The Other Regulatory Time Bomb — from onedtech.philhillaa.com by Phil Hill Higher ed in the US is not prepared for what’s about to hit in April for new accessibility rules
Most higher-ed leaders have at least heard that new federal accessibility rules are coming in 2026 under Title II of the ADA, but it is apparent from conversations at the WCET and Educause annual conferences that very few understand what that actually means for digital learning and broad institutional risk. The rule isn’t some abstract compliance update: it requires every public institution to ensure that all web and media content meets WCAG 2.1 AA, including the use of audio descriptions for prerecorded video. Accessible PDF documents and video captions alone will no longer be enough. Yet on most campuses, the conversation has been understood only as a buzzword, delegated to accessibility coordinators and media specialists who lack the budget or authority to make systemic changes.
And no, relying on faculty to add audio descriptions en masse is not going to happen.
The result is a looming institutional risk that few presidents, CFOs, or CIOs have even quantified.
It begins with a basic reversal of mindset: Stop treating AI as a threat to be policed. Start treating it as the accelerant that finally forces us to build the education we should have created decades ago.
A serious institutional response would demand — at minimum — six structural commitments:
Make high-intensity human learning the norm. …
Put active learning at the center, not the margins. …
Replace content transmission with a focus on process. …
Mainstream high-impact practices — stop hoarding them for honors students. …
Redesign assessment to make learning undeniable. …
And above all: Instructional design can no longer be a private hobby.
How to Integrate AI Developmentally into Your Courses
Lower-Level Courses: Focus on building foundational skills, which includes guided instruction on how to use AI responsibly. This moves the strategy beyond mere prohibition.
Mid-Level Courses: Use AI as a scaffold where faculty provide specific guidelines on when and how to use the tool, preparing students for greater independence.
Upper-Level/Graduate Courses: Empower students to evaluate AI’s role in their learning. This enables them to become self-regulated learners who make informed decisions about their tools.
Balanced Approach: Make decisions about AI use based on the content being learned and students’ developmental needs.
Now that you have a framework for how to conceptualize including AI into your courses here are a few ideas on scaffolding AI to allow students to practice using technology and develop cognitive skills.
What was encouraging, though, is that students aren’t just passively accepting this new reality. They are actively asking for help. Almost half want their teachers to help them figure out what AI-generated content is trustworthy, and over half want clearer guidelines on when it’s appropriate to use AI in their work. This isn’t a story about students trying to cheat the system; it’s a story about a generation grappling with a powerful new technology and looking to their educators for guidance. It echoes a sentiment I heard at the recent AI Pioneers’ Conference – the issue of AI in education is fundamentally pedagogical and ethical, not just technological.
My take is this: in all of the anxiety lies a crucial and long-overdue opportunity to deliver better learning experiences. Precisely because Atlas perceives the same context in the same moment as you, it can transform learning into a process aligned with core neuro-scientific principles—including active retrieval, guided attention, adaptive feedback and context-dependent memory formation.
Perhaps in Atlas we have a browser that for the first time isn’t just a portal to information, but one which can become a co-participant in active cognitive engagement—enabling iterative practice, reflective thinking, and real-time scaffolding as you move through challenges and ideas online.
With this in mind, I put together 10 use cases for Atlas for you to try for yourself.
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6. Retrieval Practice
What: Pulling information from memory drives retention better than re-reading. Why: Practice testing delivers medium-to-large effects (Adesope et al., 2017). Try: Open a document with your previous notes. Ask Atlas for a mixed activity set: “Quiz me on the Krebs cycle—give me a near-miss, high-stretch MCQ, then a fill-in-the-blank, then ask me to explain it to a teen.” Atlas uses its browser memory to generate targeted questions from your actual study materials, supporting spaced, varied retrieval.
From DSC: A quick comment. I appreciate these ideas and approaches from Katarzyna and Rita. I do think that someone is going to want to be sure that the AI models/platforms/tools are given up-to-date information and updated instructions — i.e., any new procedures, steps to take, etc. Perhaps I’m missing the boat here, but an internal AI platform is going to need to have access to up-to-date information and instructions.
While confidence in higher education has eroded and more Americans are questioning the importance of a degree, the demand for internships among college students is skyrocketing and the odds of getting an internship at a major company are now lower than getting into the Ivy League. This begs the question: are we at a point where an internship is as valuable – or perhaps more so – than a degree itself?
While concerns about degree ROI were on the rise, the value of internships and other work-integrated learning opportunities was becoming increasingly apparent. New research and analysis have shown us how valuable it is for a student to have an internship during college: it doubles the odds they have a good job waiting for them upon graduation and doubles their odds of being engaged in their work over their lifetime. Although there are some variations in those outcomes by choice of college or academic major, those variations pale in comparison to the impact of having an internship. In short, a collegiate internship experience is a more important indicator of these outcomes than alma mater or major.
