CYCLES OF LEARNING
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When curiosity is sparked...

deep cycles of learning can occur.

Making the Lesson, Not Planning It

5/19/2026

 

A month ago I wrote about how the app is the lesson. This week I crossed a quieter threshold. I am no longer building apps as enrichment, or as a special-occasion tool. I am building them instead of planning. The app is the planning. The act of designing the interaction is the act of thinking through what students need to do.

I can see this getting addicting, and I am not entirely sure that is a bad thing.

The Withdrawal App Became a Guest Lecture

The clearest example from this week was an app I built on the neuroscience of withdrawal. It leverages clips from Basketball Diaries, Leaving Las Vegas, and Beautiful Boy to ground the synaptic story in real human stakes. I am proud of this one. It walks students through how the synapse works normally, how a drug changes synapse activity, how the body compensates, and what happens at withdrawal.

Then I used it as the spine of a guest-lecturer activity I called Company Development. Students broke into small companies, each assigned a drug (alcohol, cocaine, meth, ecstasy, fentanyl), and each company had three roles. A graphic designer built an infographic, by hand or with Canva or NotebookLM, that walked through the four stages with strategic callouts instead of paragraphs. A videographer used Play-Doh and a ring-stand overhead camera to make a stop-motion explainer using only voice and hands. A computer scientist built a public-facing web app explaining the same four stages, and got a half-day of consulting time to learn how to deploy it publicly. The whole team submitted as one Google folder with all deliverables and the live URL inside. Ten points per role, thirty total.

What I keep noticing about this kind of project is that the rigor lives inside the building. You cannot make the infographic without understanding the synapse. You cannot voice over the Play-Doh without owning the sequence. You cannot deploy the web app without choosing what to keep and what to leave out. The assessment is the artifact.

The pattern: Build the app, then let the app become the lecture, then let the lecture become a project where students build their own apps. The teacher's tool becomes the student's task. The loop closes.

The same week, I made a review game in the same format. I am loving this review-game pattern, three rounds of ten questions with a scoreboard sidebar and a timer. Building it took about as long as designing one good quiz, and it lives forever.

Which leads to the harder question this project surfaced: when is public student work appropriate, and when does it cross into territory I do not want to be in? Live URLs are powerful for motivation and for portfolio. But a public app explaining the neuroscience of fentanyl is a different artifact than a private folder of homework. I am still working out where the line is. I want students to feel the lift of authentic audience without sacrificing their privacy integrity. If you have figured this out, write back.

Digital vs Physical Companions

I added a feature to Spark Learning this week. Every time a teacher generates a cycle PDF, the system now also generates a digital companion, with a QR code on the front of the printout that opens the digital version on a phone or laptop. It is a small thing, but it has me rethinking how I want students to take notes.

My chemistry students have been working out of physical Spark notebooks all year. I cannot tell yet whether those notebooks are reducing cognitive load (everything in one place, everything chronological) or quietly overloading it (copy this, paste that, draw this diagram, transcribe this equation). Science is the tricky case. Students need to draw formulas. They need to sketch reactions. The physical notebook has a real role. But maybe not every part of the notebook needs to be physical.

What I am curious about is a hybrid. Everything digital by default, with a clean, well-curated paper notebook that students build themselves. A real table of contents. Things they choose to copy down because they decided those things mattered. Something they take pride in. Less transcription, more curation. The notebook becomes a museum of their own thinking rather than a photocopy of mine.

QR codes keep being the bridge. It is amazing how long QR codes have stood the test of time. Whatever future scanning technology arrives, the QR code is the duct tape that ties a paper page to a live web app, every single time.

Algorithmic vs Conceptual Chemistry

I am back on the question I floated last month about dimensional analysis. I do not have an answer yet, but I have a sharper version of the question. Is stoichiometry actually just fractions? Is dimensional analysis a beautiful inherited aesthetic that occasionally gets in the way of the underlying ratio reasoning? Is the mole map a clearer scaffold than the ICE table for some students, or am I just nostalgic for a tool I learned twenty years ago?

What I keep coming back to is the difference between algorithmic knowledge and conceptual knowledge. A student can run a mole-to-mole conversion correctly and not actually know what a mole is. A student can fill in an ICE table flawlessly and miss the equilibrium story. We have built a generation of routines that produce right answers without producing understanding. That is a problem the textbooks did not invent, but they did harden it.

I am drawn to the Building Thinking Classrooms approach for this reason. Vertical whiteboards. Visibly random groupings. Tasks that demand reasoning before procedure. I want this in chemistry, and I am not sure how to do it inside a class where demonstration is so prevalent. How do you build inquiry into a flame test? Into a redox demo? Into the moments where the instinct is to show, not ask? I am chewing on it.

The shift I want to make: Replace at least one algorithmic routine per unit with a thinking task on a vertical surface. The mole map is the worksheet. The conceptual question is the whiteboard.

And one related thread, mostly for the future-of-software pile: is making websites dead? Wix, Weebly, all of it. If a student can spin up a tailored app in twenty minutes, do they still need the dragged-and-dropped homepage? I am not sure. But it feels like the wind has shifted.

A Closing Reframe

One last thing. A podcast this week reframed dopamine for me in a way I have not stopped thinking about. We talk about cell phones as addictive, and we use the alcohol or cocaine model: dopamine, tolerance, withdrawal. But the podcast made the case that phone use is closer to OCD than to substance addiction. It is a hijacked compulsion loop. The reward is not what is driving the scroll. The relief from the urge to check is.

