The 2025 Global Skills Report — from coursera.org
Discover in-demand skills and credentials trends across 100+ countries and six regions to deliver impactful industry-aligned learning programs.

Access trusted insights on:

  • [NEW] Countries leading AI innovation in our AI Maturity Index
  • Skill proficiency rankings for 100+ countries in business, data, and technology
  • How people are building essential skills with micro-credentials
  • Enrollment trends in cybersecurity, critical thinking, and human skills
  • Women’s learning trends in GenAI, STEM, and Professional Certificates

AI Agents Are Rewriting The Playbook For Upskilling In 2025 — from forbes.com by Aytekin Tank

Staying competitive now depends on fast, effective training and upskilling—not just for business owners themselves, but for their teams, new and existing employees alike. AI agents are poised to change the corporate training landscape, helping businesses close skills gaps created by rapid technological change.

Traditional corporate training programs, which lean on passive content, often fall short of their goals. Companies like Uplimit are rolling out educational AI agents that promise significantly higher completion rates (upwards of 90 percent) and better results. It boils down to engagement—the active learning, with role playing and personalized feedback, is more stimulating than merely watching a video and completing a quiz. Agents can provide 24/7 assistance, responding to questions as soon as they pop up. What’s more, education and training with agents can be highly personalized.

Agents can train a higher volume of employees in the same amount of time. Employees will gain skills more efficiently, giving them more time to apply what they’ve learned—and likely boosting engagement in the process. They’ll be better prepared to stay competitive.

 

Navigating Career Transitions — from er.educause.edu by Jay James, Mike Richichi, Sarah Buszka, and Wes Johnson

In this episode, we hear from professionals at different stages of their career journeys as they reflect on risk, resilience, and growth. They share advice on stepping into leadership roles, recognizing when it may be time for a change, and overcoming imposter syndrome.

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Mary Meeker AI Trends Report: Mind-Boggling Numbers Paint AI’s Massive Growth Picture — from ndtvprofit.com
Numbers that prove AI as a tech is unlike any other the world has ever seen.

Here are some incredibly powerful numbers from Mary Meeker’s AI Trends report, which showcase how artificial intelligence as a tech is unlike any other the world has ever seen.

  • AI took only three years to reach 50% user adoption in the US; mobile internet took six years, desktop internet took 12 years, while PCs took 20 years.
  • ChatGPT reached 800 million users in 17 months and 100 million in only two months, vis-à-vis Netflix’s 100 million (10 years), Instagram (2.5 years) and TikTok (nine months).
  • ChatGPT hit 365 billion annual searches in two years (2024) vs. Google’s 11 years (2009)—ChatGPT 5.5x faster than Google.

Above via Mary Meeker’s AI Trend-Analysis — from getsuperintel.com by Kim “Chubby” Isenberg
How AI’s rapid rise, efficiency race, and talent shifts are reshaping the future.

The TLDR
Mary Meeker’s new AI trends report highlights an explosive rise in global AI usage, surging model efficiency, and mounting pressure on infrastructure and talent. The shift is clear: AI is no longer experimental—it’s becoming foundational, and those who optimize for speed, scale, and specialization will lead the next wave of innovation.

 

Also see Meeker’s actual report at:

Trends – Artificial Intelligence — from bondcap.com by Mary Meeker / Jay Simons / Daegwon Chae / Alexander Krey



The Rundown: Meta aims to release tools that eliminate humans from the advertising process by 2026, according to a report from the WSJ — developing an AI that can create ads for Facebook and Instagram using just a product image and budget.

The details:

  • Companies would submit product images and budgets, letting AI craft the text and visuals, select target audiences, and manage campaign placement.
  • The system will be able to create personalized ads that can adapt in real-time, like a car spot featuring mountains vs. an urban street based on user location.
  • The push would target smaller companies lacking dedicated marketing staff, promising professional-grade advertising without agency fees or skillset.
  • Advertising is a core part of Mark Zuckerberg’s AI strategy and already accounts for 97% of Meta’s annual revenue.

Why it matters: We’re already seeing AI transform advertising through image, video, and text, but Zuck’s vision takes the process entirely out of human hands. With so much marketing flowing through FB and IG, a successful system would be a major disruptor — particularly for small brands that just want results without the hassle.

 

So much for saving the planet. Climate careers, and many others, evaporate for class of 2025 — from hechingerreport.org by Lawrence Lanahan
The Trump administration is disrupting career paths for new graduates hoping to work in climate and sustainability, international aid, public service and the sciences

As the class of 2025 enters the workforce, the Trump administration has dismantled career pathways for graduates interested in climate and sustainability work, international aid, public service and research across the natural, behavioral and social sciences. Federal jobs are disappearing, and the administration is eliminating grants and agency divisions that sustain university research programs and nonprofits that are crucial to launching careers.

