The Third Horizon of Learning Shifting beyond the Industrial Model — from gettingsmart.com by Sujata Bhatt & Mason Pashia

Over 24 blog posts, we have sketched a bold vision of what this next horizon of education looks like in action and highlighted the many innovators working to bring it to life. These pioneers are building new models that prioritize human development, relationships, and real-world relevance as most valuable. They are forging partnerships, designing and adopting transformative technologies, developing new assessment methods, and more. These shifts transform the lived experiences of young people and serve the needs of families and communities. In short, they are delivering authentic learning experiences that better address the demands of today’s economy, society, and learners.

We’ve aggregated our findings from this blog series and turned it into an H3 Publication. Inside, you’ll find our key transformation takeaways for school designers and system leaders, as well as a full list of the contributing authors. Thank you to all of the contributors, including LearnerStudio for sponsoring the series and Sujata Bhatt at Incubate Learning for authorship, editing and curation support throughout the entirety of the series and publication.
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8 Weeks Left to Prepare Students for the AI-Enhanced Workplace — from insidehighered.com by Ray Schroeder
We are down to the final weeks left to fully prepare students for entry into the AI-enhanced workplace. Are your students ready?

The urgent task facing those of us who teach and advise students, whether they be degree program or certificate seeking, is to ensure that they are prepared to enter (or re-enter) the workplace with skills and knowledge that are relevant to 2025 and beyond. One of the first skills to cultivate is an understanding of what kinds of services this emerging technology can provide to enhance the worker’s productivity and value to the institution or corporation.

Given that short period of time, coupled with the need to cover the scheduled information in the syllabus, I recommend that we consider merging AI use into authentic assignments and assessments, supplementary modules, and other resources to prepare for AI.


Learning Design in the Era of Agentic AI — from drphilippahardman.substack.com by Dr Philippa Hardman
Aka, how to design online async learning experiences that learners can’t afford to delegate to AI agents

The point I put forward was that the problem is not AI’s ability to complete online async courses, but that online async courses courses deliver so little value to our learners that they delegate their completion to AI.

The harsh reality is that this is not an AI problem — it is a learning design problem.

However, this realisation presents us with an opportunity which we overall seem keen to embrace. Rather than seeking out ways to block AI agents, we seem largely to agree that we should use this as a moment to reimagine online async learning itself.



8 Schools Innovating With Google AI — Here’s What They’re Doing — from forbes.com by Dan Fitzpatrick

While fears of AI replacing educators swirl in the public consciousness, a cohort of pioneering institutions is demonstrating a far more nuanced reality. These eight universities and schools aren’t just experimenting with AI, they’re fundamentally reshaping their educational ecosystems. From personalized learning in K-12 to advanced research in higher education, these institutions are leveraging Google’s AI to empower students, enhance teaching, and streamline operations.


Essential AI tools for better work — from wondertools.substack.com by Jeremy Caplan
My favorite tactics for making the most of AI — a podcast conversation

AI tools I consistently rely on (areas covered mentioned below)

  • Research and analysis
  • Communication efficiency
  • Multimedia creation

AI tactics that work surprisingly well 

1. Reverse interviews
Instead of just querying AI, have it interview you. Get the AI to interview you, rather than interviewing it. Give it a little context and what you’re focusing on and what you’re interested in, and then you ask it to interview you to elicit your own insights.”

This approach helps extract knowledge from yourself, not just from the AI. Sometimes we need that guide to pull ideas out of ourselves.

 

How can businesses stay ahead of trends and technologies that are rapidly changing their industries? — from linkedin.com by Tanja Schindler; via her Dancing with Uncertainty newsletter

Companies need to develop a sense of curiosity about both the observable trends in the present and the unobserved factors that could significantly influence their futures. While current trends can drive us in certain directions, we also need to imagine possible futures that could either disrupt our industry or offer tremendous opportunities for growth.

To stay ahead of the game, companies should focus on recognising weak signals in the present – subtle hints of emerging trends – and deciding whether to encourage or discourage these signals to avoid undesirable futures and encourage desirable ones. This process is a constant dance between the push of the present (existing trends) and the pull of the future (visions of the future we want to create).

