Making AI Work: Leadership, Lab, and Crowd — from oneusefulthing.org by Ethan Mollick
A formula for AI in companies

How do we reconcile the first three points with the final one? The answer is that AI use that boosts individual performance does not naturally translate to improving organizational performance. To get organizational gains requires organizational innovation, rethinking incentives, processes, and even the nature of work. But the muscles for organizational innovation inside companies have atrophied. For decades, companies have outsourced this to consultants or enterprise software vendors who develop generalized approaches that address the issues of many companies at once. That won’t work here, at least for a while. Nobody has special information about how to best use AI at your company, or a playbook for how to integrate it into your organization.
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Galileo Learn™ – A Revolutionary Approach To Corporate Learning — from joshbersin.com

Today we are excited to launch Galileo Learn™, a revolutionary new platform for corporate learning and professional development.

How do we leverage AI to revolutionize this model, doing away with the dated “publishing” model of training?

The answer is Galileo Learn, a radically new and different approach to corporate training and professional development.

What Exactly is Galileo Learn™?
Galileo Learn is an AI-native learning platform which is tightly integrated into the Galileo agent. It takes content in any form (PDF, word, audio, video, SCORM courses, and more) and automatically (with your guidance) builds courses, assessments, learning programs, polls, exercises, simulations, and a variety of other instructional formats.


Designing an Ecosystem of Resources to Foster AI Literacy With Duri Long — from aialoe.org

Centering Public Understanding in AI Education
In a recent talk titled “Designing an Ecosystem of Resources to Foster AI Literacy,” Duri Long, Assistant Professor at Northwestern University, highlighted the growing need for accessible, engaging learning experiences that empower the public to make informed decisions about artificial intelligence. Long emphasized that as AI technologies increasingly influence everyday life, fostering public understanding is not just beneficial—it’s essential. Her work seeks to develop a framework for AI literacy across varying audiences, from middle school students to adult learners and journalists.

A Design-Driven, Multi-Context Approach
Drawing from design research, cognitive science, and the learning sciences, Long presented a range of educational tools aimed at demystifying AI. Her team has created hands-on museum exhibits, such as Data Bites, where learners build physical datasets to explore how computers learn. These interactive experiences, along with web-based tools and support resources, are part of a broader initiative to bridge AI knowledge gaps using the 4As framework: Ask, Adapt, Author, and Analyze. Central to her approach is the belief that familiar, tangible interactions and interfaces reduce intimidation and promote deeper engagement with complex AI concepts.

 

‘What I learned when students walked out of my AI class’ — from timeshighereducation.com by Chris Hogg
Chris Hogg found the question of using AI to create art troubled his students deeply. Here’s how the moment led to deeper understanding for both student and educator

Teaching AI can be as thrilling as it is challenging. This became clear one day when three students walked out of my class, visibly upset. They later explained their frustration: after spending years learning their creative skills, they were disheartened to see AI effortlessly outperform them at the blink of an eye.

This moment stuck with me – not because it was unexpected, but because it encapsulates the paradoxical relationship we all seem to have with AI. As both an educator and a creative, I find myself asking: how do we engage with this powerful tool without losing ourselves in the process? This is the story of how I turned moments of resistance into opportunities for deeper understanding.


In the AI era, how do we battle cognitive laziness in students? — from timeshighereducation.com by Sean McMinn
With the latest AI technology now able to handle complex problem-solving processes, will students risk losing their own cognitive engagement? Metacognitive scaffolding could be the answer, writes Sean McMinn

The concern about cognitive laziness seems to be backed by Anthropic’s report that students use AI tools like Claude primarily for creating (39.8 per cent) and analysing (30.2 per cent) tasks, both considered higher-order cognitive functions according to Bloom’s Taxonomy. While these tasks align well with advanced educational objectives, they also pose a risk: students may increasingly delegate critical thinking and complex cognitive processes directly to AI, risking a reduction in their own cognitive engagement and skill development.


Make Instructional Design Fun Again with AI Agents — from drphilippahardman.substack.com by Dr. Philippa Hardman
A special edition practical guide to selecting & building AI agents for instructional design and L&D

Exactly how we do this has been less clear, but — fuelled by the rise of so-called “Agentic AI” — more and more instructional designers ask me: “What exactly can I delegate to AI agents, and how do I start?”

