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. .
– assessment
– funding
– deportations
– opposition to trans students
– mental health
– AI/AGI world
– a struggle to engage students
– too many hats
– war risks
– resource redistribution and civil conflict
There’s a half-billion-dollar federal program that is supposed to help students with disabilities get into the workforce when they leave high school, but most parents — and even some school officials — don’t know it exists. As a result, hundreds of thousands of students who could be getting help go without it. New Jersey had the nation’s lowest proportion — roughly 2 percent — of eligible students receiving these services in 2023.
More than a decade ago, Congress recognized the need to help young people with disabilities get jobs, and earmarked funding for pre-employment transition services to help students explore and train for careers and send them on a pathway to independence after high school. Yet, today, fewer than 40 percent of people with disabilities ages 16 to 64 are employed, even though experts say most are capable of working.
Both vocational rehabilitation agencies and schools are required by law to provide certain transition services and supports to improve post-school outcomes of students with disabilities.
The Workforce Innovation and Opportunity Act (WIOA) amends the Rehabilitation Act of 1973 and requires vocational rehabilitation (VR) agencies to set aside at least 15% of their federal funds to provide pre-employment transition services (Pre-ETS) to students with disabilities who are eligible or potentially eligible for VR services. The intent of pre-employment transition services is to:
improve the transition of students with disabilities from school to postsecondary education or to an employment outcome, increase opportunities for students with disabilities to practice and improve workplace readiness skills, through work-based learning experiences in a competitive, integrated work setting and increase opportunities for students with disabilities to explore post-secondary training options, leading to more industry recognized credentials, and meaningful post-secondary employment.
I’m a supporter of evolving classroom spaces—of redesigning the layout of the room as the needs and interests of students develop. The easiest way to accommodate students, I’ve found, is to use the furniture itself to set up a functional, spacious, and logical classroom. There are several benefits to this approach. It provides children with safe, low-stakes environmental changes; fosters flexibility; and creates opportunities for spatial adaptation and problem-solving. Additionally, rearranging the room throughout the school year enables teachers to address potential catalysts for challenging behaviors and social conflicts that may arise, while sparking curiosity in an otherwise-familiar space.
While instructional videos were prepared out of necessity in the past, I’ve rediscovered their utility as a quick, flexible, and personal way to enhance classroom teaching. Instructional videos can be created through free screencasting software such as Screencastify, ScreenRec, Loom, or OBS Studio. Screencasting would be ideal for the direct presentation of information, like a slide deck of notes. Phone cameras make practical recording devices for live content beyond the computer screen, like a science demo. A teacher could invest in a phone stand and ring light at a nominal cost to assist in this type of recording.
However, not all teacher videos are created equal, and I’ve discovered four benefits and strategies that help make these teaching tools more effective.
6 Strategies for Building a Sustainable STEM Ecosystem — from edutopia.org by Rich Schiccatano Upper elementary teachers can use these ideas to create meaningful, interdisciplinary STEM opportunities that encourage experimentation.
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
With that out of the way, I prefer Claude.ai for writing. For larger projects like a book, create a Claude Project to keep all context in one place.
Copy [the following] prompts into a document
Use them in sequence as you write
Adjust the word counts and specifics as needed
Keep your responses for reference
Use the same prompt template for similar sections to maintain consistency
Each prompt builds on the previous one, creating a systematic approach to helping you write your book.
Using NotebookLM to Boost College Reading Comprehension— from michellekassorla.substack.com by Michelle Kassorla and Eugenia Novokshanova This semester, we are using NotebookLM to help our students comprehend and engage with scholarly texts
We were looking hard for a new tool when Google released NotebookLM. Not only does Google allow unfettered use of this amazing tool, it is also a much better tool for the work we require in our courses. So, this semester, we have scrapped our “old” tools and added NotebookLM as the primary tool for our English Composition II courses (and we hope, fervently, that Google won’t decide to severely limit its free tier before this semester ends!)
If you know next-to-nothing about NotebookLM, that’s OK. What follows is the specific lesson we present to our students. We hope this will help you understand all you need to know about NotebookLM, and how to successfully integrate the tool into your own teaching this semester.
