memory

The Essential Retrieval Practice Handbook — from edutopia.org
Retrieval practice is one of the most effective ways to strengthen learning. Here’s a collection of our best resources to use in your classroom today.
January 29, 2026

Also see:

What is retrieval practice? — from retrievalpractice.org

When we think about learning, we typically focus on getting information into students’ heads. What if, instead, we focus on getting information out of students’ heads?

“Introducing AI assistants with memory” + other items re: AI in our learning ecosystems

On 12/01/2025, in accessibility / UDL, adjunct faculty, Artificial Intelligence/Agents/LLMs/and Related, bots, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate universities / corporate training, digital learning, digital video, education, education technology, emerging technologies, experimentation, faculty/staff, future of higher education, game-changing environment, generational differences, Google, higher education, human-computer interaction (HCI), innovation, instructional design, intelligent systems, IT in HE, 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, memory, multimedia, personalized/customized learning, platforms, productivity / tips and tricks, student-related, teachers, teaching & learning, tools, training / L&D, trends, United States, universities, vendors, by Daniel Christian

4 Simple & Easy Ways to Use AI to Differentiate Instruction — from mindfulaiedu.substack.com (Mindful AI for Education) by Dani Kachorsky, PhD
Designing for All Learners with AI and Universal Design Learning

So this year, I’ve been exploring new ways that AI can help support students with disabilities—students on IEPs, learning plans, or 504s—and, honestly, it’s changing the way I think about differentiation in general.

As a quick note, a lot of what I’m finding applies just as well to English language learners or really to any students. One of the big ideas behind Universal Design for Learning (UDL) is that accommodations and strategies designed for students with disabilities are often just good teaching practices. When we plan instruction that’s accessible to the widest possible range of learners, everyone benefits. For example, UDL encourages explaining things in multiple modes—written, visual, auditory, kinesthetic—because people access information differently. I hear students say they’re “visual learners,” but I think everyone is a visual learner, and an auditory learner, and a kinesthetic learner. The more ways we present information, the more likely it is to stick.

So, with that in mind, here are four ways I’ve been using AI to differentiate instruction for students with disabilities (and, really, everyone else too):

The Periodic Table of AI Tools In Education To Try Today — from ictevangelist.com by Mark Anderson

What I’ve tried to do is bring together genuinely useful AI tools that I know are already making a difference.

For colleagues wanting to explore further, I’m sharing the list exactly as it appears in the table, including website links, grouped by category below. Please do check it out, as along with links to all of the resources, I’ve also written a brief summary explaining what each of the different tools do and how they can help.

Seven Hard-Won Lessons from Building AI Learning Tools — from linkedin.com by Louise Worgan

Last week, I wrapped up Dr Philippa Hardman’s intensive bootcamp on AI in learning design. Four conversations, countless iterations, and more than a few humbling moments later – here’s what I am left thinking about.

Finally Catching Up to the New Models — from michellekassorla.substack.com by Michelle Kassorla
There are some amazing things happening out there!

An aside: Google is working on a new vision for textbooks that can be easily differentiated based on the beautiful success for NotebookLM. You can get on the waiting list for that tool by going to LearnYourWay.withgoogle.com.
…
Nano Banana Pro
Sticking with the Google tools for now, Nano Banana Pro (which you can use for free on Google’s AI Studio), is doing something that everyone has been waiting a long time for: it adds correct text to images.

Introducing AI assistants with memory — from perplexity.ai

The simple act of remembering is the crux of how we navigate the world: it shapes our experiences, informs our decisions, and helps us anticipate what comes next. For AI agents like Comet Assistant, that continuity leads to a more powerful, personalized experience.

Today we are announcing new personalization features to remember your preferences, interests, and conversations. Perplexity now synthesizes them automatically like memory, for valuable context on relevant tasks. Answers are smarter, faster, and more personalized, no matter how you work.

From DSC :
This should be important as we look at learning-related applications for AI.

