EdTech Lens

Alex McMillan
  • 5.0 (2)
  • EDUCATION
  • UPDATED MONTHLY

Welcome to the EdTech Lens, a podcast for teachers. The show features discussions with leaders in education, and in each episode, we hear their perspectives on developments in education and technology today. Think of it as different inquiries in each episode. aienhancedprocesses.com

  1. 2D AGO

    "Gates" to Pause Processes

    Intro I’m closing out the school year by slowing down to actually look back and make sense of what happened. It’s a metacognitive act that I, for one, could certainly do more of. Over the next few weeks, I’m inviting a few guests from the podcast episode “How Did It Actually Go?” to guest-write an article. Each of them agreed to go a little deeper in writing, reflecting on how process-based learning with AI actually played out in their schools. Writing is both output and thinking. Writing is the actual process of figuring out what you believe. I’ve found this idea to be true on this Substack, and I think my guests have too. There’s a depth in that kind of deliberate slowing down that I haven’t always experienced with AI-generated text. Personally, I can’t help but wonder whether that reflective habit is at risk. The world is moving fast, and every week there’s a new exciting model. Deliberate slowing could look inefficient in that context and anti-zeitgeisty. With that, I want to thank Aimée Skidmore for this week’s post, which sits at the center of this discussion. Aimée teaches Grade 12 in Geneva and thinks hard about when GenAI is in the room, how we can maintain student agency and effortful thinking, as they are prone to wanting to move too fast in the name of completion. To get students to deliberately slow down, she created something that she calls gates that serve as pauses, or deliberate moments in a thought process, where students have to show what they are actually thinking before they earn the right to move on. The idea came from the game Dungeons and Dragons, which tells you something about how Aimée thinks. She’s practical, a little playful, and genuinely curious about the tension between structure and ownership in a classroom where AI can skip the messy middle entirely. In this piece, she walks through two iterations of the same project, what she noticed between them, and the questions she’s still thinking about. The Monday-Ready resource at the end is concrete and immediately usable, with a checklist of things we can do with gates in a process. Make sure to follow Aimée on Substack. Enjoy! From Aimée When students use GenAI, the worry is that they’ll outsource the final product. But the bigger risk is that they outsource the messy middle: the testing, rejecting, revising, deciding, and explaining. So many of us avoid this issue by designing around GenAI. And I used to spend a lot of time wrangling with how to do this with some of my lessons and projects. Now, I spend less time doing that and more time engineering moments where students have to show what they are thinking before they move on. My Grade 12 students were working in pairs to build a chatbot to help another student practice a certain habit of mind, like persistence or thinking flexibly. I wanted them to work through a Design Thinking process of empathy, define, ideate, prototype, test. Some of these steps involved getting support from GenAI, and some were not. I wanted them to be balanced in their use of tech. Alex McMillan’s AI Enhanced Process Generator was a key tool in helping me decide and communicate on which steps students might use AI to help and where I wanted them to work on their own. Full product scrolling screenshot below. At first glance, it could have looked like a dream GenAI project. Students were using AI, building something for a real purpose. They seemed to be in the flow and moving quickly. Maybe a little too quickly. I started noticing that students were at their computers, starting to build the chatbots, pretty early on. Some were even submitting the link to their final product in one class period. I felt a little panic and then decided to walk around and ask how things were going. What I found was disappointing: I couldn’t get to every student, there were some who couldn’t answer my questions about their process, and there were some who didn’t accept my suggestions to slow down and have another look at the first steps. So I went back to the drawing board to rethink the approach and rebuild it for the next cohort. How could I get them to slow down and go through all the steps of design thinking? I was trying to find out how I could get them to hand in a ‘rough draft’, like we do with essay writing, but I was more interested in checking their process than their product. I didn’t really care so much about whether the chatbot was 100% functional. It was only one small piece of the project rubric. Iterating with Gates On my second iteration of this project, I decided to add some proficiency checkpoints: a pause and check that students have to take before they move to the next stage of the work. I called them gates because I had this image of a DnD player facing an important decision