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.
While over 80% of respondents in the 2025 AI in Education Report have already used AI for school, we believe there are significant opportunities to design AI that can better serve each of their needs and broaden access to the latest innovation.1
That’s why today [10/15/25], we’re announcing AI-powered experiences built for teaching and learning at no additional cost, new integrations in Microsoft 365 apps and Learning Management Systems, and an academic offering for Microsoft 365 Copilot.
Introducing AI-powered teaching and learning Empowering educators with Teach
We’re introducing Teach to help streamline class prep and adapt AI to support educators’ teaching expertise with intuitive and customizable features. In one place, educators can easily access AI-powered teaching tools to create lesson plans, draft materials like quizzes and rubrics, and quickly make modifications to language, reading level, length, difficulty, alignment to relevant standards, and more.
From 70/20/10 to 90/10— from drphilippahardman.substack.com by Dr Philippa Hardman A new L&D operating system for the AI Era?
This week I want to share a hypothesis I’m increasingly convinced of: that we are entering an age of the 90/10 model of L&D.
90/10 is a model where roughly 90% of “training” is delivered by AI coaches as daily performance support, and 10% of training is dedicated to developing complex and critical skills via high-touch, human-led learning experiences.
Proponents of 90/10 argue that the model isn’t about learning less, but about learning smarter by defining all jobs to be done as one of the following:
Delegate (the dead skills): Tasks that can be offloaded to AI.
Co-Create (the 90%): Tasks which well-defined AI agents can augment and help humans to perform optimally.
Facilitate (the 10%): Tasks which require high-touch, human-led learning to develop.
So if AI at work is now both real and material, the natural question for L&D is: how do we design for it? The short answer is to stop treating learning as an event and start treating it as a system.
My daughter’s generation expects to learn with AI, not pretend it doesn’t exist, because they know employers expect AI fluency and because AI will be ever-present in their adult lives.
Gamified AI Learning Tools personalize education by adapting the difficulty and content to each child’s pace, fostering confidence and mastery.
Engaging & Fun: Gamified elements like quests, badges, and stories keep children motivated and enthusiastic.
Safe & Inclusive: Attention to equity, privacy, and cultural context ensures responsible and accessible learning.
How to test GenAI’s impact on learning — from timeshighereducation.com by Thibault Schrepel Rather than speculate on GenAI’s promise or peril, Thibault Schrepel suggests simple teaching experiments to uncover its actual effects
Generative AI in higher education is a source of both fear and hype. Some predict the end of memory, others a revolution in personalised learning. My two-year classroom experiment points to a more modest reality: Artificial intelligence (AI) changes some skills, leaves others untouched and forces us to rethink the balance.
This indicates that the way forward is to test, not speculate. My results may not match yours, and that is precisely the point. Here are simple activities any teacher can use to see what AI really does in their own classroom.
4. Turn AI into a Socratic partner Instead of being the sole interrogator, let AI play the role of tutor, client or judge. Have students use AI to question them, simulate cross-examination or push back on weak arguments. New “study modes” now built into several foundation models make this kind of tutoring easy to set up. Professors with more technical skills can go further, design their own GPTs or fine-tuned models trained on course content and let students interact directly with them. The point is the practice it creates. Students learn that questioning a machine is part of learning to think like a professional.
Assessment tasks that support human skills — from timeshighereducation.com by Amir Ghapanchi and Afrooz Purarjomandlangrudi Assignments that focus on exploration, analysis and authenticity offer a road map for university assessment that incorporates AI while retaining its rigour and human elements
Rethinking traditional formats
1. From essay to exploration When ChatGPT can generate competent academic essays in seconds, the traditional format’s dominance looks less secure as an assessment task. The future lies in moving from essays as knowledge reproduction to assessments that emphasise exploration and curation. Instead of asking students to write about a topic, challenge them to use artificial intelligence to explore multiple perspectives, compare outputs and critically evaluate what emerges.
Example: A management student asks an AI tool to generate several risk plans, then critiques the AI’s assumptions and identifies missing risks.
What your students are thinking about artificial intelligence — from timeshighereducation.com by Florencia Moore and Agostina Arbia GenAI has been quickly adopted by students, but the consequences of using it as a shortcut could be grave. A study into how students think about and use GenAI offers insights into how teaching might adapt
However, when asked how AI negatively impacts their academic development, 29 per cent noted a “weakening or deterioration of intellectual abilities due to AI overuse”. The main concern cited was the loss of “mental exercise” and soft skills such as writing, creativity and reasoning.
