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.
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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.
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 researchlanded 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”.
GRAND RAPIDS, MI — A new course at Grand Rapids Community College aims to help students learn about artificial intelligence by using the technology to solve real-world business problems.
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In a release, the college said its grant application was supported by 20 local businesses, including Gentex, TwistThink and the Grand Rapids Public Museum. The businesses have pledged to work with students who will use business data to develop an AI project such as a chatbot that interacts with customers, or a program that automates social media posts or summarizes customer data.
“This rapidly emerging technology can transform the way businesses process data and information,” Kristi Haik, dean of GRCC’s School of Science, Technology, Engineering and Mathematics, said in a statement. “We want to help our local business partners understand and apply the technology. We also want to create real experiences for our students so they enter the workforce with demonstrated competence in AI applications.”
As Patrick Bailey said on LinkedIn about this article:
Nice to see a pedagogy that’s setting a forward movement rather than focusing on what could go wrong with AI in a curriculum.
As a 30 year observer and participant, it seems to me that previous technology platform shifts like SaaS and mobile did not fundamentally change the LMS. AI is different. We’re standing at the precipice of LMS 2.0, where the branding change from Course Management System to Learning Management System will finally live up to its name. Unlike SaaS or mobile, AI represents a technology platform shift that will transform the way participants interact with learning systems – and with it, the nature of the LMS itself.
Given the transformational potential of AI, it is useful to set the context and think about how we got here, especially on this 30th anniversary of the LMS.
Where AI is disruptive is in its ability to introduce a whole new set of capabilities that are best described as personalized learning services. AI offers a new value proposition to the LMS, roughly the set of capabilities currently being developed in the AI Tutor / agentic TA segment. These new capabilities are so valuable given their impact on learning that I predict they will become the services with greatest engagement within a school or university’s “enterprise” instructional platform.
In this way, by LMS paradigm shift, I specifically mean a shift from buyers valuing the product on its course-centric and course management capabilities, to valuing it on its learner-centric and personalized learning capabilities.
This anthology reveals how the integration of AI in education poses profound philosophical, pedagogical, ethical and political questions. As this global AI ecosystem evolves and becomes increasingly ubiquitous, UNESCO and its partners have a shared responsibility to lead the global discourse towards an equity- and justice-centred agenda. The volume highlights three areas in which UNESCO will continue to convene and lead a global commons for dialog and action particularly in areas on AI futures, policy and practice innovation, and experimentation.
As guardian of ethical, equitable human-centred AI in education.
As thought leader in reimagining curriculum and pedagogy
As a platform for engaging pluralistic and contested dialogues
AI, copyright and the classroom: what higher education needs to know — from timeshighereducation.com by Cayce Myers As artificial intelligence reshapes teaching and research, one legal principle remains at the heart of our work: copyright. Understanding its implications isn’t just about compliance – it’s about protecting academic integrity, intellectual property and the future of knowledge creation. Cayce Myers explains
Why It Matters A decade from now, we won’t say “AI changed schools.” We’ll say: this was the year schools began to change what it means to be human, augmented by AI.
This transformation isn’t about efficiency alone. It’s about dignity, creativity, and discovery, and connecting education more directly to human flourishing. The industrial age gave us schools to produce cookie-cutter workers. The digital age gave us knowledge anywhere, anytime. The AI age—beginning now—gives us back what matters most: the chance for every learner to become infinitely capable.
This fall may look like any other—bells ringing, rows of desks—but beneath the surface, education has begun its greatest transformation since the one-room schoolhouse.
Transactional and transformational leaderships’ combined impact on AI and trust Given the volatile times we live in, a leader may find themselves in a situation where they know how they will use AI, but they are not entirely clear on the goals and journey. In a teaching context, students can be given scenarios where they must lead a team, including autonomous AI agents, to achieve goals. They can then analyse the situations and decide what leadership styles to apply and how to build trust in their human team members. Educators can illustrate this decision-making process using a table (see above).
