This report investigates a profound new challenge driven by rapidly expanding use of artificial intelligence (AI) in schooling: the risk that students will outsource too much of the cognitive work that is crucial to establishing the knowledge, skill and ‘thinking infrastructure’ that enables both schooling success and lifelong capacity for ongoing learning and understanding.
With the rise of AI (Artificial Intelligence) and Generative AI that can generate new and unique content, rather than analyzing and acting on existing data, this has resulted in the release of OpenAI in 2015. A new innovative tool has recently emerged, it is named, ChatGPT and it has taken the world by storm. In just five days after its release, ChatGPT attracted over a million users globally and has rapidly gained popularity in all fields, especially in education. This new technology is again stirring up the AI versus education debate, some see it as a threat to the curren
Microsoft has released a new research report warning that no single technology can reliably distinguish AI-generated content from authentic media, and that deepening reliance on any one method risks misleading the public.
A young tech entrepreneur launched the tool Einstein this week, marketing it as a way to free students from busywork—and triggering robust faculty debate. Einstein’s creator says that was the whole point. After this story was published, Paliwal said he received a cease and desist letter from Instructure, which owns Canvas, and has since taken down Einstein’s website.
Interesting quote and perspective: “The most destructive educational technology we have is the large lecture hall. I would be happy if these technologies forced us to stop putting 400 students in a room,” he said, noting that such a change would be costly for institutions. “But if we’re really committed to teaching and learning, maybe we’re starting to learn that the transactional model isn’t going to work anymore.”
Note: Since this post 'Einstein's' creator has received a cease and desist letter from a LMS company and has closed the site down.
Peter Mellow's insight: Interesting quote and perspective: “The most destructive educational technology we have is the large lecture hall. I would be happy if these technologies forced us to stop putting 400 students in a room,” he said, noting that such a change would be costly for institutions. “But if we’re really committed to teaching and learning, maybe we’re starting to learn that the transactional model isn’t going to work anymore.”
Interesting quote and perspective: “The most destructive educational technology we have is the large lecture hall. I would be happy if these technologies forced us to stop putting 400 students in a room,” he said, noting that such a change would be costly for institutions. “But if we’re really committed to teaching and learning, maybe we’re starting to learn that the transactional model isn’t going to work anymore.”
The Typology of Generative AI Tools for Education provides educators with a list of generative AI tools arranged into nine categories that are currently being used in educational contexts. This typology follows the previously published Typology of Free Web-based Learning Technologies (Bower & Torrington, 2020) and the Typology of Web 2.0 Learning Technologies (Bower, 2015), representing the evolution of educational technology into the generative AI era. To create this typology, 211 educators from nine countries spanning early childhood through higher education completed a survey in late 2025 about their generative AI tool usage. Tools that were reported by two or more educators were included in the typology. A total of 50 unique AI Educational tools were included in the Typology, and have been arranged into nine overarching categories: General-Purpose Large Language Models, Image Creation Tools, Audio and Music Generation Tools, Video Generation Tools, Presentation Generation Tools, Research and Study Tools, AI Tutoring and Chatbots, Custom Education Tools, and Other Miscellaneous Tools. Brief descriptions and links are provided for each tool to support educators in making informed decisions about which tools might suit their teaching and learning contexts. The generative AI landscape is rapidly evolving, and it is noted that some tools offer functionality across multiple categories. This typology represents a snapshot of educator-reported usage patterns in 2025-2026, and offers educators a touchstone for the appropriate selection of Generative AI technologies in their teaching.
The promise of artificial intelligence in higher education isn't to replace human work but to create space for the human interaction students value most.
Unofficial AI use on campus reveals more about institutional gaps than misbehavior.
The institutions that thrive in the AI era will be the ones that recognize shadow AI for what it is: a signal. Shadow AI won't disappear with stricter rules. It will disappear when the sanctioned path is better than the workaround.
After turning off ChatGPT’s ‘data consent’ option, Marcel Bucher lost the work behind grant applications, teaching materials and publication drafts. Here’s what happened next.
This report investigates a profound new challenge driven by rapidly expanding use of artificial intelligence (AI) in schooling: the risk that students will outsource too much of the cognitive work that is crucial to establishing the knowledge, skill and ‘thinking infrastructure’ that enables both schooling success and lifelong capacity for ongoing learning and understanding.
"It’s a curated, constantly updated collection of the articles, research papers, frameworks, and practical resources that I’m actually reading and using in my own work. Think of it as a set of shelves, each focused on a different area: what’s new in AI, academic research on GenAI in education, frameworks and policies, practical strategies you can use in the classroom, news and media coverage, and featured posts from this blog."
The long read: I was a newcomer, negotiating all of usual classroom difficulties for the first time. Throwing AI into the mix felt like downing a coffee in the middle of a panic attack
A Pew survey also found that more than 1 in 10 U.S. teens use AI for emotional support or advice, and that they are more hopeful about the technology than adults.
Alpha School, which purports to teach children academics using AI for two hours a day, has got the support of the Trump administration, but leaves some education experts and parents unimpressed.
The Impact of AI on Work in Higher Education, an effort conducted in partnership with AIR, NACUBO, and CUPA-HR, summarizes work-related institutional AI strategies, policies, and guidelines; the risks, opportunities, and challenges associated with using AI for work in higher education; and specific examples of how staff and faculty use—and want to use—AI for work.
The Impact of AI on Work in Higher Education report provides a valuable, institution-level perspective on how AI is reshaping faculty and staff work beyond the classroom. I find it especially useful that the report balances opportunities such as increased efficiency, improved decision-making, and reduced administrative burden with clear acknowledgment of risks like workforce disruption, policy gaps, and ethical concerns. The inclusion of concrete examples of how employees are already using (and want to use) AI makes the findings feel grounded and actionable rather than speculative. What stands out most is the emphasis on the need for clear strategies, guidelines, and shared governance as AI becomes embedded in everyday institutional operations. Overall, the report reinforces that AI’s impact on higher education work will depend less on the technology itself and more on how thoughtfully institutions support, train, and protect the people doing the work.
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