The Law School Deans Driving AI Innovation in Legal Education — from natlawreview.com by Shivani Vedhere, AI & the Law Newsletter; via Colin S. Levy

Artificial intelligence is no longer a peripheral issue for legal education. It is quickly becoming one of the central questions facing law schools: how to prepare future lawyers for a profession in which AI will affect research, client counseling, litigation strategy, access to justice, and the business of law.

For decades, law schools treated legal technology as an elective or a niche interest for students already inclined toward innovation. That era is ending. Law firms are adopting AI tools at scale and even investing in developing their own tools. Clients are asking harder questions about efficiency, cost, and competence. Courts are sanctioning lawyers and litigants for AI-generated hallucinations, with the number of identified cases in the United States now exceeding 1,000. Students entering the profession will be expected to keep up with this rapidly changing landscape.

The most forward-looking law schools are responding accordingly. That transformation is being driven in large part by a group of innovative law school deans who are treating AI not as a passing trend, but as a structural change in legal education.

These initiatives signal a broader shift in legal academia where law schools are no longer merely debating whether AI belongs in the curriculum. The more pressing question is how deeply, how early, and how responsibly AI should be integrated into legal education.

 

Flipped Classrooms and Academic Achievement — from learningscientists.org by Megan Sumeracki

There are actually many, many ways to design a flipped classroom, and it has been fascinating to learn about the ways my colleague typically structures her hybrid, flipped-classroom courses. As a result, we’ve been able to engage in really interesting conversations about the best approach for this particular course, and why. As a result of some of these discussions, I came across a few recent meta-analyses related to the effects of flipped classrooms, the results of which I thought were worth sharing here (1, 2, 3).

 

 

Higher Education Can’t Wait for the Future to Arrive (Lev Gonick, Arizona State University) — from humanistxyz.substack.com by Allison Dulin Salisbury
“The biggest risk we face as a sector is assuming we can wait out AI.”

We have an opportunity right now to reorient the university around student experience—not as an aspiration, but as a necessity. I’m calling this shift TechEd, which I explore in detail in my LinkedIn series The TechEd Revolution.

AI poses a fundamental shift in how technology might empower students to own their discovery and educational journey, and to drastically reduce the friction that makes college so unappealing to so many.

To that end, we need to urgently redesign systems and opportunities around skills and competencies. That work should be far more advanced than it currently is. And one of the hardest challenges is rethinking how we operate as a workforce in academia. 

 
 

Will learning curated by employers replace degrees? — from universityworldnews.com by Louise Nicol

If universities do not future-proof their offer through deeper and more credible partnerships with employers and industry, what exactly prevents employers from educating and training people themselves?

This is why the future of higher education depends on far deeper and more operational partnerships with industry. Not symbolic advisory boards or occasional guest lectures but genuine co-design of curricula, shared ownership of applied projects and clear accountability for graduate capability.

Universities that integrate live industry problems, cross-faculty collaboration and work-based learning into the core of their programmes make themselves harder to replace. Those that acknowledge the existence of external learning platforms and deliberately build them into a broader educational journey strengthen rather than weaken their position.

The real risk for universities is not replacement but marginalisation. Employers will not abandon universities out of hostility or ideology. They will do so pragmatically if universities fail to add distinctive value beyond what employers can now deliver themselves.

 

The Current State of Play: AI in Higher Education and the Road Ahead — from er.educause.edu by Tanya Gamby, David Kil, Rachel Koblic, Paul LeBlanc, Mihnea Moldoveanu and George Siemens

The conventional explanation for this strategic vacuum points to the speed of technological change; it is moving too fast for institutions built for deliberation. That is true. . . and incomplete. The deeper issue is cultural. In fairness to higher education, many industries are struggling to keep up with the pace of AI advances. Higher education, however, moves even more slowly and is not built for the kind of transformational speed now underway. Getting institutional stakeholders to engage, rethink the work, and move faster may be the central challenge facing presidents and chancellors today, and that’s saying a lot in such volatile times.

From DSC:
I highlighted this paragraph because it hits upon the key item involved here — culture. “The deeper issue is cultural.” I think that’s a very true statement.

Part of the culture and setup of many institutions includes giving faculty members full rein of their classes and their departments. Faculty members have a great deal of leeway and power in how they do things. So trying to get X faculty members to get on board — including the Department Chairs — is not an easy task. 

