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.
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.
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.
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.
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.
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.
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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.
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.
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.
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.
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.
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.
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.
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.”
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).
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?
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.
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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.
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
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.
“Knowing is not enough; we must apply. Willing is not enough; we must do.”
Johann Wolfgang von Goethe
Learning Transfer’s ultimate outcome is behaviour change, so we must understand the conditions that trigger a behaviour to start.
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According to Fogg, three specific elements must converge at the same moment for a specific behaviour to occur. Given that learning transfer is only successful when the learner starts behaving in the desired new ways, Fogg’s work is critical to understanding how to generate these new behaviours. The Fogg Behavioural Model [*1] states that B=MAP. That is, a specific behaviour will occur if at the same moment there is sufficient motivation, sufficient ability and sufficient prompt. If the behaviour does not occur, at least one of these three elements is missing or below the threshold required.
The prompt is, in effect, a call to action to do a specific behaviour. The prompt must be ‘loud’ enough for the target person to perceive it and be consciously aware of it. Once aware of a prompt, the target immediately, and largely unconsciously, assesses their ability to carry out the requested behaviour: how difficult would this be, how long will it take, who can help me, and so on. They base this on their perception of the difficulty of the requested behaviour, and their ability, as they see it, to achieve that behaviour.
Executive function is a set of mental skills that include working memory, flexible thinking, and self-control. We use these skills every day to learn, work, and manage daily life. Trouble with executive function can make it hard to focus, follow directions, and handle emotions, among other things.
Snapshot: What executive function is
Some people describe executive function as “the management system of the brain.” That’s because the skills involved let us set goals, plan, and get things done. When people struggle with executive function, it impacts them at home, in school, and in life.
There are three main areas of executive function. They are…
Using Drawing as a Powerful Learning Tool — from edutopia.org by Selim Tlili When students draw something they’re learning about, they’re more likely to remember key details.
One of my main goals as a science teacher is to open students up to seeing all of those beautiful and interesting details. I do that by having students draw things and clearly write what they observe. Drawing something requires students to look at their subject far longer than they are accustomed. Writing what they see forces them to consciously acknowledge it. I explain to students that just as every single human is unique, so is every coin, plant, and salt crystal.
For the first time, a physical neural network has successfully been shown to learn and remember “on the fly,” in a way inspired by and similar to how the brain’s neurons work.
The Rundown: University of Sydney researchers have created a “brain-like” nanowire network capable of learning and remembering in real-time, similar to that of human brain function.
The details:
The nanowire neural network self-organizes into patterns, functioning like the brain’s synapses by responding to electrical currents.
What we teachers desperately need, though, is an ocean of examples and training. We need to see and share examples of generative AI—any type of artificial intelligence that can be used to create new text, images, video, audio, code, or data—being used across the curriculum. We need catalogs of new lesson plans and new curriculum.
And we need training on theoretical and practical levels: training to understand what artificial intelligence actually is and where it stands in the development timeline and training about how to integrate it into our classes.
So, my advice to teachers is to use any and all the generative AI you can get your hands on. Then experience—for yourself—verification of the information. Track it back to the source because in doing so, you’ll land on the adjustments you need to make in your classes next year.
From DSC: Interesting.
Learners can now seamlessly transition between AI-powered assistance (AI Tutor) and Live Expert support to get access to instant support, whether through AI-guided learning or real-time interactions with a human expert.
ASSIGNMENT MAKEOVERS IN THE AI AGE WITH DEREK BRUFF — from teachinginhighered.com by Bonni Stachowiak Derek Bruff shares about assignment makeovers in the AI age on episode 481 of the Teaching in Higher Ed podcast
Comment on this per Derek Bruff:
Why not ask ChatGPT to write what King or X would say about a current debate and then have the students critique the ChatGPT output? That would meet the same learning goals while also teaching AI literacy.
(Be sure to read Asim’s contribution for a useful take.)
Here’s a closer look at the concurrent AI landscape in schools — and a prediction of what the future holds.
So far, high-profile ventures in the instruction realm, such asKyron Learning, have fused teacher-produced, recorded content with LLM-powered conversational UX. The micro-learning tool Nolej references internet material when generating tasks and tests, but always holds the language model closely to the ground truth provided by teachers. Both are intriguing takes on re-imagining how to deliver core instruction and avoid hallucinations (generated content that is nonsensical).
