While artificial general intelligence and artificial super intelligence will mark significant improvements in AI algorithms, there is not a single clear definition of either of these terms. Therefore, some experts believe that we have already achieved AGI and that ASI is just a year or two away; others say it will be the middle of the century before either is achieved. So, without minimizing the impact of any of the steps toward general and super intelligence, I think we are better served by focusing on more solidly defined steps in AI advancement. That brings us to what may become a pivotal stage of development in AI, the use of stable quantum computing to accelerate and extend the potential of algorithms.
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Wednesday, August 19, 2026
Loss of International Students Could Cost Economy $3.4B - Kathryn Palmer, Inside Higher Ed
The United States may have as many as 112,000 fewer international students enrolled in higher education this coming academic year, according to new projections that NAFSA: Association of International Educators and JB International published Tuesday. Based on data from the Institute of International Education, the analysis estimates that about 1,057,000 international students will be enrolled at a college or university during the 2026–27 academic year, compared to an estimated 1,169,000 during the 2025–26 academic year.
Focus on the Quantum Future - Ray Schroeder, Inside Higher Ed
While artificial general intelligence and artificial super intelligence will mark significant improvements in AI algorithms, there is not a single clear definition of either of these terms. Therefore, some experts believe that we have already achieved AGI and that ASI is just a year or two away; others say it will be the middle of the century before either is achieved. So, without minimizing the impact of any of the steps toward general and super intelligence, I think we are better served by focusing on more solidly defined steps in AI advancement. That brings us to what may become a pivotal stage of development in AI, the use of stable quantum computing to accelerate and extend the potential of algorithms.
Tuesday, August 18, 2026
Universities would prefer not to. - Hollis Robbins, Hollis Robbins Annectdotal
Four years after ChatGPT caught so many by surprise, the primary role of higher education seems to be slowing down the public’s transition to the AI era. For many faculty, this is a win. For those focused on the future, this is the biggest institutional failure since the Victorian Post Office, with its monopoly on telegraph lines, dismissed the telephone because it had plenty of messenger boys. Adoption was slowed so much there were waiting lists for a home phone line into the 1970s.Some facts. More than 90 percent of notable AI models released in 2025 came from industry: GPT-5, Gemini 3, Claude Opus 4.5, Grok 4, Llama 4, DeepSeek-V3.2, Qwen 3, Kimi K2. The infrastructure supporting frontier development is also overwhelmingly from industry. Global AI compute capacity has been growing 3.3x annually since 2022, doubling every seven months, driven by hyperscalers and enormous data-center investments. Some universities are entering the compute space. Ten New York universities spent two years and $340 million to get to about 400 GPUs. In 2024, xAI in Memphis stood up 100,000 GPUs in 122 days. In the past two years a site in Abilene, Texas got to 500,000.2
How to Build an Education Platform That Supports People Through Different Stages of Life - Danny Wesley, Hackernoon
Despite the age difference, people are solving a similar problem: they are trying to move to the next level of what they are capable of. For a school student, that might mean getting into university. For a university student, access to the tools for a first set of professional skills. For an adult, a career change or a step up. The tools change, but the logic itself stays the same. What does the ideal education platform look like ten years from now? I think the boundaries between different digital education products will gradually disappear. People need separate courses or programs less and less as ends in themselves. What they need is a concrete result and a clear path to it. So education platforms will increasingly turn into systems that support people over time. They will help people gain knowledge, master new skills, adapt to changes in the market, and find new opportunities to grow. In my view, that is where the future of education lies.
AI-Enabled Ghost Student Fraud: How IT Leaders Are Fighting Back - Adam Stone, EdTech
Generative artificial intelligence is fueling a surge in ghost student fraud. Learn how layered identity verification, behavioral analytics and AI-driven pattern detection help higher ed IT leaders stop fraud rings before disbursement. First, there was the zombie college scam. Now it’s “ghost students,” bad actors leveraging artificial intelligence to create fake identities and enroll imaginary students to scoop up grants and loans. AI tools now allow synthetic identities to mimic genuine student behavior long enough to collect financial aid disbursements, and traditional enrollment systems are falling short. The schemes are costing the U.S. taxpayers hundreds of millions of dollars in siphoned-off federal financial aid packages
Monday, August 17, 2026
How instructional design shapes higher-order thinking among higher education students in generative artificial intelligence-supported teaching contexts - Yujia Chen & Jinling Wang, Nature
Against the backdrop of the widespread integration of generative artificial intelligence (GAI) into higher education, previous research has yielded divergent findings regarding its relationship with students’ higher-order thinking (HOT). Moving beyond outcome-oriented discussions of technology use itself, this study examines the association between HOT performance, instructional design elements, and cognitive processes in GAI-supported teaching contexts from an instructional design perspective. A multimethod analysis combining structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) was conducted. The findings indicate that HOT performance cannot be explained by technology use alone. Rather, it is more likely to be associated with cognitive conflict and cognitive elaboration processes shaped by instructional design. Different instructional design elements played differentiated roles in triggering cognitive conflict and supporting cognitive elaboration. The overall influence of disciplinary context on these cognitive processes was limited, although one individual path showed a significant difference. The configurational analysis further showed that high HOT performance did not correspond to a single pathway but was associated with multiple combinations of instructional design elements and cognitive processes, demonstrating configurational multiplicity and asymmetry.