They may need to combine transactional leadership with transformational leadership, for example. Transactional leadership focuses on planning, communicating tasks clearly and an exchange of value. This works well with both humans and automated AI agents.
.Get the 2025 Student Guide to Artificial Intelligence — from studentguidetoai.org This guide is made available under a Creative Commons license by Elon University and the American Association of Colleges and Universities (AAC&U). .
Agentic AI is taking these already huge strides even further. Rather than simply asking a question and receiving an answer, an AI agent can assess your current level of understanding and tailor a reply to help you learn. They can also help you come up with a timetable and personalized lesson plan to make you feel as though you have a one-on-one instructor walking you through the process. If your goal is to learn to speak a new language, for example, an agent might map out a plan starting with basic vocabulary and pronunciation exercises, then progress to simple conversations, grammar rules and finally, real-world listening and speaking practice.
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For instance, if you’re an entrepreneur looking to sharpen your leadership skills, an AI agent might suggest a mix of foundational books, insightful TED Talks and case studies on high-performing executives. If you’re aiming to master data analysis, it might point you toward hands-on coding exercises, interactive tutorials and real-world datasets to practice with.
The beauty of AI-driven learning is that it’s adaptive. As you gain proficiency, your AI coach can shift its recommendations, challenge you with new concepts and even simulate real-world scenarios to deepen your understanding.
Ironically, the very technology feared by workers can also be leveraged to help them. Rather than requiring expensive external training programs or lengthy in-person workshops, AI agents can deliver personalized, on-demand learning paths tailored to each employee’s role, skill level, and career aspirations. Given that 68% of employees find today’s workplace training to be overly “one-size-fits-all,” an AI-driven approach will not only cut costs and save time but will be more effective.
This is one reason why I don’t see AI-embedded classrooms and AI-free classrooms as opposite poles. The bone of contention, here, is not whether we can cultivate AI-free moments in the classroom, but for how long those moments are actually sustainable.
Can we sustain those AI-free moments for an hour? A class session? Longer?
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Here’s what I think will happen. As AI becomes embedded in society at large, the sustainability of imposed AI-free learning spaces will get tested. Hard. I think it’ll become more and more difficult (though maybe not impossible) to impose AI-free learning spaces on students.
However, consensual and hybrid AI-free learning spaces will continue to have a lot of value. I can imagine classes where students opt into an AI-free space. Or they’ll even create and maintain those spaces.
Duolingo’s AI Revolution — from drphilippahardman.substack.com by Dr. Philippa Hardman What 148 AI-Generated Courses Tell Us About the Future of Instructional Design & Human Learning
Last week, Duolingo announced an unprecedented expansion: 148 new language courses created using generative AI, effectively doubling their content library in just one year. This represents a seismic shift in how learning content is created — a process that previously took the company 12 years for their first 100 courses.
As CEO Luis von Ahn stated in the announcement, “This is a great example of how generative AI can directly benefit our learners… allowing us to scale at unprecedented speed and quality.”
In this week’s blog, I’ll dissect exactly how Duolingo has reimagined instructional design through AI, what this means for the learner experience, and most importantly, what it tells us about the future of our profession.
Medical education is experiencing a quiet revolution—one that’s not taking place in lecture theatres or textbooks, but with headsets and holograms. At the heart of this revolution are Mixed Reality (MR) AI Agents, a new generation of devices that combine the immersive depth of mixed reality with the flexibility of artificial intelligence. These technologies are not mere flashy gadgets; they’re revolutionising the way medical students interact with complicated content, rehearse clinical skills, and prepare for real-world situations. By combining digital simulations with the physical world, MR AI Agents are redefining what it means to learn medicine in the 21st century.
4 Reasons To Use Claude AI to Teach — from techlearning.com by Erik Ofgang Features that make Claude AI appealing to educators include a focus on privacy and conversational style.
