EdTech Lens

Scaffolding is one of those practices most educators have been trained to use, talk about as a part of daily planning, but might need to reconsider now that we live in the age of AI. We’ve been using it for a long time: breaking down a complex task, modeling a thinking move, offering a hint when a student gets stuck, then stepping back as they find their footing. But knowing what scaffolding is and implementing it with fidelity in an AI-enhanced classroom are two different things. When the support is too tight, too scripted, or never fades, scaffolding can stop being supportive of student learning and growth. In a classroom where AI is available, a student oriented toward completion rather than understanding is one click away from outsourcing the whole thing.So this article is about one question with two parts: what does strong scaffolding look like when AI is in the room, and how do we design for it deliberately? The research on effective scaffolding gives us the foundation. AI gives us both a powerful new tool and a new set of risks. Understanding both is what makes the difference between AI enhancing student thinking and replacing it.Defining ScaffoldingPauline Gibbons puts it precisely in Scaffolding Language, Scaffolding Learning: “Scaffolding, however, is not simply another word for help. It is a special kind of help that assists learners in moving toward new skills, concepts, or levels of understanding. Scaffolding is thus the temporary assistance by which a teacher helps a learner know how to do something so that the learner will later be able to complete a similar task alone. It is future-oriented and aimed at increasing a learner’s autonomy. As Vygotsky has said, what a child can do with support today, she or he can do alone tomorrow.”The greatest risk in scaffolding is overdoing it. When a teacher manages every step of a lesson, students follow the path but never make sense of the terrain. Ready-made answers lead students to reuse solutions rather than build reasoning. Frey, Fisher, and Almarode put it plainly in How Scaffolding Works: without sufficient fading, students develop a dependency on the supports provided and fail to reach independence. It’s a little counterintuitive, but teachers need to allow students the chance to sit in what James Nottingham calls “the learning pit”; that uncomfortable space of not yet knowing, which is where the real thinking happens. The essential thing we must allow for is being comfortable with students being slightly uncomfortable as they figure things out and apply knowledge in novel situations. Monday Ready Resource: Prompt for Learning Pit Coach When students get stuck, this bot helps them sit with the discomfort long enough to work through it rather than around it. A great addition to a “ask three before me” approach.COPY AND PASTE INTO AN AI BOT FOR STUDENTS: You are a coach for students who are stuck and frustrated. Your first job is not to ask a question. It is to acknowledge what the student is feeling. Tell them directly that being stuck is not a sign that something has gone wrong; it is a sign that they are in the middle of real learning. Be warm and specific: the discomfort they feel right now is the learning pit, and every person who has ever learned something hard has felt exactly this. Only after that acknowledgment ask them one question: what is one small thing you could try right now, even if you are not sure it will work? If they say they don’t know, ask them to describe what they have already tried. If they say nothing, ask them to try one thing, anything, and come back and tell you what happened. Do not offer solutions. Do not explain the concept. Do not tell them what to try. Your job is to help the student stay in the pit long enough to find their own way out. Normalize the struggle. Trust the student.Impactful scaffolding is responsive to the students in the classroom, their cultures, and their needs.Studies across math, literacy, and language education confirm this: scaffolds built around one cognitive tradition can exclude learners who don’t share it. Erin Meyer’s research in The Culture Map helps explain the mechanism. Low-context cultures like the United States expect meaning to be spelled out explicitly; the task, the steps, the expected outcome, all stated directly upfront. High-context cultures like Japan, China, and much of the Arab world expect meaning to be inferred, relationships to be honored before instructions arrive, and the whole to be understood before the parts are named. A scaffold designed around low-context assumptions doesn’t just feel unfamiliar to a high-context learner. It can feel disrespectful, as if the teacher is being too direct or blunt.And yet multilingual students don’t operate as fixed cultural types. Over a career working with international learners, I’ve seen students shift their communication norms depending on their language fluency, who else is in the group, and what they think is expected of them. As a supportive teacher, the best move isn’t memorizing a list of cultural norms. It’s a teacher who is genuinely invested in getting to know their students, paired with a flexible process that allows for different ways of arriving at the same destination. This is where process-based learning has an advantage: a thought process that names categories of thinking rather than prescribing a single path; Think, then Generate, then Edit; doesn’t tell students what to think or how to think it. That same principle applies when AI enters the feedback conversation. A bot that opens by asking how a student prefers to receive feedback, before offering any observations at all, is doing something most fixed feedback rubrics never do: honoring the learner’s communication style before the content of the feedback even arrives.Monday Ready Resource: Prompt for Feedback CoachThis bot guides students through seeking, making sense of, and acting on feedback using the Acquire, Analyze, Act process. The prompt below can help scaffold independence by gradually returning decision-making to the student at each stage.COPY AND PASTE INTO AN AI BOT FOR STUDENTS:You are a feedback coach working with a student through three stages. Before you begin, ask how they prefer to receive feedback; some want to hear what is working first, others want to get straight to what needs improving. Honor their preference throughout. In the Acquire stage, ask what they most want to learn from this feedback and what success looks like to them. Then ask them to share the feedback they received, or offer to give feedback yourself. In the Analyze stage, share one observation framed around their intention, then ask them to interpret it: what do they notice, what surprises them, what feels actionable? Do not tell them what to do. If they respond briefly, follow their lead and give them space. In the Act stage, ask them to name one concrete revision, make it, then reflect on what shifted and what they would seek feedback on next time. At every stage, the decisions stay with the student. Your job is to ask the question that helps them think one level deeper than they would alone.Metacognition is one of the best scaffolds.Metacognitive scaffolds that