NotebookLM is one of my favorite AI tools for reading scholarly articles. — from linkedin.com by Med Kharbach, PhD
On 07/19/2025,
in change, changing business models, colleges, faculty/staff, future of higher education, game-changing environment, global, higher education, learning ecosystem, United States, universities,
by Daniel Christian
A 20% decline in new international student enrollment could cost U.S. colleges & universities over $1.7 billion in annual tuition revenue — from linkedin.com by Paxton Riter
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On 07/12/2025,
in Artificial Intelligence/Agents/LLMs/and Related, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, education, education technology, faculty/staff, future of higher education, game-changing environment, generational differences, higher education, human-computer interaction (HCI), instructional design, intelligent systems, IT in HE, learning ecosystem, Learning Experience Design, liberal arts, Microsoft, Open AI, parents/guardians, pedagogy, productivity / tips and tricks, professional development, teachers, teaching & learning, tools, training / L&D, United States, universities, using teams, vendors, writing,
by Daniel Christian
Tech check: Innovation in motion: How AI is rewiring L&D workflows — from chieflearningofficer.com by Gabrielle Pike
AI isn’t here to replace us. It’s here to level us up.
For today’s chief learning officer, the days of just rolling out compliance training are long gone. In 2025, learning and development leaders are architects of innovation, crafting ecosystems that are agile, automated and AI-infused. This quarter’s Tech Check invites us to pause, assess and get strategic about where tech is taking us. Because the goal isn’t more tools—it’s smarter, more human learning systems that scale with the business.
Sections include:
- The state of AI in L&D: Hype vs. reality
- AI in design: From static content to dynamic experiences
- AI in development: Redefining production workflows
- Strategic questions CLOs should be asking
- Future forward: What’s next?
- Closing thought
NEW YORK – The AFT, alongside the United Federation of Teachers and lead partner Microsoft Corp., founding partner OpenAI, and Anthropic, announced the launch of the National Academy for AI Instruction today. The groundbreaking $23 million education initiative will provide access to free AI training and curriculum for all 1.8 million members of the AFT, starting with K-12 educators. It will be based at a state-of-the-art bricks-and-mortar Manhattan facility designed to transform how artificial intelligence is taught and integrated into classrooms across the United States.
The academy will help address the gap in structured, accessible AI training and provide a national model for AI-integrated curriculum and teaching that puts educators in the driver’s seat.
Students Are Anxious about the Future with A.I. Their Parents Are, Too. — from educationnext.org by Michael B. Horn
The fast-growing technology is pushing families to rethink the value of college
In an era when the college-going rate of high school graduates has dropped from an all-time high of 70 percent in 2016 to roughly 62 percent now, AI seems to be heightening the anxieties about the value of college.
According to the survey, two-thirds of parents say AI is impacting their view of the value of college. Thirty-seven percent of parents indicate they are now scrutinizing college’s “career-placement outcomes”; 36 percent say they are looking at a college’s “AI-skills curriculum,” while 35 percent respond that a “human-skills emphasis” is important to them.
This echoes what I increasingly hear from college leadership: Parents and students demand to see a difference between what they are getting from a college and what they could be “learning from AI.”
This next item on LinkedIn is compliments of Ray Schroeder:
How to Prepare Students for a Fast-Moving (AI)World — from rdene915.com by Dr. Rachelle Dené Poth
Preparing for a Future-Ready Classroom
Here are the core components I focus on to prepare students:
1. Unleash Creativity and Problem-Solving.
2. Weave in AI and Computational Thinking.
3. Cultivate Resilience and Adaptability.
AI Is Reshaping Learning Roles—Here’s How to Future-Proof Your Team — from onlinelearningconsortium.org by Jennifer Mathes, Ph.D., CEO, Online Learning Consortium; via Robert Gibson on LinkedIn
Culture matters here. Organizations that foster psychological safety—where experimentation is welcomed and mistakes are treated as learning—are making the most progress. When leaders model curiosity, share what they’re trying, and invite open dialogue, teams follow suit. Small tests become shared wins. Shared wins build momentum.