After experimenting using Claude AI on various teaching exercises, from generating quizzes to tutoring and offering writing suggestions, I found that it’s not perfect, but I think it behaves favorably compared to other AI tools in general, with an easy-to-use interface and some unique features that make it particularly suited for use in education.
DC: THIS could unfortunately be the ROI companies will get from large investments in #AI — reduced headcount/employees/contract workers. https://t.co/zEWlqCSWzI
Duolingo will “gradually stop using contractors to do work that AI can handle,” according to an all-hands email sent by cofounder and CEO Luis von Ahn announcing that the company will be “AI-first.” The email was posted on Duolingo’s LinkedIn account.
According to von Ahn, being “AI-first” means the company will “need to rethink much of how we work” and that “making minor tweaks to systems designed for humans won’t get us there.” As part of the shift, the company will roll out “a few constructive constraints,” including the changes to how it works with contractors, looking for AI use in hiring and in performance reviews, and that “headcount will only be given if a team cannot automate more of their work.”
Something strange, and potentially alarming, is happening to the job market for young, educated workers.
According to the New York Federal Reserve, labor conditions for recent college graduates have “deteriorated noticeably” in the past few months, and the unemployment rate now stands at an unusually high 5.8 percent. Even newly minted M.B.A.s from elite programs are struggling to find work. Meanwhile, law-school applications are surging—an ominous echo of when young people used graduate school to bunker down during the great financial crisis.
What’s going on? I see three plausible explanations, and each might be a little bit true.
The new workplace trend is not employee friendly. Artificial intelligence and automation technologies are advancing at blazing speed. A growing number of companies are using AI to streamline operations, cut costs, and boost productivity. Consequently, human workers are facing facing layoffs, replaced by AI. Like it or not, companies need to make tough decisions, including layoffs to remain competitive.
Corporations including Klarna, UPS, Duolingo, Intuit and Cisco are replacing laid-off workers with AI and automation. While these technologies enhance productivity, they raise serious concerns about future job security. For many workers, there is a big concern over whether or not their jobs will be impacted.
Key takeaway: Career navigation has remained largely unchanged for decades, relying on personal networks and static job boards. The advent of AI is changing this, offering personalised career pathways, better job matching, democratised job application support, democratised access to career advice/coaching, and tailored skill development to help you get to where you need to be.Hundreds of millions of people start new jobs every year, this transformation opens up a multi-billion dollar opportunity for innovation in the global career navigation market.
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A.4 How will AI disrupt this segment? Personalised recommendations: AI can consume a vast amount of information (skills, education, career history, even youtube history, and x/twitter feeds), standardise this data at scale, and then use data models to match candidate characteristics to relevant careers and jobs. In theory, solutions could then go layers deeper, helping you position yourself for those future roles. Currently based in Amsterdam, and working in Strategy at Uber and want to work in a Product role in the future? Here are X,Y,Z specific things YOU can do in your role today to align yourself perfectly. E.g. find opportunities to manage cross functional projects in your current remit, reach out to Joe Bloggs also at Uber in Amsterdam who did Strategy and moved to Product, etc.
No matter the school, no matter the location, when I deliver an AI workshop to a group of teachers, there are always at least a few colleagues thinking (and sometimes voicing), “Do I really need to use AI?”
Nearly three years after ChatGPT 3.5 landed in our lives and disrupted workflows in ways we’re still unpacking, most schools are swiftly catching up. Training sessions, like the ones I lead, are springing up everywhere, with principals and administrators trying to answer the same questions: Which tools should we use? How do we use them responsibly? How do we design learning in this new landscape?
But here’s what surprises me most: despite all the advances in AI technology, the questions and concerns from teachers remain strikingly consistent.
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In this article, I want to pull back the curtain on those conversations. These concerns aren’t signs of reluctance – they reflect sincere feelings. And they deserve thoughtful, honest answers.