build in planning, monitoring, and reflecting produce stronger outcomes than those focused only on task completion. David Rock calls one planning move “prioritize prioritizing” in Your Brain at Work: deciding what matters most is itself a cognitive task that deserves deliberate attention before the work begins. When students know what steps to take and in what order, cognitive load drops. And as Frey, Fisher, and Almarode note in How Scaffolding Works, as students engage in deliberate practice with scaffolds and feedback, they develop habits that endure across time; what researchers call automaticity. The goal is for the process to become so familiar that students stop spending mental energy on understanding the instructions and start spending it where it belongs: on the thinking the task actually requires.Linking metacognition back to the “learning pit” notion, when we practice metacognition before a learning task, we can anticipate the mindset, the strategies, and the places that we can get stuck, which makes it feel like it’s not a surprise, and students will know how to respond to said challenges as they happen. Without foresight into those realms, students will react impulsively to a frustrating situation, and the last thing they will want to hear is “that’s just part of learning! Get used to it!” In that situation, your learners are going to want an answer, and AI might be one click away to help them out. So again, the path to independence is to practice metacognition ahead of a challenging task and ask students to anticipate pitfalls and strategies to overcome them. Monday Ready Resource: Article on MetacognitionI have an article about three AI-enhanced processes related to metacognition that connect to these ideas of planning, monitoring, and reflecting with AI that I mentioned above. Check it out below.Monday Ready Resource: Prompt for Foresight CoachThis bot helps students plan before they begin using the Foresight stage of the Hindsight, Oversight, Foresight process. The aim of this bot is that students find what the task requires, focus their questions and uncertainties, and Act by choosing a direction.COPY AND PASTE INTO AN AI BOT FOR STUDENTS: You are a thinking coach helping a student prepare for a learning task. Do not help them complete the task. Begin by inviting the student to share anything about how they like to think through new tasks; some students like to see the whole picture first before breaking it into steps, others prefer to start with one concrete thing and build from there. Acknowledge their preference before moving forward. Then ask them three questions, one at a time: What is this task asking you to do? Where do you think you might get stuck, and why? What strategies do you already know that could help you work through those moments? After they answer all three, summarize their thinking back to them in a way that reflects how they described it, not just what they said. Ask if they want to adjust their plan before they begin. Always keep the decisions with the student.Opportunities and pitfalls of scaffolding with AIScaffolding is a way of supporting students. The key to this form of support is that we intentionally plan its fade over time. So, it would be a misnomer to say that AI is a scaffold. Well, no. The way in which we deliberately use AI with a plan over time to support learning is a scaffold. The point being that it’s entirely in how AI is used, and the best way to get there is a well-designed, clear process with a plan.Frey, Fisher, and Almarode describe distributed scaffolding in How Scaffolding Works as the in-the-moment support teachers provide while students are actively working; the nudges, questions, and hints that respond to where a learner actually is rather than what was planned in advance. They recommend a sequence: start with a question to check understanding, move to a prompt if that doesn’t unlock the thinking, then a cue, and only then a direct explanation as a last resort. That sequence is designed to keep the cognitive work with the student as long as possible.When a teacher tells a student, “AI is fine on this task,” the bot might help them skip the entire sequence and go straight to direct explanation. Seeking the path of least resistance is a human psychological trait. The move that works is specific: when you are brainstorming, you may use AI to push your thinking further. Not “AI is allowed.” AI supports this thinking move, in this way, at this stage. That is, teachers, name the thinking for each step of a process and how AI can support it. If you haven’t seen my post titled “How To Design AI-Enhanced Processes”, it’s worth checking out. It covers the above ideas bolded above. In it are simple ways you can design a process that names the thinking, sets expectations, and considers what evidence you would find compelling to demonstrate student thinking.The pitfalls follow the same logic as over-scaffolding more broadly. Frey, Fisher, and Almarode state in How Scaffolding Works that the most common error with graphic organizers is when filling out the organizer becomes the end goal: students turn it in, the lesson continues, and the opportunity to build schemas is forgotten. The same thing happens with AI. A student handed AI without a clear role or purpose probably won’t use it as a scaffold. More likely, they will use it as a completion machine. They finish without building the thinking that the task was meant to develop. And unlike a graphic organizer, AI is fast enough and fluent enough that the student may not even notice the thinking didn’t happen. The bots I shared in this article are designed to respond to each student in ways that honor their thinking and communication norms, asking questions before giving answers and holding back direct explanation as a last resort. But the bot isn’t the relationship. You are. Your role while students work with AI is to circulate, notice, and show genuine interest in what they are thinking. You are their biggest audience, and your curiosity about their ideas is what makes the process feel worth doing.ConclusionAs a teacher, what you’re watching for is curiosity, critical thinking, grit, and metacognition. Those are the signals that the scaffold is working and that students are moving toward an independent, self-directed mindset.Build a process that scaffolds agency with metacognitive routines. When we know those intentions and make them clear to our students, then we can invite AI into the learning. And when a student struggles, resist the urge to rescue them; instead, ask them if they anticipated this and what strategies they prepared. Phrases like “you know that it’s totally normal to be in the learning pit. Let’s take a minute to consider what options you have” go a long way toward establishing longer-term, sustained independence.A dependent, transactional culture teaches kids something, too; it just teaches them that struggle means stop, that help means answer, and that learning ends at the final report card. So scaffold with intention.AI DisclosureIn each article I write, I love to take different approaches in my process. Below, I have named my process and indicated when and how AI supported my