 

From DSC:
Look out Google, Amazon, and others! Nvidia is putting the pedal to the metal in terms of being innovative and visionary! They are leaving the likes of Apple in the dust.

The top talent out there is likely to go to Nvidia for a while. Engineers, programmers/software architects, network architects, product designers, data specialists, AI researchers, developers of robotics and autonomous vehicles, R&D specialists, computer vision specialists, natural language processing experts, and many more types of positions will be flocking to Nvidia to work for a company that has already changed the world and will likely continue to do so for years to come. 



NVIDIA’s AI Superbowl — from theneurondaily.com by Noah and Grant
PLUS: Prompt tips to make AI writing more natural

That’s despite a flood of new announcements (here’s a 16 min video recap), which included:

  1. A new architecture for massive AI data centers (now called “AI factories”).
  2. A physics engine for robot training built with Disney and DeepMind.
  3. partnership with GM to develop next-gen vehicles, factories and robots.
  4. A new Blackwell chip with “Dynamo” software that makes AI reasoning 40x faster than previous generations.
  5. A new “Rubin” chip slated for 2026 and a “Feynman” chip set for 2028.

For enterprises, NVIDIA unveiled DGX Spark and DGX Station—Jensen’s vision of AI-era computing, bringing NVIDIA’s powerful Blackwell chip directly to your desk.


Nvidia Bets Big on Synthetic Data — from wired.com by Lauren Goode
Nvidia has acquired synthetic data startup Gretel to bolster the AI training data used by the chip maker’s customers and developers.


Nvidia, xAI to Join BlackRock and Microsoft’s $30 Billion AI Infrastructure Fund — from investopedia.com by Aaron McDade
Nvidia and xAI are joining BlackRock and Microsoft in an AI infrastructure group seeking $30 billion in funding. The group was first announced in September as BlackRock and Microsoft sought to fund new data centers to power AI products.



Nvidia CEO Jensen Huang says we’ll soon see 1 million GPU data centers visible from space — from finance.yahoo.com by Daniel Howley
Nvidia CEO Jensen Huang says the company is preparing for 1 million GPU data centers.


Nvidia stock stems losses as GTC leaves Wall Street analysts ‘comfortable with long term AI demand’ — from finance.yahoo.com by Laura Bratton
Nvidia stock reversed direction after a two-day slide that saw shares lose 5% as the AI chipmaker’s annual GTC event failed to excite investors amid a broader market downturn.


Microsoft, Google, and Oracle Deepen Nvidia Partnerships. This Stock Got the Biggest GTC Boost. — from barrons.com by Adam Clark and Elsa Ohlen


The 4 Big Surprises from Nvidia’s ‘Super Bowl of AI’ GTC Keynote — from barrons.com by Tae Kim; behind a paywall

AI Super Bowl. Hi everyone. This week, 20,000 engineers, scientists, industry executives, and yours truly descended upon San Jose, Calif. for Nvidia’s annual GTC developers’ conference, which has been dubbed the “Super Bowl of AI.”


 

Who does need college anymore? About that book title … — from Education Design Lab

As you may know, Lab founder Kathleen deLaski just published a book with a provocative title: Who Needs College Anymore? Imagining a Future Where Degrees Won’t Matter.

Kathleen is asked about the title in every media interview, before and since the Feb. 25 book release. “It has generated a lot of questions,” she said in our recent book chat. “I tell people to focus on the word, ‘who.’ Who needs college anymore? That’s in keeping with the design thinking frame, where you look at the needs of individuals and what needs are not being met.”

In the same conversation, Kathleen reminded us that only 38% of American adults have a four-year degree. “We never talk about the path to the American dream for the rest of folks,” she said. “We currently are not supporting the other really interesting pathways to financial sustainability — apprenticeships, short-term credentials. And that’s really why I wrote the book, to push the conversation around the 62% of who we call New Majority Learners at the Lab, the people for whom college was not designed.” Watch the full clip

She distills the point into one sentence in this SmartBrief essay:  “The new paradigm is a ‘yes and’ paradigm that embraces college and/or other pathways instead of college or bust.”

