What does ‘age appropriate’ AI literacy look like in higher education? — from timeshighereducation.com by Fun Siong Lim
As AI literacy becomes an essential work skill, universities need to move beyond developing these competencies at ‘primary school’ level in their students. Here, Fun Siong Lim reflects on frameworks to support higher-order AI literacies

Like platforms developed at other universities, Project NALA offers a front-end interface (known as the builder) for faculty to create their own learning assistant. An idea we have is to open the builder up to students to allow them to create their own GenAI assistant as part of our AI literacy curriculum. As they design, configure and test their own assistant, they will learn firsthand how generative AI works. They get to test performance-enhancement approaches beyond prompt engineering, such as grounding the learning assistant with curated materials (retrieval-augmented generation) and advanced ideas such as incorporating knowledge graphs.

They should have the opportunity to analyse, evaluate and create responsible AI solutions. Offering students the opportunity to build their own AI assistants could be a way forward to develop these much-needed skills.


How to Use ChatGPT 4o’s Update to Turn Key Insights Into Clear Infographics (Prompts Included) — from evakeiffenheim.substack.com by Eva Keiffenheim
This 3-step workflow helps you break down books, reports, or slide-decks into professional visuals that accelerate understanding.

This article shows you how to find core ideas, prompt GPT-4o3 for a design brief, and generate clean, professional images that stick. These aren’t vague “creative visuals”—they’re structured for learning, memory, and action.

If you’re a lifelong learner, educator, creator, or just someone who wants to work smarter, this process is for you.

You’ll spend less time re-reading and more time understanding. And maybe—just maybe—you’ll build ideas that not only click in your brain, but also stick in someone else’s.


SchoolAI Secures $25 Million to Help Teachers and Schools Reach Every Student — from globenewswire.com
 The Classroom Experience platform gives every teacher and student their own AI tools for personalized learning

SchoolAI’s Classroom Experience platform combines AI assistants for teachers that help with classroom preparation and other administrative work, and Spaces–personalized AI tutors, games, and lessons that can adapt to each student’s unique learning style and interests. Together, these tools give teachers actionable insights into how students are doing, and how the teacher can deliver targeted support when it matters most.

“Teachers and schools are navigating hard challenges with shrinking budgets, teacher shortages, growing class sizes, and ongoing recovery from pandemic-related learning gaps,” said Caleb Hicks, founder and CEO of SchoolAI. “It’s harder than ever to understand how every student is really doing. Teachers deserve powerful tools to help extend their impact, not add to their workload. This funding helps us double down on connecting the dots for teachers and students, and later this year, bringing school administrators and parents at home onto the platform as well.”


AI in Education, Part 3: Looking Ahead – The Future of AI in Learning — from rdene915.com by Dr. Rachelle Dené Poth

In the first and second parts of my AI series, I focused on where we see AI in classrooms. Benefits range from personalized learning and accessibility tools to AI-driven grading and support of a teaching assistant. In Part 2, I chose to focus on some of the important considerations related to ethics that must be part of the conversation. Schools need to focus on data privacy, bias, overreliance, and the equity divide. I wanted to focus on the future for this last part in the current AI series. Where do we go from here?


Anthropic Education Report: How University Students Use Claude — from anthropic.com

The key findings from our Education Report are:

  • STEM students are early adopters of AI tools like Claude, with Computer Science students particularly overrepresented (accounting for 36.8% of students’ conversations while comprising only 5.4% of U.S. degrees). In contrast, Business, Health, and Humanities students show lower adoption rates relative to their enrollment numbers.
  • We identified four patterns by which students interact with AI, each of which were present in our data at approximately equal rates (each 23-29% of conversations): Direct Problem Solving, Direct Output Creation, Collaborative Problem Solving, and Collaborative Output Creation.
  • Students primarily use AI systems for creating (using information to learn something new) and analyzing (taking apart the known and identifying relationships), such as creating coding projects or analyzing law concepts. This aligns with higher-order cognitive functions on Bloom’s Taxonomy. This raises questions about ensuring students don’t offload critical cognitive tasks to AI systems.