The boundary between the human and the artificial does not seem so easy to draw, but as the poet Antonio Machado once said: “Traveller, there is no path; the path is made by walking.”
There is nothing new about students trying to get one over on their teachers — there are probably cuneiform tablets about it — but when students use AI to generate what Shannon Vallor, philosopher of technology at the University of Edinburgh, calls a “truth-shaped word collage,” they are not only gaslighting the people trying to teach them, they are gaslighting themselves. In the words of Tulane professor Stan Oklobdzija, asking a computer to write an essay for you is the equivalent of “going to the gym and having robots lift the weights for you.”
As part of the collaboration, Deloitte will establish a Claude Center of Excellence with trained specialists who will develop implementation frameworks, share leading practices across deployments, and provide ongoing technical support to create the systems needed to move AI pilots to production at scale. The collaboration represents Anthropic’s largest enterprise AI deployment to date, available to more than 470,000 Deloitte people.
Deloitte and Anthropic are co-creating a formal certification program to train and certify 15,000 of its professionals on Claude. These practitioners will help support Claude implementations across Deloitte’s network and Deloitte’s internal AI transformation efforts.
Everboarding flips this model. Rather than ending after orientation, everboarding provides ongoing, role-specific training and support throughout the employee journey. It adapts to evolving responsibilities, reinforces standards, and helps workers grow into new roles. For high-turnover, high-pressure environments like retail, it’s a practical solution to a persistent challenge.
AI agents will be instrumental in the success of everboarding initiatives; they can provide a much more tailored training and development process for each individual employee, keeping track of which training modules may need to be completed, or where staff members need or want to develop further. This personalisation helps staff to feel not only more satisfied with their current role, but also guides them on the right path to progress in their individual careers.
Digital frontline apps are also ideal for everboarding. They offer bite-sized training that staff can complete anytime, whether during quiet moments on shift or in real time on the job, all accessible from their mobile devices.
As I and many others have pointed out in recent months, LLMs are great assistants but very ineffective teachers. Despite the rise of “educational LLMs” with specialised modes (e.g. Anthropic’s Learning Mode, OpenAI’s Study Mode, Google’s Guided Learning) AI typically eliminates the productive struggle, open exploration and natural dialogue that are fundamental to learning.
In this week’s blog post, I deep dive what the research found and share the six key findings — including reflections on how well TeachLM performs on instructional design.
AI as an assessment tool represents an existential threat to education because no matter how you try and establish guardrails or best practices around how it is employed, using the technology in place of an educator ultimately cedes human judgment to a machine-based process. It also devalues the entire enterprise of education and creates a situation where the only way universities can add value to education is by further eliminating costly human labor.
For me, the purpose of higher education is about human development, critical thinking, and the transformative experience of having your ideas taken seriously by another human being. That’s not something we should be in a rush to outsource to a machine.
A growing number of U.S. law schools are now requiring students to train in artificial intelligence, marking a shift from optional electives to essential curriculum components. What was once treated as a “nice-to-have” skill is fast becoming integral as the legal profession adapts to the realities of AI tools.
From Experimentation to Obligation
Until recently, most law schools relegated AI instruction to upper-level electives or let individual professors decide whether to incorporate generative AI into their teaching. Now, however, at least eight law schools require incoming students—especially in their first year—to undergo training in AI, either during orientation, in legal research and writing classes, or via mandatory standalone courses.
Some of the institutions pioneering the shift include Fordham University, Arizona State University, Stetson University, Suffolk University, Washington University in St. Louis, Case Western, and the University of San Francisco.
There’s a vision that’s been teased Learning & Development for decades: a vision of closing the gap between learning and doing—of moving beyond stopping work to take a course, and instead bringing support directly into the workflow. This concept of “learning in the flow of work” has been imagined, explored, discussed for decades —but never realised. Until now…?
This week, an article published Harvard Business Review provided some some compelling evidence that a long-awaited shift from “courses to coaches” might not just be possible, but also powerful.
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The two settings were a) traditional in-classroom workshops, led by an expert facilitator and b) AI-coaching, delivered in the flow of work.The results were compelling….
TLDR: The evidence suggests that “learning in the flow of work” is not only feasible as a result of gen AI—it also show potential to be more scalable, more equitable and more efficient than traditional classroom/LMS-centred models.