As a result, real-time 3D jobs are among the most in demand within the tech industry. According to Unity’s vice president of Education and Social Impact, Jessica Lindl, demand is 50% higher than traditional IT jobs—adding that salaries for real-time 3D jobs are 60% greater.
“We want to provide really simple on ramps and pathways that will lead you into entry level jobs so that at any point in your career, you can decide to transfer into the industry,” Lindl says.
University World News continues its exploration of generative AI in our new special report on ‘AI and Higher Education’. In commentaries and features, academics and our journalists around the world investigate issues and developments around AI that are impacting on universities. Generative AI tools are challenging and changing higher education systems and institutions — how they are run as well as ways of teaching and learning and conducting research.
My advice for you today is this: fill your LinkedIn-feed and/or inbox with ideas, inspirational writing and commentary on AI.
This will get you up to speed quickly and is a great way to stay informed on the newest movements you need to be aware of.
My personal recommendation for you is to check out these bright people who are all very active on LinkedIn and/or have a newsletter worth paying attention to.
I have kept the list fairly short – only 15 people – in order to make it as easy as possible for you to begin exploring.
It is crucial to recognize that the intrinsic value of higher education isn’t purely in its ability to adapt to market fluctuations or technological innovations. Its core strength lies in promoting critical thinking, nurturing creativity, and instilling a sense of purpose and belonging. As AI progresses, these traits will likely become even more crucial. The question then becomes if higher education institutions as we know them today are the ony ones, or indeed the best ones, equipped to convey those core strengths to students.
Higher education clearly finds itself caught in a whirlwind of transformation, both in its essence and execution. The juxtaposition of legacy structures and the evolving technological landscape paints a complex picture.
For institutional leaders, the dual challenge lies in proactively seeking and initiating change (not merely adapting to it) without losing sight of their foundational principles. Simultaneously, they must equip students with skills and perspectives that AI cannot replicate.
“They begged, bargained with, and berated their instructor in pursuit of better grades — not “because they like points,” but rather, “because the education system has told them that these points are the currency with which they can buy a successful future.””
Habit #2: Engage students in a brain dump or two things as an entry ticket or exit ticket. Spend one minute or less having students write down everything (or just two things) they remember from class. The key: Don’t grade it! Keep retrieval practice no-stakes to emphasize it’s a learning strategy, not an assessment strategy.
Teaching from the heart in 13 steps — from timeshighereducation.com by Beiting He Engaging your students through empathy requires teachers to share their own stories and vulnerabilities and foster a safe space for learning. Here, Beiting He offers 13 ways to create a caring classroom
In summary, “I wish” is about proposing positive changes and improvements, while “I wonder” is about asking thoughtful questions to gain insight and foster meaningful conversations within the team.
If we want students to remember – to lock new information or ideas into long-term memory – getting meaningful repetitions still is key. And the science of learning still backs that up.
So … if we want students to get repetitions to make new learning permanent, how can they do it? Here are 10 ways to help students get repetitions for practice – and how classroom technology can help.
In this episode, I share ten engaging activities that combine education, technology, and plenty of fun to make the first week of class super memorable. From digital scavenger hunts to virtual field trips, hear about a few of my favorite ways to create an interactive start to your school year.
Tips for First Week of School Activity Ideas
Establish routines in a fun way.
Provide opportunities for collaboration.
Introduce tech tools that will be used all year.
From DSC: Dr. Burns has a great list of tools/tips/resources in this posting.
Four directions for assessment redesign in the age of generative AI— from timeshighereducation.com by Julia Chen The rise of generative AI has led universities to rethink how learning is quantified. Julia Chen offers four options for assessment redesign that can be applied across disciplines
Direction 1: From written description to multimodal explanation and application
Direction 2: From literature review alone to referencing lectures
Direction 3: From presentation of ideas to defence of views
Direction 4: From working alone to student-staff partnership
With the latest national test results showing a dispiriting lack of progress in catching students up academically in the wake of the pandemic, one potential explanation stands out: stubbornly high rates of student absenteeism. Vast numbers of students haven’t returned to class regularly since schools reopened.