From the Kuali Days 2025 Conference: A CEO’s View of Planning for AI — from campustechnology.com by Mary Grush
A Conversation with Joel Dehlin

How can a company serving higher education navigate the changes AI brings to the ed tech marketplace? What will customers expect in this dynamic? Here, CT talks with Kuali CEO Joel Dehlin, who shared his company’s AI strategies in a featured plenary session, “Sneak Peek of AI in Kuali Build,” at Kuali Days 2025 in Anaheim.


How students can use generative AI — from aliciabankhofer.substack.com by Alicia Bankhofer
Part 4 of 4 in my series on Teaching and Learning in the AI Age

This article is the culmination of a series exploring AI’s impact on education.

Part 1: What Educators Need outlined essential AI literacy skills for teachers, emphasizing the need to move beyond basic ChatGPT exploration to understand the full spectrum of AI tools available in education.

Part 2: What Students Need addressed how students require clear guidance to use AI safely, ethically, and responsibly, with emphasis on developing critical thinking skills alongside AI literacy.

Part 3: How Educators Can Use GenAI presented ten practical use cases for teachers, from creating differentiated resources to designing assessments, demonstrating how AI can reclaim 5-7 hours weekly for meaningful student interactions.

Part 4: How Students Can Use GenAI (this article) provides frameworks for guiding student AI use based on Joscha Falck’s dimensions: learning about, with, through, despite, and without AI.


Mapping a Multidimensional Framework for GenAI in Education — from er.educause.edu by Patricia Turner
Prompting careful dialogue through incisive questions can help chart a course through the ongoing storm of artificial intelligence.

The goal of this framework is to help faculty, educational developers, instructional designers, administrators, and others in higher education engage in productive discussions about the use of GenAI in teaching and learning. As others have noted, theoretical frameworks will need to be accompanied by research and teaching practice, each reinforcing and reshaping the others to create understandings that will inform the development of approaches to GenAI that are both ethical and maximally beneficial, while mitigating potential harms to those who engage with it.


Instructional Design Isn’t Dying — It’s Specialising — from drphilippahardman.substack.com by Dr. Philippa Hardman
Aka, how AI is impacting role & purpose of Instructional Design

Together, these developments have revealed something important: despite widespread anxiety, the instructional design role isn’t dying—it’s specialising.

What we’re witnessing isn’t the automation of instructional design and the death of the instructional designer, but rather the evolution of the ID role into multiple distinct professional pathways.

The generalist “full stack” instructional designer is slowly but decisively fracturing into specialised roles that reflect both the capabilities of generative AI and the strategic imperatives facing modern organisations.

In this week’s blog post, I’ll share what I’ve learned about how our field is transforming, and what it likely means for you and your career path.

Those instructional designers who cling to traditional generalist models risk being replaced, but those who embrace specialisation, data fluency, and AI collaboration will excel and lead the next evolution of the field. Similarly, those businesses that continue to view L&D as a cost centre and focus on automating content delivery will be outperformed, while those that invest in building agile, AI-enabled learning ecosystems will drive measurable performance gains and secure their competitive advantage.


Adding AI to Every Step in Your eLearning Design Workflow — from learningguild.com by George Hanshaw

We know that eLearning is a staple of training and development. The expectations of the learners are higher than ever: They expect a dynamic, interactive, and personalized learning experience. As instructional designers, we are tasked with meeting these expectations by creating engaging and effective learning solutions.

The integration of Artificial Intelligence (AI) into our eLearning design process is a game-changer that can significantly enhance the quality and efficiency of our work.

No matter if you use ADDIE or rapid prototyping, AI has a fit in every aspect of your workflow. By integrating AI, you can ensure a more efficient and effective design process that adapts to the unique needs of your learners. This not only saves time and resources but also significantly enhances the overall learning experience. We will explore the needs analysis and the general design process.

 

Organizing Teams for Continuous Learning: A Complete Guide — from intelligenthq.com

In today’s fast-paced business world, continuous learning has become a vital element for both individual and organizational growth. Teams that foster a culture of learning remain adaptable, innovative, and competitive. However, simply encouraging learning isn’t enough; the way teams are structured and supported plays a huge role in achieving long-term success. In this guide, we’ll explore how to effectively organize teams for continuous learning, leveraging tools, strategies, and best practices.

 

From DSC:
After seeing Sam’s posting below, I can’t help but wonder:

  • How might the memory of an AI over time impact the ability to offer much more personalized learning?
  • How will that kind of memory positively impact a person’s learning-related profile?
  • Which learning-related agents get called upon?
  • Which learning-related preferences does a person have while learning about something new?
  • Which methods have worked best in the past for that individual? Which methods didn’t work so well with him or her?