How AI Actually works - Cris Tolomia, Quartz
This piece is not about whether AI is good or bad. It's about what it actually is: how it learns, how it generates output, where its failures come from, and why the problems that afflict these systems are structural rather than incidental. Understanding these things won't make you a machine learning engineer. It will make you a sharper reader of AI coverage, a more careful user of AI tools, and a better judge of claims made by the companies building them. The 15 concepts here cover the full chain — from how models are trained to why they hallucinate, from what "parameters" actually means to why the alignment problem is harder than it looks. Some of these ideas are technical but not complicated. Others are philosophical but grounded in real engineering decisions. All of them matter if you want to engage honestly with the technology reshaping how work gets done, how content is made, and how decisions are reached in medicine, law, finance, and government.
Building expertise in the age of AI: Who trains the next generation? - Bryan Hancock, McKinsey
For decades, organizations have relied on early-career talent to do the routine, lower-risk work that supports the business and to serve as a training ground for future leaders. Think of Peggy Olson’s trajectory on Mad Men, from novice assistant to Don Draper’s protégé to confident copy chief at an advertising agency—a climb that began because routine work kept her in the room where judgment was practiced, and where her own could be noticed. In real life, advances in automation and AI are changing the composition of entry-level work itself. Tasks such as research, documentation, data cleanup, basic coding, and preliminary analysis are being streamlined or absorbed into AI systems. These are precisely the activities through which young employees have traditionally built instincts, developed judgment, and earned the right to take on more. At the same time, fears are growing about the impact of AI on jobs. In the 2025 Women in the Workplace report by McKinsey and LeanIn.Org, entry-level workers, particularly women, reported feeling the most worried of all age groups about how AI use will affect their jobs.
Friday, August 14, 2026
How to make your academic work visible to AI - Darshan Vigneswaran, Times Higher Education
Here is the brutal truth about AI discoverability: it is not replacing citation metrics. It is layering itself on top of them. So, work that is already cited, circulated and sitting inside recognisable debates is likely to become even more visible. The rich get richer, now with a chatbot assistant. If Google Scholar sometimes buries obscure work, AI tools might simply forget it was ever born. This is grim news for anyone who believes good research should glow naturally in the dark. It does not. Visibility is not a moral reward for intellectual virtue. It is a distribution problem.
Lifelong learning in an AI-driven world: assistance, personalization and automation under scrutiny - Gerardo Alfredo RodrÃguez, Andres Chiappe, Fabiola Sáez-Delgado, Frontiers in Education
This scoping review examines the growing intersection between lifelong learning (LLL) and artificial intelligence (AI), focusing on whether the promises of assistance, personalization, and automation are aligned with the broader educational, social, and equity-oriented aims of LLL. The review addresses a central concern: although AI is increasingly promoted as a transformative resource for lifelong education, its deployment may not always correspond to the paradigms, geographical contexts, and vulnerability profiles emphasised in LLL literature.
Improving GPT‑5.6 Sol in ChatGPT—and expanding access to GPT‑5.6 Luna for free users - OpenAI
Our mission is to ensure that artificial general intelligence benefits all of humanity. We’re introducing updates to ChatGPT that improve everyday conversations while expanding access for Free users. For Plus and Pro users, we’re updating GPT‑5.6 Sol in Chat to be more reliable with facts and provide more focused answers. A new slider lets you choose how much thought ChatGPT puts into each response. For Free users, we're updating the default model to GPT‑5.6 Luna and expanding access with unlimited text chats. For questions that need more thought, a new Think button lets you access higher reasoning for harder questions.
Thursday, August 13, 2026
Top 10 Online Course Apps and Websites for Learning New Skill - Sekolapedia
The global education landscape has undergone a permanent shift. Up-skilling, continuous learning, and professional certifications are no longer optional extras—they are essential requirements for navigating an increasingly automated and competitive workforce. Online learning platforms have democratized education, allowing anyone with an internet connection to learn from top university professors, industry practitioners, and subject-matter experts.
Self-directed learning ability and online student engagement among nursing students: the mediating role of information literacy and the moderating role of self-control - Haihong Zhang, et al; NIH National Library of Medicine
Self-directed learning ability had a significant positive direct effect on online student engagement (β = 0.511, t = 17.586, p < 0.001). Information literacy mediated the relationship between self-directed learning ability and online student engagement, with an indirect effect of 0.346, accounting for 67.7% of the total effect. Self-control negatively moderated the direct effect of self-directed learning ability on online student engagement (β = −0.310, t = −2.140, p < 0.01).
