learning

The “Cognitive Offloading” Paradox [Hardman]

On 04/19/2026, in Artificial Intelligence/Agents/LLMs/and Related, Asia, colleges, community colleges, digital learning, education technology, emerging technologies, Europe, higher education, human-computer interaction (HCI), learning, learning ecosystem, Learning Experience Design, learning theories, student-related, teaching & learning, UK, United States, by Daniel Christian

The “Cognitive Offloading” Paradox — from drphilippahardman.substack.com by Dr. Philippa Hardman
New research shows that offloading learning tasks to AI can improve – rather than erode – human thinking and learning

The Rise of the “Offloading Paradox”
In March 2026, the International Journal of Educational Technology in Higher Education published a study that went beyond the question “does offloading hurt?” and asked a harder one: when students form genuine partnerships with AI — treating it as an intellectual collaborator rather than a passive tool — what actually happens to the way they think and learn? Specifically, do two cognitive responses — critical evaluation of AI outputs (what the researchers call cognitive vigilance) and strategic delegation to AI (cognitive offloading) — compete with each other, or can they coexist?

Based on previous research, Wang and Zhang hypothesised that cognitive offloading would hurt transformative learning. They expected the familiar story: delegation reduces cognitive struggle, struggle is where learning happens, therefore delegation undermines learning.

The study — 912 students across China, Europe, and the United States, using a three-wave time-lagged survey design that measured partnership orientation first, cognitive strategies two weeks later, and learning outcomes two weeks after that — found something more interesting than a simple reversal.

Make learning accessible to all in higher education — from The Times Higher Education

When accessibility is placed at the heart of teaching and learning, rather than treated as a bolt-on, every student benefits. This week’s spotlight guide offers advice on designing universally accessible learning, in-person and online. Find out how to ease the burden of disability disclosure with universal design for learning, better support neurodivergent students and students with hearing or vision issues, design more accessible assessments and ensure digital tools work for all.

Also see:

Dr. Ian Kelleher’s introduction to his paper here on LinkedIn

The Course Is Dying as the Unit of Learning. Here’s why, and what’s replacing It [Hardman]

On 04/07/2026, in adult learning, corporate / business world, corporate universities / corporate training, emerging technologies, ideas, instructional design, intelligent systems, learning, learning agents, learning ecosystem, Learning Experience Design, productivity / tips and tricks, training / L&D, UK, workplace, by Daniel Christian

The Course Is Dying as the Unit of Learning — from drphilippahardman.substack.com by Dr Philippa Hardman
Here’s why, and what’s replacing It

What the Bleeding Edge Looks like in Practice
So what does “the new stack” actually look like when organisations lean into this? Here are four real patterns already in play.

Engineering: from engine courses to in-workflow AI coaching.
Product development: from courses to craft-specific agents.
Compliance: from annual course to nudge systems.|
Enablement systems, not catalogues.

…

The quest to build a better AI tutor [Barshay]

On 04/06/2026, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, digital learning, education, education technology, emerging technologies, engagement / engaging students, future, game-changing environment, generational differences, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, K-12 related, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning theories, online learning, participation, personalized/customized learning, research, student-related, teachers, technologies for your home, United States, universities, by Daniel Christian

The quest to build a better AI tutor — from hechingerreport.org by Jill Barshay
Researchers make progress with an older ed tech idea: personalized practice

One promising idea has less to do with how an AI tutor explains concepts and more with what it asks students to practice next.

A team at the University of Pennsylvania, which included some AI skeptics, recently tested this approach in a study of close to 800 Taiwanese high school students learning Python programming. All the students used the same AI tutor, which was designed not to give away answers.

But there was one key difference. Half the students were randomly assigned to a fixed sequence of practice problems, progressing from easy to hard. The other half received a personalized sequence with the AI tutor continuously adjusting the difficulty of each problem based on how the student was performing and interacting with the chatbot.

The idea is based on what educators call the “zone of proximal development.” When problems are too easy, students get bored. When they’re too hard, students get frustrated. The goal is to keep students in a sweet spot: challenged, but not overwhelmed.