What can colleges do moving forward?
In this excellent Q&A with Inside Higher Ed, Kathleen shares her No. 1 suggestion: “College needs to be designed as a stepladder approach, where people can come in and out of it as they need, and at the very least, they can build earnings power along the way to help afford a degree program.”

In her Hechinger Report essay, Kathleen lists four more steps colleges can take to meet the demand for more choices, including “affordability must rule.”

From white-collar apprenticeships and micro-credential programs at local community colleges to online bootcamps, self-instruction using YouTube, and more—students are forging alternative paths to GREAT high-paying jobs. (source)

 

Introducing NextGenAI: A consortium to advance research and education with AI — from openai.com; via Claire Zau
OpenAI commits $50M in funding and tools to leading institutions.

Today, we’re launching NextGenAI, a first-of-its-kind consortium with 15 leading research institutions dedicated to using AI to accelerate research breakthroughs and transform education.

AI has the power to drive progress in research and education—but only when people have the right tools to harness it. That’s why OpenAI is committing $50M in research grants, compute funding, and API access to support students, educators, and researchers advancing the frontiers of knowledge.

Uniting institutions across the U.S. and abroad, NextGenAI aims to catalyze progress at a rate faster than any one institution would alone. This initiative is built not only to fuel the next generation of discoveries, but also to prepare the next generation to shape AI’s future.


 ‘I want him to be prepared’: why parents are teaching their gen Alpha kids to use AI — from theguardian.com by Aaron Mok; via Claire Zau
As AI grows increasingly prevalent, some are showing their children tools from ChatGPT to Dall-E to learn and bond

“My goal isn’t to make him a generative AI wizard,” White said. “It’s to give him a foundation for using AI to be creative, build, explore perspectives and enrich his learning.”

White is part of a growing number of parents teaching their young children how to use AI chatbots so they are prepared to deploy the tools responsibly as personal assistants for school, work and daily life when they’re older.

 

Are Entry-Level Jobs Going Away? The Hidden Workforce Shift — from forbes.com by Dr. Diane Hamilton; via Ryan Craig

The problem is that these new roles demand a level of expertise that wasn’t expected from entry-level candidates in the past. Where someone might have previously learned on the job, they are now required to have relevant certifications, AI proficiency, or experience with digital platforms before they even apply.

Some current and emerging job titles that serve as entry points into industries include:

  • Digital marketing associate – This role often involves content creation, social media management, and working with AI-driven analytics tools.
  • Junior AI analyst – Employees in this role assist data science teams by labeling and refining machine learning datasets.
  • Customer success associate – Replacing traditional customer service roles, these professionals help manage AI-enhanced customer support systems.
  • Technical support specialist – While this role still involves troubleshooting software, it now often includes AI-driven diagnostics and automation oversight.
 

6 Characteristics of an Education that Students Want — from gettingsmart.com by IDEA (School of Industrial Design, Engineering and Arts) Students in Tacoma Washington

As current high school students, we want:

  1. Education for the Real World
  2. Personalized and Flexible Education
  3. Cultivating Agency
  4. Creativity and Divergent Thinking
  5. Joyful Learning and Community Building
  6. Empathy and Emotional Growth

Also from gettingsmart.com

Diving into the Evidence: Virtual and Hybrid Models as High-Quality School Choice Options

Key Points

  • The Learning Accelerator is building an evidence base of what high-quality virtual and hybrid learning looks like and how it can be a catalyst for expanding access to powerful learning opportunities.
  • An analysis of 64 high-quality models revealed that virtual and hybrid learning occurs in various contexts, from state-based, fully-virtual programs to individual, hybrid schools and meets the needs of different student populations, including those underserved or disengaged by traditional education systems as well as looking for increased flexibility and course access.
 

