From the Cool Cat Teacher Blog by Vicki Davis

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AI with intention. AI with integrity. Is it possible? Tony Frontier, author of AI with Intention, is talking about how we value learning in the age of AI. He shares the language we can use to evaluate what we’re doing, how we’re talking about AI, and how we’re measuring learning, and ultimately, why education needs to change more than ever.

I also open this show with some highlights from the Report of MIT’s Ad Hoc Committee on AI Use in Teaching, Learning, and Research Training and what it means for learning, and they use a term I think we should all be discussing: cognitive surrender. We cannot let our kids cognitively surrender and let AI do the work for them. They also talk about helping students understand that their learning, integrity, and judgment are the product of college, not the grades. So many challenges we have now, but this week has been about sharing the conversations and thought leaders to help you improve the AI conversation in your school. I hope this Thursday helps you be a thought leader in your school!

Listen to my conversation with Dr. Tony Frontier — or watch it on YouTube, or read the full transcript at the bottom of this page.

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The AI Policy Dr. Tony Frontier Says Actually Works

You can listen to the whole conversation in the player above or read the full transcript below. Here is the framework Tony walked through, piece by piece. He has been running focus groups in high schools around the country — urban, suburban, rural, public, private, parochial — and his first finding is the one that should worry us: you cannot tell one school’s transcript from another.

Kids are using AI tools. Typically, kids say they use it twenty-five to forty percent of the time for their schoolwork… And there’s a group of kids say they use it all the time. I’ve had kids say they haven’t read anything since they were a freshman. They just have AI summarize everything.

— Dr. Tony Frontier

The second finding is the one we can actually do something about. Students told him they are not getting instruction. “There’s some vague permission, there’s a lot of outright bans, but there’s very little focused, specific lessons. Here’s how, here’s why.”

The 3 Choices Schools Have Right Now

Tony frames three approaches schools are taking. He says, “if you have access to a search bar, you have access to an AI tool that can do pretty much all of your homework, kindergarten through PhD.” So there are three doors:

1. Let kids figure it out on their own. “A lot of videos out there on TikTok about how to use AI to cheat.”
2. Let the tech companies decide. Just let the kids do everything.
3. Take the lead. “The kids are ahead of us right now and we have to get ahead of the kids.”

✏️✏️✏️

Part 1: Guidelines and Boundaries

Boundaries say what is off-limits. Guidelines describe what good looks like. Tony’s warning is that most schools write only the first kind and think they are done. Wow, are we giving kids guidelines? Are we modeling good uses?

Do you have any good uses of AI that you can model for your students tomorrow? Can you show them the chat and what you did? Can you show them how you figured out AI was wrong on something or why you made other choices than the AI did for the work. This is part of disclosure and transparency, but also modeling and giving guidelines.

Part 2: Define Effective, Ineffective, and Inappropriate Use

Sit down and define what these look like in your school. Sit down with paper and write one-sentence definitions for what this looks like. Tony’s point is that the definitions have to be specific enough to provide direction but general enough not to micromanage a teacher’s judgment or expire the moment a tool changes.

• Effective — aligned and intentional.
• Ineffective — “I used AI to complete my work, but I can’t explain the work that I completed.”
• Inappropriate — privacy violations, cheating, “things that are completely inappropriate.”

He notes there is a toolkit with worked examples published through the AI Center for Effective Teaching and Learning.

Part 3: The Core Commitments

This is the part that Tony says many schools skip entirely, but that is essential. Remember that whatever we ask of students, we model. I’ve included quotes from Tony for each of these, but listen to the show for the full context. (And remember his book AI with Intention: Principles and Action Steps for Teachers and School Leaders has many of these items.)

3 Commitments for Students:

1. Integrity — “Can a student say I used AI tools in ways that are aligned to my teacher’s communicated expectations?”
2. Transparency — “I document and report any tool or resource I use.”
3. Explainability — the student “is always accountable to explain, justify, or further explain the work that they did.”

3 Commitments for Teachers

1. Fidelity — is this aligned to stated priorities for teaching and learning? “I don’t mean everyone’s on page 263 of the teacher’s manual.”
2. Transparency — “We need to model the transparency we expect from our kids.”
3. Explainability — “If I used AI to create a slideshow or an assessment, I should be able to say, here’s why this specific academic language is here.”

Tony really implies these aren’t for “gotchability” but a framework for intentionality and admin support within the commitments.

Not because we’re looking to catch people doing the wrong thing… If I’m a teacher and I’m awake at two AM worried about something, and I know I used AI for something the day before, I want to know that I have administrative support.

— Dr. Tony Frontier

Make “Who Helped You With This?” a Normal Question

One point here is important to hear: “I’ve yet to hear a compelling reason why kindergarten through fifth-grade kids should be using LLMs.” He also talks about making transparency with who did the work part of what is done, to level the playing field as much as anything.

We should just make it normal starting in kindergarten. Who helped you with this? My mom helped me, or my older sibling helped me… Because if I don’t know what you can and can’t do independently, I can’t teach you.

— Dr. Tony Frontier

In my AP Computer Science Principles classroom, my students can use AI to write code. However, they must be prepared to explain every line of code, what it does, and how the code works. If they cannot, I reserve the right to have them remove the code to see if it still works. I care more about learning detection than AI detection. In fact, students who resisted AI in that course, in my opinion, did not do as well as those who used it wisely for learning support.

Cognitive surrender — Falling back on AI at the first hint of struggle, and getting the illusion of learning instead of the learning. This is not Tony’s phrase and it is not mine — it comes from the Report of MIT’s Ad Hoc Committee on AI Use in Teaching, Learning, and Research Training (August 25, 2026), which I read from at the top of this episode. MIT’s point is that giving in to that option cheats students out of the cognitive friction that actual learning requires.

Explainability — A student’s accountability to explain, justify, or further explain the work they turned in.
⚠️ Be careful with this one: in the AI industry, “explainability” means something else entirely — whether a human can understand why the model produced a given output. Tony is using it about the student, not the machine. Both meanings are legitimate; they are just not the same word doing the same job. Source: Dr. Tony Frontier, AI Center for Effective Teaching and Learning.

Agency / agentic learner — A learner who asks questions, seeks clarification, wants personal relevance, and can say “help me out here, I need that differently.”
⚠️ Same caution: “agentic AI” in the tech press means software acting on its own. Tony’s “agentic learner” is about the human doing the acting. As he puts it, our most agentic learners are our kindergartners. Source: AI Center for Effective Teaching and Learning.

Humanizer — A tool that rewrites AI-generated text so it will not trip an AI detector. There is no official definition for this one; it is student vocabulary. Tony’s finding is the part worth knowing: some students start using humanizers after being falsely accused — “I didn’t use AI, but once I got accused, now I run everything through a humanizer.”

These are new to my AI Vocabulary List — I’m adding them. Want to find out how many of these words you already know? Play Spy the AI, the free vocabulary game I vibe coded from that same list.

Stop Doing AI Detection. Start Doing Learning Detection.

As I said in the show, AI detection whack-a-mole, to me as a teacher, is pretty pointless. I have moved to at least two oral assessments every grading period. So I as told him: we shouldn’t be about AI detection; we should be about learning detection. He says the same thing in a similar way.

He said “Exactly” — and then told me the session he had just given is called Catch Them Learning. That is great!

Here is why the switch matters, in his words. It changes who carries the burden of proof. I think this table helps explain it.

What a lot of people realize is their academic integrity policy — it’s really a what we’ll do if we catch you cheating policy. It’s really about what not to do.

— Dr. Tony Frontier

As he said earlier, students need to be modeled what to do with AI and not be given a list of things that you can’t do.

What To Watch Out For: Tony had some lines we need to read.

• The arms race you cannot win. (13:48) — “The technology arms race is always going to be one that the students can win. Simply because there are more of them than there are of us.”
• False accusations create the behavior. (13:48) — “I’ve had a few kids in a few different schools say, I didn’t use AI, but once I got accused, now I run everything through a humanizer.” As Tony puts it: “it’s like the teacher forced them into using AI.”
• Detectors catch the wrong students. (13:33) — my own line, and Tony confirmed it from his focus groups: the only kids who get caught using AI are the ones who don’t know how to use AI.
• Policies that try to put the genie back. (17:16) — see the Blockbuster section below.

Where We Lose Kids

I asked Tony a question that I, as a mom of a couple of dysgraphics, wonder: does it make it okay if you can pay to have a human writing coach, but not okay to turn AI into a writing coach? His answer started with IEPs and case-by-case judgment and he says that is important. But then, he makes a great point that speaks to equity.

When my kids came home from school, stuck on their schoolwork, they had a dad with a PhD and a mom with a master’s degree to help them. No one ever asked, right, did your parents help you with this? But we’re hyper-concerned now about, did I help you with this? We should have been asking those questions all along.

— Dr. Tony Frontier

Then he described the moment a student’s inner voice turns. What happens when a kid says “I’m stuck, I don’t get it?” But it can happen often by second or third grade, sometimes as early as the end of first, the next voice becomes “I must not be very smart.” That kid stops trying. And the only tool they can think to reach for is one that hands them the answer. This is not good. (It is the cognitive surrender that MIT talked about in their report and one we need to be watching out to prevent!)

Our Most Agentic Learners Are Kindergartners

Our students with the greatest level of agency in our schools, they’re our kindergartners. They come in, they ask questions, they want to know, they want to tell you. That’s how we want kids to interact with AI tools.

— Dr. Tony Frontier

And the skills turn out to be the same ones we already teach: “Asking questions, seeking clarification. If something isn’t working for your learning, can you stand up and say, help me out here? I need that differently.”

An Image to Help: The Blockbuster Boardroom

When Tony hears schools talk about ramping up policies to catch cheating, this is what it sounds like to him:

Some of the conversations that were probably happening at the Blockbuster video boardroom right around 2010. Where it was like, you know, if we just get this late fee thing right, everything’s gonna be fine. No — that was a transactional solution to a transformational challenge.

— Dr. Tony Frontier

The transformational challenge, he says, is that how people receive and consume entertainment had completely changed. It did not matter how hard Blockbuster chased the late fee policy. It was the wrong conversation.

And perhaps instead of the AI “whack-a-mole” detection impossibility (wrong conversation) we should instead be having a conversation about what truly makes education (the right convo to have, perhaps?)

Tony says: “We have an education model that’s built on 1890s technology. We’re gonna batch process kids, roll them down the conveyor belt” — same page, same pace, same time, because that is how you manufacture things. His argument is that these tools, used well, finally make it possible to stop.

Try This Tomorrow: The Quarter Sheet of Paper

When I told Tony this kind of conversation takes time, he agreed. Then he gave the single most usable thing in the episode. Students upload the assignment the night before. The next day, on a quarter sheet of paper:

1. Here is an important word from last night’s homework. Write your definition of it.
2. What was the main idea?
3. What was your biggest takeaway from last night’s assignment?

No, you cannot grade a hundred and forty of those every day. That is not the point.

It’s not just turning it in. I want to know what you know. I want to know what you don’t know. I want to know what questions you have. It starts to shift the culture.

— Dr. Tony Frontier

I remember in 1991 I started teaching people how to use the internet. I remember people being scared. Others were angry. And I received criticism that I was somehow a bad person because I believed people needed to learn to use the Internet properly and civilize it. Internet used to be a proper noun. In 2016, we started using internet in lowercase. That is how much the internet became part of everything we do. Enough to no longer be a proper noun! It is no longer a question of whether we use the internet; it is how, when, and why. We need intentionality there, too.

The criticism that came with Web 2 stung a little less. But by now, I just move forward. AI is the most powerful technology we’ve ever encountered as a general populace, and it comes with far more responsibility.

