The California State University system has partnered with OpenAI to launch the largest deployment of AI in higher education to date.
The CSU system, which serves nearly 500,000 students across 23 campuses, has announced plans to integrate ChatGPT Edu, an education-focused version of OpenAI’s chatbot, into its curriculum and operations. The rollout, which includes tens of thousands of faculty and staff, represents the most significant AI deployment within a single educational institution globally.
We’re still in the early stages of AI adoption in education, and it is critical that the entire ecosystem—education systems, technologists, educators, and governments—work together to ensure that all students globally have access to AI and develop the skills to use it responsibly
Leah Belsky, VP and general manager of education at OpenAI.
As you read through these use cases, you’ll notice that each one addresses multiple tasks from our list above.
1. Researching a topic for a lesson
2. Creating Tasks For Practice
3. Creating Sample Answers
4. Generating Ideas
5. Designing Lesson Plans
6. Creating Tests
7. Using AI in Virtual Classrooms
8. Creating Images
9. Creating worksheets
10. Correcting and Feedback
What if students had the power to design their own learning journeys?
Across the U.S., states are moving beyond one-size-fits-all education and embracing unbundled learning, creating personalized pathways that equip students with the skills they need for the future. Getting Smart’s Unbundled Learning Podcast Series explores how Colorado, Arizona, and New Hampshire are leading the way—expanding real-world learning, shifting to competency-based models, empowering learner agency, and aligning education with workforce needs.
For policymakers, the newly released Policymaker’s Guide offers a roadmap for fostering unbundled systems. It highlights key priorities such as competency-driven accountability, flexible credentialing, and funding models that prioritize equity, helping state leaders create policies that expand opportunities for all learners.
Explore how unbundled learning is shaping the future of education and how states can build more personalized, future-ready systems.
New Pathways > Unbundled Learning — from gettingsmart.com We used to think that learning had to happen in a school building. Spoiler alert…that was never true.
How might we create an ecosystem where learning doesn’t just happen at school? With Unbundled Learning, learners don’t need permission to have equitable experiences. Unbundled Learning removes all the barriers and allows learning to happen at school, after school, with industry partners and anywhere a learner can imagine. Unbundled Learning is the foundation for which new learning models are built, learners are supported and systems are scaled.
If we used to think that school was the only answer, now we know we have options. .
When technologist Luis von Ahn was building the popular language-learning platform Duolingo, he faced a big problem: Could an app designed to teach you something ever compete with addictive platforms like Instagram and TikTok? He explains how Duolingo harnesses the psychological techniques of social media and mobile games to get you excited to learn — all while spreading access to education across the world. .
The most revolutionary aspect of DeepSeek for education isn’t just its cost—it’s the combination of open-source accessibility and local deployment capabilities. As Azeem Azhar notes, “R-1 is open-source. Anyone can download and run it on their own hardware. I have R1-8b (the second smallest model) running on my Mac Mini at home.”
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Real-time Learning Enhancement
AI tutoring networks that collaborate to optimize individual learning paths
Immediate, multi-perspective feedback on student work
Continuous assessment and curriculum adaptation
The question isn’t whether this technology will transform education—it’s how quickly institutions can adapt to a world where advanced AI capabilities are finally within reach of every classroom.
I know through your feedback on my social media and blog posts that several of you have legitimate concerns about the impact of AI in education, especially those related to data privacy, academic dishonesty, AI dependence, loss of creativity and critical thinking, plagiarism, to mention a few. While these concerns are valid and deserve careful consideration, it’s also important to explore the potential benefits AI can bring when used thoughtfully.
Tools such as ChatGPT and Claude are like smart research assistants that are available 24/7 to support you with all kinds of tasks from drafting detailed lesson plans, creating differentiated materials, generating classroom activities, to summarizing and simplifying complex topics. Likewise, students can use them to enhance their learning by, for instance, brainstorming ideas for research projects, generating constructive feedback on assignments, practicing problem-solving in a guided way, and much more.
