personalized/customized learning

“Faculty AI Guides” + “Teachers using AI tools more regularly” + other items re: AI in our learning ecosystems

On 05/27/2025, in Artificial Intelligence/Agents/LLMs/and Related, assessment, Australia, colleges, community colleges, content development, aggregation, repositories, digital learning, digital textbooks, education, education reform, education technology, educational games / serious games, emerging technologies, engagement / engaging students, experimentation, faculty/staff, future, future of higher education, game-changing environment, generational differences, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, informal learning, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning preferences, liberal arts, personalized/customized learning, skills, student-related, teachers, teaching & learning, tools, trends, United States, universities, user experience (UX), vendors, vision/possibilities, by Daniel Christian

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.

Differentiated instruction
Intelligent textbooks
Improved assessment
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.

Loving the journey, not just the destination
Being a question-asker, not just an answer-getter
Trying, failing, and trying differently
Seeing the whole picture
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.

“A radically new and different approach to corporate training & professional development.” [Bersin]+ other items re: AI in our LE’s

On 05/22/2025, in 21st century, 24x7x365 access, adult learning, Artificial Intelligence/Agents/LLMs/and Related, career development, changing business models, colleges, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, experimentation, future, game-changing environment, higher education, human-computer interaction (HCI), personalized/customized learning, platforms, productivity / tips and tricks, professional development, skills, tools, traditional / tradition, training / L&D, trends, United States, universities, workplace, by Daniel Christian

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.
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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.
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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’ [Hogg] + other items re: AI in our learning ecosystems

On 05/19/2025, in Artificial Intelligence/Agents/LLMs/and Related, assessment, business side of he, change, colleges, communications, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, creativity, education technology, emerging technologies, engagement / engaging students, experimentation, faculty/staff, future, future of higher education, game-changing environment, generational differences, higher education, human-computer interaction (HCI), ideas, IT in HE, K-12 related, law schools, learning, learning ecosystem, Learning Experience Design, liberal arts, metacognition / metacognitive skills, personalized/customized learning, platforms, productivity / tips and tricks, professional development, student-related, teachers, teaching & learning, UK, United States, universities, vendors, workplace, youth, by Daniel Christian

‘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.
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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:

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.

“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

On 05/12/2025, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, bots, business, change, colleges, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, creativity, digital learning, digital video, education, education technology, emerging technologies, engagement / engaging students, expectations, experimentation, Facebook / Meta Platforms, faculty/staff, formal learning, future, future of higher education, game-changing environment, generational differences, global, Google, health, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, immersion, informal learning, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, languages and translation, law schools, learner profiles, learning, learning agents, learning ecosystem, Learning Experience Design, learning preferences, learning spaces, media/film, Microsoft, Mixed Reality (MR), multimedia, new media literacies, online media, online tutoring, pedagogy, personalized/customized learning, platforms, productivity / tips and tricks, professional development, skills, society, staying relevant, student teaching/teacher education, student-related, teachers, teaching & learning, teaching online, technologies for your home, tools, training / L&D, trends, United States, universities, usability, user experience (UX), user interface design, vendors, vision/possibilities, voice recognition / voice enabled interfaces, wearables, workplace, XR - extended reality, youth, by Daniel Christian

.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.
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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.

“AI agents arrive in US classrooms” [Rajkumar] + other items re: AI in our learning ecosystems

On 04/25/2025, in Artificial Intelligence/Agents/LLMs/and Related, colleges, community colleges, content development, aggregation, repositories, creativity, education, education technology, emerging technologies, experimentation, faculty/staff, game-changing environment, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, liberal arts, personalized/customized learning, podcasting, research, teachers, teaching & learning, trends, UK, United States, universities, vendors, by Daniel Christian

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.

How might the memory of an AI — over time — impact personalized and lifelong learning? [Christian]

On 04/11/2025, in 21st century, 24x7x365 access, adjunct faculty, adult learning, Artificial Intelligence/Agents/LLMs/and Related, cloud-based computing / apps / other cloud-related, colleges, community colleges, corporate universities / corporate training, Daniel S. Christian, education, education reform, education technology, emerging technologies, experimentation, faculty/staff, formal learning, future, future of higher education, game-changing environment, generational differences, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, informal learning, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning preferences, lifelong learning, online learning, online media, online tutoring, personalized/customized learning, platforms, skills, society, student-related, teachers, teaching & learning, teaching online, technologies for your home, training / L&D, trends, universities, vendors, vision/possibilities, web-based collaboration, by Daniel Christian

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?

we have greatly improved memory in chatgpt–it can now reference all your past conversations!

this is a surprisingly great feature imo, and it points at something we are excited about: ai systems that get to know you over your life, and become extremely useful and personalized.