This technology is literally different for everyone who uses it. Previously, if I logged in to an app, I might have a similar experience to yours. No more. A thousand tiny nuances from how we speak and type to what we ask can cause our experiences to be far different. The challenges with bringing student-facing and teacher-facing AI to schools are many, but it is here, and we have to move forward and have the conversations that matter. AI detection is just so not the convo to be having.

I hope that you’ll pick up Tony’s book and use what I’ve shared with you here to add to the conversations you’re having at your school.

Resources Mentioned in This Episode

• Report of MIT’s Ad Hoc Committee on AI Use in Teaching, Learning, and Research Training — released August 25, 2026. The report I read from at the top of the show, and the source of “cognitive surrender.” Read it yourself; do not use AI to summarize it.
• The AI Center Implementation Toolkit — the toolkit Tony references on air, with the worked examples of effective, ineffective, and inappropriate use. It includes a four-phase planning process plus the full set of guidelines, boundaries, and shared commitments.
• Guiding Principles and Action Steps — the free PDF for leadership teams and teacher teams, from the AI Center.
• AI with Intention: Principles and Action Steps for Teachers and School Leaders — Tony’s newest book, with a foreword by Jay McTighe. Also available from ASCD.
• Students’ Perceptions of AI in Seven High Schools: Moving from Avoidance and Deterrence to Responsible Engagement — Tony’s write-up of the focus-group work he describes in this episode. This is where the twenty-five-to-forty-percent finding comes from.
• The AI Center for Effective Teaching and Learning — Tony directs it. Also home to the AI2TPS teacher-perception survey and the student focus-group protocol, if you want to run this in your own school.
• Experience AI — this episode’s sponsor. Free AI literacy lessons from the Raspberry Pi Foundation and Google DeepMind.

About Dr. Tony Frontier

Dr. Tony Frontier was a teacher in Milwaukee Public Schools and a high school principal, K-12 curriculum director, and University Professor. He is currently the Director of the AI Center for Effective Teaching and Learning where he works with schools and districts to ensure AI tools are used in ways that support, rather than undermine, effective teaching and learning. He is author of 6 books and numerous articles. His most recent book, AI with Intention, Principles and Action Steps for Teachers and School Leaders with a foreword by Jay McTighe, and has been praised by John Hattie as “the best book I have read to introduce all to optimize the power of AI.”

Find Tony: AI Center for Effective Teaching and Learning · LinkedIn · ASCD

Other Shows for Teachers and Administrators Writing AI Policy

• Creativity and Art in an AI World — Susan M. Riley on why creativity is the defining skill of the AI era. This is the Monday show where we used the phrase “hard fun,” which MIT uses in this report too.
• How to Build Your Own Data Dashboard: No Coding Required — A.J. Juliani on building your own AI tools, de-identifying student data, and the one question to ask any vendor.
• AI With Intention: What Leaders Decide and Teachers Do — Tony as part of the AI and Edtech SuperSeries from ISTE 2026.

Disclosure of Material Connection: This is a sponsored episode and blog post. Experience AI has compensated me to share information about the Experience AI program. However, all opinions expressed are my own. I have personally reviewed these resources and only recommend tools I believe offer genuine value to classroom teachers. My endorsement is limited to the educational products and services discussed in this episode. I am disclosing this in accordance with the Federal Trade Commission’s 16 CFR, Part 255: “Guides Concerning the Use of Endorsements and Testimonials in Advertising.” The sponsor has no impact on the editorial content of this show.

Disclosure of Material Connection: This episode includes some affiliate links. This means that if you choose to buy I will be paid a commission on the affiliate program. However, this is at no additional cost to you. Regardless, I only recommend products or services I believe will be good for my readers and are from companies I can recommend. I am disclosing this in accordance with the Federal Trade Commission’s 16 CFR, Part 255: “Guides Concerning the Use of Endorsements and Testimonials in Advertising.” This company has no impact on the editorial content of the show.

The post AI in Schools: Stop AI Detection, Start Learning Detection appeared first on Cool Cat Teacher Blog by Vicki Davis @coolcatteacher helping educators be excellent every day. Meow!

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From the Cool Cat Teacher Blog by Vicki Davis

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Tim Plaehn is a teacher who writes about honor codes. In his writing class last April, he believed he had two students he knew used AI. So, he gave the whole class an opportunity to “come clean,” and he said his email began dinging while 22 of the 40 students admitted they had used AI on their papers. Tim has authored the book, The Honor Code: Students, Integrity, and our Path Forward , where he talks about integrity and how we need to be discussing integrity with our students. This is not an easy topic but an important one!

Listen to my conversation with Tim Plaehn — or watch it on YouTube, or read the full transcript.

SPONSORED: Experience AI, a free program co-developed by the Raspberry Pi Foundation and Google DeepMind, sponsored this episode. All opinions are my own and that of the guest.

Experience AI is a free AI literacy program with ready to teach lessons for ages 8 to 16. The lessons are written for teachers of all subjects including: science, math, social studies, English, and art and some don’t even need a computer to use. Support your students to become critical thinkers and better understand AI technologies today. Explore the free resources at Experience AI.

Tim spent ten years as faculty chair of the honor council at Asheville School. No, their school didn’t publicly shame students, but the situations were hard nonetheless. He was the one who sat across the table from the students. He also knows the consequences if students aren’t held accountable (and sometimes even when they are.)

He also talks about some restorative practices. For example, a letter the student writes to their parents about the situation (that never gets sent.) We have so many issues with students these days and Tim shares some practical ideas and thoughts that can help shape our conversations about honor and integrity in school today.

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Middle and high school teachers who have caught it and don’t know what to do next — and the deans, principals, and department chairs who write the policy they’re working under. If you have ever wondered whether your school’s response to cheating actually changes anybody, this is your twelve minutes.

Key Takeaways for Teachers from Tim Plaehn

• Separate conduct from honor. (06:31) Out of the dorm after lights gets a detention; cheating on a test gets a conversation with the honor council chairs about what you did and what you’re going to do about it. Two different problems were getting one response, and Tim says pulling them apart is what made the whole thing work.
• Offer restoration before you run detection. (10:57) Tim didn’t put the papers through software — he emailed forty-five students and gave them a way to come back, and twenty-two of them took it that night. A detector would have found the two he already knew about, but he would have missed that over half the class used AI. (As I’ve said before, because DETECTORS DON’T WORK!)
• Have them write the letter, then don’t send it. (07:11) Students write to their parents about what they did — and Tim tells them up front it isn’t going anywhere. It’s not the punishment; it’s the part where they have to say it in their own words.
• Answer “I know my child’s heart” honestly. (02:58) No parent knows their child’s heart well enough to rule out a mistake, and Tim’s response is the one I keep coming back to: when a kid asks “Dad, don’t you trust me?”, the answer has to be no — not because they’re bad, but because they’re fifteen.

The next time a student owns up to cheating, don’t start with the consequence. Hand them paper and have them write a letter to their parents explaining what they did and why — and tell them before they start that you are not going to send it. Tim’s whole point is that the letter isn’t evidence and it isn’t a punishment. It’s the only step in the process where the student has to put the thing into their own words, to the people whose opinion of them they actually care about. It takes one class period and costs nothing.

The part of this conversation that will divide a faculty room is the fourth line of Tim’s honor code — the one where students agree to report violations. He is candid that it is the piece most often broken, and he doesn’t pretend there is a clean answer. What he offers instead is a way of framing it that doesn’t turn a school into an informant culture: snitching, he says, is what you call it when a community is protecting the person who did wrong instead of the community itself.

I mention the Common Sense Media research in this episode. Here is the current number: 86% of kids ages 9 to 17 use AI, and nearly a quarter use it every day — 81% of 9-to-12-year-olds, 89% of 13-to-15-year-olds, and 92% of 16-and-17-year-olds. More than four in ten say no parent or guardian has ever talked with them about AI safety, and while three-quarters say their school has covered what they can and cannot use AI for, only just over half have been taught how to use it safely. Source: The Common Sense Media Census: AI Use by Tweens and Teens (2026), released June 8, 2026, surveying 1,204 children.

Resources Mentioned in This Episode

• The Honor Code: Students, Integrity, and Our Path Forward — Tim’s book, built on four real honor cases he fictionalized to protect the students in them. He explains why at 01:33: at his school, an honor case is nobody else’s business.
• Tim Plaehn’s Substack — where he writes about integrity in schools and in the wider culture, and publishes excerpts from the book.
• The Honor Code podcast — Tim’s own show, on the same subject as the book.
• Asheville School — the North Carolina boarding school where Tim teaches American Studies and chaired the honor council for ten years. The campus detail he describes at 08:01 — laptops and backpacks left out in the open because nobody expects them to be taken — is the culture the honor code is protecting.
• The West Point Cadet Honor Code — the non-toleration model Tim admires at 10:02.
• The Common Sense Media Census: AI Use by Tweens and Teens (2026) — the research behind the number I cite at 14:12. Released June 8, 2026; 1,204 children ages 9–17.

Editor’s note on the West Point honor code: Tim paraphrases it in conversation. The code itself reads, “A Cadet will not lie, cheat, steal, or tolerate those who do.” Asheville School’s own code — the one whose fourth line Tim is describing — reads, “I will not lie, cheat, or steal, and I will report any violations of the honor code.”

About Tim Plaehn

Tim Plaehn is a writer and teacher living in Asheville, North Carolina. Over his thirty-year career in education he has taught in Las Vegas, Hartford, Atlanta, and Asheville and has earned advanced degrees from Harvard’s Graduate School of Education and the Bread Loaf School of English. He has been awarded Clark County’s New Teacher of the Year Award, the Charles N. Carter Leadership Award in Coaching, and the William F. Lewis Faculty Chair for Teaching and Coaching Excellence, among others.

His first screenplay, The Panjiayuan Diary, won the Beijing International Screenwriting Competition, and he followed that up with The Reconstruction of Huck Finn (Over Mark Twain’s Dead Body!), a Nicholl Fellowship semi-finalist in 2017. His play West Asheville was selected to The Barefoot Theatre’s reading series at the Art of Acting Studio in Los Angeles and for a workshop performance at the Cherry Lane Theatre in New York. His short play Jenna Feldman, A One-Woman Show won the audience favorite award at The Hickory Playground’s One-Act Play Festival, and Metallica Is the Last Straw was selected for a performance at Toronto’s InspiraTO Festival. He’s been published in Short Story America and Creative Loafing and has written screenplays on sumo wrestling, golfing across America, and a family reunion in Ireland gone terribly wrong. That last screenplay had a Top 3 finish in The Nantucket Film Festival’s screenplay competition in 2022, prompting Olivia Wingate to sign on as producer. He was also awarded Ireland’s Aran Islands Poetry Fellowship, and he spent a month cold, wet, and happy on Inis Mor.

His book is The Honor Code: Students, Integrity, and Our Path Forward.

Find Tim: timplaehn.substack.com · The Honor Code podcast

Other Shows for Teachers and Administrators Facing the Honesty Question

• AI and Academic Honesty: The Second Crisis in Schools — philosopher Dr. Christian Miller, author of The Honesty Crisis, on why the internet was the first honesty crisis and AI is the second — and why it runs on both sides of the desk. If this episode landed, that one is the companion.
• Honest Conversations About AI: The Need for Truth — the Cool Cat Teacher Talk episode with MIT’s Justin Reich and Dr. Christian Miller on research, integrity, and what we are actually measuring.
• The Human Side of AI: A Student’s ChatGPT Experience — a student who ran his teachers’ assignments through ChatGPT for his senior project to see which ones held up. The other side of Tim’s story.

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If your school is still arguing about detection software, send this one to whoever writes the policy.