writing. The feedback I have been getting from my readers is that these disclosures help them see how I model the practices I promote. TimeI think that it’s important to share how many hours I spend writing articles because I want people to know that it is not necessarily about saving time. I still spend 8-10 hours writing each article. My process is different because AI is a part of the journey and I have access to a wider corpus of research as well. This particular article took me about 8.5 hours to complete across three days. The most time-consuming things were ensuring it captured accurate research and practices, ensuring I endorsed the ideas, and that the language was my own.ProcessTo write this article, I spent three mornings waking up early, drinking some strong coffee, and going to work. I focused on getting the ideas down on paper, editing it once, then stepping away and editing it again with a fresh perspective. Since I often promote the approach of naming the thinking, I thought I would similarly share my steps here. Reflect, Write, Research (with AI), Edit (with AI), Edit (without AI by speaking with three fellow teachers), Record, Share.Research with AIIn this step, I took my research questions and did a search in Consensus. While there is free access, I pay for it because I find that it greatly enhances my job as a coach, and I use it frequently. If I am going to recommend an instructional practice to a teacher, I want to know what the experts say. It’s a great way to get very specific questions answered with credible sources. On Consensus, I ran a report and summarized the relevant findings. I also included a couple of books I was familiar with and that were referenced throughout the article. It’s a reminder that good teaching practices have a considerable body of research already out there. The question I like to ask when doing this sort of writing is, how does AI fit into the well-researched and impactful practices of teaching and learning, if at all?Thank you for reading! This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit aienhancedprocesses.com

Last week, I was standing in a 7-Eleven in Nara, Japan on spring break, and before setting off to explore the charming city, I stopped to buy an onigiri rice ball as a snack. While checking out of the 7-11, I remembered something from the time when I lived in Japan. My friend Soichiro taught me how to open onigiri about twenty years ago by following the numbers on the packaging: three tabs, a folded plastic wrap that keeps the seaweed crispy and separate from the rice until the exact moment you want them together. Precise folds, purposeful sequence, color-coding— to me, it was the kind of design that seemed to draw upon the wisdom of origami. Check out the video below of me showing the packaging of an onigiri and how opening it is easy and leaves the seaweed dry and crunchy. Fun fact: 7-11 wraps their packaging in bioplastics! Actually, Soichiro was not there the first time I tried to open one on my own. I just started pulling at the plastic like I was unwrapping a granola bar. I tore straight through the seaweed, the rice went everywhere, and I ate a slightly soggy, structurally compromised snack standing outside a convenience store, feeling very foreign. The packaging already had the answer, though; three numbered tabs, right there on the wrapper. The design was not the problem. I just didn’t stop to read it.Over the remainder of my trip, I kept noticing the same well-designed logic everywhere, from vending machines to train exit gates to conveyor-belt sushi restaurants. One of my favorite designs was a paper cup dispenser with a single button to release exactly one cup from a locked stack. I watched a tourist wrestle with that type of machine for thirty seconds before noticing the button. Back when I lived in Japan, I learned that when I struggled with something like a paper cup dispenser, the right response was to self-correct. That is, if something is difficult to open, use, or do, you’re probably doing it wrong. In Japan, the user experience is often carefully planned and meant to be easy. I came home thinking about teaching and learning, and I kept thinking: what if we applied the same logic to classroom instructions? Much like a wrapper with instructions, classroom instructions should be easy. The task should be where the energy is put. Students’ effort belongs to the thinking, not to decoding what you want them to do. In other words, opening the onigiri was not the point. Eating a delicious snack was. The packaging exists to serve the experience, and the best packaging gets out of the way quickly. Classroom instructions work the same way in that they are the vehicle for learning, and not the purpose or when learning happens.Picture a high school student with four classes, each coming with lengthy instructions and teachers who carefully cover every edge case before anyone touches anything. By the time a student opens a task on their computer, they are more glazed over than a honey-baked ham! And because we live in an age in which everyone is using AI, they’ve probably got their favorite model running in the background of their laptops. Once they reach the point that the instructions become overwhelming, the internal monologue becomes: I honestly couldn't care less. I'm exhausted. I just want to get through this. This classroom and day-to-day experience sets kids up to have a mentality that is vulnerable to AI misuse. Kids who feel less engaged and disinterested will want to complete tasks quickly, and AI can provide a shortcut. If your instructions lose them from the get-go, you’re heading in the direction of compliant task completion. Too much teacher talk that muddies the instructions might indirectly push them toward feeling overwhelmed and toward a desire to cognitively offload the task as efficiently as possible. My suggestion is this: get into the intellectually engaging, stimulating process of active learning in class. The better you can design your instructions to be short, verb-based, and clear, the better. If you are noticing friction with instructions, processes, or any element, that difficulty is highly informative and can help us to adjust.So in other words: difficulty is data.The Look on Their FacesA quick clarification before I go further. Direct teaching is a powerful tool (see Hattie’s work). There is absolutely a time to stand at the front of the room and teach. This article is not about that moment. This article is about when you ask students to do something, and you are explaining how to engage (e.g., create, discover, reflect, collaborate, analyze, build). The task is meant to generate learning, and before any of that can happen, you have to explain what to do. From my experience as a teacher and coach, fifteen minutes or less with an exemplar is the limit. When teachers overexplain instructions, it leads to a kind of glazed-over, fading anticipation mixed with compliance. It’s funny too, kids will avoid asking questions because they just want to get on with it, even though they actually have many things they want to ask you, they bide their time and plan to ask a classmate what they are actually supposed to