Career development must be part of this equation. As roles evolve, people will need pathways forward. Some will shift into new specialties. Others may leave familiar roles for entirely new ones. Making space for that evolution—through upskilling, mobility, and mentorship—shows your people that you’re not just investing in AI, you’re investing in them.
And above all, people need transparency. Teams don’t expect perfection. But they do need clarity. They need to understand what’s changing, why it matters, and how they’ll be supported through it. That kind of trust-building communication is the foundation for any successful change.
These shifts may play out differently across sectors—but the core leadership questions will likely be similar.
AI marks a turning point—not just for technology, but for how we prepare our people to lead through disruption and shape the future of learning.
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On 07/11/2025,
in Africa, business, career development, change, collaboration, colleges, communities of practice, community colleges, corporate / business world, curriculum, entrepreneurship, experimentation, faculty/staff, higher education, ideas, India, teaching & learning, United States, universities,
by Daniel Christian
Is graduate employability a core university priority? — from timeshighereducation.com by Katherine Emms and Andrea Laczik
Universities, once judged primarily on the quality of their academic outcomes, are now also expected to prepare students for the workplace. Here’s how higher education is adapting to changing pressures
A clear, deliberate shift in priorities is under way. Embedding employability is central to an Edge Foundation report, carried out in collaboration with UCL’s Institute of Education, looking at how English universities are responding. In placing employability at the centre of their strategies – not just for professional courses but across all disciplines – the two universities that were analysed in this research show how they aim to prepare students for the labour market overall. Although the employability strategy is initialled by the universities’ senior leaders, the research showed that realising this employability strategy must be understood and executed by staff at all levels across departments. The complexity of offering insights into industry pathways and building relevant skills involves curricula development, student-centred teaching, careers support, partnership work and employer engagement.
Every student can benefit from an entrepreneurial mindset — from timeshighereducation.com by Nicolas Klotz
To develop the next generation of entrepreneurs, universities need to nurture the right mindset in students of all disciplines. Follow these tips to embed entrepreneurial education
This shift demands a radical rethink of how we approach entrepreneurial mindset in higher education. Not as a specialism for a niche group of business students but as a core competency that every student, in every discipline, can benefit from.
At my university, we’ve spent the past several years re-engineering how we embed entrepreneurship into daily student life and learning.
What we’ve learned could help other institutions, especially smaller or resource-constrained ones, adapt to this new landscape.
The first step is recognising that entrepreneurship is not only about launching start-ups for profit. It’s about nurturing a mindset that values initiative, problem-solving, resilience and creative risk-taking. Employers increasingly want these traits, whether the student is applying for a traditional job or proposing their own venture.
Build foundations for university-industry partnerships in 90 days— from timeshighereducation.com by Raul Villamarin Rodriguez and Hemachandran K
Graduate employability could be transformed through systematic integration of industry partnerships. This practical guide offers a framework for change in Indian universities
The most effective transformation strategy for Indian universities lies in systematic industry integration that moves beyond superficial partnerships and towards deep curriculum collaboration. Rather than hoping market alignment will occur naturally, institutions must reverse-engineer academic programmes from verified industry needs.
Our six-month implementation at Woxsen University demonstrates this framework’s practical effectiveness, achieving more than 130 industry partnerships, 100 per cent faculty participation in transformation training, and 75 per cent of students receiving industry-validated credentials with significantly improved employment outcomes.
On 07/11/2025,
in 21st century, career development, change, changing business models, cloud-based computing / apps / other cloud-related, colleges, community colleges, computer science, corporate / business world, curriculum, emerging technologies, experimentation, faculty/staff, game-changing environment, higher education, human-computer interaction (HCI), innovation, instructional design, learning ecosystem, Learning Experience Design, new business models, programming, teaching & learning, tools, United States, universities,
by Daniel Christian
How Do You Teach Computer Science in the A.I. Era? — from nytimes.com by Steve Lohr; with thanks to Ryan Craig for this resource
Universities across the country are scrambling to understand the implications of generative A.I.’s transformation of technology.