The 10 Most Popular AI Chatbots For Educators — from techlearning.com by Erik Ofgang Educators don’t need to use each of these chatbots, but it pays to be generally aware of the most popular AI tools
I’ve spent time testing many of these AI chatbots for potential uses and abuses in my own classes, so here’s a quick look at each of the top 10 most popular AI chatbots, and what educators should know about each. If you’re looking for more detail on a specific chatbot, click the link, as either I or other Tech & Learning writers have done deeper dives on all these tools.
Generative artificial intelligence isn’t just a new tool—it’s a catalyst forcing the higher education profession to reimagine its purpose, values, and future.
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As experts in educational technology, digital literacy, and organizational change, we argue that higher education must seize this moment to rethink not just how we use AI, but how we structure and deliver learning altogether.
Over the past decade, microschools — experimental small schools that often have mixed-age classrooms — have expanded.
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Some superintendents have touted the promise of microschools as a means for public schools to better serve their communities’ needs while still keeping children enrolled in the district. But under a federal administration that’s trying to dismantle public education and boost homeschool options, others have critiqued poor oversight and a lack of information for assessing these models.
Microschools offer a potential avenue to bring innovative, modern experiences to rural areas, argues Keith Parker, superintendent of Elizabeth City-Pasquotank Public Schools.
Imagining Teaching with AI Agents… — from michellekassorla.substack.com by Michelle Kassorla Teaching with AI is only one step toward educational change, what’s next?
More than two years ago I started teaching with AI in my classes. At first I taught against AI, then I taught with AI, and now I am moving into unknown territory: agents. I played with Manus and n8n and some other agents, but I really never got excited about them. They seemed more trouble than they were worth. It seemed they were no more than an AI taskbot overseeing some other AI bots, and that they weren’t truly collaborating. Now, I’m looking at Perplexity’s Comet browser and their AI agent and I’m starting to get ideas for what the future of education might hold.
I have written several times about the dangers of AI agents and how they fundamentally challenge our systems, especially online education. I know there is no way that we can effectively stop them–maybe slow them a little, but definitely not stop them. I am already seeing calls to block and ban agents–just like I saw (and still see) calls to block and ban AI–but the truth is they are the future of work and, therefore, the future of education.
So, yes! This is my next challenge: teaching with AI agents. I want to explore this idea, and as I started thinking about it, I got more and more excited. But let me back up a bit. What is an agent and how is it different than Generative AI or a bot?
Moodle Higher Ed
This kept getting underplayed, probably because its exact shape is still undetermined and it will arrive “soon” (where, to quote Marie, “soon is a relative term”). But it’s big in that Moodle HQ is developing a premium product for higher education.
The Moodle execs were careful to say that Moodle Higher Ed won’t be an LMS, per se.
So over the next few years we’re bringing something new to the Moodle product ecosystem. A tailored solution for higher education. Just as Workplace is a specialized product built on top of Moodle LMS for corporate and government needs, we’re bringing that same philosophy to higher ed with an AI assistance strategy focused on point solutions that deliver real institutional value.
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”.
In this episode, we explore why digital accessibility can be so important to the student experience. My guest is Amy Lomellini, director of accessibility at Anthology, the company that makes the learning management system Blackboard. Amy teaches educational technology as an adjunct at Boise State University, and she facilitates courses on digital accessibility for the Online Learning Consortium. In our conversation, we talk about the importance of digital accessibility to students, moving away from the traditional disclosure-accommodation paradigm, AI as an assistive technology, and lots more.
A day in the life: The next 25 years A learner wakes up. Their AI-powered learning coach welcomes them, drawing their attention to their progress and helping them structure their approach to the day. A notification reminds them of an upcoming interview and suggests reflections to add to their learning portfolio.
Rather than a static gradebook, their portfolio is a dynamic, living record, curated by the student, validated by mentors in both industry and education, and enriched through co-creation with maturing modes of AI. It tells a story through essays, code, music, prototypes, journal reflections, and team collaborations. These artifacts are not “submitted”, they are published, shared, and linked to verifiable learning outcomes.
And when it’s time to move, to a new institution, a new job, or a new goal, their data goes with them, immutable, portable, verifiable, and meaningful.
From DSC: And I would add to that last solid sentence that the learner/student/employee will be able to control who can access this information. Anyway, some solid reflections here from Lev.