The point here is that AI is here to stay and expand, and we better learn how to use it thoughtfully and responsibly rather than avoid it out of fear or skepticism.
As part of our updates to the Edtech Insiders Generative AI Map, we’re excited to release a new mini market map and article deep dive on Generative AI tools that are specifically designed for Instructional Materials use cases.
In our database, the Instructional Materials use case category encompasses tools that:
Assist educators by streamlining lesson planning, curriculum development, and content customization
Enable educators or students to transform materials into alternative formats, such as videos, podcasts, or other interactive media, in addition to leveraging gaming principles or immersive VR to enhance engagement
Empower educators or students to transform text, video, slides or other source material into study aids like study guides, flashcards, practice tests, or graphic organizers
Engage students through interactive lessons featuring historical figures, authors, or fictional characters
Customize curriculum to individual needs or pedagogical approaches
Empower educators or students to quickly create online learning assets and courses
I am always happy when my work generates a public discussion. That happened after a January column I wrote about a prominent scholar’s critique of the evidence for including children with disabilities in general education classrooms. Advocates, parents and teachers argued for inclusion, against inclusion and for some hybrid of the two. The director of education at the Learning Disabilities Association of America weighed in, as did the commissioner of special education research at the U.S. Department of Education. More than 160 people commented on one Reddit discussion about the story. Here’s a sampling of views I received or saw on social media.
That’s why, today, the question I’m asking is: How best can we proactively guide AI’s use in higher education and shape its impact on our students, faculty and institution? The answer to that broad, strategic question lies in pursuing four objectives that, I believe, are relevant for many colleges and universities.
Learning to use business software is different from learning to think. But if the software is sufficiently complex, how different is it really? What if AI’s primary impact on education isn’t in the classroom, but rather shifting the locus of learning to outside the classroom?
Instead of sitting in a classroom listening to a teacher, high school and college students could be assigned real work and learn from that work. Students could be matched with employers or specific projects provided by or derived from employers, then do the work on the same software used in the enterprise. As AI-powered digital adoption platforms (DAPs) become increasingly powerful, they have the potential to transform real or simulated work into educational best practice for students only a few years away from seeking full-time employment.
If DAPs take us in this direction, four implications come to mind….
In this week’s blog post, I share a summary of five recent studies on the impact of Gen AI on learning to bring you right up to date.
… Implications for Educators and Developers
For Educators:
Combine ChatGPT with Structured Activities: …
Use ChatGPT as a Supplement, Not a Replacement:…
Promote Self-Reflection and Evaluation:
For Developers:
Reimagine AI for Reflection-First Design: …
Develop Tools that Foster Critical Thinking: …
Integrate Adaptive Support: …
Assessing the GenAI process, not the output — from timeshighereducation.com by Paul McDermott, Leoni Palmer, and Rosemary Norton A framework for building AI literacy in a literature-review-type assessment
In this resource, we outline our advice for implementing an approach that opens AI use up to our students through a strategy of assessing the process rather than outputs.
To start with, we recommend identifying learning outcomes for your students that can be achieved in collaboration with AI.
What’s New: The Updated Edtech Insiders Generative AI Map — from edtechinsiders.substack.com by Sarah Morin, Alex Sarlin, and Ben Kornell A major expansion on our previously released market map, use case database, and AI tool company directory.
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Tutorial: 4 Ways to Use LearnLM as a Professor— from automatedteach.com by Graham Clay Create better assessments, improve instructions and feedback, and tutor your students with this fine-tuned version of Gemini.
I cover how to use LearnLM
to create sophisticated assessments that promote learning
to develop clearer and more effective assignment instructions
to provide more constructive feedback on student work, and
to support student learning through guided tutoring
Key question: What business results do you expect from your microlearning strategy?
Why it’s valuable: Clear, measurable outcomes create a foundation for alignment and accountability.
Purpose
Key question: Why does this microlearning initiative exist?