For the last three days, my Substack has been in the top “Rising in Education” list. I realize this is based on a hugely flawed metric, but it still feels good. ?

– Michael G Wagner

Read on Substack

I’m a Professor. A.I. Has Changed My Classroom, but Not for the Worse. — from nytimes.com by Carlo Rotella [this should be a gifted article]
My students’ easy access to chatbots forced me to make humanities instruction even more human.

“The AI opportunity in L&D isn’t one thing – it’s five different capability unlocks.” [Vinauskaite] + other items re: AI in our LE’s

On 11/21/2025, in Artificial Intelligence/Agents/LLMs/and Related, business, cloud-based computing / apps / other cloud-related, colleges, community colleges, corporate / business world, corporate universities / corporate training, digital learning, emerging technologies, faculty/staff, game-changing environment, higher education, innovation, instructional design, learning agents, learning ecosystem, Learning Experience Design, memory, online learning, Open AI, pedagogy, platforms, productivity / tips and tricks, professional development, simulations, skills, student-related, teachers, teaching & learning, tools, training / L&D, United States, universities, workplace, by Daniel Christian

AI’s Role in Online Learning > Take It or Leave It with Michelle Beavers, Leo Lo, and Sara McClellan — from intentionalteaching.buzzsprout.com by Derek Bruff

You’ll hear me briefly describe five recent op-eds on teaching and learning in higher ed. For each op-ed, I’ll ask each of our panelists if they “take it,” that is, generally agree with the main thesis of the essay, or “leave it.” This is an artificial binary that I’ve found to generate rich discussion of the issues at hand.

“OpenAI’s Atlas: the End of Online Learning—or Just the Beginning?” [Hardman] + other items re: AI in our LE’s

On 10/28/2025, in 21st century, 24x7x365 access, adult learning, Artificial Intelligence/Agents/LLMs/and Related, assessment, assistive technologies, change, collaboration, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate universities / corporate training, digital learning, education technology, emerging technologies, experimentation, faculty/staff, game-changing environment, generational differences, heutagogy, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, internet, IT in HE, K-12 related, law schools, learner profiles, learning, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning preferences, learning spaces, learning theories, liberal arts, library / librarians, lifelong learning, memory, online learning, online media, online tutoring, Open AI, pedagogy, personalized/customized learning, platforms, productivity / tips and tricks, reading, student-related, teachers, teaching & learning, teaching online, technologies for your home, tools, training / L&D, trends, United States, universities, usability, user experience (UX), vendors, virtual tutoring, vision/possibilities, web-based collaboration, by Daniel Christian

OpenAI’s Atlas: the End of Online Learning—or Just the Beginning? — from drphilippahardman.substack.com by Dr. Philippa Hardman

My take is this: in all of the anxiety lies a crucial and long-overdue opportunity to deliver better learning experiences. Precisely because Atlas perceives the same context in the same moment as you, it can transform learning into a process aligned with core neuro-scientific principles—including active retrieval, guided attention, adaptive feedback and context-dependent memory formation.

Perhaps in Atlas we have a browser that for the first time isn’t just a portal to information, but one which can become a co-participant in active cognitive engagement—enabling iterative practice, reflective thinking, and real-time scaffolding as you move through challenges and ideas online.

With this in mind, I put together 10 use cases for Atlas for you to try for yourself.
…

6. Retrieval Practice
What: Pulling information from memory drives retention better than re-reading.
Why: Practice testing delivers medium-to-large effects (Adesope et al., 2017).
Try: Open a document with your previous notes. Ask Atlas for a mixed activity set: “Quiz me on the Krebs cycle—give me a near-miss, high-stretch MCQ, then a fill-in-the-blank, then ask me to explain it to a teen.”
Atlas uses its browser memory to generate targeted questions from your actual study materials, supporting spaced, varied retrieval.