I know a lot of readers will disagree with this, and the timeline feels aggressive (the future always arrives more slowly than pundits expect) but I think the overall premise is sound: “The concept of a tipping point in education – where AI surpasses traditional schools as the dominant learning medium – is increasingly plausible based on current trends, technological advancements, and expert analyses.”
The Rundown: In this tutorial, you will learn how to combine NotebookLM with ChatGPT to master any subject faster, turning dense PDFs into interactive study materials with summaries, quizzes, and video explanations.
Step-by-step:
Go to notebooklm.google.com, click the “+” button, and upload your PDF study material (works best with textbooks or technical documents)
Choose your output mode: Summary for a quick overview, Mind Map for visual connections, or Video Overview for a podcast-style explainer with visuals
Generate a Study Guide under Reports — get Q&A sets, short-answer questions, essay prompts, and glossaries of key terms automatically
Take your PDF to ChatGPT and prompt: “Read this chapter by chapter and highlight confusing parts” or “Quiz me on the most important concepts”
Combine both tools: Use NotebookLM for quick context and interactive guides, then ChatGPT to clarify tricky parts and go deeperPro Tip: If your source is in EPUB or audiobook, convert it to PDF before uploading. Both NotebookLM and ChatGPT handle PDFs best.
Claude can now create and edit Excel spreadsheets, documents, PowerPoint slide decks, and PDFs directly in Claude.ai and the desktop app. This transforms how you work with Claude—instead of only receiving text responses or in-app artifacts, you can describe what you need, upload relevant data, and get ready-to-use files in return.
Also see:
Microsoft to lessen reliance on OpenAI by buying AI from rival Anthropic — from techcrunch.com byRebecca Bellan
Microsoft will pay to use Anthropic’s AI in Office 365 apps, The Information reports, citing two sources. The move means that Anthropic’s tech will help power new features in Word, Excel, Outlook, and PowerPoint alongside OpenAI’s, marking the end of Microsoft’s previous reliance solely on the ChatGPT maker for its productivity suite. Microsoft’s move to diversify its AI partnerships comes amid a growing rift with OpenAI, which has pursued its own infrastructure projects as well as a potential LinkedIn competitor.
In this episode of Unfixed, we talk with Ray Schroeder—Senior Fellow at UPCEA and Professor Emeritus at the University of Illinois Springfield—about Artificial General Intelligence (AGI) and what it means for the future of higher education. While most of academia is still grappling with ChatGPT and basic AI tools, Schroeder is thinking ahead to AI agents, human displacement, and AGI’s existential implications for teaching, learning, and the university itself. We explore why AGI is so controversial, what institutions should be doing now to prepare, and how we can respond responsibly—even while we’re already overwhelmed.
Data from the State of AI and Instructional Design Report revealed that 95.3% of the instructional designers interviewed use AI in their daily work [1]. And over 85% of this AI use occurs during the design and development process.
These figures showcase the immense impact AI is already having on the instructional design world.
If you’re an L&D professional still on the fence about adding AI to your workflow or an AI convert looking for the next best tools, keep reading.
This guide breaks down 5 of the top AI tools for instructional designers in 2025, so you can streamline your development processes and build better training faster.
But before we dive into the tools of the trade, let’s address the elephant in the room:
Miro and GenAI as drivers of online student engagement — from timeshighereducation.com by Jaime Eduardo Moncada Garibay A set of practical strategies for transforming passive online student participation into visible, measurable and purposeful engagement through the use of Miro, enhanced by GenAI
To address this challenge, I shifted my focus from requesting participation to designing it. This strategic change led me to integrate Miro, a visual digital workspace, into my classes. Miro enables real-time visualisation and co-creation of ideas, whether individually or in teams.
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The transition from passive attendance to active engagement in online classes requires deliberate instructional design. Tools such as Miro, enhanced by GenAI, enable educators to create structured, visually rich learning environments in which participation is both expected and documented.
While technology provides templates, frames, timers and voting features, its real pedagogical value emerges through intentional facilitation, where the educator’s role shifts from delivering content to orchestrating collaborative, purposeful learning experiences.
In the past, it was typical for faculty to teach online courses as an “overload” of some kind, but BOnES data show that 92% of online programs feature courses taught as part of faculty member’s standard teaching responsibilities. Online teaching has become one of multiple modalities in which faculty teach regularly.