— Sam Altman (@sama) April 10, 2025

Starting today, memory in ChatGPT can now reference all of your past chats to provide more personalized responses, drawing on your preferences and interests to make it even more helpful for writing, getting advice, learning, and beyond. pic.twitter.com/s9BrWl94iY

— OpenAI (@OpenAI) April 10, 2025

Reflections on “Are You Ready for the AI University? Everything is about to change.” [Latham]

On 04/10/2025, in 21st century, 24x7x365 access, accreditation, adjunct faculty, adult learning, Artificial Intelligence/Agents/LLMs/and Related, assessment, Blockchain, bots, career development, change, changing business models, cloud-based computing / apps / other cloud-related, CMS/LMS, collaboration, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, cost of getting a degree, credentialing, culture, curriculum, dangers of the status quo, Daniel S. Christian, data related items, Design Thinking, digital learning, disruption, education technology, emerging technologies, Emotion, engagement / engaging students, expectations, experimentation, faculty/staff, future, future of higher education, game-changing environment, generational differences, global, Google, higher education, human-computer interaction (HCI), IBM, ideas, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, leadership, learner profiles, learning, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning preferences, learning spaces, liberal arts, lifelong learning, MBA, Michigan, new business models, online learning, online media, online tutoring, organizational change, pace of change, pedagogy, personalized/customized learning, platforms, productivity / tips and tricks, professional development, reinvent, skills, society, staying relevant, strategy, student-related, surviving, teaching & learning, technologies for your home, tools, trends, United States, universities, usability, user experience (UX), virtual tutoring, vision/possibilities, web-based collaboration, workplace, by Daniel Christian

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Are You Ready for the AI University? Everything is about to change. — from chronicle.com by Scott Latham

Over the course of the next 10 years, AI-powered institutions will rise in the rankings. US News & World Report will factor a college’s AI capabilities into its calculations. Accrediting agencies will assess the degree of AI integration into pedagogy, research, and student life. Corporations will want to partner with universities that have demonstrated AI prowess. In short, we will see the emergence of the AI haves and have-nots.
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What’s happening in higher education today has a name: creative destruction. The economist Joseph Schumpeter coined the term in 1942 to describe how innovation can transform industries. That typically happens when an industry has both a dysfunctional cost structure and a declining value proposition. Both are true of higher education.
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Out of the gate, professors will work with technologists to get AI up to speed on specific disciplines and pedagogy. For example, AI could be “fed” course material on Greek history or finance and then, guided by human professors as they sort through the material, help AI understand the structure of the discipline, and then develop lectures, videos, supporting documentation, and assessments.
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In the near future, if a student misses class, they will be able watch a recording that an AI bot captured. Or the AI bot will find a similar lecture from another professor at another accredited university. If you need tutoring, an AI bot will be ready to help any time, day or night. Similarly, if you are going on a trip and wish to take an exam on the plane, a student will be able to log on and complete the AI-designed and administered exam. Students will no longer be bound by a rigid class schedule. Instead, they will set the schedule that works for them.

Early and mid-career professors who hope to survive will need to adapt and learn how to work with AI. They will need to immerse themselves in research on AI and pedagogy and understand its effect on the classroom.

From DSC:
I had a very difficult time deciding which excerpts to include. There were so many more excerpts for us to think about with this solid article. While I don’t agree with several things in it, EVERY professor, president, dean, and administrator working within higher education today needs to read this article and seriously consider what Scott Latham is saying.

Change is already here, but according to Scott, we haven’t seen anything yet. I agree with him and, as a futurist, one has to consider the potential scenarios that Scott lays out for AI’s creative destruction of what higher education may look like. Scott asserts that some significant and upcoming impacts will be experienced by faculty members, doctoral students, and graduate/teaching assistants (and Teaching & Learning Centers and IT Departments, I would add). But he doesn’t stop there. He brings in presidents, deans, and other members of the leadership teams out there.

There are a few places where Scott and I differ.

The foremost one is the importance of the human element — i.e., the human faculty member and students’ learning preferences. I think many (most?) students and lifelong learners will want to learn from a human being. IBM abandoned their 5-year, $100M ed push last year and one of the key conclusions was that people want to learn from — and with — other people:

To be sure, AI can do sophisticated things such as generating quizzes from a class reading and editing student writing. But the idea that a machine or a chatbot can actually teach as a human can, he said, represents “a profound misunderstanding of what AI is actually capable of.”