From DSC:
A quick comment. I appreciate these ideas and approaches from Katarzyna and Rita. I do think that someone is going to want to be sure that the AI models/platforms/tools are given up-to-date information and updated instructions — i.e., any new procedures, steps to take, etc. Perhaps I’m missing the boat here, but an internal AI platform is going to need to have access to up-to-date information and instructions.

From siloed tools to intelligent journeys: Reimagining learning experience in the age of ‘Experience AI’ [Gonick]

On 10/17/2025, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, changing business models, CMS/LMS, collaboration, colleges, community colleges, digital learning, education, education technology, emerging technologies, engagement / engaging students, experimentation, faculty/staff, future of higher education, game-changing environment, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, memory, multimedia, personalized/customized learning, platforms, student-related, teaching & learning, United States, universities, vision/possibilities, by Daniel Christian

From siloed tools to intelligent journeys: Reimagining learning experience in the age of ‘Experience AI’ — from linkedin.com by Lev Gonick

Experience AI: A new architecture of learning
Experience AI represents a new architecture for learning — one that prioritizes continuity, agency and deep personalization. It fuses three dimensions into a new category of co-intelligent systems:

Agentic AI that evolves with the learner, not just serves them
Persona-based AI that adapts to individual goals, identities and motivations
Multimodal AI that engages across text, voice, video, simulation and interaction

Experience AI brings learning into context. It powers personalized, problem-based journeys where students explore ideas, reflect on progress and co-create meaning — with both human and machine collaborators.

Making Retrieval Practice a Classroom Routine [edutopia.org]

On 10/06/2025, in education, ideas, instructional design, learning, Learning Experience Design, learning theories, memory, pedagogy, student-related, teachers, teaching & learning, United States, by Daniel Christian

Making Retrieval Practice a Classroom Routine — from edutopia.org
By regularly working in activities that get students to recall content they’ve learned in the past and apply it, teachers can ensure deeper understanding.

Also see:

The Teaching Tips section out at RetrievalPractice.org
Retrieval practice is a simple research-based teaching strategy that dramatically raises students’ grades. When students retrieve and bring information to mind, this mental challenge produces durable long-term learning. Easy learning leads to easy forgetting. Stop cramming, reviewing, and re-teaching. Instead, simply ask students what they remember. No prep, no grading, just powerful teaching. The science of learning exists. It’s time to unleash it.

ChatGPT: the world’s most influential teacher [Hardman]

On 09/20/2025, in 21st century, 24x7x365 access, adult learning, Artificial Intelligence/Agents/LLMs/and Related, assessment, bots, cloud-based computing / apps / other cloud-related, colleges, communities of practice, community colleges, corporate / business world, corporate universities / corporate training, digital learning, education, education technology, emerging technologies, faculty/staff, future, future of higher education, game-changing environment, generational differences, heutagogy, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), instructional design, intelligent systems, intelligent tutoring, internet, IT in HE, K-12 related, law schools, learner profiles, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning preferences, learning spaces, learning theories, liberal arts, library / librarians, lifelong learning, memory, metacognition / metacognitive skills, Open AI, pedagogy, personalized/customized learning, platforms, productivity / tips and tricks, society, student-related, teachers, teaching & learning, technologies for your home, tools, training / L&D, trends, United States, universities, vendors, web-based collaboration, by Daniel Christian

ChatGPT: the world’s most influential teacher — from drphilippahardman.substack.com by Dr. Philippa Hardman; emphasis DSC
New research shows that millions of us are “learning with AI” every week: what does this mean for how (and how well) humans learn?

This week, an important piece of research landed that confirms the gravity of AI’s role in the learning process. The TLDR is that learning is now a mainstream use case for ChatGPT; around 10.2% of all ChatGPT messages (that’s ~2BN messages sent by over 7 million users per week) are requests for help with learning.

The research shows that about 10.2% of all messages are tutoring/teaching, and within the “Practical Guidance” category, tutoring is 36%. “Asking” interactions are growing faster than “Doing” and are rated higher quality by users. Younger people contribute a huge share of messages, and growth is fastest in low- and middle-income countries (How People Use ChatGPT, 2025).