Episode Transcript

This transcript was generated using AI and has been reviewed by humans for accuracy. Minor errors or artifacts may remain but I worked my best to find any issues with the transcript as I reviewed the show. – Vicki

Disclosure of Material Connection: This is a sponsored episode and blog post. Experience AI has compensated me to share information about the Experience AI program. However, all opinions expressed are my own. I have personally reviewed these resources and only recommend tools I believe offer genuine value to classroom teachers. My endorsement is limited to the educational products and services discussed in this episode. I am disclosing this in accordance with the Federal Trade Commission’s 16 CFR, Part 255: “Guides Concerning the Use of Endorsements and Testimonials in Advertising.” The sponsor has no impact on the editorial content of this show.

Disclosure of Material Connection: This episode includes some affiliate links. This means that if you choose to buy I will be paid a commission on the affiliate program. However, this is at no additional cost to you. Regardless, I only recommend products or services I believe will be good for my readers and are from companies I can recommend. I am disclosing this in accordance with the Federal Trade Commission’s 16 CFR, Part 255: “Guides Concerning the Use of Endorsements and Testimonials in Advertising.” This company has no impact on the editorial content of the show.

The post Academic Integrity: What 22 Confessions Taught a Teacher appeared first on Cool Cat Teacher Blog by Vicki Davis @coolcatteacher helping educators be excellent every day. Meow!

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From the Cool Cat Teacher Blog by Vicki Davis

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Generative answers are everywhere. People like them because they are simple and they just “give the answer.” But what if the answer is nuanced. And what if, in the case of the generative tool, it is so eager to give an answer that it makes mistakes that any researcher would understand. Let’s go through an example.

So, first, Generative Adversarial Networks were used from roughly 2017 to 2022 to make deepfake videos. So, one model generates the video, another model evaluates it, and they go back and forth until the video quality becomes so good that it could become undetectable from the real thing. At first I called what I was doing a GAN, but it turns out a GAN is a training architecture, not what I’m doing. The right word is ensembling. Some may call it a “multi-agent debate” or “cross-model verification.” How did I find this out? I am training my AI tools to teach me more about AI and check my word choices and teach me about the models that underlie what I’m doing. It is a helpful method for learning in a domain of knowledge, to be up front with the tools you use about the pursuit of knowledge in that domain. It creates a mini spotlight that the AI tool will use to funnel me more of what I want to learn about.

As I dug into ensemble methods, I found the ROVER Method is one that I’m really using for these transcripts that are more accurate. So, I use Riverside which generates a transcript. Then, I put a video into Adobe Premiere Pro which uses another model to generate a transcript. Finally, I use Auphonic which then uses Whisper to generate a transcript. Then, Claude Cowork has a skill that I built which takes the bio of the guest and the topic to ensure that all acronyms are appropriate for that domain of knowledge and defined in the transcript and I also have fact checking to double check anything said built in. And the transcripts are compared until a final transcript emerges. I’ve found that each model is better at different things. Adobe for timings and finding subtle noises and words. Riverside for getting the names accurate. And Whisper for double-checking hard-to-hear phrases and such. And between them as I run them “against” one another, and have Claude ask me about discrepancies, I can get transcripts that are more accurate, less expensive, and less time consuming than what I’ve ever done before. It is a technique. By running the models against each other, I’m getting better results.

What About Fact Checking

We know about AI “hallucination” or as many prefer to say “confabulation” where AI just makes stuff up. But now, AI can cite things so it is supposed to be better, right?

Well, I went through an example that I’ll be using with students because it really shows the nuances of AI and research studies. Simpler is not always better when it means we think we understand and state error as fact.

Now, do not stop at Step 2, or even at Step 3. I need you to follow this chain of reasoning here so we can answer the question: how accurate are “AI Overviews” and is the question even the right question to ask?

Step 1: Google Search

So, first, I’m working to find hallucination rates for AI currently, so I did a simple Google search.

This is a number I update quite frequently, but I was curious as to the accuracy of these numbers in the generative search box. The first thing that bothers me is that whenever I see numbers presented without citations, an alarm bell goes off. See the words “high rates” and “legal research” and “low rates” – perhaps the citation on the second bullet is there, but sometimes it isn’t.

STEP 2: Claude Fact Checking Skill

So, I took a screenshot of the Google search and went to Claude. Now, granted, if I had pasted in the research links, more accurate information would have happened arguably at this step. But I want to demonstrate how we’re fact checking at a conference or event, that we might take a screenshot, so for now, this test is using screenshots.

So, I went into Claude and pasted the screenshot and asked it to “fact-check these numbers from a Google search.” Then, after it came back with errors, I asked it to update the Google graphic with information on what it found. On the right are Claude’s verdicts, and on the left is the original search. But wait, we need to get the ensemble activated here. We’re not done yet. Gemini may not be so bad, and Claude might not be so good. (Again, I didn’t give links, or item 2 would have been a different answer.) I use ChatGPT Pro and Perplexity Pro as part of this process.

Note: I have programmed my AI tools to help me teach. Everything I create is in the context of teaching someone, even myself, so you can see the lesson for the student emerge organically from that memory file.

STEP 3: Fact Check with ChatGPT Pro set to “high”

So, now I took the graphic from Claude that is above and I pasted it into ChatGPT, again using the screenshots. Its conclusion, “There are errors on both sides.” So, now this third model is finding errors on both sides of the equation, both Gemini and Claude. Here is the summary it found.

ChatGPT, to summarize, found the following:

• Claude got Vectara backwards and found the November 19, 2025 announcement and not the newer announcement.
• ChatGPT’s wording is important here, “I would not call most of Google’s individual numbers hallucinations. The more serious issue is they answer different questions…those percentages cannot meaningfully be placed on one common ruler. Here is what ChatGPT states about these.

A Vectara 1.8% means roughly: When the model is handed the source document and told to summarize only that material, how often does the summary contain something unsupported?

The Stanford legal number means: When an older general-purpose LLM is asked precise questions about federal court cases without necessarily being handed authoritative source material, how often is its response inconsistent with the legal facts?

The Mount Sinai clinical number means: If researchers deliberately planted a nonexistent medical fact in a case, how often will the model fall for the trap and elaborate on it?

AA-Omniscience asks yet another question about whether models guess rather than admit they do not know. Its hallucination rate denominator is specifically incorrect / (incorrect + partial + not attempted).

Oh my, so you mean my fact-check tool can be wrong too? Now, we’re getting past hallucination, and we need to be careful about throwing around this word. We’re talking about accuracy here, and mismatched research outputs can make a big mess.

As ChatGPT said, we don’t have one ruler; we have four rulers here, and they have mixed together things that don’t go together. Humans make mistakes. So do AI models that trained themselves on humans, and for the sake of simplicity, start boiling together ingredients that are basically like mixing chocolate and vinegar and dirt for good measure and expecting a Flambé.

STEP 4: Pasting ChatGPT’s answer back into Claude and asking for a Response

Ok, this is where the apologies start. We all know the drill. We catch AI making mistakes and then it is sickly sorry for what it has done. The two apologies included:

• Vectara Leaderboard, it pulled November 2025 instead of May 11, 2026. This is a good catch and precisely how you see how multiple models can help things.
• ChatGPT caught a logic error because it implied that o1 was not a reasoning model, but it was, so that comparison can’t demonstrate that reasoning models hallucinate more, only that the newer one scored worse than an older one.
• It said it had dismissed suprmind.ai as an “SEO content hub” without looking at the source of the numbers on that page. So, it looked at the source that held the numbers and didn’t realize that it also had a source, revealing a flaw. If something is searchable and findable and holds a number, sometimes AI only goes to that page instead of tracking back to the original sources.

So, then it said that ChatGPT was not right about Gemini 3 Flash at 92%, as it found that Gemini 3 Flash was at 88%, so they disagreed on that model so it is more accurate to leave the ceiling out.

At this point, I think most people would fatigue and say “what is right here” but I’m about to do a big old mammoth update to throw a whole bunch of data into my tool to help determine what is right but the conclusion – by the Ai models themselves – is going to be a powerful one if you can persist. Again, we’re running models against models. And in the end, students need to understand not only are there errors, but sometimes, those errors are there because of mistakes in looking at the wrong information and aren’t just “hallucinations.” That research is nuanced and that human eyeballs are valuable.

STEP 5: Multiple model fact checking

So, I just wanted to be done with this, so I took Claude’s results and put them into both ChatGPT and Perplexity. I specifically told Perplexity that I had used Claude and ChatGPT, and that I had put it in orchestrator mode, so it might need to use other models. I’ve linked the chats above for transparency and so you can see some of the exciting nuance that comes out of these.

Interesting tidbits:

• Perplexity and Claude both used the older November 2025 article instead of the newer article. As Claude said, “Perplexity confidently endorsed my wrong verdict using the same bad method that produced it.”
• ChatGPT was the tool that found that Llama 2 was the wrong example to use for Google’s ceiling.
• Because of “disagreements” between models and the fact they didn’t report the ceiling of some numbers, it is better to leave it out.

Now, if you look at my Claude chat for this, you’ll see a “retrospective,” which is where Claude analyzes what it got wrong. There is a method to my madness here with this and I’ll get there in a moment. But the Perplexity chat says something interesting:

"The teaching point in your footer is the real lesson: the primary sources (live leaderboard, paper abstract, system card) beat any AI summary of them, including one AI's summary of another AI's summary."

So, the AI itself acknowledges that we have a big old mess without consulting the original sources. So, then I took information from both ChatGPT and Perplexity and here’s the current output of AI evaluating the Google AI Overview.

OK, so this is interesting now. I want a graphic evaluating Google, and Claude is interjecting evaluations of itself. This is “mission drift” in action, particularly when you are fact-checking. So, I’m having to ask for a final graphic evaluating the Google generative results on the hallucination rates of AI models.

STEP 6: Re-generate the original graphic for the original purpose of this task

Now, I want you to note a few issues that I do not like about the information above:

• The citations are small and listed at the top. Again, we have a graphic and it is hard to fact check. I, thus, asked AI to generate a research box so I can read information and double check the conclusions.
• I would really like all models used to be documented somewhere somehow. It is citing the human, for sure, me – Vicki Davis- but it isn’t putting “Created using Claude Cowork” or any other models that I used in the fact-checking process. I think model disclosure will be very helpful in the future, even as we humans are held accountable. Being able to be cognizant of the need to document chats in this way is important. When you see the chat, you’ll see what I mean.
• Before I would produce this as “research,” I would need to sit down and read every single study, and I would argue that, with all of this back and forth, reading original source documents is more important than ever. We should be researching slower not faster when we see this happen.
• I would really like to be able to generate a link to share this claude check but because I run Claude Cowork on my computer, I’ll have to generate a PDF instead which I will paste below.

When you look at this, you’ll notice how I use Claude to fact-check my writing. Now, you might think – Claude was wrong; why would you use it to fact-check? Well, particularly in AI terminology, I’m learning and need to keep learning and understand various models. I believe that workflow is more important than ever, as are AI techniques, and to teach this, I have to understand and use the proper vocabulary. I live in rural Georgia — to call it the sticks might be an insult to sticks. So I can’t really go to my local coffee shop and hang out with the other AI nerds. I have to watch them on YouTube and read their articles on LinkedIn, so I’ve programmed the AI to help me be more accurate and precise in my AI speech. This is an example of using AI for learning. Also, the ability to produce a PDF of an AI chat is a valuable part of documentation as we look at the process of research.

STEP 7: Generate the Research Used for This Output with Hyperlinks.

I like to generate research as an HTML box I can paste into WordPress and then I can click on the links and review them in a new browser.

Research Citations

Every figure in the graphic above traces to one of the primary sources below, verified September 1, 2026. No aggregator numbers, no launch announcements, and no AI summaries were used as evidence.

Sources used

Grounded summarization
Vectara Hallucination Leaderboard (live repository, updated May 11, 2026). github.com/vectara/hallucination-leaderboard — source of the 1.8%, 3.1%, and 3.3% figures. The 9.6% median across 105 models was computed directly from this table.
Awadallah, A. and Mendelevitch, O. “Introducing the Next Generation of Vectara’s Hallucination Leaderboard.” Vectara, November 19, 2025. Read the announcement — cited for methodology only.