Nitta, who still holds deep respect for the Watson lab, admits, “We missed something important. At the heart of education, at the heart of any learning, is engagement. And that’s kind of the Holy Grail.”

— Satya Nitta, a longtime computer researcher at
IBM’s Watson Research Center in Yorktown Heights, NY
.

By the way, it isn’t easy for me to write this. As I wanted AI and other related technologies to be able to do just what IBM was hoping that it would be able to do.

Also, I would use the term learning preferences where Scott uses the term learning styles.

Scott also mentions:

“In addition, faculty members will need to become technologists as much as scholars. They will need to train AI in how to help them build lectures, assessments, and fine-tune their classroom materials. Further training will be needed when AI first delivers a course.”

It has been my experience from working with faculty members for over 20 years that not all faculty members want to become technologists. They may not have the time, interest, and/or aptitude to become one (and vice versa for technologists who likely won’t become faculty members).

That all said, Scott relays many things that I have reflected upon and relayed for years now via this Learning Ecosystems blog and also via The Learning from the Living [AI-Based Class] Room vision — the use of AI to offer personalized and job-relevant learning, the rising costs of higher education, the development of new learning-related offerings and credentials at far less expensive prices, the need to provide new business models and emerging technologies that are devoted more to lifelong learning, plus several other things.

So this article is definitely worth your time to read, especially if you are working in higher education or are considering a career therein!

Addendum later on 4/10/25:

U-M’s Ross School of Business, Google Public Sector launch virtual teaching assistant pilot program — from news.umich.edu by Jeff Karoub; via Paul Fain

Google Public Sector and the University of Michigan’s Ross School of Business have launched an advanced Virtual Teaching Assistant pilot program aimed at improving personalized learning and enlightening educators on artificial intelligence in the classroom.

The AI technology, aided by Google’s Gemini chatbot, provides students with all-hours access to support and self-directed learning. The Virtual TA represents the next generation of educational chatbots, serving as a sophisticated AI learning assistant that instructors can use to modify their specific lessons and teaching styles.

The Virtual TA facilitates self-paced learning for students, provides on-demand explanations of complex course concepts, guides them through problem-solving, and acts as a practice partner. It’s designed to foster critical thinking by never giving away answers, ensuring students actively work toward solutions.

“8 Weeks Left to Prepare Students for the AI-Enhanced Workplace” [Schroeder] + other items re: AI in our LEs

On 03/21/2025, in adjunct faculty, Artificial Intelligence/Agents/LLMs/and Related, assessment, career development, change, cloud-based computing / apps / other cloud-related, colleges, community colleges, content development, aggregation, repositories, corporate / business world, curriculum, digital learning, education technology, emerging technologies, expectations, experimentation, faculty/staff, future, game-changing environment, Google, higher education, human-computer interaction (HCI), ideas, instructional design, intelligent systems, learning, Learning Experience Design, liberal arts, new business models, online learning, pedagogy, personalized/customized learning, platforms, productivity / tips and tricks, professional development, research, staying relevant, student-related, surviving, teaching & learning, teaching online, trends, United States, universities, workplace, by Daniel Christian

8 Weeks Left to Prepare Students for the AI-Enhanced Workplace — from insidehighered.com by Ray Schroeder
We are down to the final weeks left to fully prepare students for entry into the AI-enhanced workplace. Are your students ready?

The urgent task facing those of us who teach and advise students, whether they be degree program or certificate seeking, is to ensure that they are prepared to enter (or re-enter) the workplace with skills and knowledge that are relevant to 2025 and beyond. One of the first skills to cultivate is an understanding of what kinds of services this emerging technology can provide to enhance the worker’s productivity and value to the institution or corporation.
…
Given that short period of time, coupled with the need to cover the scheduled information in the syllabus, I recommend that we consider merging AI use into authentic assignments and assessments, supplementary modules, and other resources to prepare for AI.