If AI is already acting as a global tutor, the question isn’t “will people learn with AI?”—they already are. The real question we need to ask is: what does great learning actually look like, and how should AI evolve to support it? That’s where decades of learning science help us separate “feels like learning” from “actually gaining new knowledge and skills”.

Let’s dive in.

15 Quick (and Mighty) Retrieval Practices — from edutopia.org by Daniel Leonard
From concept maps to flash cards to Pictionary, these activities help students reflect on—and remember—what they’ve learned.

But to genuinely commit information to long-term memory, there’s no replacement for active retrieval—the effortful practice of recalling information from memory, unaided by external sources like notes or the textbook. “Studying this way is mentally difficult,” Willingham acknowledged, “but it’s really, really good for memory.”
…
From low-stakes quizzes to review games to flash cards, there are a variety of effective retrieval practices that teachers can implement in class or recommend that students try at home. Drawing from a wide range of research, we compiled this list of 15 actionable retrieval practices.

And speaking of cognitive science, also see:

‘Cognitive Science,’ All the Rage in British Schools, Fails to Register in U.S. — from the74million.org by Greg Toppo
Educators blame this ‘reverse Beatles effect’ on America’s decentralized system and grad schools that are often hostile to research.

When Zach Groshell zoomed in as a guest on a longstanding British education podcast last March, a co-host began the interview by telling listeners he was “very well-known over in the U.S.”

Groshell, a former Seattle-area fourth-grade teacher, had to laugh: “Nobody knows me here in the U.S.,” he said in an interview.

But in Britain, lots of teachers know his name. An in-demand speaker at education conferences, he flies to London “as frequently as I can” to discuss Just Tell Them, his 2024 book on explicit instruction. Over the past year, Groshell has appeared virtually about once a month and has made two personal appearances at events across England.

The reason? A discipline known as cognitive science. Born in the U.S., it relies on decades of research on how kids learn to guide teachers in the classroom, and is at the root of several effective reforms, including the Science of Reading.

Getting (and Keeping) Early Learners’ Attention — from edutopia.org by Heather Sanderell
These ideas for lesson hooks—like using songs, video clips, and picture walks—can motivate young students to focus on learning.

How do you grasp and maintain the attention of a room full of wide-eyed students with varying interests and abilities? Do you use visuals and games or interactive activities? Do you use art and sports and music or sounds? The answer is yes, to all!

When trying to keep the attention of your learners, it’s important to stimulate their senses and pique their diverse interests. Educational theorist and researcher Robert Gagné devised his nine events of instructional design, which include grabbing learners’ attention with a lesson hook. This is done first to set the tone for the remainder of the lesson.

3 Ways to Help Students Overcome the Forgetting Curve — from edutopia.org by Cathleen Beachboard
Our brains are wired to forget things unless we take active steps to remember. Here’s how you can help students hold on to what they learn.

You teach a lesson that lights up the room. Students are nodding and hands are flying up, and afterward you walk out thinking, “They got it. They really got it.”

And then, the next week, you ask a simple review question—and the room falls silent.

If that situation has ever made you question your ability to teach, take heart: You’re not failing, you’re simply facing the forgetting curve. Understanding why students forget—and how we can help them remember—can transform not just our lessons but our students’ futures.

The good news? You don’t have to overhaul your curriculum to beat the forgetting curve. You just need three small, powerful shifts in how you teach.

From DSC:
Along these same lines, also see:

https://www.retrievalpractice.org/

.

7 Nature Experiments to Spark Student Curiosity — from edutopia.org by Donna Phillips
Encourage your students to ask questions about and explore the world around them with these hands-on lessons.

Children are natural scientists—they ask big questions, notice tiny details, and learn best through hands-on exploration. That’s why nature experiments are a classroom staple for me. From growing seeds to using the sun’s energy, students don’t just learn science, they experience it. Here are my favorite go-to nature experiments that spark curiosity.

“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.

