The 5 college majors students are betting on right now — from linkedin.com by Taylor Border
From MLive.com’s John Hiner — in his Letter from the Editor dated 8/6/26:
40 years of change taught me this: It’s never really been about the technology
What I’ve learned over 40 years is that people rarely resist change because they dislike innovation. More often, it’s because they’re worried they’ll lose something they value.
What Nobody Warns You About Teaching College for the First Time — from facultyfocus.com by Christopher Morales; this article is behind a firewall
What became clear throughout these conversations was that secondary and postsecondary education often prioritize very different instructional skill sets.
In K–12 education, teachers frequently receive formal preparation in:
- classroom management,
- scaffolding,
- differentiation,
- assessment design,
- engagement strategies,
- and developmental learning theory.
In higher education, disciplinary expertise is often treated as the primary qualification for teaching.
Yet many instructors pointed out that expertise alone does not automatically translate into effective instruction.
Also from Faculty Focus, see:
The Syllabus and the Scar Tissue: What Leadership Preparation Programs Leave Out and Why It Matters — from facultyfocus.com Andy Szeto, EdD; this article is also behind a firewall
The 2031 Crisis in Higher Education: a stark scenario — from bryanalexander.org by Bryan Alexander — with commentary on a posting by Matthew F. Wilson, Ph.D.
Today’s post is about a scenario for higher ed’s future. It’s not from me, but created by one Matthew F. Wilson, director of Research Translation and AI Strategy at Baylor’s Institute for Global Human Flourishing. “The 2031 Crisis in Higher Education” is a dark one, imagining an accelerating decline for American colleges and universities.
…
One key assumption of this scenario is that most colleges and universities will be unable to redesign themselves for the changing time.
…
All of that said, it’s a fascinating and daunting scenario. It’s an interesting vision of my post-peak higher ed world.
A graphic from Matthew Wilson:
From DSC:
From what I can tell and have read, the things in the above graphic are already happening — and have been happening for some time now.
Also, I don’t think traditional institutions of higher education have the culture(s) it takes to change. So that part about colleges and U’s not being able to redesign themselves for the changing times could easily turn out to be the case.
Why AI Is Changing What It Means to Be Intelligent — from facultyfocus.com by Lydia Elliott, EdD; article may be behind a paywall
Practical adjustments may include:
- oral explanations of written work
- case-based or scenario-based exercises
- reflective reasoning assignments
- feedback conversations
- requiring students to justify decisions
These approaches do not eliminate AI. They place learning where AI cannot substitute:
Digital Accessibility Lawsuits in 2026: Five Trends Companies Should Know — from blog.usablenet.com
Here are five findings companies should understand, along with practical steps for reducing risk.
1. Digital accessibility lawsuits are on pace to reach 6,000
2. Where a company sells matters more than where it is headquartered
3. E-commerce remains the primary target
…and more
From DSC:
Below is an item on futures thinking. Don’t blow this off. This topic — and skill/strategy — is important not only to traditional institutions of higher education, but also to businesses and organizations of all sizes. In fact, even students can practice developing a list of potential scenarios and implement their plans of action if one of those scenarios occurs.
Why Engineering Is No Longer A Sure Thing College Major When It Comes To Jobs — from forbes.com by Courtney Connley-Hampton; this article is behind a paywall
Exclusive LinkedIn data shows engineering majors have been hit hard in today’s weak, AI-affected job market. Here’s what specialties are hurting and what top schools are doing to respond.
While lots of recent college graduates are being battered by a weak hiring market, perhaps no group is more shocked by their current plight than those who majored in engineering, long considered among the safest, most secure, and highest-paying majors. Yes, engineering grads still make more than education and English majors.
Also relevant/see:
AI & Accessibility: 5 Practical Ways to Use LLMs to Support Inclusive Learning — from learningguild.com by Dr. Athena Joyce Stanley (B.A., M.A.E., Ph.D.)
The following strategies focus on how instructional designers can design for accessibility by embedding or enabling AI-supported tools within learning experiences. These approaches move beyond access to content and begin to support access to understanding, expression, and participation.
…
Personalized Clarification Through AI Copilots
Learners often need additional explanation, but may hesitate to ask questions in live sessions or require more individualized support.
Instructional designers can integrate AI copilots, LLM-powered conversational interfaces, into learning environments to provide on-demand clarification. These tools can act as digital coaches, helping learners understand concepts through simplified explanations and relevant examples.
This approach supports learners who benefit from additional processing time and personalized guidance.
Sample Prompt (for IDs Configuring Copilot Behavior)
You are a workplace learning coach.