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

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

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

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

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

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

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

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

Research and analysis
Communication efficiency
Multimedia creation

AI tactics that work surprisingly well

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

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

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

As current high school students, we want:

Education for the Real World
Personalized and Flexible Education
Cultivating Agency
Creativity and Divergent Thinking
Joyful Learning and Community Building
Empathy and Emotional Growth

Also from gettingsmart.com

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

Key Points

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

“AI Resources for District Leaders” [Baule] + several other items re: AI in our learning ecosystems

On 02/26/2025, in Artificial Intelligence/Agents/LLMs/and Related, Bias | Diversity Equity & Inclusion (DE&I), content development, aggregation, repositories, education, education technology, Emotion, engagement / engaging students, hearts -- matters of the heart, higher education, human-computer interaction (HCI), innovation, instructional design, intelligent systems, IT in HE, K-12 related, languages and translation, leadership, learning, learning ecosystem, Learning Experience Design, NVIDIA, personalized/customized learning, platforms, productivity / tips and tricks, project-based learning, society, student-related, teachers, teaching & learning, technologies for your home, tools, trends, UK, United States, universities, vendors, by Daniel Christian

Nvidia helps launch AI platform for teaching American Sign Language — from venturebeat.com by Dean Takahashi; via Claire Zau

Nvidia has unveiled a new AI platform for teaching people how to use American Sign Language to help bridge communication gaps.

The Signs platform is creating a validated dataset for sign language learners and developers of ASL-based AI applications.
…
Nvidia, the American Society for Deaf Children and creative agency Hello Monday are helping close this gap with Signs, an interactive web platform built to support ASL learning and the development of accessible AI applications.

Using Gen AI to Design, Implement, and Assess PBL — from gettingsmart.com by David Ross

Key Points

Generative AI can significantly reduce the time and effort required in designing PBL by providing tools for research, brainstorming, and organization.
AI tools can assist educators in managing project implementation and assessment, providing formative feedback and organizing resources efficiently.

I usually conclude blogs with some pithy words, but this time I’ll turn the microphone over to Rachel Harcrow, a high school English/Language Arts teacher at Young Women’s College Prep Charter School of Rochester, NY: “After years of struggling to call myself a PBL practitioner, I finally feel comfortable saying I am, thanks to the power of Gen AI,” Harcrow told me. “Initial ideas now turn into fully fledged high-quality project plans in minutes that I can refine, giving me the space and energy to focus on what truly matters: My students.”

AI Resources for District Leaders — from techlearning.com by Steve Baule
Educational leaders aiming to effectively integrate generative AI into their schools should consider several key resources

To truly harness the transformative power of generative AI in education, district leaders must navigate a landscape rich with resources and opportunities. By delving into state and national guidelines, exploring successful case studies, utilizing innovative planning tools, and engaging in professional development, educational leaders can craft robust implementation plans. These plans can then assist in integrating AI seamlessly into their schools and elevate the learning experience to new heights.

Anthropic brings ‘extended thinking’ to Claude, which can solves complex physics problems with 96.5% accuracy — from rdworldonline.com by Brian Buntz

Anthropic, a favorite frontier AI lab among many coders and genAI power users has unveiled Claude 3.7 Sonnet, its first “hybrid reasoning” AI model. It is capable of both near-instant answers and in-depth, step-by-step reasoning within a single system.

Users can toggle an extended thinking mode where the model self-reflects before answering, considerably improving performance on complex tasks like math, physics and coding. In early testing by the author, the model largely succeeded in creating lines of Python (related to unsupervised learning) that were close to 1,000 lines long that ran without error on the first or second try, including the unsupervised machine learning task shown below:

New Tools. Old Complaints. Why AI Won’t Kill Education or Fix it — from coolcatteacher.com by Vicki Davis; via Stephen Downes

AI won’t kill education. But will it kill learning? The challenge isn’t AI itself—it’s whether students can still think for themselves when the answers are always one click away.
…

Wait. Before you go, let me ask you one thing.
AI has opportunities to help learning. But it also won’t fix it. The real question isn’t whether students can use AI—but whether they’re still learning without it.

Whether the learning is happening between the ears.

And so much of what we teach in schools isn’t the answers on a test. It answers questions like “What is my purpose in life?” “How do I make friends?” and “How can I help my team be stronger.” Questions that aren’t asked on a test but are essential to living a good life. These questions aren’t answered between the ears but within the heart.

That, my friends, is what teaching has always been about.

The heart.

And the heart of the matter is we have new challenges, but these are old complaints. Complaints since the beginning of time and teaching. And in those days, you didn’t need kids just to be able to talk about how to build a fire, they had to make one themselves. Their lives depend on it.

And these days, we need to build another kind of fire. A fire that sparks the joy of learning. The joy of the opportunities that await us sparked by some of the most powerful tools ever invented. Kids need to not be able to just talk about making a difference, they need to know how to build a better world tomorrow. Our lives depend on it.

How Debating Skills Can Help Us In The Fight Against AI — from adigaskell.org by Adi Gaskell

Debating skills have a range of benefits in the workplace, from helping to improve our communication to bolstering our critical thinking skills. Research from the University of Mississippi suggests it might also help us in the battle with AI in the workplace.