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

Outsourcing Thought: The Hidden Cost of Letting AI Think for You — from linkedin.com by Robert Atkinson

I’ve watched it unfold in real time. A student submits a flawless coding assignment or a beautifully written essay—clean syntax, sharp logic, polished prose. But when I ask them to explain their thinking, they hesitate. They can’t trace their reasoning or walk me through the process. The output is strong, but the understanding is shallow. As a professor, I’ve seen this pattern grow more common: AI-assisted work that looks impressive on the surface but reveals a troubling absence of cognitive depth underneath.

This article is written with my students in mind—but it’s meant for anyone navigating learning, teaching, or thinking in the age of artificial intelligence. Whether you’re a student, educator, or professional, the question is the same: What happens to the brain when we stop doing our own thinking?

We are standing at a pivotal moment. With just a few prompts, generative AI can produce essays, solve complex coding problems, and summarize ideas in seconds. It feels efficient. It feels like progress. But from a cognitive neuroscience perspective, that convenience comes at a hidden cost: the gradual erosion of the neural processes that support reasoning, creativity, and long-term learning.

VLOG: Learning in Medical School [The Learning Scientists]

On 12/07/2024, in Emotion, experimentation, faculty/staff, health, higher education, instructional design, learning, learning ecosystem, Learning Experience Design, memory, productivity / tips and tricks, student-related, teaching & learning, United States, universities, vendors, by Daniel Christian

VLOG: Learning in Medical School — from learningscientists.org by The Learning Scientists

NOTE:

This vlog is for anyone in medical school, interested in medical school, or just curious about what learning is like in medical school!

In this vlog Althea and Cindy talk about their work with medical student learners. They discuss common learning challenges in medical school, efficient learning strategies, learning in the context of attentional disorders and anxiety, and what it means to prepare future healers.

Teacher pay, Canvas/Instructure updates, special education staffing shortages & other items re: education

On 11/21/2024, in CMS/LMS, data related items, education, education technology, emerging technologies, future, K-12 related, leadership, learning, learning ecosystem, memory, neurodivergent/special needs, parents/guardians, pedagogy, teachers, United States, vendors, youth, by Daniel Christian

What Teacher Pay and Benefits Look Like, in Charts — from edweek.org by Sarah D. Sparks

Special education staffing shortages put students’ futures at risk. How to solve that is tricky. — from chalkbeat.org by Kalyn Belsha

The debate comes as the number of students with disabilities is growing. Some 7.5 million students required special education services as of the 2022-23 school year, the latest federal data shows, or around 15% of students. That was up from 7.1 million or 14% of students in the 2018-19 school year, just before the pandemic hit.

It’s unclear if the rise is due to schools getting better at identifying students with disabilities or if more children have needs now. Many young children missed early intervention and early special education services during the pandemic, and many educators say they are seeing higher behavioral needs and wider academic gaps in their classrooms.

“Students are arriving in our classrooms with a high level of dysregulation, which is displayed through their fight, flight, or freeze responses,” Tiffany Anderson, the superintendent of Topeka, Kansas’ public schools, wrote in her statement. “Students are also displaying more physically aggressive behavior.”

Expanding Access, Value and Experiences Through Credentialing — from gettingsmart.com by Nate McClennen, Tom Vander Ark and Mason Pashia
A Landscape Analysis of Credentialing and Its Impact on K-12

Executive Summary

This report examines the evolving landscape of credentialing and learner records within global education systems, highlighting a shift from traditional time-based signals—such as courses and grades—to competency-based signals (credentials and learner records).

Also recommended by Getting Smart, see:

New Goals Learning Experiences and Signals — — from gettingsmart.com by Tom Vander Ark and Carri Schneider

Retrieval practice improves learning for neurodiverse students — from by Pooja K. Agarwal, Ph.D.

In my 15+ years of teaching, I have had students with autism spectrum disorder, ADHD, dyslexia, and a range of learning disabilities. I have grown in my understanding of inclusive teaching practices and I strive to incorporate universal design principles in my teaching.

