digital learning

Tips on how to use Claude’s “Reading & Learning Mode” [Saidul Islam]

On 11/06/2026, in adjunct faculty, adult learning, Artificial Intelligence/Agents/LLMs/and Related, colleges, community colleges, corporate / business world, corporate universities / corporate training, digital learning, education, education technology, emerging technologies, experimentation, faculty/staff, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, learning, learning ecosystem, Learning Experience Design, liberal arts, library / librarians, personalized/customized learning, productivity / tips and tricks, professional development, skills, tools, vendors, by Daniel Christian

AI can improve performance, but did anyone learn? [Rodrigues]

On 10/27/2026, in adult learning, Artificial Intelligence/Agents/LLMs/and Related, business, career development, corporate / business world, corporate universities / corporate training, digital learning, emerging technologies, human-computer interaction (HCI), ideas, instructional design, learning, learning ecosystem, research, society, training / L&D, United States, workplace, by Daniel Christian

AI can improve performance, but did anyone learn? — from chieflearningofficer.com by Alexandre Rodrigues
Better AI-assisted performance does not always mean better learning. Here’s what L&D leaders can do about it.

A randomized field experiment involving thousands of knowledge workers found measurable productivity benefits from generative AI, including faster document completion. But productivity and learning are not the same outcome.

As organizations integrate AI more deeply into everyday work, L&D may need to confront an uncomfortable possibility: Employees can become better at producing results without becoming proportionally better at producing those results independently. Performance is visible. Learning is harder to see.

L&D researchers have long distinguished between performance during practice and learning that persists after practice. As Nicholas Soderstrom and Robert Bjork observed, what people do successfully while training is not always a reliable indicator of what they will retain or transfer later.

That distinction becomes particularly consequential in AI-enabled workplaces.

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

Per Derek:

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

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

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

Online Course Video Statistics — from markstudios.com by Mark Santos

“Every figure on this page links to the organization that produced it, and each was re-checked against that source before publishing. How many people take online courses, how big the platforms are, how long course videos actually hold attention, how many learners finish, what the money looks like, and which popular online course statistics do not survive being traced to their origin.”
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How to Reduce Cognitive Load in Digital Lessons — from educationtechnologysolutions.com by etsmagazine

A digital lesson can be beautifully designed and still make learning unnecessarily hard.

Students may be asked to watch a video, remember an instruction, find a link, switch tabs, interpret unfamiliar icons and submit a response—all before they have dealt with the idea the lesson was meant to teach.

That friction is often mistaken for rigour. It is not. Productive difficulty comes from thinking about the content. Avoidable difficulty comes from navigating the lesson.

The goal is not to make learning effortless. It is to spend students’ limited attention on the knowledge and skill that matter.

The above article links to:

Managing cognitive load optimises learning — from edresearch.edu.au
Implications for policymakers

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

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

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

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

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

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

“Using AI to create the practice opportunities online students need” [Miller Perkins] + other items re: AI in our learning ecosystems

On 08/19/2026, in 21st century, 24x7x365 access, adjunct faculty, adult learning, Artificial Intelligence/Agents/LLMs/and Related, assessment, business, career development, colleges, communications, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, education, education technology, emerging technologies, Emotion, engineering, experimentation, faculty/staff, game-changing environment, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, leadership, learning, learning agents, learning ecosystem, Learning Experience Design, learning spaces, liberal arts, mathematics, online learning, personalized/customized learning, productivity / tips and tricks, professional development, student-related, teachers, teaching & learning, technologies for your home, tools, training / L&D, UK, United States, universities, vendors, workplace, youth, by Daniel Christian

Using AI to create the practice opportunities online students need— from timeshighereducation.com by Kathy Miller Perkins
For disciplines that depend on interpersonal skills such as communication, leadership, negotiation and mediation, AI can provide elusive experiential learning, particularly in asynchronous environments

What if AI’s greatest educational value lies not in generating answers but in generating experiences?