The researchers found that students in the personalized group did better on a final exam than students in the fixed problem group. The difference was characterized as the equivalent of 6 to 9 months of additional schooling, an eye-catching claim for an after-school online course that lasted only five months.
…
To address this, Chung’s team combined a large language model with a separate machine-learning algorithm that analyzes how students interact with the online course platform — how they answer the practice questions, how many times they revise or edit their coding, and the quality of their conversations with the chatbot — and uses that information to decide which problem to serve up next.

The Most Obvious Fix in Education — from michelleweise.substack.com by Michelle Weise
The No-Brainer Nobody’s Doing

We know what better learning looks like. We have known for a while.

Real problems. Real roles. Built-in conflict. Conditions that simulate the messiness of actual work. Reflection that asks not just what did you do but who are you becoming? These are not radical ideas. They are not untested theories. The research is clear, employers are asking for exactly this, and students consistently report that the closest they got to real work was the most valuable part of their education.

So why aren’t universities doing more of it?

That is the question worth sitting with — because the gap between what we know and what we do is not a knowledge problem. It is a design problem, an incentive problem, and if we’re being candid, a courage problem.

Because in the meantime, learners are paying the price. They graduate credentialed but untested. They enter labor markets that want proof of performance and experience, not transcripts. They lack the networks, the exposure, and the scar tissue that comes from navigating real work.

Also relevant, see:

The Apprenticeship (R)Evolution — from insidehighered.com by Sara Weissman and Colleen Flaherty
Once synonymous with hard hats and tool belts, apprenticeships are branching into health care, artificial intelligence, business services, advanced manufacturing and more.

Such programs also challenge stereotypes about apprenticeships—namely that they’re only in construction, an earn-and-learn catchall for traditionally apprenticeable occupations such as bricklayer, plumber, carpenter and electrician. In integrating robotics, automation, machining and logistics, the manufacturing development program is a bridge to understanding how apprenticeships are evolving to support some of the nation’s fastest-growing industries. These include advanced manufacturing, but also health care, information technology and other business services.

Hidden in Plain Sight: How Microschools Can Unlock the Power of Public Libraries [Blassingame & Flynn]

On 03/25/2026, in education, education reform, engagement / engaging students, learning, learning ecosystem, Learning Experience Design, learning hubs & pods & microschooling, learning spaces, library / librarians, parents/guardians, society, student-related, teachers, United States, youth, by Daniel Christian

Hidden in Plain Sight: How Microschools Can Unlock the Power of Public Libraries — from microschoolingcenter.org by Tiffany Blassingame & Erin Flynn

The Library as a Learning Campus
Many microschool founders are wrestling with the same core challenge: how do you provide students with enriching, hands-on experiences when you’re working with a small team and a lean budget? Erin’s answer is deceptively simple — walk through the library’s front door.

Modern public libraries are far more than book repositories. Most educators walk past an entire ecosystem of free resources without realizing what’s available. Need printing, computers, or digital tools? Libraries offer them at little or no cost. Looking for hands-on science programming? Many branches host makerspaces and science stations built for exactly that kind of exploration. Need a space to hold a small class, workshop, or seminar? Bookable collaboration rooms are often just a phone call away.

Beyond the physical infrastructure, libraries frequently offer life skills programming — resume writing, financial literacy, job readiness — that can support the families surrounding a microschool, not just its students. And in some branches, social workers are embedded on site, providing the kind of wraparound support that few microschools could ever access on their own.

Libraries are also deeply invested in expanding their community reach. A microschool brings exactly the kind of engaged, mission-driven partnership that many branches are actively seeking. The relationship benefits both sides from day one.