This week, in advance of major announcements from us and other vendors, I give you a good overview of the AI Agent market, and discuss the new role of AI governance platforms, AI agent development tools, AI agent vendors, and how AI agents will actually manifest and redefine what we call an “application.”
I discuss ServiceNow, Microsoft, SAP, Workday, Paradox, Maki People, and other vendors. My goal today is to “demystify” this space and explain the market, the trends, and why and how your IT department is going to be building a lot of the agents you need. And prepare for our announcements next week!
DeepSeek has quietly launched Prover V2, an open-source model built to solve math problems using Lean 4 assistant, which ensures every step of a proof is rigorously verified.
What’s impressive about it?
Massive scale: Based on DeepSeek-V3 with 671B parameters using a mixture-of-experts (MoE) architecture, which activates only parts of the model at a time to reduce compute costs.
Theorem solving: Uses long context windows (32K+ tokens) to generate detailed, step-by-step formal proofs for a wide range of math problems — from basic algebra to advanced calculus theorems.
Research grade: Assists mathematicians in testing new theorems automatically and helps students understand formal logic by generating both Lean 4 code and readable explanations.
New benchmark: Introduces ProverBench, a new 325-question benchmark set featuring problems from recent AIME exams and curated academic sources to evaluate mathematical reasoning.
The need for deep student engagement became clear at Dartmouth Geisel School of Medicine when a potential academic-integrity issue revealed gaps in its initial approach to artificial intelligence use in the classroom, leading to significant revisions to ensure equitable learning and assessment.
From George Siemens “SAIL: Transmutation, Assessment, Robots e-newsletter on 5/2/25
All indications are that AI, even if it stops advancing, has the capacity to dramatically change knowledge work. Knowing things matters less than being able to navigate and make sense of complex environments. Put another way, sensemaking, meaningmaking, and wayfinding (with their yet to be defined subelements) will be the foundation for being knowledgeable going forward.
That will require being able to personalize learning to each individual learner so that who they are (not what our content is) forms the pedagogical entry point to learning.(DSC: And I would add WHAT THEY WANT to ACHIEVE.)LLMs are particularly good and transmutation. Want to explain AI to a farmer? A sentence or two in a system prompt achieves that. Know that a learner has ADHD? A few small prompt changes and it’s reflected in the way the LLM engages with learning. Talk like a pirate. Speak in the language of Shakespeare. Language changes. All a matter of a small meta comment send to the LLM. I’m convinced that this capability to change, transmute, information will become a central part of how LLMS and AI are adopted in education.
… Speaking of Duolingo– it took them 12 years to develop 100 courses. In the last year, they developed an additional 148. AI is an accelerant with an impact in education that is hard to overstate. “Instead of taking years to build a single course with humans the company now builds a base course and uses AI to quickly customize it for dozens of different languages.”
FutureHouse is launching our platform, bringing the first publicly available superintelligent scientific agents to scientists everywhere via a web interface and API. Try it out for free at https://platform.futurehouse.org.
Over the course of the next 10 years, AI-powered institutions will rise in the rankings. US News & World Report will factor a college’s AI capabilities into its calculations. Accrediting agencies will assess the degree of AI integration into pedagogy, research, and student life. Corporations will want to partner with universities that have demonstrated AI prowess. In short, we will see the emergence of the AI haves and have-nots.
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What’s happening in higher education today has a name: creative destruction. The economist Joseph Schumpeter coined the term in 1942 to describe how innovation can transform industries. That typically happens when an industry has both a dysfunctional cost structure and a declining value proposition. Both are true of higher education.
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Out of the gate, professors will work with technologists to get AI up to speed on specific disciplines and pedagogy. For example, AI could be “fed” course material on Greek history or finance and then, guided by human professors as they sort through the material, help AI understand the structure of the discipline, and then develop lectures, videos, supporting documentation, and assessments.