where they need to slow down, check equipment and consult with their party before going through. Here are the two I built: Here’s what happened: The pace slowed. Students appeared to be more thoughtful in their choices. They had to sit through the struggle and check their own work before asking me. The talk changed. I was able to have short conversations with each student when they called me over to sign off. Over time, our talk became less about me checking their work and more about “Tell me where you are now.” “What do you like about this tool so far?” Students started explaining choices. “What led you to that decision?” I was able to redirect them when I saw they were not thinking deeply enough and ask them some questions that made my coach’s heart flutter. “What was challenging here for you? And what else?” They noticed problems earlier. Before they handed it in, they were able to make improvements because they could see those changes would make the final product stronger. The project became less about “my chatbot works” and more about “my chatbot is designed for a real learner.” This felt like a real win. The gates did what I hoped they would do. They slowed the project down in the right places. They made the process more visible and gave students a reason to explain their choices before rushing ahead. And this is the part I’m still thinking about. I feel a tension here about how much of the process I should define for them. When I create something, I do not move through the work in a straight line. I start in one place, jump to building, get stuck, jump somewhere else, come back, revise, test, rethink, and slowly find my way through. That movement feels natural to me now, but it took years to build. Students are still learning what that kind of process feels like. So the questions I’m sitting with now are: how do we give students enough structure to support their thinking, without turning the process into another set of steps they simply complete for us? How do I avoid a heavy process that will lead to more paperwork and overfunctioning for me? Because if I build too many gates, or if every gate depends on my approval, I risk creating the very thing I’m trying to move away from: students waiting for me to tell them if they are doing it right, if they are allowed to continue. So, the next version of this project might have students deciding where the gates go. It might involve more student self-checks, more peer testing, and more room for students to say, “This is what we tried. This is what we changed. This is why we’re moving forward.” And probably more modeling from me, too. Not modeling the perfect process, but showing what it looks like to get stuck, change direction, reject an idea, return to an earlier version, and keep working. That feels important because students do not learn ownership by being dropped into total freedom. They learn it by practicing responsibility within a structure that helps them keep going. The gate is not the point. The pause is the point. And what students do inside that pause is where the learning lives. That, to me, is one of the real design challenges with GenAI in the classroom. Yes, the tool can make the work move quickly. My job is to help students slow down enough to notice what they are doing, make real choices, and stay awake inside the process. Monday-Ready Resources Resource #1 - Checklist when Using Gates Separate the gate from the grade. If students associate checkpoints with judgment, they’ll perform readiness rather than demonstrate it. Frame the gate as a conversation. “Walk me through your thinking” lands differently than “let me check your work.” Unpack the steps before students take them. When you introduce a process, explain why each stage exists. Human psychology is consistent on this: we do not expend effort on things that feel arbitrary. If students understand why the empathy phase comes before the prototype phase, they’re more likely to take it seriously. Use a student-facing checklist, then release some gates over time. Before students call you over, they should be able to say yes to two or three concrete criteria. This shifts the first layer of accountability to them and changes what the teacher conversation is actually for. Over time, some gates can become peer-checked or self-certified. Early on, every checkpoint might involve the teacher. Once students show they understand the process, they can take on more of the checking themselves. This builds toward ownership without dropping them into total freedom before they’re ready. You can see how I built this into Step 5. Test on the Project Worksheet. (link below) Create a process journal and build in feedback before moving on. Ask students to document their thinking at each stage before they call you over. The journal becomes evidence of the work, not just the product. A peer can respond first; the teacher becomes the second reader. You will see how I did this through a Project Worksheet. (link below) Practice the process more than once. Research on habit formation and classroom routines suggests it takes roughly thr

    15 min

  2. MAY 17

    How Did It Actually Go?