The National Science Foundation, for example, halved graduate research fellowships, canceled some undergraduate research grants, stopped awarding new grants, froze funding for existing ones, and eliminated several hundred grants for focusing on diversity, equity and inclusion. In March, Robert F. Kennedy Jr. announced 10,000 layoffs at his agency, the Department of Health and Human Services; earlier buyouts and firings had already cut another 10,000 jobs.

 

“The AI-enhanced learning ecosystem” [Jennings] + other items re: AI in our learning ecosystems

The AI-enhanced learning ecosystem: A case study in collaborative innovation — from chieflearningofficer.com by Kevin Jennings
How artificial intelligence can serve as a tool and collaborative partner in reimagining content development and management.

Learning and development professionals face unprecedented challenges in today’s rapidly evolving business landscape. According to LinkedIn’s 2025 Workplace Learning Report, 67 percent of L&D professionals report being “maxed out” on capacity, while 66 percent have experienced budget reductions in the past year.

Despite these constraints, 87 percent agree their organizations need to develop employees faster to keep pace with business demands. These statistics paint a clear picture of the pressure L&D teams face: do more, with less, faster.

This article explores how one L&D leader’s strategic partnership with artificial intelligence transformed these persistent challenges into opportunities, creating a responsive learning ecosystem that addresses the modern demands of rapid product evolution and diverse audience needs. With 71 percent of L&D professionals now identifying AI as a high or very high priority for their learning strategy, this case study demonstrates how AI can serve not merely as a tool but as a collaborative partner in reimagining content development and management.
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How we use GenAI and AR to improve students’ design skills — from timeshighereducation.com by Antonio Juarez, Lesly Pliego and Jordi Rábago who are professors of architecture at Monterrey Institute of Technology in Mexico; Tomas Pachajoa is a professor of architecture at the El Bosque University in Colombia; & Carlos Hinrichsen and Marietta Castro are educators at San Sebastián University in Chile.
Guidance on using generative AI and augmented reality to enhance student creativity, spatial awareness and interdisciplinary collaboration

Blend traditional skills development with AI use
For subjects that require students to develop drawing and modelling skills, have students create initial design sketches or models manually to ensure they practise these skills. Then, introduce GenAI tools such as Midjourney, Leonardo AI and ChatGPT to help students explore new ideas based on their original concepts. Using AI at this stage broadens their creative horizons and introduces innovative perspectives, which are crucial in a rapidly evolving creative industry.

Provide step-by-step tutorials, including both written guides and video demonstrations, to illustrate how initial sketches can be effectively translated into AI-generated concepts. Offer example prompts to demonstrate diverse design possibilities and help students build confidence using GenAI.

Integrating generative AI and AR consistently enhanced student engagement, creativity and spatial understanding on our course. 


How Texas is Preparing Higher Education for AI — from the74million.org by Kate McGee
TX colleges are thinking about how to prepare students for a changing workforce and an already overburdened faculty for new challenges in classrooms.

“It doesn’t matter if you enter the health industry, banking, oil and gas, or national security enterprises like we have here in San Antonio,” Eighmy told The Texas Tribune. “Everybody’s asking for competency around AI.”

It’s one of the reasons the public university, which serves 34,000 students, announced earlier this year that it is creating a new college dedicated to AI, cyber security, computing and data science. The new college, which is still in the planning phase, would be one of the first of its kind in the country. UTSA wants to launch the new college by fall 2025.

But many state higher education leaders are thinking beyond that. As AI becomes a part of everyday life in new, unpredictable ways, universities across Texas and the country are also starting to consider how to ensure faculty are keeping up with the new technology and students are ready to use it when they enter the workforce.


In the Room Where It Happens: Generative AI Policy Creation in Higher Education — from er.educause.edu by Esther Brandon, Lance Eaton, Dana Gavin, and Allison Papini

To develop a robust policy for generative artificial intelligence use in higher education, institutional leaders must first create “a room” where diverse perspectives are welcome and included in the process.


Q&A: Artificial Intelligence in Education and What Lies Ahead — from usnews.com by Sarah Wood
Research indicates that AI is becoming an essential skill to learn for students to succeed in the workplace.