We can often assume that debate teaches us nothing more than how to argue our point, but in order to do this, we have to understand both our own take on a subject and that of our opponent. This allows us to see both sides of any issue we happen to be debating.

“Even though AI has offered a shortcut through the writing process, it actually still is important to be able to write and speak and think on your own,” the researchers explain. “That’s what the focus of this research is: how debate engenders those aspects of being able to write and speak and study and research on your own.”

The Learning & Development Global Sentiment Survey 2025 [Taylor]

On 02/20/2025, in 21st century, adult learning, Artificial Intelligence/Agents/LLMs/and Related, Asia, Augmented Reality (AR), Australia, business, Canada, change, CMS/LMS, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, education technology, elearning, emerging technologies, Europe, experimentation, faculty/staff, game-changing environment, generational differences, global, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, K-12 related, learning, learning ecosystem, Learning Experience Design, learning preferences, lifelong learning, microlearning, personalized/customized learning, platforms, productivity / tips and tricks, skills, technology (general), training / L&D, trends, UK, United States, universities, vendors, Virtual Reality (VR) / worlds / learning, XR - extended reality, by Daniel Christian

The Learning & Development Global Sentiment Survey 2025 — from donaldhtaylor.co.uk by Don Taylor

The L&D Global Sentiment Survey, now in its 12th year, once again asked two key questions of L&D professionals worldwide:

What will be hot in workplace learning in 2025?
What are your L&D challenges in 2025?

For the obligatory question on what they considered ‘hot’ topics, respondents voted for one to three of 15 suggested options, plus a free text ‘Other’ option. Over 3,000 voters participated from nearly 100 countries. 85% shared their challenges for 2025.

The results show more interest in AI, a renewed focus on showing the value of L&D, and some signs of greater maturity around our understanding of AI in L&D.

“AI in K12: Today’s Breakthroughs and Tomorrow’s Possibilities” + other items re: AI in our learning ecosystems

On 02/20/2025, in 21st century, 24x7x365 access, adjunct faculty, adult learning, Artificial Intelligence/Agents/LLMs/and Related, colleges, communications, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, Daniel S. Christian, digital audio, e-readers, education technology, emerging technologies, engagement / engaging students, experimentation, faculty/staff, future of higher education, game-changing environment, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, languages and translation, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning preferences, legislatures / government / legal, liberal arts, mathematics, multimedia, pedagogy, personalized/customized learning, platforms, research, STEAM-related, student-related, teachers, tools, training / L&D, trends, United States, universities, vendors, vision/possibilities, by Daniel Christian

AI in K12: Today’s Breakthroughs and Tomorrow’s Possibilities (webinar)
How AI is Transforming Classrooms Today and What’s Next

Audio-Based Learning 4.0 — from drphilippahardman.substack.com by Dr. Philippa Hardman
A new & powerful way to leverage AI for learning?

At the end of all of this my reflection is that the research paints a pretty exciting picture – audio-based learning isn’t just effective, it’s got some unique superpowers when it comes to boosting comprehension, ramping up engagement, and delivering feedback that really connects with learners.

While audio has been massively under-used as a mode of learning, especially compared to video and text, we’re at an interesting turning point where AI tools are making it easier than ever to tap into audio’s potential as a pedagogical tool.

What’s super interesting is how the solid research backing audio’s effectiveness is and how well this is converging with these new AI capabilities.

From DSC:
I’ve noticed that I don’t learn as well via audio-only based events. It can help if visuals are also provided, but I have to watch the cognitive loads. My processing can start to get overloaded — to the point that I have to close my eyes and just listen sometimes. But there are people I know who love to listen to audiobooks and prefer to learn that way. They can devour content and process/remember it all. Audio is a nice change of pace at times, but I prefer visuals and reading often times. It needs to be absolutely quiet if I’m tackling some new information/learning.