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In the near future, if a student misses class, they will be able watch a recording that an AI bot captured. Or the AI bot will find a similar lecture from another professor at another accredited university. If you need tutoring, an AI bot will be ready to help any time, day or night. Similarly, if you are going on a trip and wish to take an exam on the plane, a student will be able to log on and complete the AI-designed and administered exam. Students will no longer be bound by a rigid class schedule. Instead, they will set the schedule that works for them.
Early and mid-career professors who hope to survive will need to adapt and learn how to work with AI. They will need to immerse themselves in research on AI and pedagogy and understand its effect on the classroom.
From DSC: I had a very difficult time deciding which excerpts to include. There were so many more excerpts for us to think about with this solid article. While I don’t agree with several things in it, EVERY professor, president, dean, and administrator working within higher education today needs to read this article and seriously consider what Scott Latham is saying.
Change is already here, but according to Scott, we haven’t seen anything yet. I agree with him and, as a futurist, one has to consider the potential scenarios that Scott lays out for AI’s creative destruction of what higher education may look like. Scott asserts that some significant and upcoming impacts will be experienced by faculty members, doctoral students, and graduate/teaching assistants (and Teaching & Learning Centers and IT Departments, I would add). But he doesn’t stop there. He brings in presidents, deans, and other members of the leadership teams out there.
There are a few places where Scott and I differ.
The foremost one is the importance of the human element — i.e., the human faculty member and students’ learning preferences. I think many (most?) students and lifelong learners will want to learn from a human being. IBM abandoned their 5-year, $100M ed push last year and one of the key conclusions was that people want to learn from — and with — other people:
To be sure, AI can do sophisticated things such as generating quizzes from a class reading and editing student writing. But the idea that a machine or a chatbot can actually teach as a human can, he said, represents “a profound misunderstanding of what AI is actually capable of.”
Nitta, who still holds deep respect for the Watson lab, admits, “We missed something important. At the heart of education, at the heart of any learning, is engagement. And that’s kind of the Holy Grail.”
— Satya Nitta, a longtime computer researcher at
IBM’s Watson Research Center in Yorktown Heights, NY .
By the way, it isn’t easy for me to write this. As I wanted AI and other related technologies to be able to do just what IBM was hoping that it would be able to do.
Also, I would use the term learning preferences where Scott uses the term learning styles.
Scott also mentions:
“In addition, faculty members will need to become technologists as much as scholars. They will need to train AI in how to help them build lectures, assessments, and fine-tune their classroom materials. Further training will be needed when AI first delivers a course.”
It has been my experience from working with faculty members for over 20 years that not all faculty members want to become technologists. They may not have the time, interest, and/or aptitude to become one (and vice versa for technologists who likely won’t become faculty members).
That all said, Scott relays many things that I have reflected upon and relayed for years now via this Learning Ecosystems blog and also via The Learning from the Living [AI-Based Class] Room vision — the use of AI to offer personalized and job-relevant learning, the rising costs of higher education, the development of new learning-related offerings and credentials at far less expensive prices, the need to provide new business models and emerging technologies that are devoted more to lifelong learning, plus several other things.
So this article is definitely worth your time to read, especially if you are working in higher education or are considering a career therein!
Google Public Sector and the University of Michigan’s Ross School of Business have launched an advanced Virtual Teaching Assistant pilot program aimed at improving personalized learning and enlightening educators on artificial intelligence in the classroom.
The AI technology, aided by Google’s Gemini chatbot, provides students with all-hours access to support and self-directed learning. The Virtual TA represents the next generation of educational chatbots, serving as a sophisticated AI learning assistant that instructors can use to modify their specific lessons and teaching styles.
The Virtual TA facilitates self-paced learning for students, provides on-demand explanations of complex course concepts, guides them through problem-solving, and acts as a practice partner. It’s designed to foster critical thinking by never giving away answers, ensuring students actively work toward solutions.
The Tutoring Revolution— from educationnext.org by Holly Korbey More families are seeking one-on-one help for their kids. What does that tell us about 21st-century education?