 

Do I Need a Degree in Instructional Design? It Depends. — from teamedforlearning.com

It’s a common question for those considering a career in instructional design: Do I need a degree to land a job? The answer? It depends.

Hiring managers aren’t just looking for a degree—they want proof that you have the knowledge, skills, and abilities to succeed. In fact, most employers focus on 3 key factors when assessing candidates. You typically need at least 2 of these to be considered:

  1. A Credential – A degree or certification in instructional design, learning experience design, or a related field.
  2. Relevant Work Experience – Hands-on experience designing and developing learning solutions.
  3. Proof of Abilities – A strong portfolio showcasing eLearning modules, course designs, or learning strategies.

The good news? You don’t have to spend years earning a degree to break into the field. If you’re resourceful, you can fast-track your way in through volunteer projects, contract work, and portfolio building.

Whether you’re a recent graduate, a career changer, or a working professional looking for your next opportunity, focusing on these key factors can help you stand out and get hired.

 

The 2025 AI Index Report — from Stanford University’s Human-Centered Artificial Intelligence Lab (hai.stanford.edu); item via The Neuron

Top Takeaways

  1. AI performance on demanding benchmarks continues to improve.
  2. AI is increasingly embedded in everyday life.
  3. Business is all in on AI, fueling record investment and usage, as research continues to show strong productivity impacts.
  4. The U.S. still leads in producing top AI models—but China is closing the performance gap.
  5. The responsible AI ecosystem evolves—unevenly.
  6. Global AI optimism is rising—but deep regional divides remain.
  7. …and several more

Also see:

The Neuron’s take on this:

So, what should you do? You really need to start trying out these AI tools. They’re getting cheaper and better, and they can genuinely help save time or make work easier—ignoring them is like ignoring smartphones ten years ago.

Just keep two big things in mind:

  1. Making the next super-smart AI costs a crazy amount of money and uses tons of power (seriously, they’re buying nuclear plants and pushing coal again!).
  2. Companies are still figuring out how to make AI perfectly safe and fair—cause it still makes mistakes.

So, use the tools, find what helps you, but don’t trust them completely.

We’re building this plane mid-flight, and Stanford’s report card is just another confirmation that we desperately need better safety checks before we hit major turbulence.


Addendum on 4/16:

 

Uplimit raises stakes in corporate learning with suite of AI agents that can train thousands of employees simultaneously — from venturebeat.com by Michael Nuñez|

Uplimit unveiled a suite of AI-powered learning agents today designed to help companies rapidly upskill employees while dramatically reducing administrative burdens traditionally associated with corporate training.

The San Francisco-based company announced three sets of purpose-built AI agents that promise to change how enterprises approach learning and development: skill-building agents, program management agents, and teaching assistant agents. The technology aims to address the growing skills gap as AI advances faster than most workforces can adapt.

“There is an unprecedented need for continuous learning—at a scale and speed traditional systems were never built to handle,” said Julia Stiglitz, CEO and co-founder of Uplimit, in an interview with VentureBeat. “The companies best positioned to thrive aren’t choosing between AI and their people—they’re investing in both.”


Introducing Claude for Education — from anthropic.com

Today we’re launching Claude for Education, a specialized version of Claude tailored for higher education institutions. This initiative equips universities to develop and implement AI-enabled approaches across teaching, learning, and administration—ensuring educators and students play a key role in actively shaping AI’s role in society.

As part of announcing Claude for Education, we’re introducing:

  1. Learning mode: A new Claude experience that guides students’ reasoning process rather than providing answers, helping develop critical thinking skills
  2. University-wide Claude availability: Full campus access agreements with Northeastern University, London School of Economics and Political Science (LSE), and Champlain College, making Claude available to all students
  3. Academic partnerships: Joining Internet2 and working with Instructure to embed AI into teaching & learning with Canvas LMS
  4. Student programs: A new Claude Campus Ambassadors program along with an initiative offering API credits for student projects

A comment on this from The Rundown AI:

Why it matters: Education continues to grapple with AI, but Anthropic is flipping the script by making the tech a partner in developing critical thinking rather than an answer engine. While the controversy over its use likely isn’t going away, this generation of students will have access to the most personalized, high-quality learning tools ever.