In Conversation With… Ashton Cousineau — from drphilippahardman.substack.com by Dr. Philippa Hardman
A new video series exploring how L&D professionals are working with AI on the ground

In Conversation With… Ashton Cousineau by Dr Philippa Hardman

A new video series exploring how L&D professionals are working with AI on the ground

Read on Substack

The Learning Research Digest vol. 28 — from learningsciencedigest.substack.com by Dr. Philippa Hardman

Hot Off the Research Press This Month:

AI-Infused Learning Design – A structured approach to AI-enhanced assignments using a three-step model for AI integration.
Mathematical Dance and Creativity in STEAM – Using AI-powered motion capture to translate dance movements into mathematical models.
AI-Generated Instructional Videos – How adaptive AI-powered video learning enhances problem-solving and knowledge retention.
Immersive Language Learning with XR & AI – A new framework for integrating AI-driven conversational agents with Extended Reality (XR) for task-based language learning.
Decision-Making in Learning Design – A scoping review on how instructional designers navigate complex instructional choices and make data-driven decisions.
Interactive E-Books and Engagement – Examining the impact of interactive digital books on student motivation, comprehension, and cognitive engagement.
Elevating Practitioner Voices in Instructional Design – A new initiative to amplify instructional designers’ contributions to research and innovation.

Deep Reasoning, Agentic AI & the Continued Rise of Specialised AI Research & Tools for Education — from learningfuturesdigest.substack.com by Dr. Philippa Hardman

Here’s a quick teaser of key developments in the world of AI & learning this month:

DeepSeek R-1, OpenAI’s Deep Seek & Perplexity’s ‘Deep Research’ are the latest additions to a growing number of “reasoning models” with interesting implications for evidence-based learning design & development.
The U.S. Education Dept release an AI Toolkit and a fresh policy roadmap enabling the adoption of AI use in schools.
Anthropic Release “Agentic Claude”, another AI agent that clicks, scrolls, and can even successfully complete e-learning courses…
Oxford University Announce the AIEOU Hub, a research-backed research lab to support research and implementation on AI in education.
“AI Agents Everywhere”: A Forbes peek at how agentic AI will handle the “boring bits” of classroom life.
[Bias klaxon!] Epiphany AI: My own research leads to the creation of a specialised, “pedagogy first” AI co-pilot for instructional design marking the continued growth of specialised AI tools designed for specific industries and workflows.

AI is the Perfect Teaching Assistant for Any Educator — from unite.ai by Navi Azaria, CPO at Kaltura

Through my work with leading educational institutions at Kaltura, I’ve seen firsthand how AI agents are rapidly becoming indispensable. These agents alleviate the mounting burdens on educators and provide new generations of tech-savvy students with accessible, personalized learning, giving teachers the support they need to give their students the personalized attention and engagement they deserve.

Learning HQ — from ai-disruptor-hq.notion.site

This HQ includes all of my AI guides, organized by tool/platform. This list is updated each time a new one is released, and outdated guides are removed/replaced over time.

How AI Is Reshaping Teachers’ Jobs — from edweek.org

Artificial intelligence is poised to fundamentally change the job of teaching. AI-powered tools can shave hours off the amount of time teachers spend grading, lesson-planning, and creating materials. AI can also enrich the lessons they deliver in the classroom and help them meet the varied needs of all students. And it can even help bolster teachers’ own professional growth and development.

Despite all the promise of AI, though, experts still urge caution as the technology continues to evolve. Ethical questions and practical concerns are bubbling to the surface, and not all teachers feel prepared to effectively and safely use AI.

In this special report, see how early-adopter teachers are using AI tools to transform their daily work, tackle some of the roadblocks to expanded use of the technology, and understand what’s on the horizon for the teaching profession in the age of artificial intelligence.

“Leadership & Generative AI: Hard-Earned Lessons That Matter” [Klitgaard Stricker] + other items re: AI in our learning ecosystems

On 01/22/2025, in 21st century, 24x7x365 access, adjunct faculty, adult learning, Artificial Intelligence/Agents/LLMs/and Related, change, cloud-based computing / apps / other cloud-related, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, education, education technology, emerging technologies, experimentation, faculty/staff, future, future of higher education, game-changing environment, generational differences, Google, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, leadership, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, library / librarians, lifelong learning, Michigan, microlearning, multimedia, Natural Language Processing (NLP), personalized/customized learning, platforms, productivity / tips and tricks, reading, research, strategy, student-related, teachers, teaching & learning, technologies for your home, tools, training / L&D, trends, United States, universities, vendors, writing, by Daniel Christian

Your AI Writing Partner: The 30-Day Book Framework — from aidisruptor.ai by Alex McFarland and Kamil Banc
How to Turn Your “Someday” Manuscript into a “Shipped” Project Using AI-Powered Prompts

With that out of the way, I prefer Claude.ai for writing. For larger projects like a book, create a Claude Project to keep all context in one place.

Copy [the following] prompts into a document
Use them in sequence as you write
Adjust the word counts and specifics as needed
Keep your responses for reference
Use the same prompt template for similar sections to maintain consistency

Each prompt builds on the previous one, creating a systematic approach to helping you write your book.