Recent research suggests that the number of students seeking help with academics is growing, and that over the last couple of decades, more families have been turning to tutoring for that help.
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What the Future Holds Digital tech has made private tutoring more accessible, more efficient, and more affordable. Students whose families can’t afford to pay $75 an hour at an in-person center can now log on from home to access a variety of online tutors, including Outschool, Wyzant, and Anchorbridge, and often find someone who can cater to their specific skills and needs—someone who can offer help in French to a student with ADHD, for example. Online tutoring is less expensive than in-person programs. Khan Academy’s Khanmigo chatbot can be a student’s virtual AI tutor, no Zoom meeting required, for $4 a month, and nonprofits like Learn to Be work with homeless shelters and community centers to give virtual reading and math tutoring free to kids who can’t afford it and often might need it the most.
Duolingo’s new Video Call feature represents a leap forward in language practice for learners. This AI-powered tool allows Duolingo Max subscribers to engage in spontaneous, realistic conversations with Lily, one of Duolingo’s most popular characters. The technology behind Video Call is designed to simulate natural dialogue and provides a personalized, interactive practice environment. Even beginner learners can converse in a low-pressure environment because Video Call is designed to adapt to their skill level. By offering learners the opportunity to converse in real-time,Video Call builds the confidence needed to communicate effectively in real-world situations. Video Call is available for Duolingo Max subscribers learning English, Spanish, and French.
Ello, the AI reading companion that aims to support kids struggling to read, launched a new product on Monday that allows kids to participate in the story-creation process.
Called “Storytime,” the new AI-powered feature helps kids generate personalized stories by picking from a selection of settings, characters, and plots. For instance, a story about a hamster named Greg who performed in a talent show in outer space.
What An Agent Is
Agents are computer programs that can autonomously perform tasks, make decisions and interact with humans or other computers. There are many different types of agents, and they are designed to achieve specific goals spanning our lives and nearly every industry, making them an integral and unstoppable part of our future.
Learning: AI agents will transform education by providing personalized learning experiences such as one-to-one tutoring. ChatGPT and other large language models (LLMs) are providing access to all digital knowledge now. An “agent” would act as a more personalized version of an LLM.
The hacking and control of an AI agent could lead to disastrous consequences, affecting privacy, security, the economy and societal stability. Proactive and comprehensive security strategies are essential to mitigate these risks in the future.
LearnLM is our new family of models fine-tuned for learning, and grounded in educational research to make teaching and learning experiences more active, personal and engaging.
We often talk about what Generative AI will do for coders, healthcare, science or even finance, but what about the benefits for the next generation? Permit me if you will, here I’m thinking about teachers and students.
It’s no secret that some of the most active users of ChatGPT in its heyday, were students. But how are other major tech firms thinking about this?
I actually think one of the best products with the highest ceiling from Google I/O 2024 is LearnLM. It has to be way more than a chatbot, it has to feel like a multimodal tutor. I can imagine frontier model agents (H) doing this fairly well.
What if everyone, everywhere could have their own personal AI tutor, on any topic?
ChatGPT4o Is the TikTok of AI Models — from nickpotkalitsky.substack.com by Nick Potkalitsky In Search of Better Tools for AI Access in K-12 Classrooms
Nick makes the case that we should pause on the use of OpenAI in the classrooms:
In light of these observations, it’s clear that we must pause and rethink the use of OpenAI products in our classrooms, except for rare cases where accessibility needs demand it. The rapid consumerization of AI, epitomized by GPT4o’s transformation into an AI salesperson, calls for caution.
Hello GPT-4o — from openai.com We’re announcing GPT-4o, our new flagship model that can reason across audio, vision, and text in real time.