In this week’s post, I share my thoughts on exactly what instructional design tasks can be delegated to AI agents, and provide a step-by-step approach to building and testing your first AI agent.

Here’s a sneak peak….


AI Personality Matters: Why Claude Doesn’t Give Unsolicited Advice (And Why You Should Care) — from mikekentz.substack.com by Mike Kentz
First in a four-part series exploring the subtle yet profound differences between AI systems and their impact on human cognition

After providing Claude with several prompts of context about my creative writing project, I requested feedback on one of my novel chapters. The AI provided thoughtful analysis with pros and cons, as expected. But then I noticed what wasn’t there: the customary offer to rewrite my chapter.

Without Claude’s prompting, I found myself in an unexpected moment of metacognition. When faced with improvement suggestions but no offer to implement them, I had to consciously ask myself: “Do I actually want AI to rewrite this section?” The answer surprised me – no, I wanted to revise it myself, incorporating the insights while maintaining my voice and process.

The contrast was striking. With ChatGPT, accepting its offer to rewrite felt like a passive, almost innocent act – as if I were just saying “yes” to a helpful assistant. But with Claude, requesting a rewrite required deliberate action. Typing out the request felt like a more conscious surrender of creative agency.


Also re: metacognition and AI, see:

In the AI era, how do we battle cognitive laziness in students? — from timeshighereducation.com by Sean McMinn
With the latest AI technology now able to handle complex problem-solving processes, will students risk losing their own cognitive engagement? Metacognitive scaffolding could be the answer, writes Sean McMinn

The concern about cognitive laziness seems to be backed by Anthropic’s report that students use AI tools like Claude primarily for creating (39.8 per cent) and analysing (30.2 per cent) tasks, both considered higher-order cognitive functions according to Bloom’s Taxonomy. While these tasks align well with advanced educational objectives, they also pose a risk: students may increasingly delegate critical thinking and complex cognitive processes directly to AI, risking a reduction in their own cognitive engagement and skill development.

By prompting students to articulate their cognitive processes, such tools reinforce the internalisation of self-regulated learning strategies essential for navigating AI-augmented environments.


EDUCAUSE Panel Highlights Practical Uses for AI in Higher Ed — from govtech.com by Abby Sourwine
A webinar this week featuring panelists from the education, private and nonprofit sectors attested to how institutions are applying generative artificial intelligence to advising, admissions, research and IT.

Many higher education leaders have expressed hope about the potential of artificial intelligence but uncertainty about where to implement it safely and effectively. According to a webinar Tuesday hosted by EDUCAUSE, “Unlocking AI’s Potential in Higher Education,” their answer may be “almost everywhere.”

Panelists at the event, including Kaskaskia College CIO George Kriss, Canyon GBS founder and CEO Joe Licata and Austin Laird, a senior program officer at the Gates Foundation, said generative AI can help colleges and universities meet increasing demands for personalization, timely communication and human-to-human connections throughout an institution, from advising to research to IT support.


Partly Cloudy with a Chance of Chatbots — from derekbruff.org by Derek Bruff

Here are the predictions, our votes, and some commentary:

  • “By 2028, at least half of large universities will embed an AI ‘copilot’ inside their LMS that can draft content, quizzes, and rubrics on demand.” The group leaned toward yes on this one, in part because it was easy to see LMS vendors building this feature in as a default.
  • “Discipline-specific ‘digital tutors’ (LLM chatbots trained on course materials) will handle at least 30% of routine student questions in gateway courses.” We learned toward yes on this one, too, which is why some of us are exploring these tools today. We would like to be ready how to use them well (or avoid their use) when they are commonly available.
  • “Adaptive e-texts whose examples, difficulty, and media personalize in real time via AI will outsell static digital textbooks in the U.S. market.” We leaned toward no on this one, in part because the textbook market and what students want from textbooks has historically been slow to change. I remember offering my students a digital version of my statistics textbook maybe 6-7 years ago, and most students opted to print the whole thing out on paper like it was 1983.
  • “AI text detectors will be largely abandoned as unreliable, shifting assessment design toward oral, studio, or project-based ‘AI-resilient’ tasks.” We leaned toward yes on this. I have some concerns about oral assessments (they certainly privilege some students over others), but more authentic assignments seems like what higher ed needs in the face of AI. Ted Underwood recently suggested a version of this: “projects that attempt genuinely new things, which remain hard even with AI assistance.” See his post and the replies for some good discussion on this idea.
  • “AI will produce multimodal accessibility layers (live translation, alt-text, sign-language avatars) for most lecture videos without human editing.” We leaned toward yes on this one, too. This seems like another case where something will be provided by default, although my podcast transcripts are AI-generated and still need editing from me, so we’re not there quite yet.