Using NotebookLM to Boost College Reading Comprehension — from michellekassorla.substack.com by Michelle Kassorla and Eugenia Novokshanova
This semester, we are using NotebookLM to help our students comprehend and engage with scholarly texts

We were looking hard for a new tool when Google released NotebookLM. Not only does Google allow unfettered use of this amazing tool, it is also a much better tool for the work we require in our courses. So, this semester, we have scrapped our “old” tools and added NotebookLM as the primary tool for our English Composition II courses (and we hope, fervently, that Google won’t decide to severely limit its free tier before this semester ends!)

If you know next-to-nothing about NotebookLM, that’s OK. What follows is the specific lesson we present to our students. We hope this will help you understand all you need to know about NotebookLM, and how to successfully integrate the tool into your own teaching this semester.

Leadership & Generative AI: Hard-Earned Lessons That Matter — from jeppestricker.substack.com by Jeppe Klitgaard Stricker
Actionable Advice for Higher Education Leaders in 2025

AFTER two years of working closely with leadership in multiple institutions, and delivering countless workshops, I’ve seen one thing repeatedly: the biggest challenge isn’t the technology itself, but how we lead through it. Here is some of my best advice to help you navigate generative AI with clarity and confidence:

Break your own AI policies before you implement them. …
Fund your failures. …
Resist the pilot program. …
Host Anti-Tech Tech Talks …
…+ several more tips

While generative AI in higher education obviously involves new technology, it’s much more about adopting a curious and human-centric approach in your institution and communities. It’s about empowering learners in new, human-oriented and innovative ways. It is, in a nutshell, about people adapting to new ways of doing things.

Maria Anderson responded to Clay’s posting with this idea:

Here’s an idea: […] the teacher can use the [most advanced] AI tool to generate a complete solution to “the problem” — whatever that is — and demonstrate how to do that in class. Give all the students access to the document with the results.

And then grade the students on a comprehensive followup activity / presentation of executing that solution (no notes, no more than 10 words on a slide). So the students all have access to the same deep AI result, but have to show they comprehend and can iterate on that result.

Grammarly just made it easier to prove the sources of your text in Google Docs — from zdnet.com by Jack Wallen
If you want to be diligent about proving your sources within Google Documents, Grammarly has a new feature you’ll want to use.

In this age of distrust, misinformation, and skepticism, you may wonder how to demonstrate your sources within a Google Document. Did you type it yourself, copy and paste it from a browser-based source, copy and paste it from an unknown source, or did it come from generative AI?

You may not think this is an important clarification, but if writing is a critical part of your livelihood or life, you will definitely want to demonstrate your sources.

That’s where the new Grammarly feature comes in.

The new feature is called Authorship, and according to Grammarly, “Grammarly Authorship is a set of features that helps users demonstrate their sources of text in a Google doc. When you activate Authorship within Google Docs, it proactively tracks the writing process as you write.”

AI Agents Are Coming to Higher Education — from govtech.com
AI agents are customizable tools with more decision-making power than chatbots. They have the potential to automate more tasks, and some schools have implemented them for administrative and educational purposes.

Custom GPTs are on the rise in education. Google’s version, Gemini Gems, includes a premade version called Learning Coach, and Microsoft announced last week a new agent addition to Copilot featuring use cases at educational institutions.

Generative Artificial Intelligence and Education: A Brief Ethical Reflection on Autonomy — from er.educause.edu by Vicki Strunk and James Willis
Given the widespread impacts of generative AI, looking at this technology through the lens of autonomy can help equip students for the workplaces of the present and of the future, while ensuring academic integrity for both students and instructors.

The principle of autonomy stresses that we should be free agents who can govern ourselves and who are able to make our own choices. This principle applies to AI in higher education because it raises serious questions about how, when, and whether AI should be used in varying contexts. Although we have only begun asking questions related to autonomy and many more remain to be asked, we hope that this serves as a starting place to consider the uses of AI in higher education.