Another part of culture involves being willing — or not — to change in the first place. Some institutions are like Google and are used to making changes and being more innovative. But those institutions are not the norm, at least in my experience. And this doesn’t even address another topic the article mentioned — the pace of these changes. As the authors point out, most institutions of traditional higher education are not equipped to deal with the current pace of change (nor are most of our other types of institutions and our corporations as well). 

I’m going to end this posting with another brief excerpt from the article:

Institutions rooted in human relationships, committed to truth-seeking, and oriented toward the full development of persons play a central role. AI cannot manufacture the experience of mattering to another human being. It cannot model intellectual courage or ethical discernment. It cannot build the kind of community in which students discover who they are and what they believe.

These are not small things. They are, in fact, the things most worth doing. At their best, colleges and universities are not only preparing better workers but shaping individuals and strengthening society.

 

From DSC:
I used to be able to bring up Firefly on the web and use it “free” of charge — I didn’t have to go purchase tokens or credits. (I was actually paying for the Adobe Creative Cloud Pro suite of tools…so it wasn’t really free.)

But the other day I was trying to figure out what the latest pricing is at Adobe with that suite of tools and the use of credits for AI-based features. They say Adobe Creative Cloud Pro users get 4000 credits a month. Well, I have that suite and I’m still getting prompted to purchase credits. Firefly for individuals runs from $9.99 (2,000 credits/month) to $139.91 per month (50,000 credits per month). Not inexpensive, right? Below are other items along these lines.


The Era of Affordable AI Is Over. What Comes Next? — from builtin.com by Ameya Kanitkar
AI providers are shifting to usage-based billing for their services. AI fluency is more important now than ever to make the most of your tools to avoid unnecessary spending.

Summary: The era of cheap, flat-rate AI is ending as providers shift to usage-based billing. Every prompt now carries a direct cost, turning casual use into major budget risks, as seen when Uber depleted its 2026 AI budget in four months. Leaders must now track real-time value and token efficiency.

For a brief window, companies had access to the most transformative technology in a generation at the cost of a streaming subscription. Tools like ChatGPT put AI within reach of anyone with a browser and time for experimentation, while GitHub Copilot came in at just $10 a month, with token costs remaining relatively low. In the beginning, experimentation felt cost-effective, easy and relatively low-risk. 

But that era is ending, and the bill is coming due faster than a lot of enterprise leaders anticipated. 


The Fable of AI in Education — from downes.ca by Stephen Downes
Marc Watkins, Rhetorica, Jun 17, 2026

Tokenomics will be a hot topic of discussion on university campuses because, as Marc Watkins notes in this article, there is no realistic path forward to providing all students with access to advanced AI.


From this posting on LinkedIn.com from Dr. Nick Jackson:

And now there is a third layer emerging. Institutions are waking up to a systems-level question they are likely not remotely prepared for. Who pays for AI? How are budgets managed when there are unclear token consumption pricing models? How is AI procured? Who decides what tools get used and by whom and who gets access and at what level?

.


 

What a disco ball teaches us about learning and leadership — from timeshighereducation.com by Lauren Flannery
By acknowledging that perspectives are evolving and relational, educators and leaders can encourage contribution and connection without sacrificing what makes people distinct

It also shows us that difference does not always need to be resolved. In teaching, learning and leadership, the aim is not to create uniformity but to create conditions in which different people can contribute, connect and shine without losing what makes them distinct.

In classrooms, inclusion is sometimes approached as ensuring access to the same knowledge, resources and opportunities for all students. The beach ball helps here: it encourages us to explore multiple perspectives. But the disco ball pushes us further to explore how learning environments can support students to bring their experiences, identities and knowledge into the room – not to smooth them out but to draw from them.

Designing for multiple perspectives also means recognising that expressing an opinion is not only about confidence; it is also about conditions. People are more likely to speak when they feel their contribution will be heard without being dismissed, appropriated or flattened. Creating those conditions may involve discussing uncertainty, welcoming challenge, slowing down decision-making or making space for quieter forms of participation. The aim is not to make everyone agree, but to allow different reflections to interact in ways that generate richer understanding.

 

If AI Eats the Entry-Level Job, Where Do Young People Learn to Work? (Ryan Craig, Achieve Partners) — from humanistxyz.substack.com by Allison Dulin Salisbury; via Ryan Craig
“The public should not be subsidizing colleges whose students lack relevant, paid, in-field work experience.”