Why it’s valuable: L&D needs to know if they are solving a specific problem, supporting a broader strategy, or providing foundational knowledge.
Potential
Key question: What opportunities exist if the purpose is actualized?
Why it’s valuable: This helps to put into focus the measurable outcomes or if it is a true need for L&D to address.
Evaluation
Key question: How will you measure success?
Why it’s valuable: Defining metrics that track learner progress and link to business impact ensures that the design of these pieces is part of the overall solution and implementation plan.
…and more
By focusing on short-term wins, auditing for gaps, and planning strategically, L&D leaders can create initiatives that deliver meaningful, sustained results.
At the end of 2024 and start of 2025, we’ve witnessed some fascinating developments in the world of AI and education, from from India’s emergence as a leader in AI education and Nvidia’s plans to build an AI school in Indonesia to Stanford’s Tutor CoPilot improving outcomes for underserved students.
Other highlights include Carnegie Learning partnering with AI for Education to train K-12 teachers, early adopters of AI sharing lessons about implementation challenges, and AI super users reshaping workplace practices through enhanced productivity and creativity.
India emerges as Global Leader in AI Education: Bosch Tech Compass 2025 — from medianews4u.com 57% Indians receive employer-provided AI training, surpassing Germany, and other European nations
Bengaluru: India is emerging as a global leader in artificial intelligence (AI) education, with over 50% of its population actively self-educating in AI-related skills, according to Bosch’s fourth annual Tech Compass Survey. The report highlights India’s readiness to embrace AI in work, education, and daily life, positioning the nation as a frontrunner in the AI revolution.
AI for Education reviewed the ElevenLabs AI Voice Tool through an educator lens, digging into the new autonomous voice agent functionality that facilitates interactive user engagement. We showcase the creation of a customized vocabulary bot, which defines words at a 9th-grade level and includes options for uploading supplementary material. The demo includes real-time testing of the bot’s capabilities in defining terms and quizzing users.
The discussion also explored the AI tool’s potential for aiding language learners and neurodivergent individuals, and Mandy presented a phone conversation coach bot to help her 13-year-old son, highlighting the tool’s ability to provide patient, repetitive practice opportunities.
While acknowledging the technology’s potential, particularly in accessibility and language learning, we also want to emphasize the importance of supervised use and privacy considerations. Right now the tool is currently free, this likely won’t always remain the case, so we encourage everyone to explore and test it out now as it continues to develop.
Why Combine Them? Faster Onboarding: Start broad with Deep Research, then refine and clarify concepts through Learn About. Finally, use NotebookLM to synthesize everything into a cohesive understanding.
Deeper Clarity: Unsure about a concept uncovered by Deep Research? Head to Learn About for a primer. Want to revisit key points later? Store them in NotebookLM and generate quick summaries on demand.
Adaptive Exploration: Create a feedback loop. Let new terms or angles from Learn About guide more targeted Deep Research queries. Then, compile all findings in NotebookLM for future reference. .
There are several challenges to making policy that make institutions hesitant to or delay their ability to produce it. Policy (as opposed to guidance) is much more likely to include a mixture of IT, HR, and legal services. This means each of those entities has to wrap their heads around GenAI—not just for their areas but for the other relevant areas such as teaching & learning, research, and student support. This process can definitely extend the time it takes to figure out the right policy.
That’s naturally true with every policy. It does not often come fast enough and is often more reactive than proactive.
Still, in my conversations and observations, the delay derives from three additional intersecting elements that feel like they all need to be in lockstep in order to actually take advantage of whatever possibilities GenAI has to offer.
Which Tool(s) To Use
Training, Support, & Guidance, Oh My!
Strategy: Setting a Direction…
Prophecies of the Flood — from oneusefulthing.org by Ethan Mollick What to make of the statements of the AI labs?