GPT-4o (“o” for “omni”) is a step towards much more natural human-computer interaction—it accepts as input any combination of text, audio, image, and video and generates any combination of text, audio, and image outputs. It can respond to audio inputs in as little as 232 milliseconds, with an average of 320 milliseconds, which is similar to human response time in a conversation. It matches GPT-4 Turbo performance on text in English and code, with significant improvement on text in non-English languages, while also being much faster and 50% cheaper in the API. GPT-4o is especially better at vision and audio understanding compared to existing models.
Providing inflection, emotions, and a human-like voice
Understanding what the camera is looking at and integrating it into the AI’s responses
Providing customer service
With GPT-4o, we trained a single new model end-to-end across text, vision, and audio, meaning that all inputs and outputs are processed by the same neural network. Because GPT-4o is our first model combining all of these modalities, we are still just scratching the surface of exploring what the model can do and its limitations.
This demo is insane.
A student shares their iPad screen with the new ChatGPT + GPT-4o, and the AI speaks with them and helps them learn in *realtime*.
Imagine giving this to every student in the world.
Since AI in education has been moving at the speed of light, we built this AI Tools in Education database to keep track of the most recent AI tools in education and the changes that are happening every day. This database is intended to be a community resource for educators, researchers, students, and other edtech specialists looking to stay up to date. This is a living document, so be sure to come back for regular updates.
The day started out with a short talk about AI (slides). Some of it is my usual schtick where I do a bit of Q&A with folks around myths and misunderstandings of generative AI in order to establish some common ground. These are often useful both in setting the tone and giving folks a sense of how I come to explore generative AI: with a mixture of humor, concern, curiosity, and of course, cat pics.
From there, we launched into a series of mini-workshops where folks had time to first play around with some previously created prompts around teaching and learning before moving onto prompts for administrative work. The prompts and other support materials are in this Workshop Resource Document. The goal was to just get them into using one or more AI tools with some useful prompts so they can learn more about its capabilities.
The Edtech Insiders Rundown of ASU+GSV 2024 — from edtechinsiders.substack.com by by Sarah Morin, Alex Sarlin, and Ben Kornell And more on Edtech Insiders+, upcoming events, Gauth, AI Reading Tutors, The Artificial Intelligence Interdisciplinary Institute, and TeachAI Policy Resources
Alex Sarlin
4. Everyone is Edtech Now This year, in addition to investors, entrepreneurs, educators, school leaders, university admins, non-profits, publishers, and operators from countless edtech startups and incumbents, there were some serious big tech companies in attendance like Meta, Google, OpenAI, Microsoft, Amazon, Tiktok, and Canva. Additionally, a horde of management consultancies, workforce organizations, mental health orgs, and filmmakers were in attendance.
Edtech continues to expand as an industry category and everyone is getting involved.
It was such a delight to chat with Ana. She’s brilliant and passionate, a talented educator, and an advocate for better ways of learning for children and adults. We cover ways to transform schools so that students get real-world skills, learn resilience and how to embrace challenges, and are prepared for an unpredictable future. And we go hard on why we must keep learning no matter our age, become generalists, and leverage technology in order to adapt to the fast-changing world.
The Texas Tribune reports an “automated scoring engine” that utilizes natural language processing — the technology that enables chatbots like OpenAI’s ChatGPT to understand and communicate with users — is being rolled out by the Texas Education Agency (TEA) to grade open-ended questions on the State of Texas Assessments of Academic Readiness (STAAR) exams. The agency is expecting the system to save $15–20 million per year by reducing the need for temporary human scorers, with plans to hire under 2,000 graders this year compared to the 6,000 required in 2023.
Debating About AI: An Easy Path to AI Awareness and Basic Literacy — from stefanbauschard.substack.com by Stefan Bauschard If you are an organization committed to AI literacy, consider sponsoring some debate topics and/or debates next year and expose thousands of students to AI literacy.
Resolved: Teachers should integrate generative AI in their teaching and learning.
The topic is simple but raises an issue that students can connect with.
While helping my students prepare and judging debates, I saw students demonstrate an understanding of many key issues and controversies.