‘We Have to Really Rethink the Purpose of Education’
The Ezra Klein Show

Description: I honestly don’t know how I should be educating my kids. A.I. has raised a lot of questions for schools. Teachers have had to adapt to the most ingenious cheating technology ever devised. But for me, the deeper question is: What should schools be teaching at all? A.I. is going to make the future look very different. How do you prepare kids for a world you can’t predict?

And if we can offload more and more tasks to generative A.I., what’s left for the human mind to do?

Rebecca Winthrop is the director of the Center for Universal Education at the Brookings Institution. She is also an author, with Jenny Anderson, of “The Disengaged Teen: Helping Kids Learn Better, Feel Better, and Live Better.” We discuss how A.I. is transforming what it means to work and be educated, and how our use of A.I. could revive — or undermine — American schools.


 

Sleep No More: Live experiential learning that’s more like an escape room than a classroom — from chieflearningofficer.com by Clare S. Dygert
The time for passive learning is over. Your learners are ready for experiences that resonate, challenge and transform, and they’re looking to you to provide them.

Live experiential learning: ILT as usual?
Is live experiential learning, or LEL, just a surface rebranding of traditional instructor-led training?

Absolutely not. In fact, LEL is as distant from traditional ILT as Sleep No More is from traditional theater.

Instead of sitting politely, nodding along — or nodding off — as an instructor carefully reads aloud from their slide deck, learners roam about, get their hands dirty and focus on the things that matter to them (yes, even if that means they don’t get to every topic or encounter them in the way we would have liked).

In short, LEL has the ability to shake up your learners, in a good way. And when they realize that this isn’t learning as usual, they land in a mental space that makes them more curious and receptive.

So what does this look like, really? And how does it work?


Improving team performance with collaborative problem-solving — from chieflearningofficer.com by
Exercises for improving the way your team communicates, trusts each other, solves problems and makes decisions.

As learning and development leaders, you can create fun, engaging and challenging exercises for teams that develop these important characteristics and improve numerous markers of team efficacy. Exercises to improve team performance should be focused on four themes: negotiation, agreement, coordination and output. In this article, I’ll discuss each type of exercise briefly, then how I use a framework to create challenging and engaging exercises to improve collaborative problem-solving and performance on my teams.


Microlearning Secrets from Marketers: How to Make Learning Stick — from learningguild.com by Danielle Wallace

Marketers have spent billions of dollars testing what works—and their insights can revolutionize microlearning. By borrowing from marketing’s best strategies, L&D professionals can create microlearning that cuts through the noise, engages learners, and drives real behavior change.

If marketing can make people remember a product, L&D can make people remember a skill.

 

“Student Guide to AI”; “AI Isn’t Just Changing How We Work — It’s Changing How We Learn”; + other items re: AI in our LE’s

.Get the 2025 Student Guide to Artificial Intelligence — from studentguidetoai.org
This guide is made available under a Creative Commons license by Elon University and the American Association of Colleges and Universities (AAC&U).
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AI Isn’t Just Changing How We Work — It’s Changing How We Learn — from entrepreneur.com by Aytekin Tank; edited by Kara McIntyre
AI agents are opening doors to education that just a few years ago would have been unthinkable. Here’s how.

Agentic AI is taking these already huge strides even further. Rather than simply asking a question and receiving an answer, an AI agent can assess your current level of understanding and tailor a reply to help you learn. They can also help you come up with a timetable and personalized lesson plan to make you feel as though you have a one-on-one instructor walking you through the process. If your goal is to learn to speak a new language, for example, an agent might map out a plan starting with basic vocabulary and pronunciation exercises, then progress to simple conversations, grammar rules and finally, real-world listening and speaking practice.