Open-domain factual recall
AA-Omniscience evaluation page, Artificial Analysis (live scores and metric definition). artificialanalysis.ai/evaluations/omniscience
Jackson, D., Keating, W., Cameron, G. and Hill-Smith, M. “AA-Omniscience: Evaluating Cross-Domain Knowledge Reliability in Large Language Models.” arXiv:2511.13029, 2025. Read the paper

Reasoning models
OpenAI. “OpenAI o3 and o4-mini System Card,” April 2025, Table 4. Read the system card

Legal research
Dahl, M., Magesh, V., Suzgun, M. and Ho, D. E. “Large Legal Fictions: Profiling Legal Hallucinations in Large Language Models.” Journal of Legal Analysis, 16(1), 2024, pp. 64–93. Read the paper · Stanford RegLab summary

Clinical decision support
“Multi-model assurance analysis showing large language models are highly vulnerable to adversarial hallucination attacks during clinical decision support.” Communications Medicine (Nature Portfolio), 2025. Icahn School of Medicine at Mount Sinai. Read the study · PubMed listing

Methods and terminology

Fiscus, J. G. “A Post-Processing System to Yield Reduced Word Error Rates: Recognizer Output Voting Error Reduction (ROVER).” Proceedings of the IEEE Workshop on Automatic Speech Recognition and Understanding, Santa Barbara, CA, 1997, pp. 347–354. NIST record — the documented technique for combining multiple speech-recognition outputs into one composite transcript more accurate than any single system.

Du, Y., Li, S., Torralba, A., Tenenbaum, J. B. and Mordatch, I. “Improving Factuality and Reasoning in Language Models through Multiagent Debate.” arXiv:2305.14325, 2023; published at ICML 2024. Read the paper — multiple model instances debate an answer across rounds, improving factual validity.

Goodfellow, I. et al. “Generative Adversarial Networks.” arXiv:1406.2661, 2014. Read the paper — cited for contrast. A GAN trains a generator and a discriminator together in one loop, with the discriminator’s judgment updating the generator’s weights. It is a training architecture, not a method for comparing finished models.

Sources Rejected, and Why

This list is the more useful one for classroom use. Each source below showed up during the research and was deliberately left out. Every link in this section is marked “nofollow” on purpose — see my note below.

1. Vectara’s launch blog post, quoted as current data. It is a snapshot from November 19, 2025, not the live leaderboard. Quoting its top scores as today’s produced the false claim that no model scores under 2%. The live repository shows 1.8%. The rule: a launch announcement records the day a benchmark was newest. For current numbers, open the artifact the announcement points to. See the announcement

2. AA-Omniscience’s launch article, quoted as current data. The same error on a second benchmark. Its “lowest at 26%” was quoted as the current floor; the live page shows 1%. Two details worth showing students: the article states its own figure inconsistently (28% in one bullet, 26% in another), and it explicitly says “For up to date AA-Omniscience scores, see the AA-Omniscience evaluation page.” The correction was printed right there and still got missed. See the launch article

3. Aggregator and content-hub pages. No methodology, no version history, no date-stamp showing which snapshot a number came from. The subtlety worth teaching: one such page’s numbers were actually correct. It was first dismissed for looking like a content farm rather than for any test of its figures — right conclusion, wrong reasoning. The real test is not whether a page looks credible but whether its numbers trace to a primary source you can open. See the page in question

4. “22% to 94% across 26 models,” attributed to the Stanford AI Index 2026. Could not be verified against the AI Index itself, and the descriptions that could be found identify it as sycophancy-induced hallucination — a different measurement. Two numbers both labeled “hallucination rate” are not necessarily measuring the same thing. See the AI Index report

5. “Gemini 3 Flash at 92%.” Sources disagreed and none was primary: reachable sources said 88%, two AI models later said 91%, the original claim was 92%. The live page publishes lowest scores but not highest, so the question stayed open. The graphic says “above 90%” instead. The rule: when sources conflict and no primary source settles it, report the range you can defend rather than the most quotable figure. See the Gemini 3 Flash analysis

6. Legal AI tool rates (Lexis+ AI 17%, Westlaw 33%). These come from a real follow-up study, but that paper was never opened during this check. Plausible is not the same as verified, so they were left out. See the follow-up study

7. A “1.47% real-world clinical hallucination rate.” Surfaced in passing, never traced to its source, so it was not used. No link — the source was never located, which is exactly why it was dropped.

8. The AI summary’s own citations. Worth pointing out to students: the visible citations under the search result pointed to content-marketing pages rather than to the Vectara leaderboard, the Stanford paper, the OpenAI system card, or the Mount Sinai study — the actual origins of every number it quoted. See one of the cited pages

A caution for anyone reusing this graphic: benchmarks update continuously. These figures were current on September 1, 2026. Check the live pages before quoting them later.

Notes about the research citations above from Vicki: So, do you see what I did there, it said “we” but then when it cited it, it cited “me” – Vicki. I don’t like this subtle use of pronouns. AI is a tool and I’m accountable. However, if I look at the chat, I am using the word we as well — I have to think on that. wow. Look at that.

Additionally, I would like the links to the articles that were rejected. Update: When I looked at adding those links, Claude pointed out something I had forgotten, that the presence of a true link passes SEO on for credibility to those sites, something I’m not really wanting to do so it will mark them as “no follow” links. This is an interesting aspect of citing rejected articles. Also, note that when I do this again, I’m going to create a version of this skill that stops and lets me make the decision as this chat was in “auto mode” for speed. I really had no idea this would be such a hard question to get right in Google generative search, but I’m glad I did this activity and it is one I will be doing with students.

STEP 8: Updating the Fact Checking Skill in Claude Cowork

Now, I’m coming back to the fact-checking skill I’ve built in Claude so you can see why I keep coming back. When I’m done, I ask it to analyze every mistake and then update the fact-checking skill. This is a whole other process because now, I’m working to teach the AI tool how I like to operate and to learn from interacting with other AI tools about the flaws and mistakes in that tool.

This is why skills will become valuable intellectual property for companies (if indeed they can be owned by the company and not harvested by the AI models themselves, which is a whole other topic.)

RETROSPECTIVE

In every chat, I ask Claude Cowork, ChatGPT, or Gemini to conduct a retrospective analysis of what worked, what mistakes were made, and how to prevent those mistakes in the future. It is a learning model. Our purpose in interacting with AI is both to get a job done and to make doing that job better in the future.

Additionally, by doing this sort of orchestration, we can build distrust for the overly simplified generative answers we’re getting from Google right now – or really any tool, for that matter. No tool is always right. Different domains of knowledge have different accuracy rates, and different ways of using AI can yield higher accuracy. Sometimes we need an ensemble in order to do complex tasks.

But here is a big takeaway: When in doubt, go to the original documents to check it out.

When we start using multiple AI tools to check for answers, we see that each tool is flawed and that we must use discernment to understand the nuances. Plus, rushing to get something out can lead to mistakes.

So, I’ve just written this as I’ve gone through the process, when I realized this wasn’t going to be an easy check. I was actually preparing a presentation about research using AI and just wanted to expose flaws, and the rabbit hole went much deeper than I thought!

The post AI Fact Checking Using the Ensemble Method appeared first on Cool Cat Teacher Blog by Vicki Davis @coolcatteacher helping educators be excellent every day. Meow!

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From the Cool Cat Teacher Blog by Vicki Davis

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A.J. Juliani has been leading cohorts of educators and administrators to learn how to build data dashboards that improve student learning. I love how he focuses on the human aspect of learning. In today’s show, we’ll talk through the “interview mode” of using AI that is so powerful in addition to using data to improve the experience of school for our learners and teachers. We’ll talk about personally identifiable information, the importance of removing it, and some tips and tricks for interacting with AI to generate data dashboards and other tools of your choice.

Listen to my conversation with A.J. Juliani — or watch it on YouTube, or read the full transcript at the bottom of this page.

SPONSORED: Experience AI, a free program co-developed by the Raspberry Pi Foundation and Google DeepMind, sponsored this episode. All opinions are my own and that of the guest.

Experience AI is a free AI literacy program with ready to teach lessons for ages 8 to 16. The lessons are written for teachers of all subjects including: science, math, social studies, English, and art and some don’t even need a computer to use. Support your students to become critical thinkers and better understand AI technologies today. Explore the free resources at Experience AI.

Watch this video on YouTube.Subscribe to the Cool Cat Teacher Channel on YouTube

How to Build a Data Dashboard from A.J. Juliani

You can listen to the whole conversation in the player above or read the full transcript below. Here’s what A.J. walked through, step by step.

The Problem that Educators Can Solve with AI Created Data Dashboards

Students have data everywhere. But we need to talk to our data. As I approach the one-thousandth episode of my podcast, I downloaded a CSV file into Claude Cowork and used Claude to “talk to my data.” This is a different approach for data analysis. I don’t write the word “game-changer” since I just wrote about how I hate that word on Linked In. I will, however, say that those of us who learned spreadsheets, pivot tables, formula creation and data analysis need to learn the newest tools for analyzing our data. This is another step in the progression of data analytics.

AJ talks about the problem we’ve had with data by saying:

✏️✏️✏️

How to Build a Data Dashboard without Writing Code

Understanding the methods A.J. teaches can guide you through creating data dashboards. If you can only have one takeaway, pick 2, the “AI interrogatory” method of starting with an AI interview prompt.

STEP 1: Start with the Problem Not the Tool

AJ says that they first went and prompted the tool they chose (in this case, Claude):

What are ten ways we can use data effectively in our [school or district or classroom] with our objective of [insert objective].

They worked to identify the problem before selecting a tool with brainstorming how the data could be used and the kinds of dashboards that could be created.

STEP 2: Let the AI Interview You

On a recent Cool Cat Teacher Talk show, Dr. Jie Tao discussed the interview method as one of the most powerful ways to interact with AI. AJ gives this sample prompt.

I want to build a dashboard for my [district, school, classroom] that focuses on [what things you want to focus on] Help me walk through this process and ask me questions to tailor specifically what this data dashboard should look like."

From there, the AI tool takes over. It acts as the interviewer, interviewing the educator, “and that is the real key that I think people miss along the way,” says A.J., “You don’t have to prompt it for everything. It can ask you questions and then take your answers to create it. A couple of years ago people were talking about how we have to have the exact right prompt and these different types of things. With a lot of these tools now, that’s not the case.”

STEP 3: Talk to the AI Tool, Not at It

As you get a MVP (minimum viable product), then you can start talking with your AI tool about what is missing, about formatting issues, about how the data can be more meaningful.

TIP: Sometimes, AI can put information in a spreadsheet for you as well, particularly if you want formulas. But you have to explicitly ask it to enter formulas into the fields; otherwise, it might just total the numbers and enter them into the spreadsheet cells. This leaves room for error. Excel can use both Claude Cowork and now Copilot is available (but you have to save it in the Cloud or on OneDrive or SharePoint with AutoSave turned on with a paid Microsoft 365 Copilot or Copilot Pro license.)

Last year, when I taught my students spreadsheets, I also taught them to use AI to help them build pivot tables and interpret data, and I was shocked at how quickly they learned and advanced more deeply into data analytics than I could ever get them before.

But here, we’re talking about HTML files that open in a web browser, not a spreadsheet. Just realize that people build dashboards in different ways. I do recommend trying the HTML dashboard. I am a spreadsheet nerd, but I am blown away by the power of a data dashboard in HTML, as AJ describes!

STEP 4: Build the Conversation into the Dashboard Itself

A.J. went on to remind us that data doesn’t need to be static but can be built for analysis.

“So instead of teams just seeing the data and just seeing the connection, why not build that conversation feeder right into it? So, PLC teams, district teams, communities can look at district data dashboards and actually have conversations with the data, visualize it in different ways.”