What concerns me most isn’t whether the labs are right about this timeline – it’s that we’re not adequately preparing for what even current levels of AI can do, let alone the chance that they might be correct. While AI researchers are focused on alignment, ensuring AI systems act ethically and responsibly, far fewer voices are trying to envision and articulate what a world awash in artificial intelligence might actually look like. This isn’t just about the technology itself; it’s about how we choose to shape and deploy it. These aren’t questions that AI developers alone can or should answer. They’re questions that demand attention from organizational leaders who will need to navigate this transition, from employees whose work lives may transform, and from stakeholders whose futures may depend on these decisions. The flood of intelligence that may be coming isn’t inherently good or bad – but how we prepare for it, how we adapt to it, and most importantly, how we choose to use it, will determine whether it becomes a force for progress or disruption. The time to start having these conversations isn’t after the water starts rising – it’s now.
An Arizona charter school will use AI instead of human teachers for two hours a day on academic lessons.
The AI will customize lessons in real-time to match each student’s needs.
The company has only tested this idea at private schools before but claims it hugely increases student academic success.
One school in Arizona is trying out a new educational model built around AI and a two-hour school day. When Arizona’s Unbound Academy opens, the only teachers will be artificial intelligence algorithms in a perfect utopia or dystopia, depending on your point of view.
In order to encourage and facilitate debate on key controversies related to AI, I put together this free 130+ page guide to the main arguments and ideas related to the controversies.
Universities need to step up their AGI game — from futureofbeinghuman.com by Andrew Maynard As Sam Altman and others push toward a future where AI changes everything, universities need to decide if they’re going to be leaders or bystanders in helping society navigate advanced AI transitions
And because of this, I think there’s a unique opportunity for universities (research universities in particular) to up their game and play a leadership role in navigating the coming advanced AI transition.
Of course, there are already a number of respected university-based initiatives that are working on parts of the challenge. Stanford HAI (Human-centered Artificial Intelligence) is one that stands out, as does the Leverhulm Center for the Future of Intelligence at the University of Cambridge, and the Center for Governance of AI at the University of Oxford. But these and other initiatives are barely scratching the surface of what is needed to help successfully navigate advanced AI transitions.
If universities are to be leaders rather than bystanders in ensuring human flourishing in an age of AI, there’s an urgent need for bolder and more creative forward-looking initiatives that support research, teaching, thought leadership, and knowledge mobilization, at the intersection of advanced AI and all aspects of what it means to thrive and grow as a species.
Ever since a new revolutionary version of chat ChatGPT became operable in late 2022, educators have faced several complex challenges as they learn how to navigate artificial intelligence systems.
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Education Week produced a significant amount of coverage in 2024 exploring these and other critical questions involving the understanding and use of AI.
Here are the five most popular stories that Education Week published in 2024 about AI in schools.
Dr. Lodge said there are five key areas the higher education sector needs to address to adapt to the use of AI:
1. Teach ‘people’ skills as well as tech skills
2. Help all students use new tech
3. Prepare students for the jobs of the future
4. Learn to make sense of complex information
5. Universities to lead the tech change
“I mean, that’s what I’ll always want for my own children and, frankly, for anyone’s children,” Khan said. “And the hope here is that we can use artificial intelligence and other technologies to amplify what a teacher can do so they can spend more time standing next to a student, figuring them out, having a person-to-person connection.”
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“After a week you start to realize, like, how you can use it,” Brockman said. “That’s been one of the really important things about working with Sal and his team, to really figure out what’s the right way to sort of bring this to parents and to teachers and to classrooms and to do that in a way…so that the students really learn and aren’t just, you know, asking for the answers and that the parents can have oversight and the teachers can be involved in that process.”
More than 100 colleges and high schools are turning to a new AI tool called Nectir, allowing teachers to create a personalized learning partner that’s trained on their syllabi, textbooks, and assignments to help students with anything from questions related to their coursework to essay writing assistance and even future career guidance.
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With Nectir, teachers can create an AI assistant tailored to their specific needs, whether for a single class, a department, or the entire campus. There are various personalization options available, enabling teachers to establish clear boundaries for the AI’s interactions, such as programming the assistant to assist only with certain subjects or responding in a way that aligns with their teaching style.