Three-quarters of chief online officers surveyed said they plan to have a great market share of online enrollments in the future, but only 23% said their current marketing is better than their competitors. The rising tide of online enrollments won’t lift all boats–some institutions will fare better than others.
Staffing at online education units is growing, with the median staff size increasing from 15 last year to 20 this year. Julie pointed out that successful online education requires investment of resources. You might need as many buildings as onsite education does, but you need people and you need technology.
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.
SINGAPORE Sept. 3, 2025 /PRNewswire/ — Today, Midoo AIproudly announces the launch of the world’s first AI language learning agent, a groundbreaking innovation set to transform language education forever.
For decades, language learning has pursued one ultimate goal: true personalization. Traditional tools offered smart recommendations, gamified challenges, and pre-written role-play scripts—but real personalization remained out of reach. Midoo AI changes that. Here is the >launch video of Midoo AI.
Imagine a learning experience that evolves with you in real time. A system that doesn’t rely on static courses or scripts but creates a dynamic, one-of-a-kind language world tailored entirely to your needs. This is the power of Midoo’s Dynamic Generation technology.
“Midoo is not just a language-learning tool,” said Yvonne, co-founder of Midoo AI. “It’s a living agent that senses your needs, adapts instantly, and shapes an experience that’s warm, personal, and alive. Learning is no longer one-size-fits-all—now, it’s yours and yours alone.”
Language learning apps have traditionally focused on exercises, quizzes, and progress tracking. Midoo AI introduces a different approach. Instead of presenting itself as a course provider, it acts as an intelligent learning agent that builds, adapts, and sustains a learner’s journey.
This review examines how Midoo AI operates, its feature set, and what makes it distinct from other AI-powered tutors.
Midoo AI in Context: Purpose and Position
Midoo AI is not structured around distributing lessons or modules. Its core purpose is to provide an agent-like partner that adapts in real time. Where many platforms ask learners to select a “level” or “topic,”
Midoo instead begins by analyzing goals, usage context, and error patterns. The result is less about consuming predesigned units and more about co-constructing a pathway.
Turning Time Saved Into Better Learning
AI can save teachers time, but what can that time be used for (besides taking a breath)? For most of us, it means redirecting energy into the parts of teaching that made us want to pursue this profession in the first place: connecting with our students and helping them grow academically.
Differentiation Every classroom has students with different readiness levels, language needs, and learning preferences. AI tools like Diffit or MagicSchool can instantly create multiple versions of a passage or assignment, differentiated by grade level, complexity, or language. This allows every student to engage with the same core concept, moving together as one cohesive class. Instead of spending an evening retyping and rephrasing, teachers can review and tweak AI drafts in minutes, ready for the next lesson.
Mass Intelligence — from oneusefulthing.org by Ethan Mollick From GPT-5 to nano banana: everyone is getting access to powerful AI
When a billion people have access to advanced AI, we’ve entered what we might call the era of Mass Intelligence. Every institution we have — schools, hospitals, courts, companies, governments — was built for a world where intelligence was scarce and expensive. Now every profession, every institution, every community has to figure out how to thrive with Mass Intelligence. How do we harness a billion people using AI while managing the chaos that comes with it? How do we rebuild trust when anyone can fabricate anything? How do we preserve what’s valuable about human expertise while democratizing access to knowledge?
By the time today’s 9th graders and college freshman enter the workforce, the most disruptive waves of AGI and robotics may already be embedded into part society.
What replaces the old system will not simply be a more digital version of the same thing. Structurally, schools may move away from rigid age-groupings, fixed schedules, and subject silos. Instead, learning could become more fluid, personalized, and interdisciplinary—organized around problems, projects, and human development rather than discrete facts or standardized assessments.
AI tutors and mentors will allow for pacing that adapts to each student, freeing teachers to focus more on guidance, relationships, and high-level facilitation. Classrooms may feel less like miniature factories and more like collaborative studios, labs, or even homes—spaces for exploring meaning and building capacity, not just delivering content.
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If students are no longer the default source of action, then we need to teach them to:
Design agents,
Collaborate with agents,
Align agentic systems with human values,
And most of all, retain moral and civic agency in a world where machines act on our behalf.
We are no longer educating students to be just doers.
We must now educate them to be judges, designers, and stewards of agency.
Meet Your New AI Tutor — from wondertools.substack.com by Jeremy Caplan Try new learning modes in ChatGPT, Claude, and Gemini
AI assistants are now more than simple answer machines. ChatGPT’s new Study Mode, Claude’s Learning Mode, and Gemini’s Guided Learningrepresent a significant shift. Instead of just providing answers, these free tools act as adaptive, 24/7 personal tutors.