Q: How do you expect to see AI embraced more in the future in college and the workplace?
I do believe it’s going to become a permanent fixture for multiple reasons. I think the national security imperative associated with AI as a result of competing against other nations is going to drive a lot of energy and support for AI education. We also see shifts across every field and discipline regarding the usage of AI beyond college. We see this in a broad array of fields, including health care and the field of law. I think it’s here to stay and I think that means we’re going to see AI literacy being taught at most colleges and universities, and more faculty leveraging AI to help improve the quality of their instruction. I feel like we’re just at the beginning of a transition. In fact, I often describe our current moment as the ‘Ask Jeeves’ phase of the growth of AI. There’s a lot of change still ahead of us. AI, for better or worse, it’s here to stay.




AI-Generated Podcasts Outperform Textbooks in Landmark Education Study — form linkedin.com by David Borish

A new study from Drexel University and Google has demonstrated that AI-generated educational podcasts can significantly enhance both student engagement and learning outcomes compared to traditional textbooks. The research, involving 180 college students across the United States, represents one of the first systematic investigations into how artificial intelligence can transform educational content delivery in real-time.


What can we do about generative AI in our teaching?  — from linkedin.com by Kristina Peterson

So what can we do?

  • Interrogate the Process: We can ask ourselves if we I built in enough checkpoints. Steps that can’t be faked. Things like quick writes, question floods, in-person feedback, revision logs.
  • Reframe AI: We can let students use AI as a partner. We can show them how to prompt better, revise harder, and build from it rather than submit it. Show them the difference between using a tool and being used by one.
  • Design Assignments for Curiosity, Not Compliance: Even the best of our assignments need to adapt. Mine needs more checkpoints, more reflective questions along the way, more explanation of why my students made the choices they did.

Teachers Are Not OK — from 404media.co by Jason Koebler

The response from teachers and university professors was overwhelming. In my entire career, I’ve rarely gotten so many email responses to a single article, and I have never gotten so many thoughtful and comprehensive responses.

One thing is clear: teachers are not OK.

In addition, universities are contracting with companies like Microsoft, Adobe, and Google for digital services, and those companies are constantly pushing their AI tools. So a student might hear “don’t use generative AI” from a prof but then log on to the university’s Microsoft suite, which then suggests using Copilot to sum up readings or help draft writing. It’s inconsistent and confusing.

I am sick to my stomach as I write this because I’ve spent 20 years developing a pedagogy that’s about wrestling with big ideas through writing and discussion, and that whole project has been evaporated by for-profit corporations who built their systems on stolen work. It’s demoralizing.

 

NAMLE 2025 Conference
Join us for the largest professional development conference dedicated to media literacy education in the U.S. on July 11-12, 2025.

From Pre-K to Higher Education, Community Education and Libraries, the conference provides valuable resources, technology, teacher practice and pedagogy, assessments, and core concepts of media literacy education.


 

The 2025 Global Skills Report— from coursera.org
Discover in-demand skills and credentials trends across 100+ countries and six regions to deliver impactful industry-aligned learning programs.

GenAI adoption fuels global skill demands
In 2023, early adopters flocked to GenAI, with approximately one person per minute enrolling in a GenAI course on Coursera —a rate that rose to eight per minute in 2024.  Since then, GenAI has continued to see exceptional growth, with global enrollment in GenAI courses surging 195% year-over-year—maintaining its position as one of the most rapidly growing skill domains on our platform. To date, Coursera has recorded over 8 million GenAI enrollments, with 12 learners per minute signing up for GenAI content in 2025 across our catalog of nearly 700 GenAI courses.

Driving this surge, 94% of employers say they’re likely to hire candidates with GenAI credentials, while 75% prefer hiring less-experienced candidates with GenAI skills over more experienced ones without these capabilities.8 Demand for roles such as AI and Machine Learning Specialists is projected to grow by up to 40% in the next four years.9 Mastering AI fundamentals—from prompt engineering to large language model (LLM) applications—is essential to remaining competitive in today’s rapidly evolving economy.

Countries leading our new AI Maturity Index— which highlights regions best equipped to harness AI innovation and translate skills into real-world applications—include global frontrunners such as Singapore, Switzerland, and the United States.

Insights in action

Businesses
Integrate role-specific GenAI modules into employee development programs, enabling teams to leverage AI for efficiency and innovation.

Governments
Scale GenAI literacy initiatives—especially in emerging economies—to address talent shortages and foster human-machine capabilities needed to future-proof digital jobs.

Higher education
Embed credit-eligible GenAI learning into curricula, ensuring graduates enter the workforce job-ready.

Learners
Focus on GenAI courses offering real-world projects (e.g., prompt engineering) that help build skills for in-demand roles.