“It’ll really be that customized learning partner. Every single conversation that a student has with any of their assistants will then be fed into that student profile for them to be able to see based on what the AI thinks, what should I be doing next, not only in my educational journey, but in my career journey,” Ghai said.
How Will AI Influence Higher Ed in 2025? — from insidehighered.com by Kathryn Palmer No one knows for sure, but Inside Higher Ed asked seven experts for their predictions.
As the technology continues to evolve at a rapid pace, no one knows for sure how AI will influence higher education in 2025. But several experts offered Inside Higher Ed their predictions—and some guidance—for how colleges and universities will have to navigate AI’s potential in the new year.
In the short term, A.I. will help teachers create lesson plans, find illustrative examples and generate quizzes tailored to each student. Customized problem sets will serve as tools to combat cheating while A.I. provides instant feedback.
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In the longer term, it’s possible to imagine a world where A.I. can ingest rich learner data and create personalized learning paths for students, all within a curriculum established by the teacher. Teachers can continue to be deeply involved in fostering student discussions, guiding group projects and engaging their students, while A.I. handles grading and uses the Socratic method to help students discover answers on their own. Teachers provide encouragement and one-on-one support when needed, using their newfound availability to give students some extra care.
Let’s be clear: A.I. will never replace the human touch that is so vital to education. No algorithm can replicate the empathy, creativity and passion a teacher brings to the classroom. But A.I. can certainly amplify those qualities. It can be our co-pilot, our chief of staff helping us extend our reach and improve our effectiveness.
Today, I want to reflect on two recent OpenAI developments that highlight this evolution: their belated publication of advice for students on integrating AI into writing workflows, and last week’s launch of the full GPTo1 Pro version. When OpenAI released their student writing guide, there were plenty of snarky comments about how this guidance arrives almost a year after they thoroughly disrupted the educational landscape. Fair enough – I took my own side swipes initially. But let’s look at what they’re actually advising, because the details matter more than the timing.
Tutoring programs exploded in the last five years as states and school districts searched for ways to counter plummeting achievement during COVID. But the cost of providing supplemental instruction to tens of millions of students can be eye-watering, even as the results seem to taper off as programs serve more students.
That’s where artificial intelligence could prove a decisive advantage. A report circulated in October by the National Student Support Accelerator found that an AI-powered tutoring assistant significantly improved the performance of hundreds of tutors by prompting them with new ways to explain concepts to students. With the help of the tool, dubbed Tutor CoPilot, students assigned to the weakest tutors began posting academic results nearly equal to those assigned to the strongest. And the cost to run the program was just $20 per pupil.
Faculty must have the time and support necessary to come to terms with this new technology and that requires us to change how we view professional development in higher education and K-12. We cannot treat generative AI as a one-off problem that can be solved by a workshop, an invited talk, or a course policy discussion. Generative AI in education has to be viewed as a continuum. Faculty need a myriad of support options each semester:
Course buyouts
Fellowships
Learning communities
Reading groups
AI Institutes and workshops
Funding to explore the scholarship of teaching and learning around generative AI
Education leaders should focus on integrating AI literacy, civic education, and work-based learning to equip students for future challenges and opportunities.
Building social capital and personalized learning environments will be crucial for student success in a world increasingly influenced by AI and decentralized power structures.
A Three-Phase, Rational System of Education — from petergray.substack.com by Peter Gray; with thanks to Dr. Kate Christian for this resource What will replace k-12 and college?
A Three-Phase, Rational System of Education I don’t know just how or how fast the change will happen, but I think the days of K-12 and four years of college are numbered and sanity will begin to prevail in the educational world. I envision a future with something like the following three-phase approach to education:
Phase I. Discovery: Learning about your world, your self, and how the two fit together.… Phase II. Exploring a career path.… Phase III. Becoming credentialed for specialized work.…
In this episode of My EdTech Life, I had the pleasure of interviewing Mike Kentz and Nick Potkalitsky, PhD, to discuss their new book, AI in Education: The K-12 Roadmap to Teacher-Led Transformation. We dive into the transformative power of AI in education, exploring its potential for personalization, its impact on traditional teaching practices, and the critical need for teacher-driven experimentation.