    It's time to finish up the year with one last podcast episode. I decided that I wanted to have a reflection and talk to people about how process-based learning has been going inside their schools or classrooms. I talked to a range of educators and asked them several different questions, and this episode is a series of highlights from those conversations. So, over these 20 minutes, you're going to hear a series of short recordings in which we look at process-based learning with AI from several angles. Below are notes about each of the guests with links to their websites and social media. Thank you all for contributing to this episode! Aimée Skidmore | Teaching and Learning Coach | Geneva Aimée works with experienced teachers who are tired of being the engine in the room. Her focus is student ownership: structures where students start, think, revise, and take responsibility without the teacher carrying it all. She appears twice in this episode. First, she describes what process-based AI use looks like from inside her classroom. In her second segment, she explains how deliberate checkpoint gates changed the outcome of a chatbot-building project. Aimée offers a six-week Student Ownership Sprint for secondary teachers. She also hosts the International Teacher Staffroom podcast. LinkedIn | TeachSpark Aimée wrote a companion piece to go along with this episode. After you listen, make sure to read her more in-depth write up about “gates” below. Jay Goodman, Ed.D. | PBL Consultant | Canada Jay has spent nearly two decades designing problem-based learning programs. His Ed.D. focused on PBL program design. He co-developed the Innovation Institute, an award-winning interdisciplinary PBL program in Shanghai. In this episode, he describes mentor bots: teacher-designed AI personas built around specific domains of expertise. Students identify a knowledge gap, do initial research, and then bring that thinking into a structured conversation with a field-specific model. It solves a real PBL logistics problem without replacing the thinking students need to do first. LinkedIn | Goodman Learning Partners Vamshi Mugatha | Director of Technology | American School of Brasilia Vamshi brings in a leadership perspective as an admin. Vamshi describes a familiar challenge for many schools around the implementation side of a policy. What he realized was that the missing piece was expectations. When teachers weren’t setting them, students were using AI without disclosing it. The gap between the two created tension that the policy alone couldn’t resolve. LinkedIn Leon Lam | A-Level Head of Humanities | Beijing National Day School Leon teaches A-Level economics and leads Humanities at Beijing National Day School. Last year, he vibe-coded a Socratic essay coaching chatbot designed to slow students down and move them through idea generation, outlining, and drafting as distinct stages. He’s candid about what happened. Some students engaged deeply. Others focused entirely on getting the chatbot to advance to the next stage, treating compliance as the goal. He reflects on what he’d do differently next time. His biggest takeaway is that co-designing a process with students can be a powerful way to make the process less performative and more purposeful in supporting their work. LinkedIn This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit aienhancedprocesses.com