For instance, if you’re an entrepreneur looking to sharpen your leadership skills, an AI agent might suggest a mix of foundational books, insightful TED Talks and case studies on high-performing executives. If you’re aiming to master data analysis, it might point you toward hands-on coding exercises, interactive tutorials and real-world datasets to practice with.

The beauty of AI-driven learning is that it’s adaptive. As you gain proficiency, your AI coach can shift its recommendations, challenge you with new concepts and even simulate real-world scenarios to deepen your understanding.

Ironically, the very technology feared by workers can also be leveraged to help them. Rather than requiring expensive external training programs or lengthy in-person workshops, AI agents can deliver personalized, on-demand learning paths tailored to each employee’s role, skill level, and career aspirations. Given that 68% of employees find today’s workplace training to be overly “one-size-fits-all,” an AI-driven approach will not only cut costs and save time but will be more effective.


What’s the Future for AI-Free Spaces? — from higherai.substack.com by Jason Gulya
Please let me dream…

This is one reason why I don’t see AI-embedded classrooms and AI-free classrooms as opposite poles. The bone of contention, here, is not whether we can cultivate AI-free moments in the classroom, but for how long those moments are actually sustainable.

Can we sustain those AI-free moments for an hour? A class session? Longer?

Here’s what I think will happen. As AI becomes embedded in society at large, the sustainability of imposed AI-free learning spaces will get tested. Hard. I think it’ll become more and more difficult (though maybe not impossible) to impose AI-free learning spaces on students.

However, consensual and hybrid AI-free learning spaces will continue to have a lot of value. I can imagine classes where students opt into an AI-free space. Or they’ll even create and maintain those spaces.


Duolingo’s AI Revolution — from drphilippahardman.substack.com by Dr. Philippa Hardman
What 148 AI-Generated Courses Tell Us About the Future of Instructional Design & Human Learning

Last week, Duolingo announced an unprecedented expansion: 148 new language courses created using generative AI, effectively doubling their content library in just one year. This represents a seismic shift in how learning content is created — a process that previously took the company 12 years for their first 100 courses.

As CEO Luis von Ahn stated in the announcement, “This is a great example of how generative AI can directly benefit our learners… allowing us to scale at unprecedented speed and quality.”

In this week’s blog, I’ll dissect exactly how Duolingo has reimagined instructional design through AI, what this means for the learner experience, and most importantly, what it tells us about the future of our profession.


Are Mixed Reality AI Agents the Future of Medical Education? — from ehealth.eletsonline.com

Medical education is experiencing a quiet revolution—one that’s not taking place in lecture theatres or textbooks, but with headsets and holograms. At the heart of this revolution are Mixed Reality (MR) AI Agents, a new generation of devices that combine the immersive depth of mixed reality with the flexibility of artificial intelligence. These technologies are not mere flashy gadgets; they’re revolutionising the way medical students interact with complicated content, rehearse clinical skills, and prepare for real-world situations. By combining digital simulations with the physical world, MR AI Agents are redefining what it means to learn medicine in the 21st century.




4 Reasons To Use Claude AI to Teach — from techlearning.com by Erik Ofgang
Features that make Claude AI appealing to educators include a focus on privacy and conversational style.

After experimenting using Claude AI on various teaching exercises, from generating quizzes to tutoring and offering writing suggestions, I found that it’s not perfect, but I think it behaves favorably compared to other AI tools in general, with an easy-to-use interface and some unique features that make it particularly suited for use in education.

 

Micro-Credentials Impact Report — from coursera.org
Get exclusive insights on how industry-aligned micro- credentials are bridging skill gaps, driving career outcomes, and building a future-ready workforce—with data from 2,000+ students and employers across six regions.

See how micro-credentials are driving student success, meeting industry demand, and transforming higher education institutions. Deliver industry-aligned learning with confidence—whether you’re leading a university or designing workforce development programs.

Our data shows that 90% of employers are willing to offer higher starting salaries to those with micro-credentials. Most offer 10–15% more for credit-bearing vs. non-credit credentials—even higher for GenAI. Help your graduates earn more by integrating micro-credentials into your programs.

Students are 2x as likely to choose programs with micro-credentials—even more if credentials are credit-bearing, the report finds. Higher education leaders echo this trend, with 7 in 10 saying students are more likely to enroll in programs that offer micro-credentials for academic credit.

 

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.
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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:

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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).

 
 
© 2025 | Daniel Christian