The AI-based learning platform of the future will be constantly doing this

On 03/24/2026, in 21st century, 24x7x365 access, analytics, Artificial Intelligence/Agents/LLMs/and Related, business, career development, change, cloud-based computing / apps / other cloud-related, Daniel S. Christian, data related items, education technology, emerging technologies, future, game-changing environment, generational differences, global / globalization, ideas, innovation, instructional design, intelligent systems, intelligent tutoring, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning preferences, lifelong learning, more voice more choice more control, personalized/customized learning, platforms, reinvent, skills, society, student-related, surviving, tools, United States, workplace, by Daniel Christian

From DSC:
I have been proposing that the AI-based learning platform of the future will be constantly doing this — every single day. It will know what the in-demand skills are — at any given moment in time. It will then be able to direct you to resources that will help you gain those skills. Though in my vision, the system is querying actual/open job descriptions, not analyzing learning data from enterprise learners. Perhaps I should add that to the vision.

Coursera’s Job Skills Report 2026: Top skills for your students — from coursera.org

The Job Skills Report 2026 analyzes learning data from more than 6 million enterprise learners to identify the future job skills organizations need most. It’s designed for HR and L&D leaders; data, IT, and software & product development leaders; higher education administrators; and government agencies seeking actionable insights on workforce skills trends and AI-driven transformation.
…
Drawing on data from 6 million enterprise learners across nearly 7,000 organizations, the Job Skills Report 2026 guides you through the skills reshaping the global economy. This year’s analysis spans Data, IT, and Software & Product Development—and the Generative AI skills becoming essential for every role.

“Agentic AI isn’t coming for training programs. It’s coming for the trainers who can’t adapt.” [Martin] + other items re: AI in our learning ecosystems

On 03/23/2026, in Artificial Intelligence/Agents/LLMs/and Related, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, ethics, experimentation, future, game-changing environment, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, learner profiles, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, morals/values, platforms, productivity / tips and tricks, tools, training / L&D, UK, universities, vendors, workplace, by Daniel Christian

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?

Check out some of the features an AI-powered LMS provides you with!

On 03/23/2026, in 21st century, 24x7x365 access, adult learning, analytics, Artificial Intelligence/Agents/LLMs/and Related, assessment, business, career development, cloud-based computing / apps / other cloud-related, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, educational games / serious games, emerging technologies, ideas, innovation, instructional design, intelligent systems, intelligent tutoring, languages and translation, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, lifelong learning, platforms, skills, training / L&D, United States, workplace, by Daniel Christian

Here is Pradnya’s posting out on LinkedIn.com:

From DSC…note these excerpts from Pradnya’s posting:

I’m not manually assigning 400 people anymore ? They’re actually taking relevant courses now
Shows me the data ? Suggests courses to fix it ? I look like a strategic genius
Completion rates up 34% ? Nobody’s “stuck” anymore

Pradnya links to a page out at ParadisoSolutions.com. Check out some of the functionality this AI-powered system provides:

Also from Pradnya, see this posting:

5 Tech Strategies to Enhance Student-Led Learning — from edutopia.org by Rachelle Dené Poth
While technology has potential to distract students, it can also boost engagement and help them actively demonstrate their learning.

Over the years, I have learned that engagement doesn’t happen simply by adding technology. It increases when we give students more ownership by designing experiences that allow them to build, collaborate, reflect, and teach one another. Depending on how we use it, technology can either amplify engagement or distract from it. Technology can help build students’ confidence in learning, but it can also lead to passivity. When technology is used to amplify students’ voice, choice, and ownership in learning, their engagement will naturally increase.

Here are five strategies and some digital tools that can be used across grade levels and content areas to boost student engagement, build confidence, foster collaboration, and support meaningful learning experiences.

Project-Based Learning (PBL)
Implementing a PBL Design Challenge in Your School — from edutopia.org by Lisa Beck & Kim Mishkin
A weeklong, schoolwide project-based learning challenge encourages students to try to tackle meaningful problems.

For the past five years, Hudson Lab School (HLS), a K–8 progressive school committed to project?based learning (PBL), has kicked off each school year with an exciting tradition: Design Challenge Week. In five days, students take on a real?world problem, explore each phase of the design process, and present what they created and learned to an authentic audience. Design Challenge Week introduces concepts that students will revisit all year and offers a model for how any educational setting could experiment with PBL on a smaller scale. Even short, well?designed challenges can lead to deeply engaged learning experiences.