AJ encouraged the conversation not to be just with AI but that data analysis should be done in a social context within school or district teams.

10 Things to Create Data Dashboards Worth Building

A.J. stated some things that he recommended reviewing and building data dashboards to analyze (and some may do more than one):

1. student achievement
2. attendance and chronic absenteeism
3. equity and subgroup analysis
4. intervention effectiveness
5. formative assessments
6. benchmark data
7. teacher and classroom data
8. enrollment capacity planning
9. school climate data
10. budget resource allocation

Protect the Student Privacy Before You Upload Anything

If we talk student data, we have to talk about PII (personally identifiable information) and AJ responded with his answers here.

• Does the data get uploaded anywhere? — “Files are read entirely by the browser and sent once to the AI for analysis. Nothing is saved in the server database or disk. Once you close or refresh the page, the data is gone.
• Is it encrypted? — “All communication between your browser and the server uses HTTPS… Your file can’t be intercepted while being sent.”
• Who can see what you upload? — “It’s sent normally through something like OpenAI’s API for analysis, and they don’t use API data for model training, but it does pass through their server.”
• Should you upload real student data? — No. See below.

What To Watch Out For

• Uploading real data.(13:03) — “The biggest caution is when you’re using real data and not de-identifying it. If you do that, you put yourself in a world of trouble with CIPA, COPPA, all the different types of privacy laws out there.” CIPA (the Children’s Internet Protection Act)
• Skipping the approval channels.(13:03) — “We have to go through the proper channels. We have to build policies that support this. We have to get it approved by administration, approved by boards.”
• Outsourcing everything.(09:17) — “We’re sending it to this AI company or to this company… and we’ll just worry about it there.”
• Kids under 18 on consumer tools.(09:17) — “We have kids who are under 18 just using the regular version of ChatGPT… and the privacy is terrible. There’s so many red flags there.”
• Bolting AI onto a compliance culture.(09:58) — “If your school is still built on a compliance-based model, tech only fuels that compliance — whether it was laptops or it’s AI. And a lot of times it becomes digital pacifiers.”
• Removing the human from all three steps.(09:58) — “Do you want a world where AI is helping your teachers plan tasks, the AI is helping students do the tasks, and then the AI is helping your teachers create the tasks? I mean, now we’ve just removed any human from it possible.”

4 Questions to Ask Before You Adopt Anything

As AJ guides us to consider AI dashboards, he gave four questions to help us with discerning if something is a good use of AI (or not):

• Why are we adopting this?
• Is it just helping us save time or is it helping us with better pedagogy?
• Is it just helping us save money, or is it helping with a better learning experience?
• Is it just helping us look at data more, or is it helping us with making decisions better?

“The most important skill right now is discernment – discernment of when to use it, how to use it, and where it’s applicable. You can’t build that discernment skill if you’re not using the tool.” A.J. Juliani

The One Question to Ask Any Vendor

IT Directors, and Principals

Can you give me a csv? CSV stands for “comma separated values.” Basically, it is the data fields with commas in between. Be careful as this can have PII in it (as we’ve already discussed), however, even though it is hard for us humans to read, this is the language of spreadsheets and AI and makes data something you can easily turn into a data dashboard.

Eventually, we’ll ask vendors about MCP’s, the kind of connector to connect our data directly to AI, but until we get the PII sorted out, that is probably a step away from where we are today, where we first download the CSV and then look at the data that needs to be removed (in a spreadsheet tool, most likely) and then after the data is removed, then create a new file that can be put into AI for a data dashboard.

De-identification — Removing the details that connect data to a real person — replacing student names with labels, taking out addresses and phone numbers — before the file goes anywhere near an AI tool. This is the one instruction A.J. repeats, and it is not the same as PII redaction, which is what a tool does automatically. This one is on you, and it happens first. (NIST defines it here.)

API (Application Programming Interface) — A doorway that lets one program hand data to another. A.J.’s point matters for schools: when a tool reaches an AI company through its API, your data passes through that company’s servers even when it is not used to train the model. Those are two different questions, and vendors sometimes answer only the friendlier one.

Interview Prompting — Asking the AI to interview you. It asks the questions, you answer, and it builds from your answers — instead of you trying to write one perfect prompt. A.J. calls this the thing most people miss.

These three are new to my AI Vocabulary List — I’m adding them. Want to find out how many of these words you already know? Play Spy the AI, the free vocabulary game I vibe coded from that same list.

What This Looked Like in One School

AJ describes one school that created a data dashboard that connected their gradebook, their attendance, and some of their teacher feedback tools inside of Google Classroom. He said it started flagging when a student was absent for a couple of days or wasn’t turning things in… for the teacher and student to have a conference and a conversation. The school told AJ it has completely transformed what instruction looks like, because now students know that if they’re missing something, they’re going to have conversations with their teachers right away.

An Image to Help: The Laundry and Dishes

You know what the biggest problem with pushing all-things-AI is? Wrong direction.
I want AI to do my laundry and dishes so that I can do art and writing, not for AI to do my art and writing so that I can do my laundry and dishes.

— Joanna Maciejewska (@AuthorJMac) March 29, 2024

AJ pointed to this quote from Joanna Maciejewska and said,

“What is the role of laundry and dishes in education? How can AI help us with the laundry and dishes so we can spend more time doing the things that we want to do with our students?

Resources Mentioned in This Episode

• ajjuliani.com — A.J.’s site, and the one thing he asks for on air: “You can go to my website where I link to it.” His AI-Ready School Leaders cohorts are announced through his newsletter, which has 103,000+ subscribers.
• Claude Code — the tool A.J. uses to build the dashboards. He names the ChatGPT equivalent as Codex. Both are coding tools you talk to in plain language rather than program.
• Replit — the other build environment A.J. and Vicki mention for people who want to make something without setting up a development environment. (Note from Vicki: it is no longer free.)
• CSV files — the humble format at the center of his vendor test. A CSV is just a spreadsheet, and A.J.’s point is that every AI tool can read one: “you can use it in any — you know, Gemini, ChatGPT, Claude, any of them.”
• Google Classroom — the platform in A.J.’s school example, where a grade book, attendance, and teacher feedback were connected so a student who went quiet got flagged for a conversation.
• CIPA and COPPA — the two student-privacy laws A.J. names as the reason to de-identify before uploading anything. CIPA is the Children’s Internet Protection Act; COPPA is the Children’s Online Privacy Protection Rule.

About A.J. Juliani

A.J. Juliani is faculty at the University of Pennsylvania Graduate School of Education and the Wall Street Journal and USA Today bestselling author of Adaptable: How to Create an Adaptable Curriculum and Flexible Learning Experiences That Work in Any Environment. A former English teacher, football coach, and K-12 instructional coach, he served as Director of Learning and Innovation for Centennial School District in Pennsylvania.

He is also the author of Empower: What Happens When Students Own Their Learning and LAUNCH: Using Design Thinking to Boost Creativity and Bring Out the Maker in Every Student, both with John Spencer, as well as The PBL Playbook and Intentional Innovation. He now leads AI-Ready School Leaders cohorts, helping educators and administrators build their own AI tools instead of buying them, and writes a newsletter followed by more than 103,000 leaders and learners.

Find A.J.: ajjuliani.com · X @ajjuliani · LinkedIn · Instagram @learningwithaj · YouTube

Other Shows for School Leaders and Teachers Working With Data

• Data Driven Schools: Driving Learning and Improving Relationships — the Cool Cat Teacher Talk episode this conversation first aired on. A.J.’s dashboard segment sits alongside Victoria Setaro’s cold-data-versus-warm-data framework and Dr. Deborah Dennie on a decade of data-driven leadership.
• 4 Essential Ingredients to Engage Students in the AI Age — A.J.’s previous appearance, and the show he and Vicki call back to in this episode. The four essentials: human, social, meaning-centered, and language-based.
• Data-Driven Leadership That Changes School Culture — Dr. Deborah Dennie, a Maryland Principal of the Year and NASSP national finalist, on reading attendance, discipline, and grade data together.
• 5 Things That Happen When We Empower Students — A.J. from back in 2017, on the ideas behind Empower.

Transcript for Episode 981 with A.J. Juliani

This transcript was generated using AI and has been reviewed by humans for accuracy. Minor errors or artifacts may remain but I worked my best to find any issues with the transcript as I reviewed the show. – Vicki

Disclosure of Material Connection: This is a sponsored episode and blog post. Experience AI has compensated me to share information about the Experience AI program. However, all opinions expressed are my own. I have personally reviewed these resources and only recommend tools I believe offer genuine value to classroom teachers. My endorsement is limited to the educational products and services discussed in this episode. I am disclosing this in accordance with the Federal Trade Commission’s 16 CFR, Part 255: “Guides Concerning the Use of Endorsements and Testimonials in Advertising.” The sponsor has no impact on the editorial content of this show.

Disclosure of Material Connection: This episode includes some affiliate links. This means that if you choose to buy I will be paid a commission on the affiliate program. However, this is at no additional cost to you. Regardless, I only recommend products or services I believe will be good for my readers and are from companies I can recommend. I am disclosing this in accordance with the Federal Trade Commission’s 16 CFR, Part 255: “Guides Concerning the Use of Endorsements and Testimonials in Advertising.” This company has no impact on the editorial content of the show.

The post How to Build Your Own Data Dashboard: No Coding Required appeared first on Cool Cat Teacher Blog by Vicki Davis @coolcatteacher helping educators be excellent every day. Meow!

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Creativity can be nurtured and grown and should be in every subject, particularly now when creativity is such a competitive advantage. Today’s guest, Susan M. Riley, shares how we can bring creativity into every classroom and gives specific examples for math, science, and engineering. Susan is the author of the book Creativity’s Edge.

Susan argues that creativity shouldn’t be quarantined to one part of the building. Susan shares four branches of creativity and gives concrete examples subject by subject. Math. Science. Engineering. Then, she gives us teachers encouragement to add some creativity into our own days. (I know it is hard when you’re so busy, but I know when I have done this, it has helped me.) So, let’s talk about building our edge with creativity and get some ideas for pulling it into our own classes.

SPONSORED: Experience AI, a free program co-developed by the Raspberry Pi Foundation and Google DeepMind, sponsored this episode. All opinions are my own and that of the guest.

Experience AI is a free AI literacy program with ready-to-teach lessons for ages 8 to 16. The lessons are written for teachers of all subjects, including science, math, social studies, English, and art, and some don’t even need a computer to use. Support your students to become critical thinkers and better understand AI technologies today. Explore the free resources at Experience AI.

See Experience AI’s Free Lesson Plans

Listen to the Show

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Resources Mentioned in This Episode

• Creativity’s Edge: Unleashing Humanity’s Greatest Advantage in the Age of AI by Susan M. Riley — the book behind this conversation. It is where the four branches get worked out with practices and ways to measure growth, K-12 and beyond.
• The Institute for Arts Integration and STEAM — Susan’s organization, and the place to go for lesson plans, certification, and training if this episode gave you an idea you want to actually build.
• Art Works for Teachers — Susan’s podcast. Each episode comes in audio, video, and written form with a downloadable resource, which is unusually generous.
• SusanMRiley.com — her author site.
• The National Museum of Mathematics (MoMath) — the museum in New York that Susan mentions, dedicated to exactly the art-and-math overlap she describes. If you are ever in the city with a math teacher, go.
• The Desmos Math Art Contest — open each year to students ages 13–18. This is the kind of project I describe on the show, where students build a picture entirely out of the equations of its lines.

Two things to try this week — one for your students, one for you.

Consider “hard fun” creative projects in the projects you give them for their subject. Reflect on what you’re asking students to do and count to ten past when you want to step in and let them have a little bit of struggle so they can create and invent.

And here is one for you, not for your students.