Should College Graduates Be AI Literate? — from chronicle.com by Beth McMurtrie (behind a paywall)
More institutions are saying yes. Persuading professors is only the first barrier they face.

Last fall one of Jacqueline Fajardo’s students came to her office, eager to tell her about an AI tool that was helping him learn general chemistry. Had she heard of Google NotebookLM? He had been using it for half a semester in her honors course. He confidently showed her how he could type in the learning outcomes she posted for each class and the tool would produce explanations and study guides. It even created a podcast based on an academic paper he had uploaded. He did not feel it was important to take detailed notes in class because the AI tool was able to summarize the key points of her lectures.


Showing Up for the Future: Why Educators Can’t Sit Out the AI Conversation — from marcwatkins.substack.com with a guest post from Lew Ludwig

The Risk of Disengagement
Let’s be honest: most of us aren’t jumping headfirst into AI. At many of our institutions, it’s not a gold rush—it’s a quiet standoff. But the group I worry most about isn’t the early adopters. It’s the faculty who’ve decided to opt out altogether.

That choice often comes from a place of care. Concerns about data privacy, climate impact, exploitative labor, and the ethics of using large language models are real—and important. But choosing not to engage at all, even on ethical grounds, doesn’t remove us from the system. It just removes our voices from the conversation.

And without those voices, we risk letting others—those with very different priorities—make the decisions that shape what AI looks like in our classrooms, on our campuses, and in our broader culture of learning.



Turbocharge Your Professional Development with AI — from learningguild.com by Dr. RK Prasad

You’ve just mastered a few new eLearning authoring tools, and now AI is knocking on the door, offering to do your job faster, smarter, and without needing coffee breaks. Should you be worried? Or excited?

If you’re a Learning and Development (L&D) professional today, AI is more than just a buzzword—it’s transforming the way we design, deliver, and measure corporate training. But here’s the good news: AI isn’t here to replace you. It’s here to make you better at what you do.

The challenge is to harness its potential to build digital-ready talent, not just within your organization but within yourself.

Let’s explore how AI is reshaping L&D strategies and how you can leverage it for professional development.


5 Recent AI Notables — from automatedteach.com by Graham Clay

1. OpenAI’s New Image Generator
What Happened: OpenAI integrated a much more powerful image generator directly into GPT-4o, making it the default image creator in ChatGPT. Unlike previous image models, this one excels at accurately rendering text in images, precise visualization of diagrams/charts, and multi-turn image refinement through conversation.

Why It’s Big: For educators, this represents a significant advancement in creating educational visuals, infographics, diagrams, and other instructional materials with unprecedented accuracy and control. It’s not perfect, but you can now quickly generate custom illustrations that accurately display mathematical equations, chemical formulas, or process workflows — previously a significant hurdle in digital content creation — without requiring graphic design expertise or expensive software. This capability dramatically reduces the time between conceptualizing a visual aid and implementing it in course materials.
.


The 4 AI modes that will supercharge your workflow — from aiwithallie.beehiiv.com by Allie K. Miller
The framework most people and companies won’t discover until 2026


 

Investigating Informal Learning with Technology — from learningguild.com by Katie Belle (Curry) Nelson

Informal learning is having a moment right now, and it’s about time.

As learning professionals, we can often get caught up in designing, developing, and implementing formal learning experiences, which can cause informal learning to fall to the wayside and easily be overlooked. However, informal learning experiences can have major, long-term effects on learning and business outcomes, so finding creative ways to track them can be valuable for L&D departments.

Start small
These three methods are small steps to understanding the informal learning environment and its impact on your organization. The assuring thing about informal learning is that you can start small and incorporate more methods later because formal learning is always taking place. Start with one area and begin to explore what you can find out the content your learners want to know more about, how they are learning about things, and how others in the organization are solving problems.

 




Students and folks looking for work may want to check out:

Also relevant/see:


 

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).

 
 

Blind Spot on AI — from the-job.beehiiv.com by Paul Fain
Office tasks are being automated now, but nobody has answers on how education and worker upskilling should change.

Students and workers will need help adjusting to a labor market that appears to be on the verge of a historic disruption as many business processes are automated. Yet job projections and policy ideas are sorely lacking.