The result surprised me. Students did not simply interact with the AI, they meaningfully engaged with it. Many reported that the experience felt valuable precisely because the simulated conversation partner pushed back. Unlike classmates who sometimes hesitate to challenge one another, the AI consistently maintained its position. Students had to work harder, listen more carefully and apply the communication strategies they had spent weeks learning. And, importantly, they practised.

Here’s how to show students what responsible AI use looks like — from timeshighereducation.com by Andrew Firr and Alex Fenton
Well-designed assessments can highlight generative AI’s limitations, where it can provide support and what responsible practice looks like. Andrew Firr and Alex Fenton offer strategies

We have been exploring ways to offer this in our Level 7 module for MSc engineering management students, many of whom come from the Global South. Assessment is built around a practical design problem: students examine how a real campus process operates, where delays occur, evidence they observe and how a feasible redesign might improve the system – in a 3,000-word essay.

They can use AI for planning and providing clarity, but not for generating the evidence on which the analysis rests. Invented observations, measurements, screenshots or unverifiable citations are prohibited. The assessment design reinforces this through a case study, diagram, fact-checking exercise and a short AI use statement.

Requiring an AI use statement encourages students to reflect on their processes. We ask which tool they used, how they used it, how they checked the output and which parts of the work depended on their own evidence and judgement. It reminds them that evidence must be theirs and that citations must be manually verified.

Slow math: Kids may learn more when AI makes them review mistakes — from hechingerreport.org by Jill Barshay and Kristin Fasiang
A randomized experiment involved more than 6,000 Tennessee middle school students learning fractions

In an experiment involving more than 6,000 middle schoolers in Tennessee, students learned slightly more math when an AI tutor walked them through their mistakes and then required them to demonstrate the same skill correctly three times in a row before moving on.
…
The winning combination wasn’t the addition of AI tutoring alone, but AI tutoring plus repetition, with the idea that students needed to stick with the skill to demonstrate some level of mastery. The students who practiced math with this AI-enhanced “mastery learning” approach scored about 3 percentage points higher than students receiving conventional computerized instruction. The advantage was small.

I Built a Team of AI Bots That Write Feedback Better than Me. Here’s How. — from drphilippahardman.substack.com by Dr Philippa Hardman
Aka, how to make learners love AI-assisted feedback, rather than loathe it.

This wasn’t hidden from the cohort. For reasons I’ll come to below, I always tell my cohorts at the very start that an AI assistant will be helping me draft their feedback. The aim wasn’t to remove me from the process, but to find out whether AI could help me to deliver feedback at a volume and quality that I simply couldn’t maintain without AI.

Spoiler: the experiment worked — but not for the reason I expected. In this post, I’ll share exactly what I built, tell you how to build a version for your course and reveal the three conditions that decide whether learners trust AI-assisted feedback or quietly stop reading it.

TL;DR: the spec for my feedback assistant is long not because the model needs persuading, but because it’s where my judgement lives. Every rule in it is a decision AI would otherwise make by itself, with limited expertise. A spec doesn’t make the model smarter — it makes expertise and judgement legible enough for the model to follow.

Of the five stages of AI grief, some managers are stuck in denial— from timeshighereducation.com by Shadi Mohamed
Acceptance is not surrender. It is about getting beyond a policing obsession and rethinking what assessment aims to measure, says Shadi Mohamed

In that moment of institutional blindness, it struck me: universities are not merely struggling with a technological adoption curve. They are grieving the demise of the modern university’s economic and institutional logic.

To understand the scale of this threat posed by AI, consider what the internet did to journalism. Newspapers thrived by bundling together classified advertising with quick news hits, sports scores and opinion columns, using that reliable revenue to fund the expensive social necessity of investigative reporting. The rise of internet advertising did not kill journalism outright but it shattered the bundle, leaving the expensive core product without its historical financial engine.

Universities operate on a similar logic, bundling content delivery, assessment, credentialling, research and professional formation. But generative AI is now commodifying the most visible parts of that package. When AI can deliver personalised explanations instantly and generate the essays and reports we use to measure student capability, the traditional degree loses its role in the labour market as a proxy for understanding. If the bundle breaks, the economic model that funds our deeper purposes is in peril.