Schedule a 5-minute creativity moment for yourself this week to create something. I have a planner that I put stickers in and print out photos from a small printer and put it in my planner. It is a creative outlet for me. Find a creative outlet for yourself. If you like to sing, sing a favorite song in the car. If you like to draw, take a moment to doodle. Pull something into your day that is creative, even if it is a creative moment in your lesson. See how it makes you feel and see if you want to try it the next day as well. Let me know what you think.

About Susan M. Riley

Susan M. Riley is the Founder of The Institute for Arts Integration & STEAM and host of the Art Works for Teachers podcast. A former music educator with more than two decades of leadership in creative curriculum design, she helps schools build innovative, student-centered learning environments. Riley’s work has been featured by Edutopia, Education Week, and ASCD, and her resources reach millions of educators each year. Her new book, Creativity’s Edge, explores why creativity is the defining skill of the AI era – and how educators and leaders can cultivate it with purpose. She lives in the mid-Atlantic with her family.

Connect with Susan: The Institute for Arts Integration & STEAM | SusanMRiley.com | LinkedIn | Facebook

Other Shows on Creativity and the Arts

• AI Art in the Classroom with Tim Needles — the closest companion to this episode. Tim makes the same argument Susan does, that creativity is a skill you build rather than a trait you have, and he does it from inside an art room that uses AI tools.
• AI as a Creativity Amplifier with Dr. Sarah Thomas — on AI giving teachers back the time to do the work only humans can do, plus the student data guardrails you need first.
• What AI Can’t Do: Being Beautifully Human — my own take on the same question Susan opens with. If today’s episode landed, this is the next one.

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Episode Transcript

This transcript was generated using AI and has been reviewed by humans for accuracy. Minor errors or artifacts may remain but I worked my best to find any issues with the transcript as I reviewed the show. – Vicki

Disclosure of Material Connection: This is a sponsored episode and blog post. Experience AI has compensated me to share information about the Experience AI curriculum. However, all opinions expressed are my own. I have personally reviewed these resources and only recommend tools I believe offer genuine value to classroom teachers. My endorsement is limited to the educational products and services discussed in this episode. This post also includes affiliate links to books, which means that if you choose to buy I will be paid a commission at no additional cost to you. I am disclosing this in accordance with the Federal Trade Commission’s 16 CFR, Part 255: “Guides Concerning the Use of Endorsements and Testimonials in Advertising.” The sponsor has no impact on the editorial content of this show.

The post Teaching Creativity: 4 Ideas Every Subject Can Use appeared first on Cool Cat Teacher Blog by Vicki Davis @coolcatteacher helping educators be excellent every day. Meow!

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We all have a reputation, whether we build it intentionally or not. One of my son’s favorite assignments from middle school was when a teacher asked him to draw a coat of arms. It included what he liked, what mattered to him, and what characteristics he wanted to portray. He was figuring out who he was. Who would even put the word “brand” with an activity like that? However, there are times we may want to take the approach of “building a personal brand.”

Whatever angle you want to take, Elisabeth Bostwick talks about authentic learning. Now, for those of us who automatically associate personal branding with social media, this doesn’t mean that students have to post on social media at all. Students can start with their strengths and interests and select brand colors as well. Elisabeth has done this with high school entrepreneurship students as well as fourth graders. For today’s Fab Idea Friday, think about activities that help students think through how they want to be viewed.

Listen to the Show

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Resources Mentioned in This Episode

• Elisabeth Bostwick — Inspire Innovation — her site, and the place she points students when they ask where to find resources. Speaking, books, and her blog all live here. She spells it out on the show: it’s Elisabeth with an S, not a Z.
• Take the L.E.A.P.: Ignite a Culture of Innovation by Elisabeth Bostwick — her book, and the source of the framework behind this conversation: Luminous culture, Empowered learning, Authenticity in learning, Potential soars. The A is this episode. There’s also a free discussion guide (PDF) on her site if your team wants to read it together.
• Education Write Now, Volume II: Top Strategies for Improving Relationships and Culture — edited by Jeff Zoul and Sanée Bell, with Elisabeth’s chapter on cultivating student strengths and interests. Ten education authors wrote it together over a three-day retreat, and the royalties support the Will to Live Foundation.
• Spark Joy in EDU — the podcast Elisabeth co-hosts with Tisha Richmond about actively cultivating joy in your work as an educator. Note: eighteen episodes, with the most recent published in March 2025 — the back catalog is well worth your commute, but it isn’t currently releasing new shows.
• Canva for Education — free for verified K-12 teachers and their students. Elisabeth is a Canva for Education Learning Consultant, which is why Canva runs through this whole conversation.
• Canva Websites — the specific feature she describes. Her words: “I do create websites in Canva. They’re very simple. They function similarly to creating a presentation.” That’s the low-floor entry point for a student portfolio.
• Google Sites — the other no-cost portfolio home she names, and the one my own students use. Mine build a site in eighth grade and keep updating it straight through senior year.
• LinkedIn — not for high schoolers to join, but for them to read. Elisabeth puts real public profiles on the screen and has students break down why each one does or doesn’t work.
• Common Sense Media — the resource Elisabeth names on the show for students working on how they show up online.
• Common Sense Education — Digital Literacy & Well-Being Curriculum — the free K-12 classroom side of Common Sense, and where teachers should actually start. Note: this replaced the older Digital Citizenship Curriculum, which Common Sense has announced will be archived in December 2026. If you have old lesson links saved from a few years back, they’re on the clock — use the new curriculum.

I think it is important to help students understand that there are professional networks online since that is how many people find new jobs. Here’s an activity that Elisabeth suggests. You can also create Linked In templates as well.

Pull up three real, public LinkedIn profiles on your screen. Elisabeth used current college students and a few young professionals — and she deliberately included one that wasn’t polished. Then take them apart together: Why does this one work? What are its strengths? Why might this one not work? When her high schoolers said the unpolished one looked “not as professional,” that was the opening, not the end of the conversation — the profile belonged to someone showcasing graphic design, so the whole visual feel was doing a job. Nothing to buy, nothing to get approved, and not one student has to post anything.

Notice what she is not doing. She is not asking teens to build an audience. She is teaching them to read an audience. These days I’ve had my students only share privately, she has students: build it in Google Sites or Canva, keep it private, and link it out later if and when they choose to.

About Elisabeth Bostwick

Elisabeth Bostwick, founder of Inspire Innovation, LLC, is a multi-award-winning educator passionate about creating the conditions to spark curiosity and unleash creativity to empower learning.

In addition to being a Keynote Speaker and Workshop Facilitator, she is the author of Take the L.E.A.P.: Ignite a Culture of Innovation and co-author of Education Write Now Volume 2.

As an Education Innovation Consultant and Canva for Education Learning Consultant supporting K-12 educators, Elisabeth works alongside teachers to create innovative classroom cultures where every learner thrives.

With her passion for creating a long-lasting, positive impact on education, Elisabeth supports others in identifying how to cultivate systemic change and develop essential success skills to ignite a movement of inspired, confident learners.

• Website: elisabethbostwick.com
• LinkedIn: linkedin.com/in/elisabeth-bostwick-a79687159
• X: @elisabostwick
• Bluesky: @elisabostwick.bsky.social
• Podcast: Spark Joy in EDU

Other Shows for Middle and High School Teachers

• How Can Students and Teachers Build a Good Personal Brand? — the Cool Cat Teacher Talk episode where Elisabeth and Dr. Will Deyamaport and I took on this same question from the teacher’s side as well as the student’s. If today’s show made you think about your own footprint and not just your students’, start here.
• Take the LEAP — Don’t Sit and Stick — Elisabeth’s first time on the 10 Minute Teacher, back in episode 633. She takes us inside her classroom and how she built a culture where authentic learning could actually happen. It’s the foundation underneath everything in today’s conversation.
• 5 Tips for Digital Portfolios — episode 766 with Tisha Poncio, and the practical companion to this one. Planning, student choice of tool, modeling, checkpoints, and sharing with a real audience — plus a free portfolio checklist rubric you can download.

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If this episode gave you something to try, share it with the teacher down the hall who needs it — and leave a review wherever you’re listening. It’s how other teachers find the show.

Episode Transcript

This transcript was generated using AI and has been reviewed by humans for accuracy. Minor errors or artifacts may remain but I worked my best to find any issues with the transcript as I reviewed the show. – Vicki

Disclosure of Material Connection: This episode includes some affiliate links. This means that if you choose to buy I will be paid a commission on the affiliate program. However, this is at no additional cost to you. Regardless, I only recommend products or services I believe will be good for my readers and are from companies I can recommend. I am disclosing this in accordance with the Federal Trade Commission’s 16 CFR, Part 255: “Guides Concerning the Use of Endorsements and Testimonials in Advertising.” This company has no impact on the editorial content of the show.

The post Student Personal Branding Without Social Media appeared first on Cool Cat Teacher Blog by Vicki Davis @coolcatteacher helping educators be excellent every day. Meow!

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Honesty. We need to be honest about where we are in education. Whether authentic, true, genuine learning is happening should be the question for all of us in education. None of us wants to pretend or participate in a farce. AI guilt is now “a thing” college graduates are talking about. College graduates who are not being “caught” but feel like they spent the last years pretending to learn.

Dr. Christian Miller, author of The Honesty Crisis, has spent more than a decade running some of the largest funded research projects on honesty and moral character. He says that the internet was the first honesty crisis in education. AI is the second one.

We talk about both sides of the desk on this one. Both the student writing their paper with AI and learning nothing, and the teacher giving AI-generated feedback without disclosing it to students. This is why an honest expert is staying up at night about the papers his philosophy students are writing (or if they are not).

Listen to the Show

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Resources Mentioned in This Episode

Christian’s books

• The Honesty Crisis: Preserving Our Most Treasured Virtue in an Increasingly Dishonest World (Oxford University Press) — the book at the center of this conversation. It maps six areas of society where Christian sees honesty eroding: deepfakes, infidelity, education, political misinformation, celebrity, and religion, including sermon plagiarism. Education is only one chapter. Published May 19, 2026 — we recorded this before release, so you’ll hear us both talk about it as coming. The publisher’s page is here at Oxford University Press.
• Honesty: The Philosophy and Psychology of a Neglected Virtue (Oxford University Press, 2021) — the academic book underneath the trade book. If you want the actual definition of honesty he keeps referring to, and why it is bigger than “don’t tell lies,” this is where it lives.
• The Character Gap: How Good Are We? (Oxford University Press, 2017) — his earlier book for general readers, and the most accessible entry point to his research on moral character. Good faculty-book-study material.
• Moral Character: An Empirical Theory (Oxford University Press, 2013) — where he first argues that most of us are neither virtuous nor vicious but a mixed bag, which is exactly the frame he uses in this episode to explain why good people still cheat when it gets easy.

The research projects

• The Honesty Project — the $4.4 million research effort Christian directed at Wake Forest University, funded by the John Templeton Foundation, built around five big questions about what honesty is, how much of it people actually have, and what makes it grow or collapse. Free, public, and a genuinely useful place to send a curious student.
• The Character Project — the earlier Wake Forest initiative he led on moral character across philosophy, psychology, and theology. Conference videos and funded research are posted there.
• The Beacon Project — the Wake Forest project on moral exemplars, the people who are not just good but exceptional, where Christian served as Philosophy Director.
• The John Templeton Foundation — the funder behind the Honesty Project and the Character Project.

The AI detector Christian names

• Pangram — the AI-detection company whose accuracy claims Christian says have caused him to revise his thinking. The specific number he cites, and what it does and does not settle, is broken down in the Sources section below. Read that before you take a detector result to a parent conference.
• Note: At this time, I’m not recommending any AI detector as I think we should focus on learning detection. Oral conversations, discussions, and methods for building on assignments should show students that we are focused on learning.