The benefits of agentic AI are already clear for a wide range of organizations, including small nonprofits like CareerVillage. But the ability to automate a broad range of business processes means that education programs and skills training for knowledge workers will need to change. And as Chung writes in a must-read essay, we have a blind spot with predicting the impacts of agentic AI on the labor market.

“Without robust projections,” he writes, “policymakers, businesses, and educators won’t be able to come to terms with how rapidly we need to start this upskilling.”

 

Drive Continuous Learning: AI Integrates Work & Training — from learningguild.com by George Hanshaw

Imagine with me for a moment: Training is no longer confined to scheduled sessions in a classroom, an online module or even a microlearning you click to activate during your workflow. Imagine training being delivered because the system senses what you are doing and provides instructions and job aids without you having to take an action.

The rapid evolution of artificial intelligence (AI) and wearable technology has made it easier than ever to seamlessly integrate learning directly into the workflow. Smart glasses, earpieces, and other advanced devices are redefining how employees gain knowledge and skills by delivering microlearning moments precisely when and where they are needed.

AI plays a crucial role in this transformation by sensing the optimal moment to deliver the training through augmented reality (AR).



These Schools Are Banding Together to Make Better Use of AI in Education — from edsurge.com by Emily Tate Sullivan

Kennelly and Geraffo are part of a small team at their school in Denver, DSST: College View High School, that is participating in the School Teams AI Collaborative, a year-long pilot initiative in which more than 80 educators from 19 traditional public and charter schools across the country are experimenting with and evaluating AI-enabled instruction to improve teaching and learning.

The goal is for some of AI’s earliest adopters in education to band together, share ideas and eventually help lead the way on what they and their colleagues around the U.S. could do with the emerging technology.

“Pretty early on we thought it was going to be a massive failure,” says Kennelly of last semester’s project. “But it became a huge hit. Students loved it. They were like, ‘I ran to second period to build this thing.’”



Transactional vs. Conversational Visions of Generative AI in Teaching — from elmartinsen.substack.com by Eric Lars Martinsen
AI as a Printer, or AI as a Thought Partner

As writing instructors, we have a choice in how we frame AI for our students. I invite you to:

  1. Experiment with AI as a conversation partner yourself before introducing it to students
  2. Design assignments that leverage AI’s strengths as a thought partner rather than trying to “AI-proof” your existing assignments
  3. Explicitly teach students how to engage in productive dialogue with AI—how to ask good questions, challenge AI’s assumptions, and use it to refine rather than replace their thinking
  4. Share your experiences, both positive and negative, with colleagues to build our collective understanding of effective AI integration

 

Learning as a Learning Professional: Unlock Hidden Opportunities — from learningguild.com by Will Thalheimer

As learning professionals, we help others grow—but how well are we developing ourselves? And does it really matter? Absolutely! In this article, I’ll explore why mastering the art of learning is crucial for our success and share strategies that go beyond traditional professional development.

Why learning matters for us
We need to be strong learners because our work demands broad expertise. We must understand the learning sciences, instructional design, project management, technology, evaluation, organizational dynamics, and business strategy. We also need to navigate a sea of learning frameworks, approaches, and models.


Also from learningguild.com, see:

Microlearning: The Key to Capturing Modern Learners’ Attention — by Sergiy Movchan

This shift in how we consume and process information is challenging traditional learning methods, which are finding it increasingly difficult to keep learners’ attention.

Microlearning is a bridge to the attention of today’s learners, delivering complex topics in short, manageable pieces. Whether it’s a five-minute video, a quick quiz, or a short lesson, microlearning makes it easier for students to stay engaged. Microlearning often holds learners’ attention better and for longer compared to standard learning methods.

Typical low completion rates clearly show the need for innovative approaches to content delivery and student engagement. Microlearning offers the answer to this need.

Cultivating Creativity as an L&D Professional — by Katie Belle (Curry) Nelson

Instructional designers and learning professionals are creative by nature. We are called upon to be creative with technology like Articulate, Camtasia, or Captivate. More often than we would like, organizations, red tape, and clients require us to be creative with timelines and budgets. Being creative is a core qualification and requirement of our work. So, what do we do when we feel like the creative river has run to a trickle or dried up entirely?

 

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.

 
© 2025 | Daniel Christian