Will this new company be the largest company on the Internet by 2030? [Christian]

On 08/01/2026, in 21st century, 24x7x365 access, adult learning, Artificial Intelligence/Agents/LLMs/and Related, Bias | Diversity Equity & Inclusion (DE&I), career development, cloud-based computing / apps / other cloud-related, communities of practice, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, cost of getting a degree, credentialing, curriculum, Daniel S. Christian, digital learning, disruption, education, education technology, elearning, emerging technologies, engagement / engaging students, future, future of higher education, game-changing environment, generational differences, global, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, informal learning, innovation, instructional design, intelligent systems, intelligent tutoring, internet, K-12 related, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning preferences, learning spaces, lifelong learning, love of learning, more voice more choice more control, motivation, online learning, online media, online tutoring, pathways, personalized/customized learning, platforms, productivity / tips and tricks, professional development, reinvent, society, staying relevant, student-related, teachers, teaching & learning, training / L&D, United States, vision/possibilities, web-based collaboration, youth, by Daniel Christian

From DSC:
The vision that I’ve been tracking for well over a decade begins with this graphic:
.

Could LearnVector be this next-generation company/platform? Perhaps. Time will tell.

Per Matt Tower via The EdSheet Vol. 38 dated 7/31/26:

Coursera bets $100M on its own co-founder: Andrew Ng’s new venture LearnVector lands one of the largest single checks in edtech this year — from Coursera, the company he founded 14 years ago.
.

LearnVector.ai

How Explainer Video Production Turns Ideas Into Clear Stories [Williamson]

On 07/31/2026, in adult learning, business, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, digital storytelling, digital video, ideas, instructional design, learning, Learning Experience Design, productivity / tips and tricks, training / L&D, by Daniel Christian

How Explainer Video Production Turns Ideas Into Clear Stories — from bitrebels.com by Lauren Williamson

Ideas rarely arrive in a neat order. They show up as notes, claims, diagrams, feature lists, and customer questions. Explainer video production turns that raw material into a story people can process quickly. It clarifies the problem, frames the change, and shows why the answer matters. When the script, visuals, voice, and pacing work together, viewers spend less energy decoding the message and more attention on absorbing it.

Explainer video production works because it gives ideas a usable order. It turns scattered information into a story with purpose, pace, and visual evidence. The strongest results come from careful message decisions before animation starts. When script, design, voice, and timing support one central point, viewers can follow with less effort. That clarity helps organizations teach, persuade, and make it easier to remember.

Flipped Classrooms and Academic Achievement — from learningscientists.org by Megan Sumeracki

There are actually many, many ways to design a flipped classroom, and it has been fascinating to learn about the ways my colleague typically structures her hybrid, flipped-classroom courses. As a result, we’ve been able to engage in really interesting conversations about the best approach for this particular course, and why. As a result of some of these discussions, I came across a few recent meta-analyses related to the effects of flipped classrooms, the results of which I thought were worth sharing here (1, 2, 3).

NotebookLM’s 60-second videos turned my doomscrolling curse into something useful [Sood]

On 07/06/2026, in Artificial Intelligence/Agents/LLMs/and Related, digital audio, digital learning, digital video, education technology, emerging technologies, experimentation, faculty/staff, platforms, productivity / tips and tricks, student-related, tools, by Daniel Christian

NotebookLM’s 60-second videos turned my doomscrolling curse into something useful — from digitaltrends.com by Shimul Sood

Google has announced Short Video Overviews for NotebookLM, a feature that turns dense documents and complicated sources into 60-second vertical videos that explain key ideas. Instead of staring at pages of notes, you get a quick visual walkthrough of the concept you’re trying to understand.

Doom scrolling but make it educational ?

Introducing Short Video Overviews in NotebookLM! Turn your most complex sources into 60-second, vertical videos that deep dive into any concept.