Find Christian

• christianbmiller.com — his site, with his CV, popular writing, talks, and pages for each book.
• His Honesty Project faculty page at Wake Forest University.
• @CharacterGap on X · LinkedIn · Facebook

Before you accuse anyone, ask them to walk you through the paper. When Christian gets a suspicious paper, his first move is not a detector — it is a conversation, run in the least confrontational way he can manage. Tell me about this paper. How did you write it? Walk me through the steps. Can you explain this idea? It wasn’t in the class material — where did it come from? He says students often admit it on their own at that point. And when they do, he stays lenient: there is a consequence, the grade takes a hit, but he does not fail them or send them to a hearing. They rewrite the paper and get a second chance. The whole exchange fits inside a planning period.

About Dr. Christian Miller

Christian B. Miller is the A. C. Reid Professor of Philosophy at Wake Forest University. He was most recently the Director of the Honesty Project (honestyproject.philosophy.wfu.edu/), funded by a $4.4 million grant from the John Templeton Foundation. In recent years he was the Philosophy Director of the Beacon Project (www.moralbeacons.org), funded by a $3.9 million grant from Templeton Religion Trust, and the Director of the Character Project (www.thecharacterproject.com), funded by $5.6 million in grants from the John Templeton Foundation and Templeton World Charity Foundation. He is the author of over 130 academic papers as well as Moral Psychology with Cambridge University Press (2021) and four books with Oxford University Press, Moral Character: An Empirical Theory (2013), Character and Moral Psychology (2014), The Character Gap: How Good Are We? (2017), and Honesty: The Philosophy and Psychology of a Neglected Virtue (2021). His new book, The Honesty Crisis: Preserving Our Most Treasured Virtue in an Increasingly Dishonest World, is forthcoming from Oxford in 2026.

Dr. Miller was a science contributor for Forbes, and his writings have also appeared in The New York Times, Wall Street Journal, Dallas Morning News, Slate, The Conversation, Newsweek, Aeon, and Christianity Today. Miller is the editor or co-editor of Essays in the Philosophy of Religion (OUP), Character: New Directions from Philosophy, Psychology, and Theology (OUP), Moral Psychology, Volume V: Virtue and Character (MIT Press), Integrity, Honesty, and Truth Seeking (OUP), and The Bloomsbury Handbook of Ethics (Bloomsbury Press).

Editor’s note: this bio was written before publication. The Honesty Crisis is no longer forthcoming — Oxford University Press released it on May 19, 2026, and it is available now.

Other Shows for Teachers Wrestling With AI and Academic Honesty

• Honest Conversations About AI: The Need for Truth — the Cool Cat Teacher Talk hour this interview came from, where Christian and MIT’s Justin Reich both join me. If this episode left you wanting the longer version, start here.
• AI Assisted Grading: A Teacher’s 30-Second Checklist — the practical companion to the uncomfortable half of this conversation. If you are using AI anywhere in your assessment workflow, run through this one next.
• Brain First, AI Second: Teaching Writing in the AI Era with Philip Seyfried of Teachers College, Columbia — on why AI detectors fail, what the MIT research actually showed, and how to build trust around AI in a writing classroom.
• How to Prevent AI Cheating: Integrity in the AI Age with Professor Laurel Aguilar-Kirchhoff — the assignment-design answer. She turned a midterm essay into a storyboard rather than fighting the tool.

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If this one gave you language for a conversation you have been avoiding at your school, share it with the teacher down the hall — and leave a review wherever you’re listening.

Episode Transcript

This transcript was generated using AI and has been reviewed by humans for accuracy. Minor errors or artifacts may remain but I worked my best to find any issues with the transcript as I reviewed the show. – Vicki

Disclosure of Material Connection: This episode includes some affiliate links. This means that if you choose to buy I will be paid a commission on the affiliate program. However, this is at no additional cost to you. Regardless, I only recommend products or services I believe will be good for my readers and are from companies I can recommend. I am disclosing this in accordance with the Federal Trade Commission’s 16 CFR, Part 255: “Guides Concerning the Use of Endorsements and Testimonials in Advertising.” This company has no impact on the editorial content of the show.

The post AI and Academic Honesty: The Second Crisis in Schools appeared first on Cool Cat Teacher Blog by Vicki Davis @coolcatteacher helping educators be excellent every day. Meow!

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From the Cool Cat Teacher Blog by Vicki Davis

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Wow, this is a sensitive topic. And remember that every person with autism has a different experience. But Claire O’Neill is a teacher and she’s telling her story of school.

Claire can see the roof of her old primary school from her classroom window. She remembers walking up to the school door with that gnawing, upset feeling in her stomach and the itchy, scratchy uniform that made her so uncomfortable. She says the room was either too hot or too cold. It was almost always too loud, and she says it was smelly. Claire got in trouble a lot. Now, that she’s studied autism, she understands better why.

Claire has spent more than twenty years teaching autistic students and is a PhD researcher at University College Cork (Ireland) studying what school is actually like for autistic teachers.

Claire shares her story from an educational perspective. A full-circle moment of a PhD expert teacher reflecting upon the girl she used to be and advocating to help us all understand how to help children like her.

My Mom was one of the most compassionate, intuitive teachers I’ve ever known. She always said when I had a student who learned differently and I would accommodate for the whole class, everyone in the classroom learned better. Claire says the same thing. She also talks about the importance of Universal Design for Learning (UDL).

She also encourages us to listen to our learners. Believe them when they tell you how they experience your room. And to act upon what they tell us.

Claire is an expert, but I’m not. While I’ve taught some precious students with autism and most of them thrived in my classroom (one early in my career, I wish I could go back and use strategies I know now.) I share this story with sensitivity and the knowledge that I don’t know what I don’t know but I know it is important to listen. And isn’t that what Claire tells us in the show?

I hope this show makes us all more empathetic on this Wonderful Classroom Wednesday because not every child actually thinks our classroom is wonderful and we need to listen and learn to make it better.

Listen to the Show

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Resources Mentioned in This Episode

• The Strengths-Based Guide to Supporting Autistic Children: A Positive Psychology Approach to Parenting by Claire O’Neill (Jessica Kingsley Publishers, 2023) — Claire’s solo-authored book, written for parents and teachers, on identifying and building on a child’s character strengths instead of managing a list of deficits.
• It Takes All Kinds of Minds: Fostering Neurodivergent Thriving at School edited by Rachael Davis, Claire O’Neill, and Sue Fletcher-Watson (Speechmark / Routledge) — the book Claire mentions on the show, a fifteen-chapter collection on environments, pedagogy, and relationships in and around school. You can also see the full table of contents on the publisher’s page.
• CAST — the nonprofit Claire sends teachers to first. This is the organization that created Universal Design for Learning, and it is where the free explainer videos, podcasts, and text overviews she describes actually live.
• The UDL Guidelines (version 3.0) — the official framework behind the three principles Claire names. CAST released version 3.0 in July 2024, and it is organized around Engagement, Representation, and Action & Expression. Free, and the fastest way to see what “offer more choice” actually looks like in practice.
• Dr. Margaret “Mags” Flood, Assistant Professor in Inclusive Education at Maynooth University — she wrote the Universal Design for Learning chapter in It Takes All Kinds of Minds. Claire recommends her podcast, Talking About All Things Inclusion, and her site Equity In Mind, home of #UDLchatIE.
• Professor Sue Fletcher-Watson — Claire’s co-editor, Professor of Developmental Psychology at the University of Edinburgh, and the co-editor I mention at the top of the show. She was my guest on The Beautiful Nuance of Neurodiverse Classrooms.
• University College Cork School of Education — where Claire is a PhD researcher.
• “I Saw Things through a Different Lens…”: An Interpretative Phenomenological Study of the Experiences of Autistic Teachers in the Irish Education System — Claire’s own published research with Neil Kenny, in Education Sciences, 2023. Open access and free to read. If you want to know what the teachers in your building who are neurodivergent are carrying, start here.
• Thriving Autistic — the neurodivergent-led Irish organization where Claire serves as Head of Training.

I had not heard of this term before so I wanted to highlight it in the show notes.

Claire mentions the double empathy problem while describing being in trouble at school without knowing why. The term comes from autistic researcher Damian Milton, who argued that when an autistic person and a non-autistic person fail to understand each other, the breakdown runs in both directions. It is a mismatch between two different ways of experiencing the world, not a deficit sitting inside the autistic person. That reframe is the whole reason “listen and believe” is a strategy and not just a kindness. Milton, D. (2012). On the ontological status of autism: the ‘double empathy problem.’ Disability & Society, 27(6), 883–887. Read the full paper free.

About Claire O’Neill

Claire is an experienced teacher who has worked across primary and secondary education settings in the Republic of Ireland. As a dedicated teacher-educator, her work focuses inclusion, neurodiversity and wellbeing. Claire is a significant contributor to education literature and research, having worked as author and editor on several publications related to equality and inclusion. As a neurodivergent individual, her professional commitment is deeply informed by lived experience, driving her to explore participatory, creative and innovative methods in her teaching and research.

Claire’s books: The Strengths-Based Guide to Supporting Autistic Children (author) and It Takes All Kinds of Minds: Fostering Neurodivergent Thriving at School (co-editor).

Connect with Claire: LinkedIn · Thriving Autistic

Other Shows for Teachers Reaching Neurodivergent Learners

• The Beautiful Nuance of Neurodiverse Classrooms with Professor Sue Fletcher-Watson and Vanessa Castañeda Gill — the closest companion to this episode, and it features Claire’s own co-editor on It Takes All Kinds of Minds. Sue explains the double empathy problem and monotropism, and makes the case for quiet space as a real support rather than a favor.
• What Happens to Your Student’s IEP After High School? with Dr. Toby Tomlinson Baker — what accommodations look like once a student walks out of K-12, and what we should be teaching them about asking for what they need before they get there.
• Can AI Replace Teachers? Dr. Catlin Tucker on Smarter Lesson Design and UDL — Catlin on building real student choice into a lesson, and where AI genuinely helps you plan a UDL-aligned lesson without adding hours.
• Throw Out Learning Styles and Replace it with UDL with Kathleen McClaskey — an older episode and still one of the clearest explanations of why learning styles do not hold up and what to use instead.

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If this episode gave you something to try, share it with the teacher down the hall who has a student they haven’t reached yet.

Episode Transcript

This transcript was generated using AI and has been reviewed by humans for accuracy. Minor errors or artifacts may remain but I worked my best to find any issues with the transcript as I reviewed the show. – Vicki

Disclosure of Material Connection: This episode includes some affiliate links. This means that if you choose to buy I will be paid a commission on the affiliate program. However, this is at no additional cost to you. Regardless, I only recommend products or services I believe will be good for my readers and are from companies I can recommend. I am disclosing this in accordance with the Federal Trade Commission’s 16 CFR, Part 255: “Guides Concerning the Use of Endorsements and Testimonials in Advertising.” This company has no impact on the editorial content of the show.

The post Teaching Autistic Learners: Listen, Believe, Then Act appeared first on Cool Cat Teacher Blog by Vicki Davis @coolcatteacher helping educators be excellent every day. Meow!

If you're seeing this on another site, they are "scraping" my feed and taking my content to present it to you so be aware of this.

From the Cool Cat Teacher Blog by Vicki Davis

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I find this conversation interesting because it tells a story from when ChatGPT was released about how a college student responded to it. Zach Kinzler was a junior in college. He was sitting in the front row of a systems engineering class when a friend punched him in the arm and said, “Look at this.” The student had just used ChatGPT to solve the problem on the board. And Zach’s journey began as he not only used ChatGPT to help him in his work but also talked openly with his professors about it.

He did write his papers with ChatGPT. (OK, now I’m not for this, but this is Zach’s story, and it is worth a listen.) Understandably, professors got upset. But when they did, Zach asked them to quiz him on what he wrote and what he had learned. He felt like he was learning faster.