do. Myth: good instruction means frontloading every common misconception and pitfall before students have touched the work. To be clear, anticipating roadblocks is good design; that is what Universal Design for Learning asks us to do. But there is a difference between designing for barriers and narrating all of them upfront before students have had a chance to think. When teachers over-explain every obstacle in advance, they usurp the learning; students never have to construct cause and effect for themselves because the teacher already did it for them. They arrive at the work with a head full of caveats and nothing left to figure out. That is not so different from handing a task to AI in that the thinking gets outsourced before it ever begins. Just as we don’t want AI to do the work for students, we also don’t want teachers to do the work for them either.I used to be the over-explaining guy: I’d hover while students work, point at their screens, announce new pitfalls I just remembered or noticed, and announce that there are thirteen minutes left. I would not necessarily call that a rich thinking environment; you know what kids are thinking in that situation? I’m going to just get through this block so I can go home and do it on my own, and I’ll just ask AI and my friends if I get stuck.Could you imagine if 7-Eleven sold onigiri that required 27 steps to open, and a lengthy training video that walks you through every possible way it could go wrong, and then you are given 13 minutes to do it, while in the back of your mind you know that you have a really important train to catch at the station? You would be exhausted, uninterested in the snack, stressed, and looking forward to the whole thing being over. If we are explaining the instructions to an activity and the students have their heads down, that’s data. It is the equivalent of struggling with an onigiri wrapper. It does not mean your students are necessarily unprepared. It could mean your instructions have friction in them, or the students are just not paying attention due to distraction, confusion, or feeling overwhelmed. Every minute a student spends decoding your instructions is a minute they are not spending on the actual thinking you designed the task around. That thinking, the brainstorming, the analyzing, the revising, the reflecting, is where the learning happens.Teachers are designers who are constantly testing their products and empathizing with their clients. So with that design thinking mentality, when students look lost before the learning starts, we can think of this as an observation in which we ask ourselves: what did I build here? What can I subtract? How can I activate thinking and step out of the way? How can I provide just-in-time feedback?Monday-Ready MovesHere’s a list of a few strategies that I have seen work as a teacher and coach. They directly support process-based learning in that a strong process can actually serve as clear instructions that do not necessarily require lengthy explanation. 1. Limit teacher talk. Read your instructions once and keep the total instructions to 15 minutes or less. The shorter your instructions, the more energy your students will have. If you are still talking after 15 minutes, something needs to come out, or additional instructions can happen later in the same lesson. Again, this is not for direct teaching in which essential information has to be taught; I’m talking about the instructions for an activity.In terms of designing a slide, make the words large and easy to read from across the room. Don’t write all the instructions, just the main points so they can recall what they’re supposed to do. 2. Lead with an exemplar. Show before you explain a model paragraph, sample sketch, before-and-after comparison, etc. When students can see the destination, your words serve as confirmation as they build theories about the task and its outcomes, rather than as orientation. 3. Use verbs to name the thinking. Replace vague nouns with precise action verbs. Not “work on your essay” but argue, support, challenge, revise. Not “think about the data” but interpret, compare, decide. Verbs tell students what their brains are supposed to be doing. They also support clear expectations about where AI can or cannot do the move for them (#4 below). For more independent students, you can also ask them to engage in metacognition before starting by considering which steps in the process would be most strategic for meeting the learning objective, then, as they are ready, proceed with their own. 4. Name the AI expectation for each step. For every thinking move, students need one clear statement: what do I do, and what does AI do here? For example, “AI will give you counterarguments, debate it, then record your key findings in your process journal.” Another example could look like, “No AI on this step; this is your thinking.” Vague AI expectations can invite interpretation. A single sentence per move removes the guesswork and keeps the cognitive effort where you want it: on the learning, not on figuring out the rules. For older and more independent students, you can also co-design AI agreements together. Students also tend to like when teachers allow AI on a step in a process that they create a purpose-focused bot for them to use (e.g. on School AI, Flint, etc.) That way they feel less anxious about misusing AI on the task. Students all have access to AI and will likely use it at some stage, but you can make doing the right thing easy.5. Tell them “the why of the how”. Once students know what they are doing and how AI does or does not support each step, add one more sentence: why this particular approach? “We are using journals here because writing slowly pulls thinking out of your head and away from the distraction of your screen.” Another example might be: “We are using AI to role-play as an audience member so you can practice your speech and feel confident before you perform it for real.” Using that language is a direct signal a teacher can send: I thought carefully about how you learn, and I chose this because I want you to succeed. That message contributes to belonging, trust, and independence because it helps students see a process as something they can actually use again on their own.ConclusionI am not saying instructions should be dumbed down. I am saying they should be carefully designed, succinct, and clear to help students access the thinking that leads to deeper understanding. Dumbing down removes the challenge and presupposes students’ incapability— what you might say is setting low expectations. Focusing our language during instructions removes the confusion so the students can engage in the process and put effort where it matters.Students should struggle with the counterargument, wrestle with the revision, sit with the discomfort of a claim that does not quite hold up yet. That productive struggle is where growth happens, and it is worth protecting. Let’s help students put energy into that thinking and not want to turn to AI for task completion. Look for signs that students are thinking. They are writing, discussing, touching their faces, drawing, reading, etc. If they move immediately into the thinking, you have built