Leveraging GenAI to Transform a Traditional Instructional Video into Engaging Short Video Lectures — from er.educause.edu by Hua Zheng

By leveraging generative artificial intelligence to convert lengthy instructional videos into micro-lectures, educators can enhance efficiency while delivering more engaging and personalized learning experiences.

This AI Model Never Stops Learning — from link.wired.com by Will Knight

Researchers at Massachusetts Institute of Technology (MIT) have now devised a way for LLMs to keep improving by tweaking their own parameters in response to useful new information.

The work is a step toward building artificial intelligence models that learn continually—a long-standing goal of the field and something that will be crucial if machines are to ever more faithfully mimic human intelligence. In the meantime, it could give us chatbots and other AI tools that are better able to incorporate new information including a user’s interests and preferences.

The MIT scheme, called Self Adapting Language Models (SEAL), involves having an LLM learn to generate its own synthetic training data and update procedure based on the input it receives.

Edu-Snippets — from scienceoflearning.substack.com by Nidhi Sachdeva and Jim Hewitt
Why knowledge matters in the age of AI; What happens to learners’ neural activity with prolonged use of LLMs for writing

Highlights:

Offloading knowledge to Artificial Intelligence (AI) weakens memory, disrupts memory formation, and erodes the deep thinking our brains need to learn.
Prolonged use of ChatGPT in writing lowers neural engagement, impairs memory recall, and accumulates cognitive debt that isn’t easily reversed.

Vertical wall printers create large, detailed designs directly on walls, transforming spaces with custom artwork
by @IntEngineering
#Innovation #EmergingTech #TechForGood #Technology

cc: @meisshaily @ylecun @yuhelenyu pic.twitter.com/qAiDaAnpED

— Ronald van Loon (@Ronald_vanLoon) June 18, 2025

From DSC:
This type of thing could seriously spruce up the learning spaces out there! 🙂

The Memory Paradox: Why Our Brains Need Knowledge in an Age of AI [various authors]

On 06/20/2025, in Artificial Intelligence/Agents/LLMs/and Related, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, education technology, emerging technologies, experimentation, faculty/staff, game-changing environment, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, law schools, learning, learning ecosystem, Learning Experience Design, liberal arts, memory, metacognition / metacognitive skills, participation, pedagogy, productivity / tips and tricks, psychology, research, student teaching/teacher education, student-related, teachers, teaching & learning, technologies for your home, the downsides of how people use tech, tools, training / L&D, trends, United States, universities, youth, by Daniel Christian

The Memory Paradox: Why Our Brains Need Knowledge in an Age of AI — from papers.ssrn.com by Barbara Oakley, Michael Johnston, Kenzen Chen, Eulho Jung, and Terrence Sejnowski; via George Siemens

Abstract
In an era of generative AI and ubiquitous digital tools, human memory faces a paradox: the more we offload knowledge to external aids, the less we exercise and develop our own cognitive capacities. This chapter offers the first neuroscience-based explanation for the observed reversal of the Flynn Effect—the recent decline in IQ scores in developed countries—linking this downturn to shifts in educational practices and the rise of cognitive offloading via AI and digital tools. Drawing on insights from neuroscience, cognitive psychology, and learning theory, we explain how underuse of the brain’s declarative and procedural memory systems undermines reasoning, impedes learning, and diminishes productivity. We critique contemporary pedagogical models that downplay memorization and basic knowledge, showing how these trends erode long-term fluency and mental flexibility. Finally, we outline policy implications for education, workforce development, and the responsible integration of AI, advocating strategies that harness technology as a complement to – rather than a replacement for – robust human knowledge.

Keywords
cognitive offloading, memory, neuroscience of learning, declarative memory, procedural memory, generative AI, Flynn Effect, education reform, schemata, digital tools, cognitive load, cognitive architecture, reinforcement learning, basal ganglia, working memory, retrieval practice, schema theory, manifolds

Mary Meeker’s AI Trend-Analysis + other items re: AI in general

On 06/09/2025, in Adobe, Artificial Intelligence/Agents/LLMs/and Related, colleges, communities of practice, community colleges, content development, aggregation, repositories, digital learning, disruption, education, education technology, emerging technologies, engagement / engaging students, entrepreneurship, experimentation, Facebook / Meta Platforms, faculty/staff, future, future of higher education, game-changing environment, global, Google, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, K-12 related, leadership, learning, learning ecosystem, Learning Experience Design, Microsoft, online media, Open AI, organizational change, pace of change, pedagogy, platforms, student-related, teachers, teaching & learning, teaching online, technologies for your home, the downsides of how people use tech, tools, trends, United States, universities, vendors, workplace, writing, by Daniel Christian

Mary Meeker AI Trends Report: Mind-Boggling Numbers Paint AI’s Massive Growth Picture — from ndtvprofit.com
Numbers that prove AI as a tech is unlike any other the world has ever seen.