Edtech firm Chegg confirmed Monday it is reducing its workforce by 45%, or 388 employees globally, and its chief executive officer is stepping down. Current CEO Nathan Schultz will be replaced effective immediately by executive chairman (and former CEO) Dan Rosensweig. The rise of AI-powered tools has dealt a massive blow to the online homework helper and led to “substantial” declines in revenue and traffic.Company shares have slipped over 10% this year. Chegg recently explored a possible sale, but ultimately decided to keep the company intact.
On Wednesday [October 29th, 2025], I’m launching the Beta version of an Education Accountability Website (”EDU Accountability Lab”). It analyzes federal student aid, institutional outcomes, and accountability metrics across 6,000+ colleges and universities in the US.
Our Mission The EDU Accountability Lab delivers independent, data-driven analysis of higher education with a focus on accountability, affordability, and outcomes. Our audience includes policymakers, researchers, and taxpayers who seek greater transparency and effectiveness in postsecondary education. We take no advocacy position on specific institutions, programs, metrics, or policies. Our goal is to provide clear and well-documented methods that support policy discussions, strengthen institutional accountability, and improve public understanding of the value of higher education.
But right now, there’s one area demanding urgent attention.
Starting July 1, 2026, every degree program at every institution receiving federal student aid must prove its graduates earn more than people without that credential—or lose Title IV eligibility.
This isn’t about institutions passing or failing. It’s about programs. Every Bachelor’sin Psychology. Every Master’s in Education. Every Associate in Nursing. Each one assessed separately. Each one facing the same pass-or-fail tests.
In that spirit, in this post I examine a report from Virginia’s Joint Legislative Audit and Review Commission (JLARC) on Virginia’s Community Colleges and the changing higher-education landscape. The report offers a rich view of how several major issues are evolving at the institutional level over time, an instructive case study in big changes and their implications.
Its empirical depth also prompts broader questions we should ask across higher education.
What does the shift toward career education and short-term training mean for institutional costs and funding?
How do we deliver effective student supports as enrollment moves online?
As demand shifts away from on-campus learning, do physical campuses need to get smaller?
Are we seeing a generalizable movement from academic programs to CTE to short-term options? If so, what does that imply for how community colleges are staffed and funded?
As online learning becomes a larger, permanent share of enrollment, do student services need a true bimodal redesign, built to serve both online and on-campus students effectively? Evidence suggests this urgent question is not being addressed, especially in cash-strapped community colleges.
As online learning grows, what happens to physical campuses? Improving space utilization likely means downsizing, which carries other implications. Campuses are community anchors, even for online students—so finding the right balance deserves serious debate.
Most polled Americans, 70%, disagreed that the federal government should control “admissions, faculty hiring, and curriculum at U.S. colleges and universities to ensure they do not teach inappropriate material,” according to a survey released Wednesday by the Public Religion Research Institute.
The majority of Americans across political parties — 84% of Democrats, 75% of independents and 58% of Republicans — disagreed with federal control over these elements of college operations.
The poll’s results come as the Trump administration seeks to exert control over college workings, including in its recent offer of priority for federal research funding in exchange for making sweeping policy changes aligned with the government’s priorities.
The number of education degrees awarded in the U.S. steadily decreased in the nearly two decades between 2003-04 and 2022-23, according to a new analysis of federal data by the American Association of Colleges for Teacher Education.
Bachelor’s degrees in education dipped from 109,622 annually to 90,710 while master’s degrees declined from 162,632 to 143,669 in that time span, AACTE said in its report on data from the U.S. Department of Education.
From DSC: Stephen has some solid reflections and asks some excellent questions in this posting, including:
The question is: how do we optimize an AI to support learning? Will one model be enough? Or do we need different models for different learners in different scenarios?
A More Human University: The Role of AI in Learning — from er.educause.edu by Robert Placido Far from heralding the collapse of higher education, artificial intelligence offers a transformative opportunity to scale meaningful, individualized learning experiences across diverse classrooms.
The narrative surrounding artificial intelligence (AI) in higher education is often grim. We hear dire predictions of an “impending collapse,” fueled by fears of rampant cheating, the erosion of critical thinking, and the obsolescence of the human educator.Footnote1 This dystopian view, however, is a failure of imagination. It mistakes the death rattle of an outdated pedagogical model for the death of learning itself. The truth is far more hopeful: AI is not an asteroid coming for higher education. It is a catalyst that can finally empower us to solve our oldest, most intractable problem: the inability to scale deep, engaged, and truly personalized learning.
Increasing the rate of scientific progress is a core part of Anthropic’s public benefit mission.
We are focused on building the tools to allow researchers to make new discoveries – and eventually, to allow AI models to make these discoveries autonomously.
Until recently, scientists typically used Claude for individual tasks, like writing code for statistical analysis or summarizing papers. Pharmaceutical companies and others in industry also use it for tasks across the rest of their business, like sales, to fund new research. Now, our goal is to make Claude capable of supporting the entire process, from early discovery through to translation and commercialization.