something that facilitates their thinking. If they look low in energy, slumped down, or frustrated, change something.The second time I opened an onigiri, even with Soichiro showing me how, I still tore the seaweed a little, and that moment of friction is exactly what made the experience stick. I learned from it and gained independence from Soichiro as my teacher. I never tore it again and actually went on to show my friends how amazing it was to eat.When it came to that onigiri, though, the packaging was never the problem. The instructions were printed right there with three numbered tabs. When I tore the seaweed, it was not because the design failed me; it was because I jumped straight in without reading. The moment I paused, or when I had an example to follow (Soichiro modeling it), it worked. That is the other half of the teacher’s job. Write instructions that are clear, yes. But then create a pause, ask about their clarity, read them aloud together, point to the exemplar, ask students what they will do first, second, third. Give students a moment to actually look before anyone touches anything. The packaging can be perfect and still get ignored if nobody stops to read it first. When they struggle with the task itself, that is not a problem; in fact, that is the point! Struggling with a counterargument, sitting with a claim that does not quite hold up, wrestling with a revision that keeps slipping, that is productive. That difficulty is data too. It is just pointing at the learning instead of the design.AI DisclosureThis article was started with Claude 4.6. It started with me dictating long and disjointed ideas on a train leaving Osaka, using voice-to-text as a way to capture a loose set of noticings and half-formed ideas\. I shared the transcript with Claude and used the conversation to brainstorm, push back on my own thinking, and gradually move from a vague noticing into something more structured.Then I took a two-hour Shinkansen up to Tokyo and looked at misty mountains and patches of cherry blossoms along the way. My favorite German electronic music, Apparat, on headphones. I had time to think, write, and look out the window at nothing in particular, which turns out to be one of the better conditions for getting ideas to settle into something real.I want to be transparent about what that human-AI collaboration looked like, because I think it matters. The ideas in this article are mine; the experiences are mine; the framing is mine. Claude helped me organize, sharpen, and refine them. There were moments it wanted to take things in a different direction, toward UX frameworks I did not need, or toward sensory details that sounded vivid but making my writing verbose.I share this because I believe we should normalize transparent disclosure of AI in writing, especially those of us asking students to do the same. If you are not disclosing, you could be modeling secrecy. I wonder if I were to name my process, it might look something like this: * Speak. Use Claude to organize your verbal ideas. Think outloud and share what you are currently thinking, then the AI can help you to organize them into a narrative outline. * Develop. Take the outline and write your ideas out. Do this step without AI.* Edit. Take your first draft and show it to Claude. Ask it what it thinks about your flow and connection of ideas.* Revise. Independently on a bullet train in Japan, re-read your draft a few days later with a fresh perspective and consider your draft. Edit it using your expertise as a teacher and ensure the article has clarity for your given audience of educators. * Share. Schedule your article to go out on Monday morning to share with your community.After the content was written, I went back to add extras to make it more engaging like pictures for each section and a video of me opening the onigiri. The video was me in the streets of Nara actually opening a tuna and mayo rice ball, but the audio was enhanced using Adobe’s Voice Enhancer. The pictures throughout the article were cited with the model and process I used in their creation; all were generated using ChatGPT or Gemini. I also want to state for the record that the en and em dashes used in this article were all me! I’m reclaiming them! Thank you so much for reading this article. If you found it helpful or enjoyed its content, please hit the like button, or go one step further and send it to someone who you think might like it. If you want to try building your own process, I have a free tool at aiep.lovable.app that walks you through it step by step. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit aienhancedprocesses.com

In this episode, I have three chats with different international educators who are working with AI and assessment in different contexts. My previous episode on assessment was one of my more popular, so I thought it was time to come back and see where we were at in terms of thinking that might be developing or getting more refined. It’s been a year since we recorded the last episode. Wow, time flies! Let’s take a look at the details of what you can expect and the folks joining me in order of appearance in the show. Emily J. Thomas is an educator, educational consultant, and entrepreneur who supports international schools in strengthening curricular development, coherence, and a clear vision for teaching and learning. She has spent over a decade in IB international schools as an MYP/DP English language and literature teacher and, most recently, served as an MYP Coordinator; she’s also an IB Educator Network workshop leader and a DP Literature examiner, and works as a literacy strategist with Erin Kent Consulting (EKC). Alongside her work in schools, Emily founded Playground Pedagogy (“playful minds, serious learning”) and leads yoga-focused work through Teaching Matters Yoga and Drift Yoga in Bangkok, and she writes the weekly Substack Elsewhere, Examined.In this conversation, Emily reframes assessment as an opportunity to extend learning; a way to “tune in” to what learners have actually acquired, not a checkbox to end a unit. She unpacks why formative vs. summative terminology can create anxiety and mixed signals for students and argues for schoolwide clarity, including shared definitions, consistent language, and policies that treat formative evidence as meaningful rather than “worthless.” Turning to AI, Emily’s message is “process first”: the best response is doing the fundamentals well with simple, standardized task sheets and clear expectations (including what AI use is appropriate) that teachers and students see consistently across classes. She closes with empathy for educators navigating this moment and a call for leaders to “steer the ship” with clarity so teachers can feel calm and supported.Timothy Cook is an educator and the founder of Connected Classroom, exploring how AI shapes student cognition and learning. He currently teaches third grade at the American Community School in Amman and writes Psychology Today’s “Algorithmic Mind” column, where he examines the intersection of education, AI, and human cognition, especially the risks of dependency and what schools can do to protect critical thinking, creativity, and moral