Here are some incredibly powerful numbers from Mary Meeker’s AI Trends report, which showcase how artificial intelligence as a tech is unlike any other the world has ever seen.

AI took only three years to reach 50% user adoption in the US; mobile internet took six years, desktop internet took 12 years, while PCs took 20 years.
ChatGPT reached 800 million users in 17 months and 100 million in only two months, vis-à-vis Netflix’s 100 million (10 years), Instagram (2.5 years) and TikTok (nine months).
ChatGPT hit 365 billion annual searches in two years (2024) vs. Google’s 11 years (2009)—ChatGPT 5.5x faster than Google.

Above via Mary Meeker’s AI Trend-Analysis — from getsuperintel.com by Kim “Chubby” Isenberg
How AI’s rapid rise, efficiency race, and talent shifts are reshaping the future.

The TLDR
Mary Meeker’s new AI trends report highlights an explosive rise in global AI usage, surging model efficiency, and mounting pressure on infrastructure and talent. The shift is clear: AI is no longer experimental—it’s becoming foundational, and those who optimize for speed, scale, and specialization will lead the next wave of innovation.

Also see Meeker’s actual report at:

Trends – Artificial Intelligence — from bondcap.com by Mary Meeker / Jay Simons / Daegwon Chae / Alexander Krey

The Rundown: Meta aims to release tools that eliminate humans from the advertising process by 2026, according to a report from the WSJ — developing an AI that can create ads for Facebook and Instagram using just a product image and budget.

The details:

Companies would submit product images and budgets, letting AI craft the text and visuals, select target audiences, and manage campaign placement.
The system will be able to create personalized ads that can adapt in real-time, like a car spot featuring mountains vs. an urban street based on user location.
The push would target smaller companies lacking dedicated marketing staff, promising professional-grade advertising without agency fees or skillset.
Advertising is a core part of Mark Zuckerberg’s AI strategy and already accounts for 97% of Meta’s annual revenue.

Why it matters: We’re already seeing AI transform advertising through image, video, and text, but Zuck’s vision takes the process entirely out of human hands. With so much marketing flowing through FB and IG, a successful system would be a major disruptor — particularly for small brands that just want results without the hassle.

“The AI-enhanced learning ecosystem” [Jennings] + other items re: AI in our learning ecosystems

On 06/09/2025, in 21st century, 24x7x365 access, 3D, A/V -- audio/visual, active learning, adjunct faculty, adult learning, architecture, Augmented Reality (AR), bots, business, career development, change, colleges, communities of practice, community colleges, computer science, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, creativity, curriculum, data related items, design, digital learning, education technology, emerging technologies, engagement / engaging students, experimentation, faculty/staff, future, future of higher education, game-changing environment, generational differences, global, Google, health, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, K-12 related, law schools, leadership, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, legal technologies, legislatures / government / legal, library / librarians, lifelong learning, online learning, online media, online tutoring, pedagogy, personalized/customized learning, platforms, podcasting, policy, productivity / tips and tricks, professional development, skills, society, student-related, teachers, teaching & learning, teaching online, technologies for your home, tools, traditional / tradition, training / L&D, trends, United States, universities, vendors, vision/possibilities, visualizing information, workplace, XR - extended reality, by Daniel Christian

The AI-enhanced learning ecosystem: A case study in collaborative innovation — from chieflearningofficer.com by Kevin Jennings
How artificial intelligence can serve as a tool and collaborative partner in reimagining content development and management.

Learning and development professionals face unprecedented challenges in today’s rapidly evolving business landscape. According to LinkedIn’s 2025 Workplace Learning Report, 67 percent of L&D professionals report being “maxed out” on capacity, while 66 percent have experienced budget reductions in the past year.

Despite these constraints, 87 percent agree their organizations need to develop employees faster to keep pace with business demands. These statistics paint a clear picture of the pressure L&D teams face: do more, with less, faster.

This article explores how one L&D leader’s strategic partnership with artificial intelligence transformed these persistent challenges into opportunities, creating a responsive learning ecosystem that addresses the modern demands of rapid product evolution and diverse audience needs. With 71 percent of L&D professionals now identifying AI as a high or very high priority for their learning strategy, this case study demonstrates how AI can serve not merely as a tool but as a collaborative partner in reimagining content development and management.
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How we use GenAI and AR to improve students’ design skills — from timeshighereducation.com by Antonio Juarez, Lesly Pliego and Jordi Rábago who are professors of architecture at Monterrey Institute of Technology in Mexico; Tomas Pachajoa is a professor of architecture at the El Bosque University in Colombia; & Carlos Hinrichsen and Marietta Castro are educators at San Sebastián University in Chile.
Guidance on using generative AI and augmented reality to enhance student creativity, spatial awareness and interdisciplinary collaboration

Blend traditional skills development with AI use
For subjects that require students to develop drawing and modelling skills, have students create initial design sketches or models manually to ensure they practise these skills. Then, introduce GenAI tools such as Midjourney, Leonardo AI and ChatGPT to help students explore new ideas based on their original concepts. Using AI at this stage broadens their creative horizons and introduces innovative perspectives, which are crucial in a rapidly evolving creative industry.