AFTER two years of working closely with leadership in multiple institutions, and delivering countless workshops, I’ve seen one thing repeatedly: the biggest challenge isn’t the technology itself, but how we lead through it. Here is some of my best advice to help you navigate generative AI with clarity and confidence:
Break your own AI policies before you implement them. …
Fund your failures. …
Resist the pilot program. …
Host Anti-Tech Tech Talks …
…+ several more tips
While generative AI in higher education obviously involves new technology, it’s much more about adopting a curious and human-centric approach in your institution and communities. It’s about empowering learners in new, human-oriented and innovative ways. It is, in a nutshell, about people adapting to new ways of doing things.
Maria Anderson responded to Clay’s posting with this idea:
Here’s an idea: […] the teacher can use the [most advanced] AI tool to generate a complete solution to “the problem” — whatever that is — and demonstrate how to do that in class. Give all the students access to the document with the results.
And then grade the students on a comprehensive followup activity / presentation of executing that solution (no notes, no more than 10 words on a slide). So the students all have access to the same deep AI result, but have to show they comprehend and can iterate on that result.
In this age of distrust, misinformation, and skepticism, you may wonder how to demonstrate your sources within a Google Document. Did you type it yourself, copy and paste it from a browser-based source, copy and paste it from an unknown source, or did it come from generative AI?
You may not think this is an important clarification, but if writing is a critical part of your livelihood or life, you will definitely want to demonstrate your sources.
That’s where the new Grammarly feature comes in.
The new feature is called Authorship, and according to Grammarly, “Grammarly Authorship is a set of features that helps users demonstrate their sources of text in a Google doc. When you activate Authorship within Google Docs, it proactively tracks the writing process as you write.”
AI Agents Are Coming to Higher Education — from govtech.com AI agents are customizable tools with more decision-making power than chatbots. They have the potential to automate more tasks, and some schools have implemented them for administrative and educational purposes.
Custom GPTs are on the rise in education. Google’s version, Gemini Gems, includes a premade version called Learning Coach, and Microsoft announced last week a new agent addition to Copilot featuring use cases at educational institutions.
Generative Artificial Intelligence and Education: A Brief Ethical Reflection on Autonomy— from er.educause.edu by Vicki Strunk and James Willis Given the widespread impacts of generative AI, looking at this technology through the lens of autonomy can help equip students for the workplaces of the present and of the future, while ensuring academic integrity for both students and instructors.
The principle of autonomy stresses that we should be free agents who can govern ourselves and who are able to make our own choices. This principle applies to AI in higher education because it raises serious questions about how, when, and whether AI should be used in varying contexts. Although we have only begun asking questions related to autonomy and many more remain to be asked, we hope that this serves as a starting place to consider the uses of AI in higher education.
I had the privilege of moderating a discussion between Josh Eyler and Robert Cummings about the future of AI in education at the University of Mississippi’s recent AI Winter Institute for Teachers. I work alongside both in faculty development here at the University of Mississippi. Josh’s position on AI sparked a great deal of debate on social media:
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To make my position clear about the current AI in education discourse I want to highlight several things under an umbrella of “it’s very complicated.”
Most importantly, we all deserve some grace here. Dealing with generative AI in education isn’t something any of us asked for. It isn’t normal. It isn’t fixable by purchasing a tool or telling faculty to simply ‘prefer not to’ use AI. It is and will remain unavoidable for virtually every discipline taught at our institutions.
If one good thing happens because of generative AI let it be that it helps us clearly see how truly complicated our existing relationships with machines are now. As painful as this moment is, it might be what we need to help prepare us for a future where machines that mimic reasoning and human emotion refuse to be ignored.
“AI tutoring shows stunning results.” See below article.
Learning gains were striking The learning improvements were striking—about 0.3 standard deviations. To put this into perspective, this is equivalent to nearly two years of typical learning in just six weeks.When we compared these results to a database of education interventions studied through randomized controlled trials in the developing world, our program outperformed 80% of them, including some of the most cost-effective strategies like structured pedagogy and teaching at the right level. This achievement is particularly remarkable given the short duration of the program and the likelihood that our evaluation design underestimated the true impact.