 

Making Learning Matter — from emilypittsdonahoe.substack.com by Emily Pitts Donahoe
We’ve got to get better at talking to students 

In a recent newsletter, John Warner articulated a problem I’ve been mulling over for quite some time now:

“The challenge is to convince students that there is a genuine benefit in the struggle of learning as something distinct from the steady forced march of schooling. How do I convey the genuine value of thinking when the cultural message of the moment is the opposite?”

If higher education is to have any meaningful future at all, we have to find real answers to this question.

So, for a long time, I’ve been lamenting that we don’t talk enough with students about the value of work in our disciplines. We should devote more time to exploring how this knowledge operates in the real world! We should explicitly communicate its benefits not only for students’ future professional lives but also for their personal lives, and for the world at large! We should give them a self-transcendent purpose for learning! We should show them that what they learn has real, tangible meaning beyond the classroom!

 


Also relevant/see:


Report: 93% of Students Believe Gen AI Training Belongs in Degree Programs — from campustechnology.com by Rhea Kelly

The vast majority of today’s college students — 93% — believe generative AI training should be included in degree programs, according to a recent Coursera report. What’s more, 86% of students consider gen AI the most crucial technical skill for career preparation, prioritizing it above in-demand skills such as data strategy and software development. And 94% agree that microcredentials help build the essential skills they need to achieve career success.

For its Microcredentials Impact Report 2025, Coursera surveyed more than 1,200 learners and 1,000 employers around the globe to better understand the demand for microcredentials and their impact on workforce readiness and hiring trends.


1 in 4 employers say they’ll eliminate degree requirements by year’s end — from hrdive.com by Carolyn Crist
Companies that recently removed degree requirements reported a surge in applications, a more diverse applicant pool and the ability to offer lower salaries.

A quarter of employers surveyed said they will remove bachelor’s degree requirements for some roles by the end of 2025, according to a May 20 report from Resume Templates.

In addition, 7 in 10 hiring managers said their company looks at relevant experience over a bachelor’s degree while making hiring decisions.

In the survey of 1,000 hiring managers, 84% of companies that recently removed degree requirements said it has been a successful move. Companies without degree requirements also reported a surge in applications, a more diverse applicant pool and the ability to offer lower salaries.


Why AI literacy is now a core competency in education — from weforum.org by Tanya Milberg

  • Education systems must go beyond digital literacy and embrace AI literacy as a core educational priority.
  • A new AI Literacy Framework (AILit) aims to empower learners to navigate an AI-integrated world with confidence and purpose.
  • Here’s what you need to know about the AILit Framework – and how to get involved in making it a success.

Also from Allison Salisbury, see:

 

Cultivating a responsible innovation mindset among future tech leaders — from timeshighereducation.com by Andreas Alexiou
The classroom is a perfect place to discuss the messy, real-world consequences of technological discoveries, writes Andreas Alexiou. Beyond ‘How?’, students should be asking ‘Should we…?’ and ‘What if…?’ questions around ethics and responsibility

University educators play a crucial role in guiding students to think about the next big invention and its implications for privacy, the environment and social equity. To truly make a difference, we need to bring ethics and responsibility into the classroom in a way that resonates with students. Here’s how.

Debating with industry pioneers on incorporating ethical frameworks in innovation, product development or technology adoption is eye-opening because it can lead to students confronting assumptions they hadn’t questioned before. For example, students could discuss the roll-out of emotion-recognition software. Many assume it’s neutral, but guest speakers from industry can highlight how cultural and racial biases are baked into design decisions.

Leveraging alumni networks and starting with short virtual Q&A sessions instead of full lectures can work well.


Are we overlooking the power of autonomy when it comes to motivating students? — from timeshighereducation.com by Danny Oppenheimer
Educators fear giving students too much choice in their learning will see them making the wrong decisions. But structuring choice without dictating the answers could be the way forward

So, how can we get students to make good decisions while still allowing them agency to make their own choices, maintaining the associated motivational advantages that agency provides? One possibility is to use choice architecture, more commonly called “nudges”: structuring choices in ways that scaffold better decisions without dictating them.

Higher education rightly emphasises the importance of belonging and mastery, but when it ignores autonomy – the third leg of the motivational tripod – the system wobbles. When we allow students to decide for themselves how they’ll engage with their coursework, they consistently rise to the occasion. They choose to challenge themselves, perform better academically and enjoy their education more.

 

AI & Schools: 4 Ways Artificial Intelligence Can Help Students — from the74million.org by W. Ian O’Byrne
AI creates potential for more personalized learning

I am a literacy educator and researcher, and here are four ways I believe these kinds of systems can be used to help students learn.