Reflections on “The Rise of the Heretical Leader” [Fitzpatrick]

On 01/17/2025, in 21st century, Artificial Intelligence/Agents/LLMs/and Related, business side of he, change, changing business models, collaboration, colleges, communications, community colleges, curriculum, dangers of the status quo, Daniel S. Christian, education, education reform, emerging technologies, experimentation, faculty/staff, future of higher education, game-changing environment, generational differences, higher education, ideas, K-12 related, leadership, learning ecosystem, Learning from the Living [Class] Room, learning preferences, liberal arts, lifelong learning, MOOCs -- Massive Open Online Courses, more voice more choice more control, new business models, online learning, personalized/customized learning, reinvent, skills, society, staying relevant, strategy, student-related, surviving, teaching & learning, teaching online, United States, universities, vision/possibilities, by Daniel Christian

The Rise of the Heretical Leader — from ditchthattextbook.com; a guest post by Dan Fitzpatrick

Now is the time for visionary leadership in education. The era of artificial intelligence is reshaping the demands on education systems. Rigid policies, outdated curricula, and reliance on obsolete metrics are failing students. A recent survey from Resume Genius found that graduates lack skills in communication, collaboration, and critical thinking. Consequently, there is a growing trend in companies hiring candidates based on skills instead of traditional education or work experience. This underscores the urgent need for educational leaders to prioritize adaptability and innovation in their systems. Educational leaders must embrace a transformative approach to keep pace.
…
[Heretical leaders] bring courage, empathy, and strategic thinking to reimagine education’s potential. Here are their defining characteristics:

Visionary Thinking: They identify bold, innovative paths to progress.
Courage to Act: These leaders take calculated risks to overcome resistance and inertia.
Relentless Curiosity: They challenge assumptions and seek better alternatives.
Empathy for Stakeholders: Understanding the personal impact of change allows them to lead with compassion.
Strategic Disruption: Their deliberate actions ensure systemic improvements.
These qualities enable Heretical leaders to reframe challenges as opportunities and drive meaningful change.

From DSC:
Readers of this blog will recognize that I believe visionary leadership is extremely important — in all areas of our society, but especially within our learning ecosystems. Vision trumps data, at least in my mind. There are times when data can be used to support a vision, but having a powerful vision is more lasting and impactful than relying on data to drive the organization.

So while I’d vote for a different term other than “heretical leaders,” I get what Dan is saying and I agree with him. Such leaders are going against the grain. They are swimming upstream. They are espousing perspectives that others often don’t buy into (at least initially or for some time).

Such were the leaders who introduced online learning into the K-16 educational systems back in the late ’90s and into the next two+ decades. The growth of online-based learning continues and has helped educate millions of people. Those leaders and the people who worked for such endeavors were going against the grain.

We haven’t seen the end point of online-based learning. I think it will become even more powerful and impactful when AI is used to determine which jobs are opening up, and which skills are needed for those jobs, and then provide a listing of sources of where one can obtain that knowledge and develop those skills. People will be key in this vision. But so will AI and personalized learning. It will be a collaborative effort.

By the way, I am NOT advocating for using AI to outsource our thinking. Also, having basic facts and background knowledge in a domain is critically important, especially to use AI effectively. But we should be teaching students about AI (as we learn more about it ourselves). We should be working collaboratively with our students to understand how best to use AI. It’s their futures at stake.

“5 Ways Teachers Can Use NotebookLM Today” [Burns} + other items re: AI in our learning ecosystems

On 12/29/2024, in 21st century, 24x7x365 access, adjunct faculty, Artificial Intelligence/Agents/LLMs/and Related, Australia, change, cloud-based computing / apps / other cloud-related, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate universities / corporate training, digital audio, digital learning, digital video, education technology, emerging technologies, experimentation, faculty/staff, future, future of higher education, game-changing environment, generational differences, Google, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), innovation, intelligent systems, intelligent tutoring, IT in HE, K-12 related, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, liberal arts, library / librarians, lifelong learning, Open AI, personalized/customized learning, platforms, productivity / tips and tricks, skills, student-related, teachers, teaching & learning, technologies for your home, the downsides of how people use tech, tools, training / L&D, United States, universities, vendors, vision/possibilities, by Daniel Christian

How AI Is Changing Education: The Year’s Top 5 Stories — from edweek.org by Alyson Klein

Ever since a new revolutionary version of chat ChatGPT became operable in late 2022, educators have faced several complex challenges as they learn how to navigate artificial intelligence systems.
…
Education Week produced a significant amount of coverage in 2024 exploring these and other critical questions involving the understanding and use of AI.

Here are the five most popular stories that Education Week published in 2024 about AI in schools.

What’s next with AI in higher education? — from msn.com by Science X Staff

Dr. Lodge said there are five key areas the higher education sector needs to address to adapt to the use of AI:

1. Teach ‘people’ skills as well as tech skills
2. Help all students use new tech
3. Prepare students for the jobs of the future
4. Learn to make sense of complex information
5. Universities to lead the tech change

5 Ways Teachers Can Use NotebookLM Today — from classtechtips.com by Dr. Monica Burns

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