How to Give Students Directions They Actually Understand — from edutopia.org by Mary Davenport
Making small changes in your instructions can have a significant impact on students’ understanding and engagement.

No more than a minute after you’ve provided instruction on the day’s targeted content and given students directions for their next task, some brave soul utters the line that brings tired teachers to their knees: “What are we supposed to be doing?”

None of us want this. As teachers, we all want students to fully understand what they’re supposed to be doing so that they can be successful as they do it.

Good news: A few small changes in how we give directions can be the lever that boosts student understanding and engagement.

Ideas on setting up excellent seating plans, using trauma-informed practices, & reducing cognitive load [edutopia.org]

On 03/13/2026, in attention, education, experimentation, graphics, ideas, K-12 related, learning, learning ecosystem, Learning Experience Design, learning spaces, learning theories, multimedia, pedagogy, strategy, student-related, teachers, by Daniel Christian

An Unconventional Seating Plan Designed to Benefit Focus and Learning — from edutopia.org by Tyler Rablin
After years of search and experimentation, this teacher finally hit on a room layout that allowed for efficient shifting between whole class, small group, and independent work.

I used to be an obsessive classroom rearranger—every six weeks or so I would find myself looking for a new desk arrangement that would improve some aspect of our work in the room. So when I finally found a desk arrangement that I didn’t want to change for the rest of the year, I knew I was on to something good.

The idea started developing when I stumbled across an article about an Australian classroom arrangement based on three “archetypal learning spaces”: campfires, caves, and watering holes. Essentially, the idea is that students need a physical space to work independently (a cave), spaces to gather informally (campfires), and a space to gather as a whole to learn from an expert (the watering hole).

Using Trauma-Informed Practices in Early Elementary Classrooms — from edutopia.org by Emily Barbour
Small changes in language and classroom routines can increase connection and improve learning for young students.

Trauma-informed practices invite a shift from reactive to proactive systems. To design classrooms that are grounded in safety and care, teachers need to embed predictability, co-regulation, and relationship-building into daily routines. Seemingly small changes like morning choice, intentional language, and shared commitments can transform the environmental conditions for students to properly regulate, feel connected, and fully access learning.

Replacing Morning Work With Morning Choice
The largest positive shift in my classroom culture occurred when I replaced traditional morning work with morning choice bins. When I began our day with worksheets, it felt like I started each day with an uphill battle. The mornings began with redirecting behavior instead of building meaningful relationships.

Reducing the Cognitive Load of Math Tasks With Strategy Cards — from edutopia.org by Katherine Efremkin
When students create a visual resource to scaffold problem-solving, they can approach independent work with more confidence and focused attention.

All three of these areas of the brain need to be activated and work together in order for a student to be successful with independent math work. To help ensure that students are able to successfully shift between their problem-solving ability, thinking, and actions to attack different parts of a problem, I teach students to create strategy cards.

These cards help reduce the cognitive load, enabling students not only to become more successful and independent within their arithmetic work, but also to dive deeper into the conceptual understanding of math concepts.

The Future of Learning Looks Like Workforce Infrastructure — from workshift.org by Bruno V. Manno

For years, “ed tech” was an umbrella term grouping schools, online platforms, courses, credentials, and software under one idea: technology applied to education. That shorthand made it easier for investors, policymakers, and institutions to talk about innovation without rethinking how learning fits into the economy. Today, it no longer explains what’s happening.

That’s the central insight of “The European Learning & Work Funding Report” by Brighteye Ventures, a research and advisory firm tracking investment at the intersection of learning, work, and productivity. The report’s seventh edition shows that learning is no longer funded primarily as education. It is increasingly funded as part of how work gets done.

Across Europe, and increasingly the U.S., capital is flowing not toward courses or credentials but toward systems that are closer to production, including hiring platforms, staffing firms, clinical decision tools, payroll systems, and compliance software. These are not educational products, though learning is embedded throughout them.

In these systems, learning is not the point. Outcomes are.