That is the trap at the center of this conversation: everyone wants to hire someone with three years of experience, and almost no one wants to provide those three years.

And Ryan’s policy prescription is unusually concrete: pay employers to hire and train apprentices, following the countries that have scaled apprenticeship far faster than the U.S.; require colleges receiving federal student aid to provide relevant, paid, in-field work experience; and build a market of intermediaries that can make the whole thing operational.

Ryan’s view is that higher education remains critically important. But college without meaningful work experience may become a much worse bet, especially for students who cannot afford to guess wrong.

 

A screenplay written by a Calvin Prison Initiative student while incarcerated is now screening at film festivals across the country. — from linkedin.com by the Calvin Prison Initiative


From DSC:
I used to work with Calvin film and media professor Geert Heetebrij — who was behind this endeavor. I went to the same church that he and his family attended. I can’t say enough good things about him. He’s just fantastic! By the way, he was there for me when twelve of us didn’t survive the fourth round of layoffs at Calvin (back then it was Calvin College). He periodically — but consistently — checked in on me as the job search continued. He prayed for me (and for my family). His steadfast encouragement meant a lot to me.

I also worked with Sam Smartt, who was also mentioned in the article. Go Geert! Go Sam! And go Calvin for continuing to do your prison ministries! You were one of the first to do this, if not thee first.


 

 

Two years ago, AI broke assessment. Now, it’s helping us to reinvent it. — from linkedin.com by Dr. Philippa Hardman


Also from Dr. Hardman, see:


A new study shows AI helped deliver 1.5 years of maths progress in 8 weeks — here’s how. — from linkedin.com by Dr. Philippa Hardman

…a new study shows AI helped deliver 1.5 years of maths progress in 8 weeks — here’s how.

Google DeepMind just shared the results of a randomised trial involving 1,763 students. Half used Gemini’s “Guided Learning” to learn maths; half didn’t.

The result: the group working with AI gained the equivalent of 1.2 to 1.7 years of extra progress compared to those who didn’t.

It’s tempting to read this as “Gemini’s Guided Learning mode works!” But the key point here is that Gemini didn’t work alone….

Look closer, and what made the difference wasn’t just the tech — it was a great teacher making expert use of it.

 

The Tyranny of College Admissions: Why It’s So Challenging to Have Real Change in K-12 Education — from gettingsmart.com by Jon Alfuth

Key Points

  • College admissions policy shapes K-12 practice. If colleges continue to privilege course sequences, seat time, and grades, high schools will remain constrained in how far they can move toward competency-based learning.
  • States and institutions already offer models for change. Wisconsin, Colorado, Indiana, and pilots like CUNY and Michigan Ross show that admissions can incorporate portfolios, demonstrations of learning, and durable skills.

If we could instead orient K-12 education around skill development and application rather than Carnegie Units and grades, we could create a new paradigm for where, when and how students demonstrate college and career readiness. Competency-based education moves schools and systems towards this desirable future that balances knowledge with skills. 

Despite tremendous evidence of its potential, efforts to accelerate this shift have been stymied by the tyranny of college admissions requirements and processes. Parents, teachers, administrators and policymakers end up in a quandary. Anyone attempting to shift away from this traditional course sequence is criticized as trying to lock kids out of higher education and we snap back to the way things have always been done. 

 

Why Students Aren’t All In on AI—And What They Want From Colleges — from insidehighered.com by  Colleen Flaherty
New Student Voice data reveal students are embracing AI as a learning tool while worrying about dependence, career disruption and inconsistent institutional responses.

Read on for six takeaways from the survey and additional insights—including how institutions can start to close the gap between students’ optimism about AI as a learning tool and their faith in their colleges’ ability to help them navigate change.

Takeaway 1: More students are using AI than ever for coursework, while a significant share—20 percent—remain resisters.

Takeaway 2: “Worried about dependence” is the most common student stance on AI.

Takeaway 3: A majority of all students expect AI to somewhat (39 percent) or very (16 percent) negatively impact their career prospects.

Takeaway 4: Just one in 10 students says that their institution is handling AI’s rise very well, in a thoughtful and proactive way.

…and more >>

 

 
 
 
© 2025 | Daniel Christian