AI won’t kill the college degree, but it will change what it’s for - Colin Gabler, Atlanta Journal Constitution
In the AI era, the value of college will not be measured by the output students generate, but whether they can form and defend the judgments they make behind it. That shift to artificial intelligence is already changing what counts as evidence of real learning in higher education, how we justify the valuable time and resources students, parents, local communities and potential employers invest in the next generation of citizens. I saw this firsthand in my MBA classroom, where students recently presented market-entry strategies to a live client. Article author, Colin Gabler says In this op-ed at the Atlanta Journal-Constitution, I argue that college is worth its cost in the age of AI only if it develops graduates who can interpret, challenge, and take responsibility for machine-shaped decisions rather than merely execute them.
https://www.ajc.com/opinion/2026/08/ai-wont-kill-the-college-degree-but-it-will-change-what-its-for/
Wednesday, August 12, 2026
AI Detectors Are Out, New Assessments Are In - Kathryn Palmer, Inside Higher Ed
“It’s a difficult, delicate moment right now. And I’m not sure we have all the answers,” Kevin Yee, director of the Faculty Center for Teaching & Learning at the University of Central Florida, told Inside Higher Ed. “If faculty had an AI detector that was reliable, that’s what they would use. But many are reluctantly moving in the direction of assignment redesign because they are at wit’s end” over AI-powered cheating. From what he’s observed, about half of faculty want to make as few changes as possible to AI-proof their assessments. But staying the course may be a viable option only for those who teach in-person classes with fewer than 30 students. In a small environment, “they can actually succeed in convincing students not to take these shortcuts, establishing strong relationships and convincing students that the learning is really what matters here,” he said. “In larger classes, there’s less of a personal connection between students and faculty, so faculty need to redesign their assessments to be more AI-resilient or a completely kind of deliverable that AI can’t do, such as a blue book exam or an in-person oral exam.”
OpenAI wants teachers and profs to foist their work off on ChatGPT - The Register
The House of Altman announced a trio of new education-focused offerings on Tuesday: one for K-12 teachers, another for college educators, and a third for college students. The new plugins, the company explained, will help students and educators make more use of ChatGPT’s agentic capabilities for both studying and teaching. The new features are available through ChatGPT Edu, an institutionally licensed suite for higher education, and ChatGPT for Teachers, a free resource available to verified US K–12 educators and school districts. The new offerings, says OpenAI, build on its educational AI philosophy that “AI should support learning, not shortcut it, and the best learning experiences keep educators and students in control.”
Education Department Approves First Workforce Pell Program - Sara Weissman, Inside Higher Ed
Students in an EMT program at Iowa Central Community College will be the first to take advantage of Workforce Pell. The U.S. Department of Education approved its first Workforce Pell program, for training emergency medical technicians at Iowa Central Community College, according to a Tuesday announcement. Students can now access Pell Grants, federal financial aid for low-income students, to pay for the 14-week program. “After decades of debate and a lot of hard work, Workforce Pell is finally here—opening up new opportunities for students to use their Pell Grants on programs that will help them jumpstart their careers,” U.S. Secretary of Education Linda McMahon said in a statement. “Today’s announcement demonstrates our commitment to providing students with affordable pathways to rewarding careers without taking on significant debt.”
Tuesday, August 11, 2026
Public Colleges Anchor State Workforce Pipelines - Kathryn Palmer, Inside Higher Ed
The type of college a person graduates from is one of the strongest predictors of whether they’ll remain in the state to work after graduation, new data shows. According to a report the Strada Institute for the Future of Work published Thursday, 62 percent of workers between the ages of 20 and 65 who graduated from a public institution attended college in their home state and now work there, compared to 44 percent of workers who graduated from a private, nonprofit institution who did the same. “State support permits public colleges to subsidize tuition for in-state students, helping to retain these students for college and often after college as well, making public postsecondary institutions anchors for states’ talent development,” the report says. “Private colleges typically do not offer such discounts; thus, students are less incentivized to choose a private college in their home state.”
Fitch: New visa limits could hurt international enrollment and revenue - Natalie Schwartz, Higher Ed Dive
The Trump administration’s new rule capping international student visa stays at four years could hurt revenue and decrease enrollment at colleges, particularly those that heavily rely on foreign students, according to a Tuesday analysis from Fitch Ratings. Financial pressure will be greatest on institutions with weaker student demand, limited financial flexibility, and a high reliance on tuition and fee revenue, Fitch analysts said. Colleges with significant STEM and graduate offerings could also be particularly hit hard, as it often takes more than four years to complete such programs. These institutions may face higher expenses “to address overseas recruitment challenges,” the analysts wrote.
Differential engagement with generative artificial intelligence in higher education: Gender, motivation, and achievement trajectories - uan-Hsuan Lee & Jiun-Yu Wu, International Journal of Educational Technology in Higher Education
Engagement frequency was shaped by learner differences: female students, those with stronger autonomous motivation, lower prior knowledge, and higher course performance interacted more frequently, while higher-performing students were less likely to abstain from use. Importantly, engagement was not merely a matter of frequency but of inquiry quality and diversity. Growing Achievers (students who began with weaker achievement but demonstrated substantial performance gains) posed more diverse and conceptually oriented questions. In contrast, Declining Performers engaged minimally and focused on narrower, procedural inquiries despite stronger initial knowledge.
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