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.

 

“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.

 

Class of 2025 grads are experiencing disconnect between job expectations and reality, study finds — from hrdive.com by Carolyn Crist
Soon-to-be graduates believe they’ll secure a job sooner than recent graduates have experienced, ZipRecruiter said.

Class of 2025 graduates’ expectations seem to be clashing with reality during their job search, especially when it comes to pay, job preferences and beliefs about the job market, according to an April 23 report from ZipRecruiter.

For instance, some graduates have found that the job search is taking longer than they expected. About 82% of those about to graduate expect to start work within three months of graduation, but only 77% of recent graduates accomplished that, and 5% said they’re still searching for a job.

 

2025 EDUCAUSE Horizon Report | Teaching and Learning Edition — from library.educause.edu

Higher education is in a period of massive transformation and uncertainty. Not only are current events impacting how institutions operate, but technological advancement—particularly in AI and virtual reality—are reshaping how students engage with content, how cognition is understood, and how learning itself is documented and valued.

Our newly released 2025 EDUCAUSE Horizon Report | Teaching and Learning Edition captures the spirit of this transformation and how you can respond with confidence through the lens of emerging trends, key technologies and practices, and scenario-based foresight.

#teachingandlearning #highereducation #learningecosystems #learning #futurism #foresight #trends #emergingtechnologies #AI #VR #gamechangingenvironment #colleges #universities #communitycolleges #faculty #staff #IT

 

MOOC-Style Skills Training — from the-job.beehiiv.com by Paul Fain
WGU and tech companies use Open edX for flexible online learning. Could community colleges be next?

Open Source for Affordable Online Reach
The online titan Western Governors University is experimenting with an open-source learning platform. So are Verizon and the Indian government. And the platform’s leaders want to help community colleges take the plunge on competency-based education.

The Open edX platform inherently supports self-paced learning and offers several features that make it a good fit for competency-based education and skills-forward learning, says Stephanie Khurana, Axim’s CEO.

“Flexible modalities and a focus on competence instead of time spent learning improves access and affordability for learners who balance work and life responsibilities alongside their education,” she says.

“Plus, being open source means institutions and organizations can collaborate to build and share CBE-specific tools and features,” she says, “which could lower costs and speed up innovation across the field.”

Axim thinks Open edX’s ability to scale affordably can support community colleges in reaching working learners across an underserved market. 

 
 

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.

 

2025 EDUCAUSE Teaching and Learning Workforce in Higher Education — from library.educause.edu

This report is the first in a series that examines three distinct workforce domains in higher education in 2025 (teaching and learning, cybersecurity and privacy, and IT leadership) to determine the priorities and challenges facing the profession. The findings in this report, taken from a survey of teaching and learning professionals in higher education, highlight their perspectives on a range of topics:

  • Flexible work arrangements
  • Integration of technologies
  • Workload and staffing
  • Job satisfaction and transition/succession planning
  • Mental health and well-being
  • Culture of belonging
  • Professional development

 

Personal Finance for Students? Teachers Could Use It, Too — from edweek.org by Elizabeth Heubeck

More states are mandating personal finance courses for high schoolers, but what if their teachers aren’t confident managing money themselves?

But as momentum grows around students’ financial education, a key issue is often overlooked: Many teachers don’t feel confident in their own financial knowledge.

It’s not a problem unique to teachers. Experts report that many U.S. adults lack financial literacy, which, until very recently, was rarely required as a high school graduation requirement. Few teachers study it in college, despite recent surveys of K-12 educators indicating a strong interest in the subject. And once in the classroom, teachers rarely take time to learn subjects that would benefit their own lives, like personal finance, says Yanely Espinal, a financial educator and former classroom teacher.

It’s very rare that you see a teacher pause and consider their own needs, asking themselves things like, ‘How can I set myself up financially? Am I on track?,’”


From DSC:
If you are working in K-12 or in higher education, don’t rely on the contributions that your organization makes to your 403(b) or your 401k plans (the type of plan depends upon your organization’s for-profit or non-profit/tax-exempt status). You should be investing wisely. Those 6-10% contributions won’t cut it these days, even after working 30+ years at a place that contributes that kind of funds to your retirement accounts. You need to invest aggressively if you are going to retire at age 65 (or even younger).

I worked in the corporate world for half of my career and I’m glad that I did. It helped me understand more about personal finance and investing. It helped me get started building a nest egg. But it was really aggressive investments in a couple of key companies that helped me the most. I’m not here to specify which companies to invest in. I’m just saying that if you are relying on 6%-10% contributions to meet your retirement-related needs, you may end up with far less than you’ll need to retire.

I’m glad that they are teaching personal finance these days in K-12. I hope they add some basic legal knowledge to the curricula as well.


 

 

AI agents arrive in US classrooms — from zdnet.com by Radhika Rajkumar
Kira AI’s personalized learning platform is currently being implemented in Tennessee schools. How will it change education?

AI for education is a new but rapidly expanding field. Can it support student outcomes and help teachers avoid burnout?