… Our evaluation demonstrates the transformative potential of generative AI in classrooms, especially in developing contexts. To our knowledge, this is the first study to assess the impact of generative AI as a virtual tutor in such settings, building on promising evidence from other contexts and formats; for example, on AI in coding classes, AI and learning in one school in Turkey, teaching math with AI (an example through WhatsApp in Ghana), and AI as a homework tutor.
Why it matters: This represents one of the first rigorous studies showing major real-world impacts in a developing nation. The key appears to be using AI as a complement to teachers rather than a replacement — and results suggest that AI tutoring could help address the global learning crisis, particularly in regions with teacher shortages.
Other items re: AI in our learning ecosystems:
Will AI revolutionise marking? — from timeshighereducation.com by Rohim Mohammed Artificial intelligence has the potential to improve speed, consistency and detail in feedback for educators grading students’ assignments, writes Rohim Mohammed. Here he lists the pros and cons based on his experience
Personal AI— from michelleweise.substack.com by Dr. Michelle Weise “Personalized” Doesn’t Have To Be a Buzzword Today, however, is a different kind of moment. GenAI is now rapidly evolving to the point where we may be able to imagine a new way forward. We can begin to imagine solutions truly tailored for each of us as individuals, our own personal AI (pAI). pAI could unify various silos of information to construct far richer and more holistic and dynamic views of ourselves as long-life learners. A pAI could become our own personal career navigator, skills coach, and storytelling agent. Three particular areas emerge when we think about tapping into the richness of our own data:
Now is the time for visionary leadership in education.The era of artificial intelligence is reshaping the demands on education systems. Rigid policies, outdated curricula, and reliance on obsolete metrics are failing students. A recent survey from Resume Genius found that graduates lack skills in communication, collaboration, and critical thinking. Consequently, there is a growing trend in companies hiring candidates based on skills instead of traditional education or work experience. This underscores the urgent need for educational leaders to prioritize adaptability and innovation in their systems. Educational leaders must embrace a transformative approach to keep pace.
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[Heretical leaders] bring courage, empathy, and strategic thinking to reimagine education’s potential. Here are their defining characteristics:
Visionary Thinking: They identify bold, innovative paths to progress.
Courage to Act: These leaders take calculated risks to overcome resistance and inertia.
Relentless Curiosity: They challenge assumptions and seek better alternatives.
Empathy for Stakeholders: Understanding the personal impact of change allows them to lead with compassion.
Strategic Disruption: Their deliberate actions ensure systemic improvements.
These qualities enable Heretical leaders to reframe challenges as opportunities and drive meaningful change.
From DSC: Readers of this blog will recognize that I believe visionary leadership is extremely important — in all areas of our society, but especially within our learning ecosystems. Vision trumps data, at least in my mind. There are times when data can be used to support a vision, but having a powerful vision is more lasting and impactful than relying on data to drive the organization.
So while I’d vote for a different term other than “heretical leaders,” I get what Dan is saying and I agree with him. Such leaders are going against the grain. They are swimming upstream. They are espousing perspectives that others often don’t buy into (at least initially or for some time).
Such were the leaders who introduced online learning into the K-16 educational systems back in the late ’90s and into the next two+ decades. The growth of online-based learning continues and has helped educate millions of people. Those leaders and the people who worked for such endeavors were going against the grain.
We haven’t seen the end point of online-based learning. I think it will become even more powerful and impactful when AI is used to determine which jobs are opening up, and which skills are needed for those jobs, and then provide a listing of sources of where one can obtain that knowledge and develop those skills. People will be key in this vision. But so will AI and personalized learning. It will be a collaborative effort.
By the way, I am NOT advocating for using AI to outsource our thinking. Also, having basic facts and background knowledge in a domain is critically important, especially to use AI effectively. But we should be teaching students about AI (as we learn more about it ourselves). We should be working collaboratively with our students to understand how best to use AI. It’s their futures at stake.