    20 min

  3. MAY 4

    Scaffolding

    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. Definitions I find that Universal Design for Learning (UDL) and differentiated instruction (DI) are often used interchangeably with scaffolding, so I want to take a minute to explore the three of them in relationship to one another before we move forward. I imagine that the conflation comes from the fact that each involves a teacher adjusting something for a learner to be successful. But there are some nuances between the three, and to make it more interesting, all three could technically exist at the same time. Defining Universal Design for Learning (UDL) CAST, the organization that developed Universal Design for Learning, describes UDL as a framework for designing curriculum so it works for all learners from the outset. Before the unit exists, a UDL-informed teacher is asking: Why are we learning this? How will I present it in multiple ways? How will students engage with it? How will they show what they know? The three principles (engagement, representation, and expression) aren't checkboxes. They're what Katie Novak might call design orientations. Many teachers and school systems treat UDL as a synonym for accommodation: extra time, modified texts, assistive technology. Those things matter, but they aren't UDL. UDL isn't retrofitting the curriculum for students who can't access it. It's designing the curriculum so the barriers don't exist in the first place. Defining Differentiated Instruction (DI) Carol Ann Tomlinson, who is arguably a leader in differentiation, has stated for decades that differentiation is a proactive mindset that a teacher brings to planning. Before the lesson begins, a differentiated teacher is asking: Who are my learners? What do I know about where they’re starting? What pathways and options can I build in so the learning reaches all of them? Multiple approaches to content, process, and product; not different destinations, but different routes to the same one. Many teachers have accepted a version of differentiation that means reducing the task for students who struggle. Fewer requirements or something like that. Tomlinson calls this myth out directly: differentiation is more qualitative than quantitative. It isn’t giving some students less of the same assignment. It’s rethinking the nature of the assignment so it fits the learner while keeping the learning objectives intact. Defining Scaffolding Scaffolding is what happens once learners are in the room, and you can see what’s actually happening. Pauline Gibbons puts it precisely in her book Scaffolding Language, Scaffolding Learning. She writes: “Scaffolding 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. 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.” In practice, scaffolding might look like a sentence frame that gives a student the language structure so their thinking can do the real work. It looks like a worked example that shows the process, not just the product. It looks like gradual release: I do, we do, you do. A think-aloud where a teacher makes their invisible reasoning visible. A guiding question that narrows the cognitive load just enough to get a student unstuck without removing the challenge. Notice what all of these have in common: none of them lower the intellectual demand. Second, with scaffolding, the aim is that students gain a level of independence to implement learning strategies on their own or with peers rather than relying on the teacher. Bringing UDL, DI, and Scaffolding Together Here’s a Claude Artifact (screenshot also below) of my understanding between UDL, Differentiated Instruction (DI), and Scaffolding as supported by several texts and AIs. All three of these practices can occupy the same classroom, the same lesson, even the same moment. Consider a history teacher designing a unit on the civil rights movement. Before the unit begins, she thinks about how students will access primary sources, how they will engage with the material, and how they will show understanding through writing, discussion, or a visual product. That’s UDL doing its work at the design stage. Within the unit, she notices some students need more time with the documents while others are ready to move into analysis. For students still wrestling with the sources, she designs a close-reading process. For students ready to push further, she moves them into a comparison and argument-building process. Different actions, same destination. That’s differentiation. Then on a Tuesday, she opens a language scaffold bot she built in advance; one that knows the sentence starters, knows the argument structure, and knows its job is to practice with students until they can do it alone. A student who can’t connect evidence to a claim works through three or four cycles with the bot; it offers a starter, the student completes it, the bot pushes back gently, and the student tries again. By the end, the student has written the sentence. The bot didn’t write it. The teacher didn’t write it either, though she designed the whole condition that made it possible. The scaffold existed for six minutes. The student is ready to meet the standard and gains a sense of independence. Over-Scaffolding and The Learning Pit 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 to sit in what James Nottingham calls "the learning pit"; that uncomfortable space of not yet knowing, which is where the real thinking happens. Tolerating that discomfort long enough for the thinking to happen isn't cruelty. It's the whole mechanism. 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 is a genuine investment in knowing your students, paired with a process that keeps expectations the same while letting expression vary. The destination doesn’t change. Every student is working toward the same learning goal. What can look different is how th

    21 min

  4. APR 12

    If It’s Difficult, You’re Doing It Wrong

    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 Faces A 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 Moves Here’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

    20 min
  5. "AI and Assessment" (Revisited)

    JAN 25

    "AI and Assessment" (Revisited)

    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

    1h 20m
  6. "Metacognition & AI"

    11/20/2025

    "Metacognition & AI"

    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

    1h 47m
  7. "Writing with AI"

    09/12/2025

    "Writing with AI"

    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

    2h 5m
  8. "Information Literacy and AI"

    08/23/2025

    "Information Literacy and AI"

    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

    34 min
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5
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About

Welcome to the EdTech Lens, a podcast for teachers. The show features discussions with leaders in education, and in each episode, we hear their perspectives on developments in education and technology today. Think of it as different inquiries in each episode. aienhancedprocesses.com

Information

  • Creator
    Alex McMillan
  • Years Active
    2025 - 2026
  • Episodes
    14
  • Rating
    Clean
  • Copyright
    © Alex McMillan
  • Show Website
    EdTech Lens