Zach leads academic sales strategies at Boodlebox and hosts the Smarter Campus Podcast. We discuss the difference between using AI to learn and using AI to skip learning. He also discusses AI agents and how they work. But here’s a point I want us all to understand – Zach has struggled with reading his whole life.

As I told a commenter today, not all uses of AI are good. However, not all are bad. I believe AI should improve human flourishing and never detract from it. Yes, AI is a flashpoint issue. People who are angry and hate it really hate it. And some who are fans really love it. I find myself somewhere in the middle. Just like in Web 2 days, actually, when I knew that social media could do good but also had the potential to do great harm.

And I don’t like to call AI a brain, but I also know that there is (and should be) room for different opinions and the voices should be heard. I’ve aired interviews of pundits and pro-AI advocates. But we need to listen, because often the way forward is in the conversation that helps us see what the future can look like. All the AI haters in the world, I don’t think, can make it go away. Nor can all the AI advocates every convince me that AI should be student-facing for many of our younger students. I am interested to see what you think after you listen to this show.

I do want to note that, as I cared for my Dad last year, I fell behind on airing some of my shows. This interview was recorded in 2025, but we’ve worked to preserve the story and relevant arguments. That delay was all mine, so if you hear anything dated, just know that’s on me. As always, thank you for listening to the show!

Listen to the Show

Watch this video on YouTube.Subscribe to the Cool Cat Teacher Channel on YouTube

Resources Mentioned in This Episode

• BoodleBox — the company Zach works for. Kinzler and the company describe it this way: a collaborative AI workspace that puts multiple AI models in one place so a team, a class, or an institution can work in a shared space rather than in separate private chat windows. It offers a free tier and paid institutional plans. They didn’t sponsor this episode and all opinions are his own.
• The Smarter Campus Podcast — Zach’s own weekly show, where he interviews students, professors, and administrators around the world about what is actually working with AI on campus. Vicki has been a guest on it.
• Zach Kinzler on LinkedIn — where he posts short explainers and clips, and the place he named on the show as the best way to reach him.
• ChatGPT — the OpenAI tool Zach got on the waitlist for as a college junior, and the one he was using when he told his teachers about it. Free and paid tiers.
• Perplexity — the AI answer engine Vicki mentions offloading research to so she can spend her own time writing instead of reading for hours.
• NotebookLM (now branded Gemini Notebook) — Google’s research and study tool. You load in your own sources, such as the PDFs Vicki gives her students, and it works only from those documents. This is the tool Vicki calls “fantastic for studying.”

A note on the first item: Zach Kinzler works for BoodleBox, and this is an editorial interview, not a sponsored one. The description above comes from the company’s own materials and from what Zach said on the show. I have not independently tested or verified BoodleBox’s security, privacy, or compliance claims, and nothing here should be read as an endorsement. Evaluate it the way you would evaluate any vendor describing its own product.

The most useful thing in this whole episode is not a tool at all. We know that tools like Google Notebook LM can do this, but this is something worth testing when you’re learning.

Make the AI ask you the questions. Zach’s habit is the reverse of what most students do. Instead of “write this for me,” he types “ask me questions about this and I’ll answer them.” Then, when something still isn’t landing, he climbs a ladder: explain this to me like I’m five, then like I’m 10, then like I’m 15. Give your students both moves at the start of one class period, in any subject, with whatever tool your school already allows. Neither one produces a single sentence a student could turn in as their own work, which is exactly why they are worth teaching first.

About Zach Kinzler

Zach Kinzler is an education and AI enthusiast with a unique blend of industry and academic experience. His career has focused on empowering students and educators through innovative technology, including his current role leading academic sales strategies at BoodleBox.ai, where he helps higher education institutions prepare students for an AI-powered future. He holds a BS in industrial engineering and a master’s degree in business analytics from the University of San Diego (CA).

Connect with Zach: LinkedIn · The Smarter Campus Podcast

Other Shows for Teachers Working Out Where the Line Is With AI

• AI in the Classroom: Assignments Students Can’t Fake with Nancy Frey — the closest companion to this episode. Zach describes what honest AI use looks like from the student’s side; Nancy takes the same problem from the assignment-design side and her expertise in learning science. Another one to listen to as well.
• Brain First, AI Second: Teaching Writing in the AI Era with Philip Seyfried of Teachers College, Columbia shares information on MIT Media Lab research, why AI detectors fail, and building classroom trust around AI. It is the research backbone under Zach’s “want to learn” argument.
• Vibe Coding, Agentic AI, and What Schools Must Teach Now — the full-hour Cool Cat Teacher Talk show on agents, if Zach’s ninety-second explanation left you wanting more.
• Honest Conversations About AI: The Need for Truth — a full hour on honesty, integrity, and transparency with AI, which is the thread running underneath everything Zach says here.

Listen and Subscribe

• Apple Podcasts
• Spotify
• YouTube
• All 10 Minute Teacher Episodes

If this one gave you something you can use tomorrow, share it with the teacher down the hall who is still deciding what to do about AI — and leave a review wherever you’re listening. It genuinely helps other teachers find the show.

Episode Transcript

This transcript was generated using AI and has been reviewed by humans for accuracy. Minor errors or artifacts may remain but I worked my best to find any issues with the transcript as I reviewed the show. – Vicki

Disclosure of Material Connection: This is not a sponsored episode and this post contains no affiliate links. No company paid for or influenced this conversation. Zach Kinzler works for BoodleBox, which is discussed in the episode, so his description of that product is his own and I have not independently verified the company’s product, privacy, or compliance claims. I am disclosing this in accordance with the Federal Trade Commission’s 16 CFR, Part 255: “Guides Concerning the Use of Endorsements and Testimonials in Advertising.”

The post AI Agents Explained: What Teachers Need to Know appeared first on Cool Cat Teacher Blog by Vicki Davis @coolcatteacher helping educators be excellent every day. Meow!

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From the Cool Cat Teacher Blog by Vicki Davis

Subscribe to the 10 Minute Teacher Podcast and Cool Cat Teacher Talk anywhere you listen to podcasts.

When you’re busy, it can be impossible to see the smoke. The smoke of your own burnout. As a teacher, for so much of my career, I’ve been busy. There have been seasons when I described the feeling to my husband as “hyperventilation.” There were times I wore the lack of sleep as a badge of honor.

Today’s guest, Dr. Jen Rafferty, was a middle school music teacher for fifteen years. Then, when she reached what she thought was the top of her career (she published her first book, was presenting all over the country) – her marriage was falling apart, her back was debilitated with pain, and she had odd red splotches on her skin that seven doctors couldn’t explain. In the end, it was stress. Looking back, she realized it was burnout.

So, in today’s Motivational Monday, we talk about what can help a teacher move out of burnout without having to quit or just try to make themselves into a different person. I find her arguments about emotional intelligence interesting, and they offer another view as we grapple with the realities and challenges of living a life of personal and professional balance and joy. Jen shares the brain science, tells her own story, and then gives us something we can do tonight. I’ve included links in the show notes below.

If this is you and you’re really struggling, remember, get help from a professional mental health professional, doctor, or minister. But if you’re deaing with life management as all teachers do, I hope you’ll find this show encouraging.

Listen to the Show

Watch this video on YouTube.Subscribe to the Cool Cat Teacher Channel on YouTube

Resources Mentioned in This Episode

• The Empowered Educator: 10 Lessons to Prevent Burnout, Reclaim Your Joy, and Unlock Your Teaching Potential by Dr. Jen Rafferty — the book behind this conversation, published August 4, 2026 by Tarcher/Penguin Random House. It is where the “space between what happens and how you respond” idea gets worked out chapter by chapter. You can also read a sample and see all three formats at Penguin Random House.
• Empowered Educator — Jen’s organization, built on the idea that the well-being of a school depends on the well-being of its educators. There is a hub for teachers and a separate one for school leaders, so start with whichever chair you sit in.
• Generational Change Begins with Empowered Teachers — Jen’s TEDx talk, given at TEDxIthacaCollege. The shortest way to hear the whole argument in one sitting, and a good one to send a colleague who thinks this is soft stuff.
• Unlock Your Teaching Potential — Jen’s own podcast. Short episodes, one idea each, still publishing weekly. If today’s show helped, this is where the next ten live.

The whole episode comes down to one small move you can make before you walk into school tomorrow, so here it is on its own.

Do the two steps Jen gives, in order, starting tonight. First, give yourself grace. Not as a slogan — as a sentence you actually say. “Of course I am feeling like this. Look at everything that is happening.” Jen’s point is that the exhaustion is your biology working correctly and asking for attention, and the trouble starts when you fight it. Then, second, go through the rest of your day 10% slower. Just 10%. Move 10% slower, talk 10% slower, answer that text 10% later. She says that small gap is what makes room between what happens to you and how you respond, and that is where all your choices live. Try it for the rest of today only. If you like it, try it again tomorrow.

About Dr. Jen Rafferty

Dr. Jen Rafferty is an educator, author, TEDx speaker, and the founder of Empowered Educator, an organization focused on transforming school culture by placing educator well-being at the center of student and school success. She holds a PhD in educational psychology, degrees in music education and vocal performance, and certifications in emotional intelligence and neuro-identity evolution.

As a former middle school music teacher, Jen understands firsthand both the joy and the pressure of life in the classroom, and what happens when educators continually place themselves last. Her own journey from burnout to balance sparked a mission to help educators reconnect with their purpose, restore their energy, and lead with greater clarity, steadiness, and intention both inside and outside the classroom.

She is the host of the podcast Unlock Your Teaching Potential and the author of The Empowered Educator, available now through Penguin Random House. Her work has also been featured in Forbes, Authority Magazine, and Best Holistic Life Magazine.

Through Empowered Educator, she has partnered with school communities across the country to navigate the real, messy work of organizational change, helping leaders build the internal capacity their teams need to move forward, by creating the conditions where educators feel supported, steady, and ready to lead.

Connect with Jen: Empowered Educator | JenRafferty.com | LinkedIn | Instagram (@jenrafferty_) | TikTok (@jenrafferty_) | The Empowered Educator Faculty Room on Facebook

Other Shows for Teachers Who Are Running on Empty

• How to Stop Teacher Burnout Before It Stops You with Dr. Patrice Buckner Jackson — the closest companion to this episode. Dr. PBJ on catching burnout early, naming what you are unwilling to lose, and why schools carry part of this and not just individual teachers.
• Teacher Burnout: How to Reconnect and Feel Fulfilled with Dr. Michelle Chanda Singh — on serving from fulfillment instead of sacrifice, plus a clarity audit you can run on your own week.
• Habits of Hope to Help Educators with Dr. Julia Garcia — hope as a practice you build rather than a feeling you wait for. This is the one I recorded shortly after my dad died, and it is honest about hard seasons.

Listen and Subscribe

• Apple Podcasts
• Spotify
• YouTube
• All 10 Minute Teacher Episodes

If this episode helped you breathe a little easier, share it with the teacher down the hall who is running on empty right now.

Episode Transcript

This transcript was generated using AI and has been reviewed by humans for accuracy. Minor errors or artifacts may remain but I worked my best to find any issues with the transcript as I reviewed the show. – Vicki

Disclosure of Material Connection: This episode includes some affiliate links. This means that if you choose to buy I will be paid a commission on the affiliate program. However, this is at no additional cost to you. Regardless, I only recommend products or services I believe will be good for my readers and are from companies I can recommend. I am disclosing this in accordance with the Federal Trade Commission’s 16 CFR, Part 255: “Guides Concerning the Use of Endorsements and Testimonials in Advertising.” This company has no impact on the editorial content of the show.

The post Teacher Burnout: Go 10% Slower and Get Your Joy Back appeared first on Cool Cat Teacher Blog by Vicki Davis @coolcatteacher helping educators be excellent every day. Meow!

If you're seeing this on another site, they are "scraping" my feed and taking my content to present it to you so be aware of this.