When seeking guidance on classroom practice, teachers—understandably—tend to trust other teachers the most. An innovative fellowship program connects teachers with one another to provide concrete examples of what effective literacy instruction looks like.
A small philanthropy called the Goyen Foundation sponsors the program, now in its third year. For each cohort, the foundation selects 12 to 14 educators who are skilled in systematically teaching foundational reading skills while simultaneously building the knowledge that enables reading comprehension.
The Goyen Literacy Fellows document their own classroom practice, mostly through videos that are posted on social media platforms like X/Twitter and Facebook. They also interact with other educators who may have heard about “structured literacy” but aren’t sure what it means or how it’s done.
Giving Kids Some Autonomy Has Surprising Results — from nytimes.com by Jenny Anderson and Rebecca Winthrop Jenny Anderson and Rebecca Winthrop are the authors of “The Disengaged Teen: Helping Kids Learn Better, Feel Better, and Live Better.”
In a polarized nation, one point of agreement deserves more attention: Young adults say they feel woefully unprepared for life in the work force, and employers say they’re right.
In a survey by Gallup and the Walton Family Foundation of more than 4,000 members of Gen Z, 49 percent of respondents said they did not feel prepared for the future. Employers complain that young hires lack initiative, communication skills, problem-solving abilities and resilience.
There’s a reason the system isn’t serving people well, and it goes beyond the usual culprits of social media and Covid. Many recent graduates aren’t able to set targets, take initiative, figure things out and deal with setbacks — because in school and at home they were too rarely afforded any agency.
Maybe it’s time to define a higher ideal for education, less about ranking and sorting students on narrow measures of achievement and more about helping young people figure out how to unlock their potential and how to operate in the world. Amid the drumbeat of evolving artificial intelligence, wars, rising authoritarianism, political polarization and digital disconnection, they need to learn a lot more than how to follow instructions.
Youth Voice & Choice
At XQ, we don’t see high schools as the tail end of K-12 education. Instead, we believe they are pivotal spaces for unleashing a young person’s sense of possibility and agency—so much so that it’s one of our Design Principles for school-wide success: Youth Voice and Choice.
Anderson and Winthrop, too, emphasize that when students feel they can shape the direction of their learning, they gain essential life skills: setting targets, identifying strategies, monitoring progress, and course-correcting when inevitable challenges arise. These aptitudes translate directly to college readiness, workforce performance, and a strong sense of agency in adulthood. As the authors note, even small doses of agency—like letting students choose which angle of a topic to explore—can radically transform how teens engage with the material and each other.
We’ve long championed youth voice and choice as a key element for transforming the traditional high school experience. By adopting this design principle, educators and school leaders empower students to be agents of their own learning journeys. They celebrate students’ personal growth and consistently provide opportunities for them to set goals and reflect on how they learn best.
By shifting away from checklists and mindless compliance, we can transform high schools into spaces of curiosity, discovery, and lasting engagement—where a spark lit in 9th grade can guide and energize students for a lifetime.
Faculty members often design and revise courses with limited direct feedback from students. In this episode, Laurel Willingham-McLain and Jacques Safari Mwayaona join us to discuss a program in which faculty work with trained student consultants to improve the student learning experience. Laurel is a consulting faculty developer at the Center for Teaching and Learning Excellence at Syracuse University. Jacques is a Faculty Development Fellow, also at Syracuse University. Laurel and Jacques both work with the Students Consulting on Teaching program at Syracuse University.
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
Introducing the 2025 Wonder Media Calendar for tweens, teens, and their families/households.Designed by Sue Ellen Christian and her students in her Global Media Literacy class (in the fall 2024 semester at Western Michigan University), the calendar’s purpose is to help people create a new year filled with skills and smart decisions about their media use. This calendar is part of the ongoing Wonder Media Library.comproject that includes videos, lesson plans, games, songs and more. The website is funded by a generous grant from the Institute of Museum and Library Services, in partnership with Western Michigan University and the Library of Michigan.
“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.