Provide step-by-step tutorials, including both written guides and video demonstrations, to illustrate how initial sketches can be effectively translated into AI-generated concepts. Offer example prompts to demonstrate diverse design possibilities and help students build confidence using GenAI.

Integrating generative AI and AR consistently enhanced student engagement, creativity and spatial understanding on our course.

How Texas is Preparing Higher Education for AI — from the74million.org by Kate McGee
TX colleges are thinking about how to prepare students for a changing workforce and an already overburdened faculty for new challenges in classrooms.

“It doesn’t matter if you enter the health industry, banking, oil and gas, or national security enterprises like we have here in San Antonio,” Eighmy told The Texas Tribune. “Everybody’s asking for competency around AI.”

It’s one of the reasons the public university, which serves 34,000 students, announced earlier this year that it is creating a new college dedicated to AI, cyber security, computing and data science. The new college, which is still in the planning phase, would be one of the first of its kind in the country. UTSA wants to launch the new college by fall 2025.

But many state higher education leaders are thinking beyond that. As AI becomes a part of everyday life in new, unpredictable ways, universities across Texas and the country are also starting to consider how to ensure faculty are keeping up with the new technology and students are ready to use it when they enter the workforce.

In the Room Where It Happens: Generative AI Policy Creation in Higher Education — from er.educause.edu by Esther Brandon, Lance Eaton, Dana Gavin, and Allison Papini

To develop a robust policy for generative artificial intelligence use in higher education, institutional leaders must first create “a room” where diverse perspectives are welcome and included in the process.

Q&A: Artificial Intelligence in Education and What Lies Ahead — from usnews.com by Sarah Wood
Research indicates that AI is becoming an essential skill to learn for students to succeed in the workplace.

Q: How do you expect to see AI embraced more in the future in college and the workplace?
I do believe it’s going to become a permanent fixture for multiple reasons. I think the national security imperative associated with AI as a result of competing against other nations is going to drive a lot of energy and support for AI education. We also see shifts across every field and discipline regarding the usage of AI beyond college. We see this in a broad array of fields, including health care and the field of law. I think it’s here to stay and I think that means we’re going to see AI literacy being taught at most colleges and universities, and more faculty leveraging AI to help improve the quality of their instruction. I feel like we’re just at the beginning of a transition. In fact, I often describe our current moment as the ‘Ask Jeeves’ phase of the growth of AI. There’s a lot of change still ahead of us. AI, for better or worse, it’s here to stay.

AI-Generated Podcasts Outperform Textbooks in Landmark Education Study — form linkedin.com by David Borish

A new study from Drexel University and Google has demonstrated that AI-generated educational podcasts can significantly enhance both student engagement and learning outcomes compared to traditional textbooks. The research, involving 180 college students across the United States, represents one of the first systematic investigations into how artificial intelligence can transform educational content delivery in real-time.

What can we do about generative AI in our teaching? — from linkedin.com by Kristina Peterson

So what can we do?

Interrogate the Process: We can ask ourselves if we I built in enough checkpoints. Steps that can’t be faked. Things like quick writes, question floods, in-person feedback, revision logs.
Reframe AI: We can let students use AI as a partner. We can show them how to prompt better, revise harder, and build from it rather than submit it. Show them the difference between using a tool and being used by one.
Design Assignments for Curiosity, Not Compliance: Even the best of our assignments need to adapt. Mine needs more checkpoints, more reflective questions along the way, more explanation of why my students made the choices they did.

Teachers Are Not OK — from 404media.co by Jason Koebler

The response from teachers and university professors was overwhelming. In my entire career, I’ve rarely gotten so many email responses to a single article, and I have never gotten so many thoughtful and comprehensive responses.

One thing is clear: teachers are not OK.
…
In addition, universities are contracting with companies like Microsoft, Adobe, and Google for digital services, and those companies are constantly pushing their AI tools. So a student might hear “don’t use generative AI” from a prof but then log on to the university’s Microsoft suite, which then suggests using Copilot to sum up readings or help draft writing. It’s inconsistent and confusing.

