Nvidia helps launch AI platform for teaching American Sign Language — from venturebeat.com by Dean Takahashi; via Claire Zau

Nvidia has unveiled a new AI platform for teaching people how to use American Sign Language to help bridge communication gaps.

The Signs platform is creating a validated dataset for sign language learners and developers of ASL-based AI applications.

Nvidia, the American Society for Deaf Children and creative agency Hello Monday are helping close this gap with Signs, an interactive web platform built to support ASL learning and the development of accessible AI applications.


Using Gen AI to Design, Implement, and Assess PBL — from gettingsmart.com by David Ross

Key Points

  • Generative AI can significantly reduce the time and effort required in designing PBL by providing tools for research, brainstorming, and organization.
  • AI tools can assist educators in managing project implementation and assessment, providing formative feedback and organizing resources efficiently.

I usually conclude blogs with some pithy words, but this time I’ll turn the microphone over to Rachel Harcrow, a high school English/Language Arts teacher at Young Women’s College Prep Charter School of Rochester, NY: “After years of struggling to call myself a PBL practitioner, I finally feel comfortable saying I am, thanks to the power of Gen AI,” Harcrow told me. “Initial ideas now turn into fully fledged high-quality project plans in minutes that I can refine, giving me the space and energy to focus on what truly matters: My students.”


AI Resources for District Leaders — from techlearning.com by Steve Baule
Educational leaders aiming to effectively integrate generative AI into their schools should consider several key resources

To truly harness the transformative power of generative AI in education, district leaders must navigate a landscape rich with resources and opportunities. By delving into state and national guidelines, exploring successful case studies, utilizing innovative planning tools, and engaging in professional development, educational leaders can craft robust implementation plans. These plans can then assist in integrating AI seamlessly into their schools and elevate the learning experience to new heights.


Anthropic brings ‘extended thinking’ to Claude, which can solves complex physics problems with 96.5% accuracy — from rdworldonline.com by Brian Buntz

Anthropic, a favorite frontier AI lab among many coders and genAI power users has unveiled Claude 3.7 Sonnet, its first “hybrid reasoning” AI model. It is capable of both near-instant answers and in-depth, step-by-step reasoning within a single system.

Users can toggle an extended thinking mode where the model self-reflects before answering, considerably improving performance on complex tasks like math, physics and coding. In early testing by the author, the model largely succeeded in creating lines of Python (related to unsupervised learning) that were close to 1,000 lines long that ran without error on the first or second try, including the unsupervised machine learning task shown below:


New Tools. Old Complaints. Why AI Won’t Kill Education or Fix it  — from coolcatteacher.com by Vicki Davis; via Stephen Downes

AI won’t kill education. But will it kill learning? The challenge isn’t AI itself—it’s whether students can still think for themselves when the answers are always one click away.

Wait. Before you go, let me ask you one thing.
AI has opportunities to help learning. But it also won’t fix it. The real question isn’t whether students can use AI—but whether they’re still learning without it.

Whether the learning is happening between the ears.

And so much of what we teach in schools isn’t the answers on a test. It answers questions like “What is my purpose in life?” “How do I make friends?” and “How can I help my team be stronger.” Questions that aren’t asked on a test but are essential to living a good life. These questions aren’t answered between the ears but within the heart.

That, my friends, is what teaching has always been about.

The heart.

And the heart of the matter is we have new challenges, but these are old complaints. Complaints since the beginning of time and teaching. And in those days, you didn’t need kids just to be able to talk about how to build a fire, they had to make one themselves. Their lives depend on it.

And these days, we need to build another kind of fire. A fire that sparks the joy of learning. The joy of the opportunities that await us sparked by some of the most powerful tools ever invented. Kids need to not be able to just talk about making a difference, they need to know how to build a better world tomorrow. Our lives depend on it.


How Debating Skills Can Help Us In The Fight Against AI — from adigaskell.org by Adi Gaskell

Debating skills have a range of benefits in the workplace, from helping to improve our communication to bolstering our critical thinking skills. Research from the University of Mississippi suggests it might also help us in the battle with AI in the workplace.