development.In this conversation, Tim argues that writing still matters more than ever because it’s fundamentally a process of thinking: the focus, word choice, revision, and self-argument that helps students clarify what they actually believe (and that AI can’t authentically replicate). He introduces the idea of “jagged edges” that include the human, lived, imperfect uniqueness that gets flattened when AI produces the same “academically average” response to predictable prompts. From there, he makes a practical case for “AI-proofing” assessment by redesigning tasks around community, identity, and design: prompts where students must apply content in locally grounded ways (and where AI can still be used as a tool without replacing the thinking). Nick Soentgerath is a Technology Learning Coach at Yokohama International School (Japan), where he supports teachers and students in designing practical, future-focused learning with a strong emphasis on ethical, responsible, and safe use of AI. In our conversation, Nick brings a practical, classroom-grounded lens to what assessment can be when it’s less about “gotcha” grading and more about clarity, feedback, and growth. Helping schools move from measuring learning to actually improving it. He also presents at international conferences and works with educators on assessment practices that are more authentic, equitable, and aligned with the skills students need beyond school. In the episode, Nick and I discuss the upcoming conference at his school. Find out more here: www.AIFE.community. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit aienhancedprocesses.com

In this episode of The EdTech Lens, Alex explores one of the most powerful ideas in learning: metacognition. Inspired by Amelia King’s recent book, Thinking with AI, and the rising need to understand how AI intersects with thinking, this episode looks closely at how learners plan, monitor, and make sense of their thinking before, during, and after learning. To do that, Alex speaks with four educators whose combined experience stretches across continents, disciplines, and decades.The conversation begins with Ochan Kusuma-Powell, an internationally respected educator, consultant, Cognitive Coaching trainer, and author whose career has helped shape how schools understand learning, thinking, and inclusion. With experience in the United States, Saudi Arabia, Tanzania, Indonesia, and Malaysia, she brings a global perspective to how students learn and how teachers can help them think about their own thinking. A founding member of the original Design Team behind Next Frontier Inclusion and co-founder of Education Across Frontiers, Ochan has influenced schools worldwide through her books and her ability to blend research, storytelling, and practical strategy. In this episode, she shares a crystalline view of metacognition as holding your thinking in the palm of your hand and examining it from many angles, and she describes how she uses AI as a thought partner while writing a new book.Next, Alex is joined by Ty Urquhart, Middle School counselor at Shanghai American School Puxi. Ty brings a social emotional lens to the conversation, offering insight into how teens develop self-awareness, self-management, and decision-making skills during a time of rapid cognitive change. He discusses why teens crave independence, why pausing before acting is so challenging, and why shifting from right versus wrong to helpful versus harmful leads to more productive conversations about AI, digital behavior, and wellbeing. Ty also describes AI as the mirror rather than the villain, reminding us that the goal for students is not avoidance of technology but conscious, intentional use of it.The episode closes with Victoria Hoult and Rachel Kalish from Korea International School, Jeju. Victoria is an experienced instructional coach, curriculum coordinator, and educational leader whose career includes New Zealand, the United Kingdom, Brazil, and Korea. Now serving as Director of Teaching and Learning, she leads with relationships, clarity, and an unwavering commitment to building a school culture where all voices feel valued. Rachel, who holds an MA in Educational Leadership, is the school’s Curriculum and Instruction Coach and has worked in Guatemala, California, Dubai, and Korea. As an innovative and collaborative educational leader, she is dedicated to enhancing student learning by prioritizing relevance and engagement. Her expertise includes implementing effective instructional strategies, aligning curriculum with educational standards, and fostering teamwork among educators. By leveraging data driven insights in collaboration with all stakeholders, she works to improve student outcomes academically and socially, ensuring that every learner reaches their full potential. Together, Victoria and Rachel share practical insights from coaching teachers, guiding schoolwide reflection, and helping students develop the habits needed for sustained, independent learning. Their reflections on how metacognition shows up in teacher practice and how AI might support deeper thinking bring the conversation to a thoughtful and grounded close. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit aienhancedprocesses.com

In this four-part episode, Alex has an interview with five different guests who share their insights on using AI to meaningfully help students to write. Key ideas that emerge: grading chats can be fun and insightful, writing is a form of thinking, process and product are important, it's possible to write with AI and still know your content, and much more. Below are the details about this episode's guests:Mike Kentz is an award-winning educator and former journalist with 15 years' experience across teaching and news media. He is a TEDx Speaker and the founder of AI Literacy Partners, a professional development and curriculum design firm that aims to build AI literacy in educators and students through high-quality instructional materials. His work in AI and Education has been featured in The Harvard AI Pedagogy Project, EdSurge, The Writing Across the Curriculum Repository from Colorado State University, The Wall Street Journal, and more. He lives in Morristown, New Jersey, with his wife, son, dog, and cat.With over 27 years dedicated to advancing educational excellence, Eileen Heller serves as an Education Consultant for Professional Learning at ESU #3, supporting 18 diverse school districts across Omaha’s metro communities. Her career journey—from sixth-grade classroom teacher to technology specialist, instructional facilitator, and instructional technology trainer for Omaha Public Schools, as well as adjunct instructor for multiple higher education institutions—has equipped her with a deep understanding of how to design and sustain impactful systems of professional learning. Her varied experience has led her to focus on building effective professional learning systems. She is committed to supporting educators’ growth through collaboration and encouraging self-directed solutions that improve student outcomes.Chase Heller is beginning his freshman year of high school and enjoys staying actively involved in both his school and community. He