These included—
*AI writing assessment/grading
*Bias
*Bullying
*Cognitive load
*Costs of AI systems
*Declining test scores
*Deep fakes
*Differentiation
*Energy consumption
*Hallucinations
*Human-to-human connection
*Inequality and inequity in access
*Neurodiversity
*Personalized learning
*Privacy
*Regulation (lack thereof)
*The future of work and unemployment
*Saving teachers time
*Soft skills
*Standardized testing
*Student engagement
*Teacher awareness and AI training; training resource trade-offs
*Teacher crowd-out
*Transparency and explainability
*Writing detectors (students had an exaggerated sense of the workability of these tools).
What if, for example, the corporate learning system knew who you were and you could simply ask it a question and it would generate an answer, a series of resources, and a dynamic set of learning objects for you to consume? In some cases you’ll take the answer and run. In other cases you’ll pour through the content. And in other cases you’ll browse through the course and take the time to learn what you need.
And suppose all this happened in a totally personalized way. So you didn’t see a “standard course” but a special course based on your level of existing knowledge?
This is what AI is going to bring us. And yes, it’s already happening today.
From DSC: This would be huge for all of our learning ecosystems, as the learning agents could remember where a particular student or employee is at in terms of their learning curve for a particular topic.
Healthcare High Schools — from the-job.beehiiv.com by Paul Fain Bloomberg and hospitals back dual-enrollment path from K-12 to high-demand jobs.
More career exploration in high school is needed to help Americans make better-informed choices about their education and job options, experts agree. And serious, employer-backed efforts to tighten connections between school and work are likely to emerge first in healthcare, given the industry’s severe staffing woes.
A new $250M investment by Bloomberg Philanthropies could be an important step in this direction. The money will seed the creation of healthcare-focused high schools in 10 U.S. locations, with a plan to enroll 6K students who will graduate directly from the early-college high schools into high-demand healthcare jobs that pay family-sustaining wages.
Last year, the landscape of K-12 education transformed as a record-breaking 20 states expanded school choice options. However, that is not the only school choice story to come out of 2023. As the nation steps into 2024, a fresh emphasis on innovation has emerged, along with new options for families. This is particularly true within the realm of microschooling.
Microschooling is an education model that is small by design — typically with 15 or fewer students of varying ages per class. It fosters a personalized and community-centric approach to learning that is especially effective in addressing the unique educational needs of diverse student populations. Programs like Education Savings Accounts are helping to fuel these microschools.
Large classes create more distractions for students who struggle to focus, and they inevitably get less attention and support as there are more students for teachers to work with. High numbers of students make it more difficult to plan for individual needs and force teachers to teach to an imaginary middle. A rigid schedule makes it easy to schedule adults and services, but it is a challenge for kids who need time to get engaged and prefer to keep working at a challenge once they are locked in.
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Now that I know what can engage and motivate these students, I can imagine creating more opportunities that allow them to harness their talents and grow their skills and knowledge. But we’re already a third of the way through the school year, and my curriculum requires me to teach certain topics for certain lengths of time, which doesn’t leave room for many of the types of experiences these kids need. Soon, June will come and I’ll pass them along to the next teacher, who won’t know what I know and will need another four months to learn it, wasting valuable time in these students’ educations.
From DSC: We need teachers and professors to be able to contribute to learners’ records. Each student can review and decide whether they want to allow access to other teachers– or even to employers. Educators could insert what they’ve found to work with a particular student, what passions/interests that student has, or what to avoid (if possible). For example, has this student undergone some trauma, and therefore trauma-informed teaching should be employed.
IEPs could be a part of learners’ records/profiles. The teams working on implementing these IEP’s could share important, searchable information.
Washington state issued new guidelines for K-12 public schools last week based on the principle of “embracing a human-centered approach to AI,” which also embraces the use of AI in the education process. The state’s Superintendent of Public Instruction, Chris Reykdal, commented in a letter accompanying the new guidelines:
