Over the past few years, OPMs—including Coursera, iDesign and 2U—have adopted AI-powered features designed to enhance support for instructors and students through coaching, content creation, tutoring and curriculum mapping. According to an April analysis, 70 percent of OPMs are now deploying AI for such purposes. But experts are skeptical that the AI boom will have a big payoff for the beleaguered OPM market, which is attempting to rebound with the help of private equity after years of declining revenues, reputational damage and mounting government scrutiny.
Tuesday, June 09, 2026
AI Didn’t Break the University. It Revealed What Was Already Broken - Samuel J. Abrams, RealClear Education
I have argued in these pages before that AI itself is not the cause of the crisis; that blaming the chatbot for cheating and the LLM for loneliness is like blaming the calculator for poor math pedagogy. The deeper failure is institutional, and it preceded the technology. As I wrote here in March, the scarce resource in higher education is no longer knowledge but the human encounter itself. The most penetrating response to Hendrick’s essay confirms that and it did not come from another professor; it came from a 49-year-old graduate student named Norma Sancho, writing in the comments. Her reply has since circulated on its own, and it deserves to be read widely.
Monday, June 08, 2026
Are academics making an (em) dash for AI? - Times Higher Education
In the four years since its commercial launch, generative artificial intelligence has had a profound impact on personal and professional life. But are academics enthusiasts or sceptics? Five scholars explain how the technology has affected their own practice – for good and bad. Artificial intelligence writing is instantly recognisable, we are told—soulless, dispassionate, and devoid of the spark that marks genuine thought. Historian Jonathan Rees, in Academe this spring, calls it “bland, unspecific, pedestrian prose”. Journalist and UCL academic Sarfraz Manzoor, in a recent piece for The Independent, concluded that an AI article his students read was “competent but forgettable”. Scroll through r/professors on any given day and you will find dozens, if not hundreds, of colleagues enthusiastically nodding along and complaining bitterly about students submitting work that any fool can see was written by a machine.
Here’s how AI is driving the real revolution in higher education - Onur Bakiner, Seattle Times
What is education supposed to be like in the age of AI? The debate could not be more polarized: According to some, responsible educators should prepare students for artificial intelligence with AI, lest those students find themselves undesirable in the workplace of the future; others believe that the incursion of AI into education is destroying critical thinking skills, and consequently, learning itself. Boosters see in AI the combination of unprecedented opportunity and peril; critics say they have seen hyped-up educational technologies too many times before. The best is yet to come; the worst is yet to come; or maybe, we’ll spend enormous time and money just to stay where we are.
Sunday, June 07, 2026
Dismissing AI is not critical thinking. It’s intellectual closure = Zach Rossmiller, University Business
As a chief information officer, I have the privilege of interacting with students in many different settings, and conversations about artificial intelligence have become increasingly common.Recently, I read several student reflections explaining why they refuse to use generative AI in their coursework. Some described it as environmentally destructive, pointing to water and energy consumption that disproportionately harms vulnerable communities. Others called it a form of cheating, no different than passing off someone else’s work as your own. Several argued that the entire point of education is the struggle itself, and that outsourcing that struggle to a language model defeats the purpose of being in school.
Is AI Killing User Experience? - Scott A. Snyder and Mike Welsh, Knowledge at Wharton
A product manager can describe a workflow and get a working prototype. A strategist can turn a client’s rough concept into a clickable experience before the meeting ends. A founder with no technical background can “vibe code” a beta version of their product for an investor pitch. This is not a small shift. It compresses time, lowers barriers, and gives more people the ability to participate in creation. For organizations trying to move faster, it feels like a gift. Yet the customers on the receiving end are not sold. Despite the perceived gains in speed and personalization, only 17% of consumers believe their experiences are getting better, according to a March 2026 Medallia report. A separate February 2026 Pega study found that more than 60% of consumers lack confidence in how businesses use AI to interact with them.
https://knowledge.wharton.upenn.edu/article/is-ai-killing-user-experience/
Saturday, June 06, 2026
Law Professors Prefer AI Over Peer Answers - Alejandro Salinas, et al; SSRN
Large language models (LLMs) are increasingly promoted as educational tutors, yet most evaluations focus on domains with a single ground truth. Many disciplines, however, hinge on judgment: reasoning, weighing ambiguity, and reaching defensible conclusions. Law provides a sharp test. We conducted a blinded evaluation of short-answer tutoring in contracts courses with sixteen U.S. law professors. Participants created 40 representative questions, wrote answers, and judged 2,918 anonymized comparisons between human and LLM responses. Professors rated LLMs far higher than their peers (average win rate = 75.33%), with models performing similarly to the best instructor. LLM responses were also rarely flagged as harmful (3.53% vs 12.06% for professors). Preferences for LLM answers were consistent across evaluators and reflected shared professional standards. Our evaluation can be reliably extended to additional models by employing a separate LLM as a judge, rendering expert agreement an effective, scalable method to evaluate AI tutors in judgment-rich domains.
How Personalized AI Tutors Can Help Students Learn - Emma Needleman, Knowledge at Wharton
The researchers built an AI tutoring platform that gives all students access to the same gen AI chatbot and course materials, but varies the sequence in which practice problems are assigned. In a five-month Python course across 10 Taipei high schools, students were randomly assigned to one of two groups: One received a standard sequence of problems progressing from easy to hard, while the other received a personalized sequence, in which an algorithm adjusted problem difficulty based on each student’s performance and interactions with the AI tutor. Because everything else was held constant, this design isolates the impact of personalized homework.
Friday, June 05, 2026
Agentic AI and job skills. How will agentic AI reshape the workforce? - McKinsey
In this video, McKinsey Senior Partners Kate Smaje and Robert Levin and Special Adviser Eric Lamarre, authors of Rewired: How Leading Companies Win with Technology and AI (Wiley, April 2026), discuss what’s real—and what isn’t—about AI-driven workforce disruption. The authors reflect on how AI is changing the kinds of skills organizations value most and what business leaders need to do now to build teams and capabilities that can keep pace with an AI-enabled enterprise. “The core issue is that we’ve really got to think about how organizations are going to work fundamentally differently,” says Smaje.
White House Aims to Establish Political Oversight of Federal Grants - Ryan Quinn, Inside Higher Ed
The White House is advancing a sweeping rule change that would give administration officials more power over billions of dollars in federal grants. The regulations seek to codify that Trump officials have the right to keep doing what they started last year: canceling thousands of grants that they said didn’t align with the president’s priorities, and shooting down new ones for the same reason. The proposed rules would set up a process for this political review, possibly helping insulate it from legal challenges that stymied the administration in the past. Among many other changes, the rules direct “senior appointees” at federal agencies to take charge of awarding and terminating new and existing research grants and other federal awards—a change that reflects an August executive order.
Thursday, June 04, 2026
2026 EDUCAUSE The Impact of AI on Learning Assessment Report - Jenay Robert, EDUCAUSE
Few areas of higher education have been as passionately debated as learning assessment in the age of AI. Since the debut and rapid adoption of readily available generative AI chatbots, educators have grappled with how learning assessment would be impacted. By only surveying individuals who are currently doing the hands-on work of learning assessment, we can provide you with information about how the learning assessment landscape is changing in practice, not just in theory. Explore the full Impact of AI on Learning Assessment report: https://library.educause.edu/resources/2026/6/2026-educause-the-impact-of-ai-on-learning-assessment-report
AI Will Deliver Wisdom - Peter H. Diamandis, Metatrends
I’ve been thinking a lot about wisdom lately. Not intelligence. Not speed. Not raw compute. Wisdom. The thing we used to reserve for grandparents, philosophers, and tribal elders who’d seen enough life to know which paths lead to ruin. Here’s how I define it: wisdom is probabilistic pattern recognition across a vast number of lived experiences. When you go to the village elders and ask, “Which direction should I take?”, they don’t run equations. They draw on decades of watching people make choices and living with the consequences. They say, “If you go this way, based on everything I’ve seen, it won’t end well. Go this other way, and you have a real chance.” That accumulated experience, compressed into judgment, is what we call wisdom.
Wednesday, June 03, 2026
Generative AI use and misuse call for assessment reform in higher education - Igor Chirikov, Ivan Smirnov, and René F. Kizilcec, Science
The debate about the impact of generative artificial intelligence (GenAI) on higher education is polarized. Some portray GenAI as normalizing cheating at scale (1), whereas others argue that misconduct patterns have changed little (2). These competing narratives underscore the need for reliable data on where GenAI use is concentrated and where misuse is most likely. Existing studies of GenAI adoption and perceptions in higher education provide useful early signals but often rely on small samples and lack measures designed to capture sensitive behaviors such as cheating across fields (3–5). We addressed this gap with survey data from 95,513 students in a representative sample of 20 major public researchintensive universities in the United States and an indirect method for estimating GenAI-assisted cheating across disciplines. We found substantial heterogeneity in GenAI use and misuse across disciplines and student groups. These patterns call for discipline-specific assessment reform, not blanket bans or universal detection regimes.
The largest study of AI use by undergrads is in, revealing disparities in access — and in cheating - Maya L. Kapoor, Berkeley News
The study, conducted in the spring of 2024, used data collected by Berkeley’s Student Experience in the Research University (SERU) Consortium, a group of research universities that collaborate on surveying students to improve higher education. About two-thirds of respondents said they used GenAI, and almost 40% used it monthly or even more frequently. What’s more, at least 9% of students who used AI reported using it to cheat. That number varied significantly by academic discipline, with more non-STEM students cheating with AI than STEM students. But the researchers caution that banning GenAI won’t stop cheating and may even harm students when they look for work in industries that expect AI proficiency.
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