I am sick to my stomach as I write this because I’ve spent 20 years developing a pedagogy that’s about wrestling with big ideas through writing and discussion, and that whole project has been evaporated by for-profit corporations who built their systems on stolen work. It’s demoralizing.

“Faculty AI Guides” + “Teachers using AI tools more regularly” + other items re: AI in our learning ecosystems

On 05/27/2025, in Artificial Intelligence/Agents/LLMs/and Related, assessment, Australia, colleges, community colleges, content development, aggregation, repositories, digital learning, digital textbooks, education, education reform, education technology, educational games / serious games, emerging technologies, engagement / engaging students, experimentation, faculty/staff, future, future of higher education, game-changing environment, generational differences, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, informal learning, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning preferences, liberal arts, personalized/customized learning, skills, student-related, teachers, teaching & learning, tools, trends, United States, universities, user experience (UX), vendors, vision/possibilities, by Daniel Christian

AI & Schools: 4 Ways Artificial Intelligence Can Help Students — from the74million.org by W. Ian O’Byrne
AI creates potential for more personalized learning

I am a literacy educator and researcher, and here are four ways I believe these kinds of systems can be used to help students learn.

Differentiated instruction
Intelligent textbooks
Improved assessment
Personalized learning

5 Skills Kids (and Adults) Need in an AI World — from oreilly.com by Raffi Krikorian
Hint: Coding Isn’t One of Them

Five Essential Skills Kids Need (More than Coding)
I’m not saying we shouldn’t teach kids to code. It’s a useful skill. But these are the five true foundations that will serve them regardless of how technology evolves.

Loving the journey, not just the destination
Being a question-asker, not just an answer-getter
Trying, failing, and trying differently
Seeing the whole picture
Walking in others’ shoes

The AI moment is now: Are teachers and students ready? — from iblnews.org

Day of AI Australia hosted a panel discussion on 20 May, 2025. Hosted by Dr Sebastian Sequoiah-Grayson (Senior Lecturer in the School of Computer Science and Engineering, UNSW Sydney) with panel members Katie Ford (Industry Executive – Higher Education at Microsoft), Tamara Templeton (Primary School Teacher, Townsville), Sarina Wilson (Teaching and Learning Coordinator – Emerging Technology at NSW Department of Education) and Professor Didar Zowghi (Senior Principal Research Scientist at CSIRO’s Data61).

Teachers using AI tools more regularly, survey finds — from iblnews.org

As many students face criticism and punishment for using artificial intelligence tools like ChatGPT for assignments, new reporting shows that many instructors are increasingly using those same programs.

Addendum on 5/28/25:

A Museum of Real Use: The Field Guide to Effective AI Use — from mikekentz.substack.com by Mike Kentz
Six Educators Annotate Their Real AI Use—and a Method Emerges for Benchmarking the Chats

Our next challenge is to self-analyze and develop meaningful benchmarks for AI use across contexts. This research exhibit aims to take the first major step in that direction.

With the right approach, a transcript becomes something else:

A window into student decision-making
A record of how understanding evolves
A conversation that can be interpreted and assessed
An opportunity to evaluate content understanding

This week, I’m excited to share something that brings that idea into practice.

Over time, I imagine a future where annotated transcripts are collected and curated. Schools and universities could draw from a shared library of real examples—not polished templates, but genuine conversations that show process, reflection, and revision. These transcripts would live not as static samples but as evolving benchmarks.

This Field Guide is the first move in that direction.

Two items for the L&D/corporate world

On 05/27/2025, in active learning, adult learning, Artificial Intelligence/Agents/LLMs/and Related, business, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, productivity / tips and tricks, professional development, skills, tools, training / L&D, United States, workplace, by Daniel Christian

Skilling Up for AI Transformation — from learningguild.com by Lauren Milstid and Megan Torrance

Lately, I’ve been in a lot of conversations—some casual, some strategy-deep—about what it takes to skill up teams for AI. One pattern keeps emerging: The organizations getting the most out of generative AI are the ones doing the most to support their people. They’re not just training on a single tool. They’re building the capacity to work with AI as a class of technology.

So let’s talk about that. Not the hype, but the real work of helping humans thrive in an AI-enabled workplace.

If Leadership Training Isn’t Applied, It Hasn’t Happened — from learningguild.com by Tim Samuels

L&D leadership training sessions often “feel” successful. A program is designed, a workshop is delivered, and employees leave feeling informed and engaged. But if that training isn’t applied in the workplace, did it actually happen? If we focus entirely on the “learning” but not the “development,” we’re wasting huge amounts of time and money. So let’s take a look at the current situation first.

The reality is stark; according to Harvard Business Review:

Only 12% of employees apply new skills learned in L&D programs
Just 25% believe their training measurably improved performance
We forget 75% of what we learn within six days unless we use it

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