We can often assume that debate teaches us nothing more than how to argue our point, but in order to do this, we have to understand both our own take on a subject and that of our opponent. This allows us to see both sides of any issue we happen to be debating.

“Even though AI has offered a shortcut through the writing process, it actually still is important to be able to write and speak and think on your own,” the researchers explain. “That’s what the focus of this research is: how debate engenders those aspects of being able to write and speak and study and research on your own.”

 

The Learning & Development Global Sentiment Survey 2025 — from donaldhtaylor.co.uk by Don Taylor

The L&D Global Sentiment Survey, now in its 12th year, once again asked two key questions of L&D professionals worldwide:

  • What will be hot in workplace learning in 2025?
  • What are your L&D challenges in 2025?

For the obligatory question on what they considered ‘hot’ topics, respondents voted for one to three of 15 suggested options, plus a free text ‘Other’ option. Over 3,000 voters participated from nearly 100 countries. 85% shared their challenges for 2025.

The results show more interest in AI, a renewed focus on showing the value of L&D, and some signs of greater maturity around our understanding of AI in L&D.


 

AI in K12: Today’s Breakthroughs and Tomorrow’s Possibilities (webinar)
How AI is Transforming Classrooms Today and What’s Next


Audio-Based Learning 4.0 — from drphilippahardman.substack.com by Dr. Philippa Hardman
A new & powerful way to leverage AI for learning?

At the end of all of this my reflection is that the research paints a pretty exciting picture – audio-based learning isn’t just effective, it’s got some unique superpowers when it comes to boosting comprehension, ramping up engagement, and delivering feedback that really connects with learners.

While audio has been massively under-used as a mode of learning, especially compared to video and text, we’re at an interesting turning point where AI tools are making it easier than ever to tap into audio’s potential as a pedagogical tool.

What’s super interesting is how the solid research backing audio’s effectiveness is and how well this is converging with these new AI capabilities.

From DSC:
I’ve noticed that I don’t learn as well via audio-only based events. It can help if visuals are also provided, but I have to watch the cognitive loads. My processing can start to get overloaded — to the point that I have to close my eyes and just listen sometimes. But there are people I know who love to listen to audiobooks and prefer to learn that way. They can devour content and process/remember it all. Audio is a nice change of pace at times, but I prefer visuals and reading often times. It needs to be absolutely quiet if I’m tackling some new information/learning. 


In Conversation With… Ashton Cousineau — from drphilippahardman.substack.com by Dr. Philippa Hardman
A new video series exploring how L&D professionals are working with AI on the ground

In Conversation With… Ashton Cousineau by Dr Philippa Hardman

A new video series exploring how L&D professionals are working with AI on the ground

Read on Substack


The Learning Research Digest vol. 28 — from learningsciencedigest.substack.com by Dr. Philippa Hardman

Hot Off the Research Press This Month:

  • AI-Infused Learning Design – A structured approach to AI-enhanced assignments using a three-step model for AI integration.
  • Mathematical Dance and Creativity in STEAM – Using AI-powered motion capture to translate dance movements into mathematical models.
  • AI-Generated Instructional Videos – How adaptive AI-powered video learning enhances problem-solving and knowledge retention.
  • Immersive Language Learning with XR & AI – A new framework for integrating AI-driven conversational agents with Extended Reality (XR) for task-based language learning.
  • Decision-Making in Learning Design – A scoping review on how instructional designers navigate complex instructional choices and make data-driven decisions.
  • Interactive E-Books and Engagement – Examining the impact of interactive digital books on student motivation, comprehension, and cognitive engagement.
  • Elevating Practitioner Voices in Instructional Design – A new initiative to amplify instructional designers’ contributions to research and innovation.

