AI

Frontier AI Models: The Engines of Modern AI

Generative AI can be useful, but only when it meets genuine expertise. In this post I outline a three-dimensional model of “Domain, Technological, and Situated” knowledge and argue that the real power of technologies like ChatGPT lies with those who already possess at least one of these strands. I introduce situated expertise: the reflexive, context-aware capacity to apply and communicate knowledge responsibly within real communities and settings.

In this post, I explore what the AI Assessment Scale means to me, and how I apply it in different contexts. I also describe what the AIAS is NOT.

ADAPT: SSU's Generative AI Course Design Checklist Center for Teaching Innovation Salem State University Questions/Comments: Please email CTI Instructional Designer Jim McGrath (he/him): jmcgrath2@salemstate.edu Last updated June 12, 2025. This checklist is meant to be a starting point for instr...

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Cogniti is a tool developed at the University of Sydney that instructors can use to create custom AI chatbots (

Offered by Lund University. This course is for educators, administrators, and educational technologists interested in how GenAI could be ... Enroll for free.

My students submit AI Transparency Statements. Here's what they share. (I just updated these this morning.) ++++ 1. What Steps They Used AI For Students design their own writing/work processes. They incorporate gen-AI when it's useful, and reject it when it's not useful (in their estimation). In the Transparency Statement, students list that process again. For each step in the process, they give a number on Leon Furze's and Dr Mike Perkins's AI Assessment Scale. (1 = no AI use; 5 = full-on AI use). They explain why they gave their AI use that number. The goal is to encourage transparency, but to avoid the trap (which recently surfaced in a conversation about students simply citing AI use) of simply announcing that a student used AI. I want to know how they used it. ----- 2. A Defense of Their Use/Non-Use This isn't just about defending our use of AI (though that's part of it). It's about defending any process we design and implement. I ask students to -- using their answers from #1 -- reflect on whether their use of AI empowered them or took away their power. I also ask them to share any steps they took to prevent AI from taking control of the framing, the iteration, and so on. ----- 3. A Reflection On Their Use of AI as a Co-Pilot or or a Co-Thinker I use this language from Elisa Farri's and Gabriele Rosani's HBR Guide to Generative AI for Managers (2025). If students used gen-AI as a co-pilot, I ask them to walk through how it worked. When did they take control? When did they hand over control to the AI for the moment? When did they truly work side-by-side? If students used the AI as a co-thinker, I also ask them to walk through it. What strategies did they use to make sure the AI wasn’t doing the heavy lifting? Who (or what) owned the ideas, in the end? ++++ My goal isn't to say "use AI for this" or "don't use AI for that." It's to guide students as they make choices, have a series of conversations about those choices, and to appreciate the individual and social implications of those choices. Images: Screenshots from one of my assignments. I lean into these questions most for my AI-Powered Communication course, for obvious reasons. | 61 comments on LinkedIn

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What should good research on AI's impact on student learning look like? The headlines are everywhere. "AI Will Destroy Critical Thinking in K-12" screams The New York Times.

Leon Furze shares about myths and metaphors in the age of generative AI on episode 572 of the Teaching in Higher Ed podcast

Two of the smartest chatbots went head-to-head

On the podcast today, I talk with four University of Virginia faculty who are serving this year as Faculty AI Guides. This provost-funded program has enlisted 51 faculty to explore potential uses of generative AI in their teaching and to share what they learn with colleagues in their departments and schools. Back in January, we invited the Faculty AI Guides to share assignments from their fall courses that thoughtfully integrated AI to support student learning. I put some of these assignments in a collection on the UVA Teaching Hub website (see the link below), and on this episode of the podcast, I talk with four of the Faculty AI Guides who contributed assignments.Kiera Allison is an assistant professor of management communication, Jamie Jirout is an associate professor of education, Spyros Simotas is an assistant professor of French, and Jun Wang is a lecturer in Chinese. In our conversation, the four Faculty AI Guides talk about their motivations for being in the program, what they have learned about AI and teaching through their experiments, how they respond to concerns about students outsourcing their learning to AI, and what’s next for their use of AI in teaching.Episode Resources·       Faculty AI Guides website·       “Integrating AI into Assignments to Support Student Learning,” UVA Teaching Hub·       “Red Lights, Green Lights, and AI-Integrated Assignments,” Derek Bruff, March 4, 2025·       AI Needs You: How We Can Change AI’s Future and Save Our Own, Verity Harding, Princeton University Press, 2024·       “How to Encourage Students to Write without AI,” Beth McMurtrie, Chronicle of Higher Education, February 13, 2025·       “AI Podcast 1.0: Rise of the Machines,” Planet Money, May 26, 2023·       “Comparing the Quality of Human and ChatGPT Feedback on Students’ Writing,” Jacob Steiss et al., Learning and Instruction, June 2024·       “Exquisite AI Corpse,” Maria Dikcis, AI Pedagogy Project

A formula for AI in companies

Students won’t be just competing against AI agents for jobs, they’ll also be competing against new graduates who know how to manage AI agents in the ways described. Who will get the job? :)

In “10 AI Tools Teachers Should Explore This Summer,” Kasey Bell shares must-try AI tools for K–12 educators, including MagicSchool, Brisk, Diffit, Curipod, ChatGPT, and more. Learn how to use artificial intelligence in education to streamline lesson planning, support student learning, and enhance engagement. This guide is ideal for teachers looking to explore AI in the classroom, experiment with educational technology, and build confidence teaching with AI.

When AI can do the tasks we call learning, how do we tell what’s real? Here's why only observable behavior can define and protect human learning.

Artificial Intelligence (AI) isn’t coming—it’s here. And as community college educators, we have a choice: we can either let AI be dictated to us by tech companies and administrative mandates, or we can step into our power, take ownership of the conversation, and shape how AI serves our students and

Discover how AI can help you explore careers, research companies, polish application materials, practice interviews, and negotiate salaries in today's job market

An edtech specialist cuts through the noise with five beginner-friendly AI tools teachers can start trying today.