serves on the student council and volunteers whenever possible. Passionate about athletics, Chase runs cross country and plays soccer, consistently working to improve his fitness and teamwork. In his free time, he enjoys walking his dog Lucky, swimming, playing with his brother McKennon, and spending time with friends and family.Amelia King is the Director of Digital Transformation at one of the UK’s leading independent schools, where she helps educators navigate new technologies without losing sight of deep learning and student wellbeing. With a Master’s in Smart EdTech and Co-Creativity, she has researched how students think when using AI, sharing her findings at international conferences and through her widely read newsletter for educators. Amelia mentors colleagues worldwide, teaches her “Thinking with AI” course, and speaks regularly about the need to blend artificial and human intelligence in education. Known for translating academic research into practical classroom strategies, she is passionate about ensuring that technology lifts attainment, deepens learning, and protects the well-being of both students and teachers. Learn more about her work at amelia-king.com.Andrew Easton is an education speaker, author, and consultant specializing in personalized learning, artificial intelligence in education, and learner engagement strategies. He serves as the Digital Learning Coordinator for Nebraska’s Educational Service Unit Coordinating Council, supporting schools across the state with innovative technology integration. A former classroom teacher with more than a decade of experience, Andrew has delivered over 50 conference presentations and 125 professional development sessions for educators across the U.S. and Canada. He is the author of Empowered to Choose: A Practical Guide to Personalized Learning and the host of The Good Life EDU Podcast, where he explores the latest ideas shaping the future of teaching and learning. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit aienhancedprocesses.com

In today's episode, Alex has a chat with Jeremy Willette, Leslie Henry, and Brenna McCandless, three library and information specialists. In the episode, we explore how we can help kids find accurate information in the age of AI. Below you can find information about the guests: Brenna McCandless: Brenna has been a pre-K through grade 12 librarian for 15 years and has lived and worked in the United States, Malaysia, China, and more. She is also knowledgeable about designing materials, AI in education, and more! Leslie Henry: Leslie Henry is her 36th and final year in education. She has worked as both a French teacher and a librarian in Canada, Russia, Indonesia and China. Leslie celebrates the sense of community and safety that libraries provide. Her passion is children’s literature. She marvels at the magic and joy that a picture book can bring to children of all ages! Leslie is the cross-river librarian at Shanghai American School.Jeremy Willette: Jeremy Willette discovered a love and appreciation for libraries as a kid growing up in rural Maine. In addition to being a frequent visitor at the nearby town library, he volunteered for years at the one in his school. Since then, he has become an international educator working for over 20 years in the USA, Brazil, Hungary, India, and China…and has helped other generations of people love the library too, from infants to adults. An avid traveler, foodie, and library advocate, Jeremy is the Library Coordinator at Shanghai American School. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit aienhancedprocesses.com

In this episode Joellen Killion joins the podcast and talks about what impactful feedback could look like as a practice as well as what it could look like in the age of AI. ⁠Joellen's Book on Feedback (link)⁠About JoellenJoellen Killion champions educator learning as the primary pathway to student success. She serves school systems, schools, regional, state, and national agencies within the U.S. and abroad as a consultant and learning facilitator. She is senior advisor to Learning Forward and formerly was its deputy executive director. Joellen leads, facilitates, and contributes to a number of initiatives related to examining the link among curriculum; leadership; quality instruction; professional development; and student learning. She has over 30 years of experience in curriculum development and implementation and planning, design, implementation, and evaluation of professional learning at the school, system, state, national, and international level. She was the recipient of the Don Deshler Leadership Award and the Adams County District 12 Merit Award. She serves on the advisory board for the Association for the Advancement of Instructional Coaching in International Schools and is a member of the editorial board of the International Journal on Mentoring and Coaching in Education.Joellen is a frequent contributor to education publications. Her books include What Works in the Middle; What Works in the Elementary Grades;, and What Works in the High School; Teachers Who Learn Kids Who Achieve: A Look at Model Professional Development; Assessing Impact: Evaluating Professional Learning, 3rd edition; Collaborative Professional Learning Teams in School and Beyond: A Tool Kit for New Jersey Educators; Taking the Lead: New Roles for Teacher and School-based Coaches; The Learning Educator: A New Era in Professional Learning; Becoming a Learning School; Coaching Matters; The Feedback Process: Transforming Feedback for Professional Learning.; and Elevate School-based Professional Learning. She authored and co-authored numerous papers, articles, reports, and workbooks such as PDK’s EDge, The Changing Face of Professional Development; A Systemic Approach to Elevating Teacher Leadership; and resources associated with the Transforming Professional Learning for Common Core Implementation initiative. She serves on the editorial board of the International Journal of Mentoring and Coaching in Education. Her particular interests are collaborative learning teams, coaching educator success, evaluation and program audits, standards for professional learning, policy to support professional learning, and comprehensive planning and implementation of high-quality, standards-based, results-focused professional learning. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit aienhancedprocesses.com

In this episode, Alex and Kim Cofino chat about the "other side" of AI-- Kim likens her experiences with social media to AI and gives us some thoughts on how we proceed as we integrate AI into our lives more and more. Kim has been an educator in international schools since August 2000. Having lived and worked in Germany, Malaysia, Thailand, and Japan, Kim has had a variety of roles in international schools, including (her favorite) instructional coach. Kim is the host of the #coachbetter podcast, and frequently speaks and writes about the power of coaching to sustain change in schools. In addition to her work in education, Kim is also a competitive powerlifter, currently on the Thai National Team as the 63kg M1 representative for Thailand. Based in Bangkok, Kim is the Founder and CEO of Eduro Learning, where she supports educators and schools to develop sustainable and successful instructional coaching programs. Kim is also the Executive Director and Founder of the Association for the Advancement of Instructional Coaching in International Schools (AAICIS). Learn more about Kim and Eduro at: https://www.edurolearning.com. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit aienhancedprocesses.com