5 Legal Tech Trends Set to Impact Law Firms in 2025 — from programminginsider.com by Marc Berman

The legal industry is experiencing swift changes, with technology becoming an ever more crucial factor in its evolution. As law firms respond to shifting client demands and regulatory changes, the pace of change is accelerating. Embracing legal tech is no longer just an advantage; it’s a necessity.

According to a Forbes report, 66% of legal leaders acknowledge this trend and intend to boost their investments in legal tech moving forward. From artificial intelligence streamlining workflows to cloud computing enabling globalized legal services, the legal landscape is undergoing a digital revolution.

In this article, we’ll explore five key legal tech trends that will define how law firms operate in 2025.


GenAI, Legal Ops, and The Future of Law Firms: A Wake-Up Call? — from echlawcrossroads.com by Stephen Embry

A new study from the Blickstein Group reveals some distributing trends for law firms that represent businesses, particularly large ones. The Study is entitled  Legal Service Delivery in the Age of AI. The Study was done jointly by FTI Technologies, a consulting group, and Blickstein. It looks at law department legal operations.

The Findings

GenAI Use by Legal Ops Personnel

The responses reflect a bullish view of what GenAI can do in the legal marketplace but also demonstrate GenAi has a ways to go:

  • Almost 80% of the respondents think that GenAI will become an “essential part of the legal profession.
  • 81% believe GenAi will drive improved efficiencies
  • Despite this belief, only some 30% have plans to purchase GenAI tools. For 81%, the primary reason for obtaining and using GenAI tools is the efficiencies these tools bring.
  • 52% say their GenAI strategy is not as sophisticated as they would like or nonexistent.

The biggest barrier to the use of GenAI among the legal ops professions is cost and security concerns and the lack of skilled personnel available to them.


Voting Is Closed, Results Are In: Here are the 15 Legal Tech Startups Selected for the 2025 Startup Alley at ABA TECHSHOW — from lawnext.com by Bob Ambrogi

Voting has now closed and your votes have been tallied to pick the 15 legal tech startups that will get to participate as finalists in the ninth-annual Startup Alley at ABA TECHSHOW 2025, taking place April 2-5 in Chicago.

These 15 finalists will face off in an opening-night pitch competition that is the opening event of TECHSHOW, with the conference’s attendees voting at the conclusion of the pitches to pick the top winners.


Balancing innovation and ethics: Applying generative AI in legal work — from legal.thomsonreuters.com

Generative artificial intelligence (GenAI) has brought a new wave of opportunities to the legal profession, opening doors to greater efficiency and innovation. Its rapid development has also raised questions about its integration within the legal industry. As legal professionals are presented with more options for adopting new technologies, they now face the important task of understanding how GenAI can be seamlessly — and ethically — incorporated into their daily operations.


Emerging Trends in Court Reporting for 2025: Legal Technology and Advantages for Law Firms — from jdsupra.com

The court reporting industry is evolving rapidly, propelled by technological advancements and the increasing demand for efficiency in the legal sector. For 2025, trends such as artificial intelligence (AI), real-time transcription technologies, and data-driven tools are reshaping how legal professionals work. Here’s an overview of these emerging trends and five reasons law firms should embrace these advancements.


 

Market scan: What’s possible in the current skills validation ecosystem? — from eddesignlab.org
Education Design Lab provides an overview of emerging practices + tools in this 2025 Skills Validation Market Scan.

Employers and opportunity seekers are excited about the possibilities of a skills-based ecosystem, but this new process for codifying a person’s experiences and abilities into skills requires one significant, and missing, piece: Trust. Employers need to trust that the credentials they receive from opportunity seekers are valid representations of their skills. Jobseekers need to trust that their digital credentials are safe, accurate, and will lead to employment and advancement.

Our hypothesis
We posit that the trust needed for the validation of skills to be brought into a meaningful reality is established through a network of skills validation methods and opportunities. We also recognize that the routes through which an individual can demonstrate skills are as varied as the individuals themselves. Therefore, in order to equitably create a skills-based employment ecosystem, the routes by which skills are validated must be held together with common standards and language, but flexible enough to accommodate a multitude of validation practices.

 

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


 

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:


 

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.


 
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