Explain the following concept in a clear, simple way:
-
- Use plain language
- Provide one practical, job-relevant example
- Avoid jargon unless necessary (and define it if used)
Then ask one follow-up question to check for understanding.
Teaching AI Literacy with Susan Ray — from intentionalteaching.buzzsprout.com by Derek Bruff and Susan Ray
Per Derek Bruff:
In my conversation with Susan, we talk about that syllabus activity, as well as the AI transparency journals she asks her students to keep during her courses. We also talk about how her personal background prepared her to navigate the challenges and opportunities that AI has posed to her teaching, how she approaches assessing student learning in this age of AI—especially in her online asynchronous courses—and much more.
Building the AI-Native University: Student Success and Lifelong Learning — from coursera.org
In this episode, you’ll discover:
- Why building an AI-native campus requires a data-first foundation
- How to build an “achievement architecture” for lifelong success
- How faculty-built AI tutors cut one program’s course attrition from 40% to 10%
- What it means to be a lifelong learning companion
We’re Raising the First AI Generation. They’re Pushing Back. (Rebecca Winthrop, Brookings) — from humanistxyz.substack.com by Allison Dulin Salisbury
“Young people harbor real anger about AI because they’re already experiencing its consequences in their schools, relationships, job prospects, and feeds.”
As Rebecca told me:
“Kids harbor real anger. They’re pissed about climate impacts. They’re upset about job prospects. They’re outraged about AI being used to plagiarize writing and produce counterfeit artwork. Their relationships are being affected, and they’re seeing deepfakes in their feeds.”
Our conversation explores what follows from taking those concerns seriously. We discuss cognitive stunting, the case for small, purpose-built AI models over frontier models in education, why students should spend far more time in explorer mode, and how schools can cultivate agency, curiosity, and independent thinking in an age of AI.
The interview ends with one of Rebecca’s most practical recommendations: every school should have a student AI council, not as a symbolic gesture, but with real influence over the tools their schools adopt, the ways they’re used, and the data students are asked to hand over.
Every generation of technology seems to relearn the same lesson: build with people, not for them. AI should be no exception.
Microsoft Discovery Platform Brings Agentic AI to Scientific Research — from campustechnology.com by Chris Paoli
Key Takeaways
- Microsoft Discovery reaches general availability, bringing agentic AI to scientific research and development workflows.
- AI agents support hypothesis generation, experimentation, data analysis, and knowledge management at scale.
- New Discovery app preview enables researchers to explore AI-driven scientific discovery with lower adoption barriers.
Why recruiters can’t find workers and new grads can’t find jobs (it’s not AI) — from washingtonpost.com by Jon Marcus
Experts say a major labor shortage looms because of population shifts and a mismatch between new graduates’ skills and employers’ needs.
Recent college graduates complain they can’t find entry-level jobs because artificial intelligence is taking over.
Yet, tech recruiter Matt Walsh and other experts say the growth of AI and the struggle to find entry-level work mask a bigger problem: The United States is facing what’s projected to become the largest labor shortage in its history.
In sectors such as semiconductor production, the problem isn’t AI or too few jobs, said Walsh, CEO of the Phoenix-based search firm Blue Signal.
“It’s ridiculous,” he said. “There just aren’t enough people.”
Economists warn that the worsening labor problem, due in part to a skills shortage and population shifts, will be vast and reach beyond tech.
Among the trends that have been leading to this moment: a mismatch between the careers college graduates are pursuing and the jobs employers are struggling to fill. Far fewer students are majoring in health care fields than are needed to meet demand, for instance.
“We have pumped so many young people into business and finance” when what’s really in demand are graduates in other fields, Hetrick said. “It’s like a factory producing these workers like widgets, even though society is saying, ‘We really don’t need them.’ And the factory just keeps pumping them out.”
“Teachers ban it. Employers demand it.”
Also relevant/see:
The Shifting Career Ladder — from nafez.substack.com by Nafez Dakkak
AI is changing how work works and quietly removing the pathways through which young people learn to become experts.
AI is reshaping how people build skills, enter professions, and move along the career ladder and through the labour market.
In this conversation, I sit down with Matt Sigelmen founder of LightCast and now the President of Burning Glass Institute. Matt has dedicated his career to understanding the labor market and helping society improve the connections within in it.
Matt and I explore why people and opportunities are often only “a few skills apart,” why entry-level work may be losing its traditional role as the first rung of expertise, and why schools, universities, and employers now need to rethink the pathways that turn potential into mastery.
Educators need to be deeply aligned with what these changes are, and they need to shift the AI discourse from “how” questions to “what” questions. What do we need to teach? What do we need to keep in the curriculum?
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.