Deep Reasoning, Agentic AI & the Continued Rise of Specialised AI Research & Tools for Education — from learningfuturesdigest.substack.com by Dr. Philippa Hardman

Here’s a quick teaser of key developments in the world of AI & learning this month:

  • DeepSeek R-1, OpenAI’s Deep Seek & Perplexity’s ‘Deep Research’ are the latest additions to a growing number of “reasoning models” with interesting implications for evidence-based learning design & development.
  • The U.S. Education Dept release an AI Toolkit and a fresh policy roadmap enabling the adoption of AI use in schools.
  • Anthropic Release “Agentic Claude”, another AI agent that clicks, scrolls, and can even successfully complete e-learning courses…
  • Oxford University Announce the AIEOU Hub, a research-backed research lab to support research and implementation on AI in education.
  • “AI Agents Everywhere”: A Forbes peek at how agentic AI will handle the “boring bits” of classroom life.
  • [Bias klaxon!] Epiphany AI: My own research leads to the creation of a specialised, “pedagogy first” AI co-pilot for instructional design marking the continued growth of specialised AI tools designed for specific industries and workflows.

AI is the Perfect Teaching Assistant for Any Educator — from unite.ai by Navi Azaria, CPO at Kaltura

Through my work with leading educational institutions at Kaltura, I’ve seen firsthand how AI agents are rapidly becoming indispensable. These agents alleviate the mounting burdens on educators and provide new generations of tech-savvy students with accessible, personalized learning, giving teachers the support they need to give their students the personalized attention and engagement they deserve.


Learning HQ — from ai-disruptor-hq.notion.site

This HQ includes all of my AI guides, organized by tool/platform. This list is updated each time a new one is released, and outdated guides are removed/replaced over time.



How AI Is Reshaping Teachers’ Jobs — from edweek.org

Artificial intelligence is poised to fundamentally change the job of teaching. AI-powered tools can shave hours off the amount of time teachers spend grading, lesson-planning, and creating materials. AI can also enrich the lessons they deliver in the classroom and help them meet the varied needs of all students. And it can even help bolster teachers’ own professional growth and development.

Despite all the promise of AI, though, experts still urge caution as the technology continues to evolve. Ethical questions and practical concerns are bubbling to the surface, and not all teachers feel prepared to effectively and safely use AI.

In this special report, see how early-adopter teachers are using AI tools to transform their daily work, tackle some of the roadblocks to expanded use of the technology, and understand what’s on the horizon for the teaching profession in the age of artificial intelligence.

 

Half A Million Students Given ChatGPT As CSU System Makes AI History — from forbes.com by Dan Fitzpatrick

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.




HOW educators can use GenAI – where to start and how to progress — from aliciabankhofer.substack.com by Alicia Bankhofer
Part of 3 of my series: Teaching and Learning in the AI Age

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


 

How to Make Learning as Addictive as Social Media | Duolingo’s Luis Von Ahn | TED — from youtube.com; via Kamil Banc at AI Adopter

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.
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DeepSeek: How China’s AI Breakthrough Could Revolutionize Educational Technology — from nickpotkalitsky.substack.com by Nick Potkalitsky
Can DeepSeek’s 90% efficiency boost make AI accessible to every school?

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.”

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.


Over 100 AI Tools for Teachers — from educatorstechnology.com by Med Kharbach, PhD

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.


Beth’s posting links to:

 


Derek’s posting on LinkedIn


From Theory to Practice: How Generative AI is Redefining Instructional Materials — from edtechinsiders.substack.com by Alex Sarlin
Top trends and insights from The Edtech Insiders Generative AI Map research process about how Generative AI is transforming Instructional Materials

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

On a somewhat-related note, also see:


 

Four objectives to guide artificial intelligence’s impact on higher education — from timeshighereducation.com by Susan C. Aldridge
How can higher education leaders manage both the challenge and the opportunity artificial intelligence presents? Here are four objectives to guide the way

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.


In This Week’s Gap Letter — by Ryan Craig

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….


The Impact of Gen AI on Human Learning: a research summary — from drphilippahardman.substack.com by  Dr. Philippa Hardman
A literature review of the most recent & important peer-reviewed studies

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
 

Your AI Writing Partner: The 30-Day Book Framework — from aidisruptor.ai by Alex McFarland and Kamil Banc
How to Turn Your “Someday” Manuscript into a “Shipped” Project Using AI-Powered Prompts

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.