  1. Differentiated instruction
  2. Intelligent textbooks
  3. Improved assessment
  4. Personalized learning


5 Skills Kids (and Adults) Need in an AI World — from oreilly.com by Raffi Krikorian
Hint: Coding Isn’t One of Them

Five Essential Skills Kids Need (More than Coding)
I’m not saying we shouldn’t teach kids to code. It’s a useful skill. But these are the five true foundations that will serve them regardless of how technology evolves.

  1. Loving the journey, not just the destination
  2. Being a question-asker, not just an answer-getter
  3. Trying, failing, and trying differently
  4. Seeing the whole picture
  5. Walking in others’ shoes

The AI moment is now: Are teachers and students ready? — from iblnews.org

Day of AI Australia hosted a panel discussion on 20 May, 2025. Hosted by Dr Sebastian Sequoiah-Grayson (Senior Lecturer in the School of Computer Science and Engineering, UNSW Sydney) with panel members Katie Ford (Industry Executive – Higher Education at Microsoft), Tamara Templeton (Primary School Teacher, Townsville), Sarina Wilson (Teaching and Learning Coordinator – Emerging Technology at NSW Department of Education) and Professor Didar Zowghi (Senior Principal Research Scientist at CSIRO’s Data61).


Teachers using AI tools more regularly, survey finds — from iblnews.org

As many students face criticism and punishment for using artificial intelligence tools like ChatGPT for assignments, new reporting shows that many instructors are increasingly using those same programs.


Addendum on 5/28/25:

A Museum of Real Use: The Field Guide to Effective AI Use — from mikekentz.substack.com by Mike Kentz
Six Educators Annotate Their Real AI Use—and a Method Emerges for Benchmarking the Chats

Our next challenge is to self-analyze and develop meaningful benchmarks for AI use across contexts. This research exhibit aims to take the first major step in that direction.

With the right approach, a transcript becomes something else:

  • A window into student decision-making
  • A record of how understanding evolves
  • A conversation that can be interpreted and assessed
  • An opportunity to evaluate content understanding

This week, I’m excited to share something that brings that idea into practice.

Over time, I imagine a future where annotated transcripts are collected and curated. Schools and universities could draw from a shared library of real examples—not polished templates, but genuine conversations that show process, reflection, and revision. These transcripts would live not as static samples but as evolving benchmarks.

This Field Guide is the first move in that direction.


 

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.

 

Michiganders in these 25 cities have the most student loan debt, ranking says — from mlive.com by Jackie Smith; this is a gifted article

Millions of former students and college graduates across the U.S. are weighed down with student loan debt, but with exactly how much may depend on where you live.

An analysis from WalletHub was released earlier this month, listing high averages student loan debts of residents in more than 2,500 American cities, including 83 in Michigan.

Student loans are the second highest form of household debt after mortgages, according to WalletHub, totaling more than $1.6 tillion, or averaging $38,000 per borrower. 

The above article links to:

Cities with the Most & Least Student Debt (2025) — from wallethub.com by Adam McCann

High balances combined with a payoff timeline that lasts into middle age force many graduates to significantly delay or forgo other financial goals such as saving for retirement or buying a home. Paying back student loans has also become even more difficult due to high inflation putting a strain on Americans’ finances.

While we have a big student-loan crisis as a country, student-loan debts are more unsustainable in some places than others. To determine where borrowers are burdened the most, WalletHub compared the median student-loan balance against the median earnings of adults ages 25 and older with a bachelor’s degree in more than 2,500 U.S. cities.

If you are considering borrowing money for college or you’re in danger of defaulting, we advise using a student loan calculator to determine an affordable payment amount and realistic payoff timeline.


Again, this graphic from 2009 comes to mind:
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‘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.


 

Stop Trying to Make Everyone Go to College — from nytimes.com by Randi Weingarten; this is a gifted article

For years, America’s approach to education has been guided by an overly simplistic formula: 4+4 — the idea that students need four years of high school and four years of college to succeed in life.

Even with this prevailing emphasis on college, around 40 percent of high schoolers do not enroll in college upon graduating, and only 60 percent of students who enroll in college earn a degree or credential within eight years of high school graduation.

While college completion has positive effects — on health, lifetime earnings, civic engagement and even happiness — it’s increasingly clear that college for all should no longer be our North Star. It’s time to scale up successful programs that create multiple pathways for students so high school is a gateway to both college and career.

I propose a different strategy: aligning high school to both college prep and in-demand vocational career pathways. Just as students who plan to go to college can get a head start through Advanced Placement programs, high schools, colleges and employers should work together to provide the relevant coursework to engage students in promising career opportunities.

 
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