On Wednesday, AI education company Kira launched a “fully AI-native learning platform” for K-12 education, complete with agents to assist teachers with repetitive tasks. The platform hosts assignments, analyzes progress data, offers administrative assistance, helps build lesson plans and quizzes, and more.

“Unlike traditional tools that merely layer AI onto existing platforms, Kira integrates artificial intelligence directly into every educational workflow — from lesson planning and instruction to grading, intervention, and reporting,” the release explains. “This enables schools to improve student outcomes, streamline operations, and provide personalized support at scale.”

Also relevant/see:

Coursera Founder Andrew Ng’s New Venture Brings A.I. to K–12 Classrooms — from observer.com by Victor Dey
Andrew Ng’s Kira Learning uses A.I. agents to transform K–12 education with tools for teachers, students and administrators.

“Teachers today are overloaded with repetitive tasks. A.I. agents can change that, and free up their time to give more personalized help to students,” Ng said in a statement.

Kira was co-founded by Andrea Pasinetti and Jagriti Agrawal, both longtime collaborators of Ng. The platform embeds A.I. directly into lesson planning, instruction, grading and reporting. Teachers can instantly generate standards-aligned lesson plans, monitor student progress in real time and receive automated intervention strategies when a student falls behind.

Students, in turn, receive on-demand tutoring tailored to their learning styles. A.I. agents adapt to each student’s pace and mastery level, while grading is automated with instant feedback—giving educators time to focus on teaching.


‘Using GenAI is easier than asking my supervisor for support’ — from timeshighereducation.com
Doctoral researchers are turning to generative AI to assist in their research. How are they using it, and how can supervisors and candidates have frank discussions about using it responsibly?

Generative AI is increasingly the proverbial elephant in the supervisory room. As supervisors, you may be concerned about whether your doctoral researchers are using GenAI. It can be a tricky topic to broach, especially when you may not feel confident in understanding the technology yourself.

While the potential impact of GenAI use among undergraduate and postgraduate taught students, especially, is well discussed (and it is increasingly accepted that students and staff need to become “AI literate”), doctoral researchers often slip through the cracks in institutional guidance and policymaking.


AI as a Thought Partner in Higher Education — from er.educause.edu by Brian Basgen

When used thoughtfully and transparently, generative artificial intelligence can augment creativity and challenge assumptions, making it an excellent tool for exploring and developing ideas.

The glaring contrast between the perceived ubiquity of GenAI and its actual use also reveals fundamental challenges associated with the practical application of these tools. This article explores two key questions about GenAI to address common misconceptions and encourage broader adoption and more effective use of these tools in higher education.


AI for Automation or Augmentation of L&D? — from drphilippahardman.substack.com by Dr. Philippa Hardman
An audio summary of my Learning Technologies talk

Like many of you, I spent the first part of this week at Learning Technologies in London, where I was lucky enough to present a session on the current state of AI and L&D.

In this week’s blog post, I summarise what I covered and share an audio summary of my paper for you to check out.


Bridging the AI Trust Gap — from chronicle.com by Ian Wilhelm, Derek Bruff, Gemma Garcia, and Lee Rainie

In a 2024 Chronicle survey, 86 percent of administrators agreed with the statement: “Generative artificial intelligence tools offer an opportunity for higher education to improve how it educates, operates, and conducts research.” In contrast, just 55 percent of faculty agreed, showing the stark divisions between faculty and administrative perspectives on adopting AI.

Among many faculty members, a prevalent distrust of AI persists — and for valid reasons. How will it impact in-class instruction? What does the popularity of generative AI tools portend for the development of critical thinking skills for Gen-Z students? How can institutions, at the administrative level, develop policies to safeguard against students using these technologies as tools for cheating?

Given this increasing ‘trust gap,’ how can faculty and administrators work together to preserve academic integrity as AI seeps into all areas of academia, from research to the classroom?

Join us for “Bridging the AI Trust Gap,” an extended, 75-minute Virtual Forum exploring the trust gap on campus about AI, the contours of the differences, and what should be done about it.

 

Higher Ed Institutions Rely Less on OPMs While Increasingly Hiring Fee-For-Service Models — from iblnews.org

market report from Validated Insights released this month notes that fewer colleges and universities hire external online program management (OPM) companies to develop their courses.

For 2024, higher education institutions launched only 81 new partnerships with OPMs —  a drop of 42% and the lowest number since 2016.

The report showed that institutions increasingly pay OPMs a fee-for-service instead of following a revenue-sharing model with big service bundles and profit splits.

Experts say revenue-sharing models, which critics denounce as predatory arrangements, incentivize service providers to use aggressive recruiting tactics to increase enrollments and maximize tuition revenue.

According to the report, fee-for-service has become the dominant business model for OPMs.


6 Online Edtech Professional Learning Communities & Resources for Teachers — from techlearning.com by Stephanie Smith Budhai, Ph.D.
These resources can help provide training, best practices, and advice, for using digital tools such as Canva, Curipod, Kahoot!, and more

While school-led professional development can be helpful, there are online professional learning communities on various edtech websites that can be leveraged. Also, some of these community spaces offer the chance to monetize your work.

Here is a summary of six online edtech professional learning spaces.

 
© 2025 | Daniel Christian