Striking a Balance: Navigating the Ethical Dilemmas of AI in Higher Education — from er.educause.edu by Katalin Wargo and Brier Anderson Navigating the complexities of artificial intelligence (AI) while upholding ethical standards requires a balanced approach that considers the benefits and risks of AI adoption.
As artificial intelligence (AI) continues to transform the world—including higher education—the need for responsible use has never been more critical. While AI holds immense potential to enhance teaching and learning, ethical considerations around social inequity, environmental concerns, and dehumanization continue to emerge. College and university centers for teaching and learning (CTLs), tasked with supporting faculty in best instructional practices, face growing pressure to take a balanced approach to adopting new technologies. This challenge is compounded by an unpredictable and rapidly evolving landscape. New AI tools surface almost daily. With each new tool, the educational possibilities and challenges increase exponentially. Keeping up is virtually impossible for CTLs, which historically have been institutional hubs for innovation. In fact, as of this writing, the There’s an AI for That website indicates that there are 23,208 AIs for 15,636 tasks for 4,875 jobs—with all three numbers increasing daily.
To support college and university faculty and, by extension, learners in navigating the complexities of AI integration while upholding ethical standards, CTLs must prioritize a balanced approach that considers the benefits and risks of AI adoption. Teaching and learning professionals need to expand their resources and support pathways beyond those solely targeting how to leverage AI or mitigate academic integrity violations. They need to make a concerted effort to promote critical AI literacy, grapple with issues of social inequity, examine the environmental impact of AI technologies, and promote human-centered design principles.1
We’re truly spoiled for choice when it comes to AI learning tools.
In principle, any free LLM can become an endlessly patient tutor or an interactive course-maker.
If that’s not enough, tools like NotebookLM’s “Audio Overviews” and ElevenLabs’ GenFM can turn practically any material into a breezy podcast.
But what if you’re looking to explore new topics in a way that’s more interactive than vanilla chatbots and more open-ended than source-grounded NotebookLM?
Well, then you might want to give one of these free-to-try learning tools a go.
Picture your enterprise as a living ecosystem,where surging market demand instantly informs staffing decisions, where a new vendor’s onboarding optimizes your emissions metrics, where rising customer engagement reveals product opportunities. Now imagine if your systems could see these connections too! This is the promise of AI agents — an intelligent network that thinks, learns, and works across your entire enterprise.
Today, organizations operate in artificial silos. Tomorrow, they could be fluid and responsive. The transformation has already begun. The question is: will your company lead it?
The journey to agent-enabled operations starts with clarity on business objectives. Leaders should begin by mapping their business’s critical processes. The most pressing opportunities often lie where cross-functional handoffs create friction or where high-value activities are slowed by system fragmentation. These pain points become the natural starting points for your agent deployment strategy.
Artificial intelligence has already proved that it can sound like a human, impersonate individuals and even produce recordings of someone speaking different languages. Now, a new feature from Microsoft will allow video meeting attendees to hear speakers “talk” in a different language with help from AI.
What Is Agentic AI? — from blogs.nvidia.com by Erik Pounds Agentic AI uses sophisticated reasoning and iterative planning to autonomously solve complex, multi-step problems.
The next frontier of artificial intelligence is agentic AI, which uses sophisticated reasoning and iterative planning to autonomously solve complex, multi-step problems. And it’s set to enhance productivity and operations across industries.
Agentic AI systems ingest vast amounts of data from multiple sources to independently analyze challenges, develop strategies and execute tasks like supply chain optimization, cybersecurity vulnerability analysis and helping doctors with time-consuming tasks.