Leadership & Generative AI: Hard-Earned Lessons That Matter — from jeppestricker.substack.com by Jeppe Klitgaard Stricker
Actionable Advice for Higher Education Leaders in 2025

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:

  1. Break your own AI policies before you implement them.
  2. Fund your failures.
  3. Resist the pilot program. …
  4. Host Anti-Tech Tech Talks
  5. …+ 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.



Grammarly just made it easier to prove the sources of your text in Google Docs — from zdnet.com by Jack Wallen
If you want to be diligent about proving your sources within Google Documents, Grammarly has a new feature you’ll want to use.

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.

 

AI Is Unavoidable, Not Inevitable — from marcwatkins.substack.com by Marc Watkins

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:

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.


From chalkboards to chatbots: Transforming learning in Nigeria, one prompt at a time — from blogs.worldbank.org by Martín E. De Simone, Federico Tiberti, Wuraola Mosuro, Federico Manolio, Maria Barron, and Eliot Dikoru

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.

Comments on this article from The Rundown AI:

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
  • Marty the Robot: Your Classroom’s AI Companion — from rdene915.com by Dr. Rachelle Dené Poth
  • Generative Artificial Intelligence: Cautiously Recognizing Educational Opportunities — from scholarlyteacher.com by Todd Zakrajsek, University of North Carolina at Chapel Hill
  • 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:

    • Personalized Learning Pathways & Dynamic Skill Assessment: …
    • Storytelling for Employers:…
    • Ongoing Mentorship and Feedback: …
  • Speak — a language learning app — via The Neuron

 

Students Pushback on AI Bans, India Takes a Leading Role in AI & Education & Growing Calls for Teacher Training in AI — from learningfuturesdigest.substack.com by Dr. Philippa Hardman
Key developments in the world of AI & Education at the turn of 2025

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.

Also mentioned by Philippa:


ElevenLabs AI Voice Tool Review for Educators — from aiforeducation.io with Amanda Bickerstaff and Mandy DePriest

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.


How to Use Google’s Deep Research, Learn About and NotebookLM Together — from ai-supremacy.com by Michael Spencer and Nick Potkalitsky
Supercharging your research with Google Deepmind’s new AI Tools.

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.
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Getting to an AI Policy Part 1: Challenges — from aiedusimplified.substack.com by Lance Eaton, PH.D.
Why institutional policies are slow to emerge in higher education

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.

  1. Which Tool(s) To Use
  2. Training, Support, & Guidance, Oh My!
  3. 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.


 

The Best of AI 2024: Top Winners Across 9 Categories — from aiwithallie.beehiiv.com by Allie Miller
2025 will be our weirdest year in AI yet. Read this so you’re more prepared.


Top AI Tools of 2024 — from ai-supremacy.com by Michael Spencer (behind a paywall)
Which AI tools stood out for me in 2024? My list.

Memorable AI Tools of 2024
Catergories included:

  • Useful
  • Popular
  • Captures the zeighest of AI product innovation
  • Fun to try
  • Personally satisfying
  1. NotebookLM
  2. Perplexity
  3. Claude

New “best” AI tool? Really? — from theneurondaily.com by Noah and Grant
PLUS: A free workaround to the “best” new AI…

What is Google’s Deep Research tool, and is it really “the best” AI research tool out there?

Here’s how it works: Think of Deep Research as a research team that can simultaneously analyze 50+ websites, compile findings, and create comprehensive reports—complete with citations.

Unlike asking ChatGPT to research for you, Deep Research shows you its research plan before executing, letting you edit the approach to get exactly what you need.

It’s currently free for the first month (though it’ll eventually be $20/month) when bundled with Gemini Advanced. Then again, Perplexity is always free…just saying.