The future of computer science education, Dr. Maher said, is likely to focus less on coding and more on computational thinking and A.I. literacy. Computational thinking involves breaking down problems into smaller tasks, developing step-by-step solutions and using data to reach evidence-based conclusions.
A.I. literacy is an understanding — at varying depths for students at different levels — of how A.I. works, how to use it responsibly and how it is affecting society. Nurturing informed skepticism, she said, should be a goal.
At Carnegie Mellon, as faculty members prepare for their gathering, Dr. Cortina said his own view was that the coursework should include instruction in the traditional basics of computing and A.I. principles, followed by plenty of hands-on experience designing software using the new tools.
“We think that’s where it’s going,” he said. “But do we need a more profound change in the curriculum?”
On 06/25/2025,
in collaboration, Emotion, face-to-face, faculty/staff, faith, health, hearts -- matters of the heart, relationships, society, teachers,
by Daniel Christian
Live Your Creed, Langston Hughes — via a recent e-newsletter from Getting Smart
I’d rather see a sermon than to hear one any day.
I’d rather one walk with me than just to show the way.
The eye is a better pupil and more willing than the ear.
Advice may be misleading but examples are always clear.
And the very best of teachers are the ones who live their
creed,
For to see good put into action is what everybody needs.
I can soon learn to do it if you let me see it done.
I can watch your hand in motion but your tongue too fast
may run
And the lectures you deliver may be very fine and true
But I’d rather get my lesson by observing what you do.
For I may misunderstand you and the fine advice you give
But there’s no misunderstanding how you act and how
you live.
On 06/23/2025,
in 21st century, 24x7x365 access, adjunct faculty, adult learning, Artificial Intelligence/Agents/LLMs/and Related, bots, change, cloud-based computing / apps / other cloud-related, CMS/LMS, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, digital video, education, education technology, emerging technologies, engagement / engaging students, experimentation, face-to-face, faculty/staff, game-changing environment, Google, heutagogy, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, law schools, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, liberal arts, library / librarians, lifelong learning, memory, metacognition / metacognitive skills, multimedia, Natural Language Processing (NLP), new media literacies, online learning, online media, Open AI, personalized/customized learning, platforms, productivity / tips and tricks, professional development, student-related, teachers, teaching & learning, teaching online, technologies for your home, tools, traditional / tradition, training / L&D, trends, United States, universities, user experience (UX), vendors, vision/possibilities, writing,
by Daniel Christian
Thoughts on thinking — from dcurt.is by Dustin Curtis
Intellectual rigor comes from the journey: the dead ends, the uncertainty, and the internal debate. Skip that, and you might still get the insight–but you’ll have lost the infrastructure for meaningful understanding. Learning by reading LLM output is cheap. Real exercise for your mind comes from building the output yourself.
The irony is that I now know more than I ever would have before AI. But I feel slightly dumber. A bit more dull. LLMs give me finished thoughts, polished and convincing, but none of the intellectual growth that comes from developing them myself.
Using AI Right Now: A Quick Guide — from oneusefulthing.org by Ethan Mollick
Which AIs to use, and how to use them
Every few months I put together a guide on which AI system to use. Since I last wrote my guide, however, there has been a subtle but important shift in how the major AI products work. Increasingly, it isn’t about the best model, it is about the best overall system for most people. The good news is that picking an AI is easier than ever and you have three excellent choices. The challenge is that these systems are getting really complex to understand. I am going to try and help a bit with both.
First, the easy stuff.
Which AI to Use
For most people who want to use AI seriously, you should pick one of three systems: Claude from Anthropic, Google’s Gemini, and OpenAI’s ChatGPT.
Also see:
Student Voice, Socratic AI, and the Art of Weaving a Quote — from elmartinsen.substack.com by Eric Lars Martinsen
How a custom bot helps students turn source quotes into personal insight—and share it with others
This summer, I tried something new in my fully online, asynchronous college writing course. These classes have no Zoom sessions. No in-person check-ins. Just students, Canvas, and a lot of thoughtful design behind the scenes.