From my classroom experience, I know that retrieval practice improves learning for all of my students, including those who are neurodiverse. But what have researchers found about retrieval practice with neurodiverse learners?

(Side note: If you’d like an intro on neurodiversity and what it means in the classroom, I recommend this podcast episode from The Learning Scientists and this podcast episode from Teaching in Higher Ed. For teaching tips, I recommend this article from the University of Illinois CITL.)

Instructure Is Ready To Lead The Next Evolution In Learning — from forbes.com by Ray Ravaglia

Learning Management In The AI Future
While LMS platforms like Canvas have positively impacted education, they’ve rarely lived up to their potential for personalized learning. With the advent of artificial intelligence (AI), this is set to change in revolutionary ways.

The promise of AI lies in its ability to automate repetitive tasks associated with student assessment and management, freeing educators to focus on education. More significantly, AI has the potential to go beyond the narrow focus on the end products of learning (like assignments) to capture insights into the learning process itself. This means analyzing the entire transcript of activities within the LMS, providing a dynamic, data-driven view of student progress rather than just seeing signposts of where students have been and what they have taken away.
…
Things become more potent by moving away from a particular student’s traversal of a specific course to looking at large aggregations of students traversing similar courses. This is why Instructure’s acquisition of Parchment, a company specializing in credential and transcript management, is so significant.

Sharpen your students’ interview skills — from timeshighereducation.com by Lewis Humphreys (though higher education-related, this is still solid information for those in K12)
The employees of the future will need to showcase their skills in job interviews. Make sure they’re prepared for each setting, writes Lewis Humphreys

In today’s ultra-competitive job market, strong interview skills are paramount for students taking their first steps into the professional world. University careers services play a crucial role in equipping our students with the tools and confidence needed to excel in a range of interview settings. From pre-recorded video interviews to live online sessions and traditional face-to-face meetings, students must be adaptable and well-prepared. Here, I’ll explore ways universities can teach interview skills to students and graduates, helping them to present themselves and their skills in the best light possible.

AI-based apps starting to remember more about us — in learning-related apps, that’s a good thing!

On 05/03/2024, in Artificial Intelligence/Agents/LLMs/and Related, colleges, community colleges, education technology, emerging technologies, future, future of higher education, game-changing environment, higher education, 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, memory, online tutoring, Open AI, personalized/customized learning, platforms, teaching & learning, technologies for your home, tools, United States, universities, vendors, by Daniel Christian

ChatGPT remembers who you are — from thebrainyacts.beehiiv.com |Brainyacts #191

OpenAI rolls out Memory feature for ChatGPT
OpenAI has introduced a cool update for ChatGPT (rolling out to paid and free users – but not in the EU or Korea), enabling the AI to remember user-specific details across sessions. This memory feature enhances personalization and efficiency, making your interactions with ChatGPT more relevant and engaging.

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Key Features

Automatic Memory Tracking
- ChatGPT now automatically records information from your interactions such as preferences, interests, and plans. This allows the AI to refine its responses over time, making each conversation increasingly tailored to you.
Enhanced Personalization
- The more you interact with ChatGPT, the better it understands your needs and adapts its responses accordingly. This personalization improves the relevance and efficiency of your interactions, whether you’re asking for daily tasks or discussing complex topics.
Memory Management Options
- You have full control over this feature. You can view what information is stored, toggle the memory on or off, and delete specific data or all memory entries, ensuring your privacy and preferences are respected.

Memory is now available to all ChatGPT Plus users. Using Memory is easy: just start a new chat and tell ChatGPT anything you’d like it to remember.

Memory can be turned on or off in settings and is not currently available in Europe or Korea. Team, Enterprise, and GPTs to come. pic.twitter.com/mlt9vyYeMK

— OpenAI (@OpenAI) April 29, 2024

From DSC:
The ability of AI-based applications to remember things about us will have major and positive ramifications for us when we think about learning-related applications of AI.

Learning Ecosystems

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