Rolling out now to Google AI Ultra and Pro subscribers on mobile & web (free users soon!) pic.twitter.com/vaOa4ELbw4

— NotebookLM (@NotebookLM) June 30, 2026

Christian: Could this be a part of our future learning ecosystems?

On 06/09/2026, in 21st century, 24x7x365 access, adult learning, Artificial Intelligence/Agents/LLMs/and Related, career development, cloud-based computing / apps / other cloud-related, CMS/LMS, communities of practice, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, Daniel S. Christian, digital learning, education technology, emerging technologies, engagement / engaging students, experimentation, faculty/staff, future, future of higher education, game-changing environment, global, heutagogy, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, informal learning, 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 hubs & pods & microschooling, learning preferences, learning spaces, liberal arts, library / librarians, lifelong learning, love of learning, microlearning, more voice more choice more control, online learning, online media, passions, personalized/customized learning, platforms, professional development, skills, social media, streams of content, student-related, teachers, teaching & learning, technologies for your home, training / L&D, United States, user experience (UX), vendors, vision/possibilities, by Daniel Christian

From DSC:
Could this be a part of our future learning ecosystems? Education as a personalized content feed.

Coursera wants users to learn through shorter, faster content — from digitaltrends.com by Moinak Pal
Coursera wants online learning to feel more like TikTok
.

Online learning platform Coursera is taking a page straight out of TikTok’s playbook. The company has launched a new AI-powered feed designed to serve short-form educational content in a scrollable, personalized format, signaling a major shift in how digital learning platforms may try to keep users engaged.

The feature introduces bite-sized video lessons, clips, and explainers curated through artificial intelligence based on a user’s interests, learning habits, career goals, and previous course activity. Instead of committing to hour-long lectures or full certification programs upfront, users can now discover short educational snippets designed to make learning feel more casual, accessible, and addictive.

Users scroll through a feed of short educational videos and AI-curated learning moments covering topics ranging from coding and business to AI, productivity, data science, and personal development.

Pinpoint, Explained | A guide to Google’s free tool, now open to all [Caplan]

On 06/05/2026, in adjunct faculty, Artificial Intelligence/Agents/LLMs/and Related, colleges, communities of practice, community colleges, content development, aggregation, repositories, data related items, digital audio, digital learning, digital video, education, education technology, faculty/staff, Google, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, IT in HE, journalism, K-12 related, languages and translation, learning, learning agents, learning ecosystem, liberal arts, library / librarians, research, teaching & learning, tools, United States, universities, vendors, by Daniel Christian

Pinpoint, Explained — from wondertools.substack.com by Jeremy Caplan
A guide to Google’s free tool, now open to all

.Jeremy prompted ChatGPT to generate illustrations in his post.

.

Learn about Pinpoint— from support.google.com

Pinpoint is an AI-powered research platform designed to help journalists and academics analyze large collections of documents. With Pinpoint, you can:

Analyze massive collections: Easily search, filter, transcribe and organize thousands of documents, including PDFs, images, and audio files.
Leverage generative AI: Use Gemini’s capabilities to answer research questions together with supporting evidence found in your documents.
Foster collaborative research: share your work with colleagues and tackle large scale projects as a team. You can also publicly share – supporting community-driven research.

For assistance with Pinpoint, please consult our Community Forum or you can contact our support team.

Cleveland Institute of Art’s Interactive Media Lab Redefines What an Art School Can Be — from edtechmagazine.com

The landscape for specialized colleges and universities such as art schools is shifting as higher education continues to evolve to fit emerging job markets and student interest.

Founded in 1882, Cleveland Institute of Art continuously challenges itself to stay modern and relevant. Years ago, the school’s leadership had the vision to partner with the city to revitalize an area due for reinvigoration.

The result was the Interactive Media Lab, which brings together the university, the city and private industry into a satellite campus that gives students and the community a space to create media, art and experiences with the most up-to-date tools available.

Also see:

Learning Ecosystems

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

How Explainer Video Production Turns Ideas Into Clear Stories [Williamson]

Cleveland Institute of Art’s Interactive Media Lab Redefines What an Art School Can Be [edtechmagazine.com]

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