To do this, we’re rolling out several improvements that aim to make Claude a better partner for those who work in the life sciences, including researchers, clinical coordinators, and regulatory affairs managers.
AI as an access tool for neurodiverse and international staff— from timeshighereducation.com by Vanessa Mar-Molinero Used transparently and ethically, GenAI can level the playing field and lower the cognitive load of repetitive tasks for admin staff, student support and teachers
Where AI helps without cutting academic corners When framed as accessibility and quality enhancement, AI can support staff to complete standard tasks with less friction. However, while it supports clarity, consistency and inclusion, generative AI (GenAI) does not replace disciplinary expertise, ethical judgement or the teacher–student relationship. These are ways it can be put to effective use:
The Sleep of Liberal Arts Produces AI — from aiedusimplified.substack.com by Lance Eaton, Ph.D. A keynote at the AI and the Liberal Arts Symposium Conference
This past weekend, I had the honor to be the keynote speaker at a really fantstistic conferece, AI and the Liberal Arts Symposium at Connecticut College. I had shared a bit about this before with my interview with Lori Looney. It was an incredible conference, thoughtfully composed with a lot of things to chew on and think about.
It was also an entirely brand new talk in a slightly different context from many of my other talks and workshops. It was something I had to build entirely from the ground up. It reminded me in some ways of last year’s “What If GenAI Is a Nothingburger”.
It was a real challenge and one I’ve been working on and off for months, trying to figure out the right balance. It’s a work I feel proud of because of the balancing act I try to navigate. So, as always, it’s here for others to read and engage with. And, of course, here is the slide deck as well (with CC license).
In every Great Lakes state except Illinois and Minnesota, students face affordability gaps greater than the national average of $1,555.
Five out of six Great Lakes states have a smaller percentage of affordable public bachelor’s-granting institutions than the national average of 35% of postsecondary institutions.
In two states (Ohio and Wisconsin), the affordability gap for students at public bachelor’s-granting institutions is more than twice the national average.
Still, a subset of states have committed to making community college more affordable. In Ohio, Indiana, and Michigan there is no affordability gap, on average, for students to attend community college.
Eye implant and high-tech glasses restore vision lost to age — from newscientist.com by Chris Simms Age-related macular degeneration is a common cause of vision loss, with existing treatments only able to slow its progression. But now an implant in the back of the eye and a pair of high-tech glasses have enabled people with the condition to read again
People with severe vision loss have been able to read again, thanks to a tiny wireless chip implanted in one of their eyes and a pair of high-tech glasses.
“This is an exciting and significant study,” says Francesca Cordeiro at Imperial College London. “It gives hope for providing vision in patients for whom this was more science fiction than reality.”
Experience AI: A new architecture of learning
Experience AI represents a new architecture for learning — one that prioritizes continuity, agency and deep personalization. It fuses three dimensions into a new category of co-intelligent systems:
Agentic AI that evolves with the learner, not just serves them
Persona-based AI that adapts to individual goals, identities and motivations
Multimodal AI that engages across text, voice, video, simulation and interaction
Experience AI brings learning into context. It powers personalized, problem-based journeys where students explore ideas, reflect on progress and co-create meaning — with both human and machine collaborators.
While over 80% of respondents in the 2025 AI in Education Report have already used AI for school, we believe there are significant opportunities to design AI that can better serve each of their needs and broaden access to the latest innovation.1
That’s why today [10/15/25], we’re announcing AI-powered experiences built for teaching and learning at no additional cost, new integrations in Microsoft 365 apps and Learning Management Systems, and an academic offering for Microsoft 365 Copilot.
Introducing AI-powered teaching and learning Empowering educators with Teach
We’re introducing Teach to help streamline class prep and adapt AI to support educators’ teaching expertise with intuitive and customizable features. In one place, educators can easily access AI-powered teaching tools to create lesson plans, draft materials like quizzes and rubrics, and quickly make modifications to language, reading level, length, difficulty, alignment to relevant standards, and more.
When it comes to innovation in higher education, most bets are being placed on technology platforms and AI. But the innovation students, faculty and industry need most can be found in a much more human dimension: co-teaching. And specifically, a certain kind of co-teaching – between industry experts and educators.
While higher education has largely embraced the value of interdisciplinary teaching across different majors or fields of study, it has yet to embrace the value of co-teaching between industry and academia. Examples of co-teaching through industry-education collaborations are rare and underutilized across today’s higher ed landscape. But they may be the most valuable and relevant way to prepare students for success. And leveraging these collaborations can help institutions struggling to satisfy unfulfilled student demand for immersive work experiences such as internships.
From DSC: It’s along these lines that I think that ADJUNCT faculty members should be highly sought after and paid much better — as the up-to-date knowledge and experience they bring into the classroom is very valuable. They should have equal say in terms of curriculum/programs and in the way a college or university is run.