Build hybrid institutions that erase boundaries. Stop forcing learners to navigate disconnected systems. Create partnerships that blend K-12 schools, community colleges, training providers, and employers into one integrated system, so students move through one coherent system, not four separate bureaucracies.

“Teach Smarter with AI” [Caplan & Eaton] + other items re: AI in our learning ecosystems

On 03/08/2026, in 21st century, 24x7x365 access, adult learning, Artificial Intelligence/Agents/LLMs/and Related, bots, business, career development, cloud-based computing / apps / other cloud-related, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, emerging technologies, experimentation, faculty/staff, Google, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, K-12 related, learning, learning agents, learning ecosystem, liberal arts, platforms, skills, teachers, teaching & learning, tools, training / L&D, United States, universities, vendors, by Daniel Christian

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:

Answers grounded in your sources (with citations):
Source toggling:
Multi-format studio & multi-source summaries:
Persistent workspace:

…
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

Shadow AI is widespread in higher education: Faculty, researchers, students, and staff are using AI tools outside official IT channels, including consumer platforms and public cloud services that may involve sensitive data.
Unauthorized AI use creates data, compliance, and cost risks: Consumer AI tools may store or reuse user data, while uncoordinated adoption drives redundant licenses, unpredictable cloud costs, and weaker security oversight.
Institutions are shifting from restriction to enablement: Some campuses are making approved paths easier by offering ready-to-use research environments, campus-managed AI tools, clear guidance on data and vendors, and streamlined approval processes.

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:

Content generation – Start testing text-based tools to get a taste of how AI can accelerate content creation. Then take it to the next level by exploring tools that generate voices, music, and sound effects.
AI coaching tools – Have AI pose as a customer co-worker or customer to get a taste of what it’s like to use it as a conversation coach. Next, use the voice and video capabilities in an app like ChatGPT to explore how AI can coach someone through tasks.
In-the-flow learning assistants – Test turning documents into a conversational avatar and interacting with it to see how it feels. Then think about how the technology could potentially transform static content into dynamic learning experiences for employees.
Vibe-coded simulations – Experiment with this technology by creating a simple, fun game. Afterwards, brainstorm some ideas on how it could quickly create simulations for your learners in the future.

The Higher Ed Playbook for AI Affordability — from campustechnology.com by Jason Dunn-Potter

Key Takeaways

Affordable AI adoption focuses on evolving existing systems: Universities are embedding AI into current devices, workflows, and legacy systems rather than rebuilding infrastructure or investing in new data centers.
Edge AI reduces costs and improves access: Running AI models on local devices or networks lowers cloud processing costs, enhances security, and supports learning use cases such as tutoring, translation, transcription, and adaptive learning.
Enterprise integration and governance drive impact: Institutions are applying AI across admissions, advising, facilities, and research workflows, supported by shared resource hubs, data governance, AI literacy, and outcome-driven implementation.

Are microschools a solution to falling public school enrollment? One district thinks so [Fradette]

On 03/03/2026, in curriculum, education, education reform, ideas, instructional design, K-12 related, learning, learning ecosystem, Learning Experience Design, learning hubs & pods & microschooling, learning preferences, learning spaces, more voice more choice more control, parents/guardians, student-related, teachers, United States, youth, by Daniel Christian

Are microschools a solution to falling public school enrollment? One district thinks so — from hechingerreport.org by Rachel Fradette
In Indiana, a rural school district leader started a network of microschools to help keep students in his schools. The model could spread

Around the same time, the concept of microschooling was gaining traction nationally. Microschools offer multiage learning environments that focus on personalized, often less-regulated instruction. Popularity grew during the pandemic when families sought learning alternatives in online, hybrid and pod options; an estimated 750,000 to 2 million students now attend the schools.

The schools are typically privately run, but Philhower saw a role for them in his small district. Last year, he won approval from the state’s charter school board to establish the Indiana Microschool Collaborative, which he says will incubate a network of microschools statewide. They will operate as charter schools, meaning they are public but have more flexibility in terms of curricula and other operations than traditional public schools.

Learning Ecosystems

The Course Is Dying as the Unit of Learning. Here’s why, and what’s replacing It [Hardman]

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