We couldn’t just take J-Cal’s word for it, so we rounded up some other takes:

Our take: We then compared Perplexity, ChatGPT Search, and Deep Research (which we’re calling DR, or “The Docta” for short) on robot capabilities from CES revealed:


An excerpt from today’s Morning Edition from Bloomberg

Global banks will cut as many as 200,000 jobs in the next three to five years—a net 3% of the workforce—as AI takes on more tasks, according to a Bloomberg Intelligence survey. Back, middle office and operations are most at risk. A reminder that Citi said last year that AI is likely to replace more jobs in banking than in any other sector. JPMorgan had a more optimistic view (from an employee perspective, at any rate), saying its AI rollout has augmented, not replaced, jobs so far.


 

 

Increasing AI Fluency Among Enterprise Employees, Senior Management & Executives — from learningguild.com by Bill Brandon

In other words, individual learning leaders need to obtain information from surveys and studies that are directly useful in their curriculum planning. This article attempts, in these early days, to provide some specific guidelines for AI curriculum planning in enterprise organizations.

The two reports identified in the first paragraph help to answer an important question. What can enterprise L&D teams do to improve AI fluency in their organizations?


The Future of Workplace Learning: Adaptive Strategies for Navigating Change — from learningguild.com by Rachel Rosenfeldt

The Importance of Building a ‘Change Muscle’
The ability to test and learn, pivot quickly, and embrace change is an increasingly foundational skill that all employees, no matter the level of experience or seniority, need in 2025 and beyond. Adaptable organizations significantly outperform more change-averse peers on nearly every metric, ranging from revenue growth to employee engagement. In other words, having agility and adaptability embedded in your culture pays dividends. Although these terms are often used interchangeably, they represent distinct yet interconnected aspects of organizational success:

  • Agility refers to the ability to swiftly and efficiently respond to immediate challenges or opportunities. It’s about being nimble and proactive, making quick decisions, and adjusting to navigate short-term obstacles.
  • Adaptability is a broader concept that encompasses the capacity to evolve and thrive in the face of long-term shifts in the environment. It’s about being resilient and flexible by modifying strategies and structures to align with fundamental changes in the market or industry.

And a quick comment from DSC:


Addressing Skills Gaps in Enterprise L&D: A High-Level Overview — from learningguild.com by Bill Brandon

Employees’ skills and abilities must match the skills and abilities required for their jobs; when they do, organizational performance and productivity improve.

Skills gaps occur when there are mismatches between employees’ skills and capabilities and the skills and capabilities needed for their work. As technology and work become more complex, identifying and correcting skills gaps become essential to optimizing employee performance.

This article discusses various methods involving skills inference and predictive analytics in addition to traditional methods to pinpoint and prevent skills gaps.


A Practical Framework for Microlearning Success: A Guide for Learning Leaders — from by Robyn A. Defelice, PhD

Another year, another opportunity to bring microlearning into your performance and talent development strategy! This is especially appealing as more and more organizations strive to deliver training in ways that meet the fast-paced needs of their employees.

However, implementing a microlearning strategy that aligns with organizational outcomes and sustains performance is no small feat. Learning and Development (L&D) leaders often grapple with questions like: Where do we start; How do we ensure our efforts are effective; and What factors should we evaluate?

The Microlearning Effectiveness (MLE) Framework offers a practical approach to addressing these challenges. Instead of rigid rules, the framework acts as a guide, encouraging leaders to evaluate their efforts against six key components:

  • Goals or measurable outcomes
  • Purpose
  • Potential
  • Evaluation
  • Implementation
  • Distributed practice
 

AI educators are coming to this school – and it’s part of a trend — from techradar.com by Eric Hal Schwartz
Two hours of lessons, zero teachers

  • 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.


AI in Instructional Design: reflections on 2024 & predictions for 2025 — from drphilippahardman.substack.com by Dr. Philippa Hardman
Aka, four new year’s resolutions for the AI-savvy instructional designer.


Debating About AI: A Free Comprehensive Guide to the Issues — from stefanbauschard.substack.com by Stefan Bauschard

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.


 

 

How AI Is Changing Education: The Year’s Top 5 Stories — from edweek.org by Alyson Klein

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.

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.


What’s next with AI in higher education? — from msn.com by Science X Staff

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


5 Ways Teachers Can Use NotebookLM Today — from classtechtips.com by Dr. Monica Burns

 
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