One activity I created was called QuoteWeaver—a PlayLab bot that helps students do more than just insert a quote into their writing.
It’s a structured, reflective activity that mimics something closer to an in-person 1:1 conference or a small group quote workshop—but in an asynchronous format, available anytime. In other words, it’s using AI not to speed students up, but to slow them down.
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The bot begins with a single quote that the student has found through their own research. From there, it acts like a patient writing coach, asking open-ended, Socratic questions such as:
What made this quote stand out to you?
How would you explain it in your own words?
What assumptions or values does the author seem to hold?
How does this quote deepen your understanding of your topic?
It doesn’t move on too quickly. In fact, it often rephrases and repeats, nudging the student to go a layer deeper.
The Disappearance of the Unclear Question — from jeppestricker.substack.com Jeppe Klitgaard Stricker
New Piece for UNESCO Education Futures
On [6/13/25], UNESCO published a piece I co-authored with Victoria Livingstone at Johns Hopkins University Press. It’s called The Disappearance of the Unclear Question, and it’s part of the ongoing UNESCO Education Futures series – an initiative I appreciate for its thoughtfulness and depth on questions of generative AI and the future of learning.
Our piece raises a small but important red flag. Generative AI is changing how students approach academic questions, and one unexpected side effect is that unclear questions – for centuries a trademark of deep thinking – may be beginning to disappear. Not because they lack value, but because they don’t always work well with generative AI. Quietly and unintentionally, students (and teachers) may find themselves gradually avoiding them altogether.
Of course, that would be a mistake.
We’re not arguing against using generative AI in education. Quite the opposite. But we do propose that higher education needs a two-phase mindset when working with this technology: one that recognizes what AI is good at, and one that insists on preserving the ambiguity and friction that learning actually requires to be successful.
Leveraging GenAI to Transform a Traditional Instructional Video into Engaging Short Video Lectures — from er.educause.edu by Hua Zheng
By leveraging generative artificial intelligence to convert lengthy instructional videos into micro-lectures, educators can enhance efficiency while delivering more engaging and personalized learning experiences.
This AI Model Never Stops Learning — from link.wired.com by Will Knight
Researchers at Massachusetts Institute of Technology (MIT) have now devised a way for LLMs to keep improving by tweaking their own parameters in response to useful new information.
The work is a step toward building artificial intelligence models that learn continually—a long-standing goal of the field and something that will be crucial if machines are to ever more faithfully mimic human intelligence. In the meantime, it could give us chatbots and other AI tools that are better able to incorporate new information including a user’s interests and preferences.
The MIT scheme, called Self Adapting Language Models (SEAL), involves having an LLM learn to generate its own synthetic training data and update procedure based on the input it receives.
Edu-Snippets — from scienceoflearning.substack.com by Nidhi Sachdeva and Jim Hewitt
Why knowledge matters in the age of AI; What happens to learners’ neural activity with prolonged use of LLMs for writing
Highlights:
- Offloading knowledge to Artificial Intelligence (AI) weakens memory, disrupts memory formation, and erodes the deep thinking our brains need to learn.
- Prolonged use of ChatGPT in writing lowers neural engagement, impairs memory recall, and accumulates cognitive debt that isn’t easily reversed.
On 06/11/2025,
in adjunct faculty, business side of he, career development, change, colleges, community colleges, Emotion, face-to-face, faculty/staff, future, higher education, ideas, law schools, leadership, podcasting, teaching & learning, United States, universities,
by Daniel Christian
Navigating Career Transitions — from er.educause.edu by Jay James, Mike Richichi, Sarah Buszka, and Wes Johnson
In this episode, we hear from professionals at different stages of their career journeys as they reflect on risk, resilience, and growth. They share advice on stepping into leadership roles, recognizing when it may be time for a change, and overcoming imposter syndrome.
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