That’s why, in preparation for my next bootcamp which kicks off September 8th 2025, I’ve just completed a full refresh of my list of the most powerful & popular AI tools for Instructional Designers, complete with tips on how to get the most from each tool.
The list has been created using my own experience + the experience of hundreds of Instructional Designers who I work with every week.
It contains the 50 most powerful AI tools for instructional design available right now, along with tips on how to optimise their benefits while mitigating their risks.
Addendums on 9/4/25:
AI Companies Roll Out Educational Tools — from insidehighered.com by Ray Schroeder This fall, Google, Anthropic and OpenAI are rolling out powerful new AI tools for students and educators, each taking a different path to shape the future of learning.
So here’s the new list of essential skills I think my students will need when they are employed to work with AI five years from now:
They can follow directions, analyze outcomes, and adapt to change when needed.
They can write or edit AI to capture a unique voice and appropriate tone in sync with an audience’s needs
They have a deep understanding of one or more content areas of a particular profession, business, or industry, so they can easily identify factual errors.
They have a strong commitment to exploration, a flexible mindset, and a broad understanding of AI literacy.
They are resilient and critical thinkers, ready to question results and demand better answers.
They are problem solvers.
And, of course, here is a new rubric built on those skills:
Educators use AI in and out of the classroom Educators’ uses range from developing course materials and writing grant proposals to academic advising and managing administrative tasks like admissions and financial planning.
Educators aren’t just using chatbots; they’re building their own custom tools with AI
Faculty are using Claude Artifacts to create interactive educational materials, such as chemistry simulations, automated grading rubrics, and data visualization dashboards.
Educators tend to automate the drudgery while staying in the loop for everything else
Tasks requiring significant context, creativity, or direct student interaction—like designing lessons, advising students, and writing grant proposals—are where educators are more likely to use AI as an enhancement. In contrast, routine administrative work such as financial management and record-keeping are more automation-heavy.
Some educators are automating grading; others are deeply opposed
In our Claude.ai data, faculty used AI for grading and evaluation less frequently than other uses, but when they did, 48.9% of the time they used it in an automation-heavy way (where the AI directly performs the task). That’s despite educator concerns about automating assessment tasks, as well as our surveyed faculty rating it as the area where they felt AI was least effective.
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The Online Education Marketplace Is Increasingly Competitive: …
Alternative Credentials Take Center Stage: …
AI Integration Lacks Strategic Coordination: …
Just 28% of faculty are considered fully prepared for online course design, and 45% for teaching. Alarmingly, only 28% of institutions report having fully developed academic continuity plans for future emergency pivots to online.
Cultural resistance remains strong. Many [Chief Online Learning Officers] COLOs say faculty and deans still believe in-person learning is “just better,” creating headwinds even for modest online growth. As one respondent at a four-year institution with a large online presence put it:
Supportive departments [that] see the value in online may have very different levels of responsiveness compared to academic departments [that] are begrudgingly online. There is definitely a growing belief that students “should” be on-ground and are only choosing online because it’s easy/ convenient. Never mind the very real and growing population of nontraditional learners who can only take online classes, and the very real and growing population of traditional-aged learners who prefer online classes; many faculty/deans take a paternalistic, “we know what’s best” approach.
… Ultimately, what we need is not just more ambition but better ambition. Ambition rooted in a realistic understanding of institutional capacity, a shared strategic vision, investments in policy and infrastructure, and a culture that supports online learning as a core part of the academic mission, not an auxiliary one. It’s time we talked about what it really takes to grow online learning , and where ambition needs to be matched by structure.
From DSC: Yup. Culture is at the breakfast table again…boy, those strategies taste good.
I’d like to take some of this report — like the graphic below — and share it with former faculty members and members of a couple of my past job families’ leadership. They strongly didn’t agree with us when we tried to advocate for the development of online-based learning/programs at our organizations…but we were right. We were right all along. And we were LEADING all along. No doubt about it — even if the leadership at the time said that we weren’t leading.
The cultures of those organizations hurt us at the time. But our cultivating work eventually led to the development of online programs — unfortunately, after our groups were disbanded, they had to outsource those programs to OPMs.
Arizona State University — with its dramatic growth in online-based enrollments.