In this episode Alex interviews Jason Prohaska from ESF, Hong Kong. Jason spoke at 21CL and had a breakout session titled "The Digital Divide" on how tech affects boys differently than girls. Jason's BioJason Prohaska serves as the Educational Technologies Lead at the English Schools Foundation in Hong Kong, developing strategic direction for technology integration across their network of 22 schools and 18,000+ students. He specializes in creating foundational frameworks for educational technology governance, ethical AI implementation, and digital citizenship while chairing the Educational Technologies Network.With over a decade of experience at Renaissance College Hong Kong and previous roles at German Swiss International School, Jason focuses on empowering educators and school leaders through professional development and strategic guidance. He holds numerous certifications including Apple Distinguished Educator and Google Certified Teacher.From his LinkedIn: "I am an experienced educational leader focused on integrating technology to transform teaching, learning, and leadership. At the heart of my leadership philosophy is a belief that technology and STEM education should always serve people—empowering students to lead with creativity, ethics, and purpose."Connect with Jason: https://www.linkedin.com/in/jasonprohaska/ This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit aienhancedprocesses.com

In this episode Alex sits down with Holly Clark and Steven Chang. The provocation to get our conversation started is: "how can we use AI as a super power like Iron Man rather than something that makes us helpless like in the film WallE?" Holly Clark is the author of "The AI Infused Classroom," and a leading global strategist for AI in education, guiding schools and districts through the integration of AI best practices and policies. As an acclaimed international speaker, bestselling author, and co-host of The Digital Learning Podcast, she draws on her trailblazing experience in one of the first 1:1 classrooms in the nation, to empower educators to adopt AI-enhanced blended learning.Guest Bios:Holly's influence on the educational landscape echoes in her other acclaimed books, "The Google Infused Classroom", "Chromebook Infused Classroom", and “The AI Infused Classroom”, which are esteemed resources for educators globally. She is a Google Certified Innovator, a Microsoft Innovative Educator Expert, and a National Board Certified Teacher. Her passion is for helping teachers find their blended learning and AI genius and learn to create and design unforgettable learning experiences. Connect with Holly on all social media via @HollyClarkEdu or visit her blog at hollyclark.orgSteven Chang was former Corporate VP of Tencent and CEO, Greater China of a global advertising agency. He is a coach and consultant for Business application, transformation, strategy formation and marketing solution of new technology, new business model and China Internet ecosystem. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit aienhancedprocesses.com

In today's episode Alex interviews three incredible educators on a panel. We chat about a hot topic in the education world at the moment-- AI and assessment. The team discusses their personal and professional backgrounds, roles, and expertise in relation to AI and assessment, with a focus on the need for a shift from traditional teaching methods to more student-centered approaches. They also critiqued external standardized tests and emphasized the importance of developing durable skills that are transferable and relevant in the modern world. The conversation ended with plans for future communication and collaboration, including the possibility of a follow-up session and the inclusion of a creative writing project in the podcast.Jennifer DeLashmutt has over 25 years of teaching and leadership experience in the United States and Asia. For the last ten years, she has served as an elementary principal and PK-12 Director of Curriculum and Professional Learning in Hong Kong ( HKIS) and Bangkok (ISB). Her background in curriculum, instructional practices, and assessment spans both primary and secondary years. She is devoted to ensuring that all learners are empowered members of their learning communities and they feel safe and valued. Jennifer is a design thinking leader who is future driven and diligently stays curious! She is an educational consultant with Novak Education. In our episode she mentions:⁠Katie Novak and Catlin Tucker - Embracing AI⁠⁠LUDIA Chatbot on Poe⁠Dr. Shannon Doak is an Edtech and Innovation Leader. Speaker, Author, Lucky Father and husband, #AI Enthusiast, #PoeCreator #CoffeeLover, and #HomeBarista | He is currently the Director of Technology at Nanjing International School. Some helpful links from Shannon are:⁠This is the book by Dr Sonny Magana⁠⁠This Grade School Offers AI-Only Classes, No Teachers Involved⁠⁠How a new Arizona school will use AI to teach students in 2-hour models⁠Walk into many schools today and you'll find a system as outdated as a sundial at NASA - not because educators aren't innovating, but because the system itself needs reimagining. John Nash partners with school leaders to close the gap between where education is and where it needs to be. John doesn’t treat school transformation like making microwave popcorn - push a button and pray. John’s approach is more like brewing the perfect cup of coffee: methodical, intentional, and guaranteed to wake people up. Drawing from 30 years in the trenches of education reform, he shows school leaders how to use design thinking to fundamentally rethink how schools work. As founding director of the University of Kentucky's Laboratory on Design Thinking, he helps transform traditional institutions into dynamic learning environments where students drive their own education. His approach on design thinking and generative AI has caught the attention of everyone from the U.S. State Department, to district superintendents, to international schools. His book "Design Thinking in Schools" (Harvard Education Press) gives leaders a tested blueprint for turning bold ideas into meaningful change. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit aienhancedprocesses.com

In today's episode, I sit down with three incredible educators: Amelia King, Vera Cubero, and Dr. Shannon Doak. We explore the idea of whether or not AI is a support or a hindrance to one's creativity. You can all three of my guests on Linked In. Finally, at the end of the episode, I share a song that I made as a collaboration with AI: I uploaded a finished song, remade it for several hours, and then mixed/looped/edited the output. I hope you enjoy the episode! This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit aienhancedprocesses.com