If that is right, the way we talk to students about phones needs to change. Not "this is addictive," but "this is eliciting an OCD-type response." That is a different conversation, a different set of strategies, and probably a different curriculum thread. I am going to try it next year and see if the language lands differently.

Which brings me back to where I started. The app I built on withdrawal taught my students about real neurochemistry. The conversation about their phones might benefit from a totally different model. The job of the teacher is to know which frame to reach for, and when. And maybe also to build the tool that helps the students see the difference for themselves.

Resources

  • Addiction & Withdrawal App
  • Addiction & Withdrawal Review Game
  • Building Thinking Classrooms
  • Maven (AI tips reference on Instagram)

One Concept, Whole Unit

5/3/2026

 

Something has been quietly shifting in the way I plan units this spring. In Neuroscience, it is action potentials. In Chemistry, it is single replacement. One concept sits at the center, and everything else is gravity around it. Pathology spins off the anchor. Case studies orbit it. Even the off-the-wall connections (an opioid called Journavx, a periodic paralysis case, a Play-Doh battery that lights a red LED but not a green one) end up tracing back to the same epicenter.

I think I am starting to understand what critical thinking actually looks like in a classroom. It might be this. The ultimate concept map. One idea, deeply, with everything radiating outward.

The Epicenter Concept

In Neuroscience this week, the action potential opened up so much room. Opioid addiction, dopamine, the new pain drug Journavx, periodic paralysis as a potassium channel disruption, multiple sclerosis as a story of myelin and demyelination. Each new topic was not a new unit. It was a new orbit around the same gravitational core.

The students saw it too. Once they understood the action potential well enough, they could predict what would go wrong in every disease we encountered. Sodium channel mutation? They knew the firing pattern would change. Demyelination? They knew the signal would slow or fail. The anchor was doing the work. I was just pointing at the orbit.

Synaptic connections is the other anchor. Once you have it, addiction makes sense. Reward circuits make sense. So much of human behavior makes sense. Two anchors. A whole semester.

The pattern: Teach one thing well, and let everything else spin off it. The concept map is not the product. The concept map is the thinking.

Inquiry Before the Explore

I have been pushing the engage phase harder this year. Not as a hook, but as a genuine hypothesis-forming moment that runs underneath the whole exploration. The students should already be reasoning before they touch the lab materials.

In Chemistry, we did this with single replacement reactions. I put the reaction of copper and silver nitrate on a time-lapse loop and asked students to watch and guess what was happening. They debated the colors. They argued about what was forming. Then I challenged them to set up the same reaction themselves, also on time-lapse. The engage moment was already an exploration.

In Neuroscience, we used a multiple sclerosis case study to launch into brain anatomy. Students started with a patient profile (blurry vision, balance issues, right-side weakness) and used the symptoms to hypothesize which parts of the brain might be affected. From there, they did a sheep brain dissection, located the regions they had predicted, and pulled small biopsies into labeled tubes. The dissection was not a separate event. It was the test of their hypothesis.

The Play-Doh battery moment was unplanned but landed beautifully. Students built a battery from Play-Doh, zinc, and copper chips, and tried to light an LED. The red one lit. The green one would not. They started hypothesizing on their own, connecting it back to the flame test activity we did at the beginning of the year. Lower energy required for red excitation versus green. I had not planned the through-line. The anchor concept did it for me.

Build the Tool, Not the Workaround

Two more apps came out of this week, both because I needed something specific and the existing tool did not fit.

I needed a better classroom timer. Not a generic one, just something simple, big, and silent. So I built one. Class Timer took about an hour. It does exactly what I need.

I also wanted students using podcasts as a homework vehicle instead of a textbook chapter. I needed an app that would help them find topic-relevant podcast episodes quickly. So I built Classroom Podcast Finder. Now homework is a curated, searchable, audio experience instead of a static page.

And inside Spark Learning's Inquiry Studio, I figured out how to generate a QR code for the lecture video and place it directly on the student handbook. That changed everything for the flipped classroom. Students watch the video during class, on their own devices, while I stay in the room. They check in with me when they finish. The video becomes personal again. The structure stays. I do not have to chase anyone down.

The shift: The flipped classroom always had a logistical problem. The video lived outside class. The accountability lived nowhere. Bringing the video back into the room, with a QR code on the page, fixes both.

Two old blog posts felt newly relevant this week as I worked through this. The Explore-Flip-Apply theoretical framework is the structure. A pedagogy-first approach to the flipped classroom is the why. Worth a re-read if it has been a while.

A Question for the Chemistry Crowd

One thing I keep turning over: are we teaching mole conversions and dimensional analysis the way we do because it is genuinely the best path, or because it is the aesthetic we inherited? I am not arguing for tossing it. But I am wondering if we are sometimes loyal to old methods at the expense of student access. Worth thinking about. I do not have an answer yet.

I will leave you with this. The anchor concept does not just structure the unit. It structures the thinking. And maybe that is what we have been chasing all along.

Resources

  • Explore-Flip-Apply theoretical framework
  • A pedagogy-first approach to the flipped classroom
  • Classroom Podcast Finder
  • Class Timer
  • Opal (Google's mini app maker), exploring how it fits
  • Springer paper on emotional regulation

The App IS the Lesson

4/19/2026

 

I stayed up late last week trying to record a lecture video on action potentials for my Neuroscience class. I kept redrawing the neuron, restarting the recording, trying to get the sequencing right. After about an hour of frustration, I stopped and asked myself a different question: why am I making a video at all?

What I actually wanted was for students to explore the process of an action potential unfolding, to interact with it, to discover the pattern before I named it. A video is passive. It shows. It tells. What I needed was something that let students do.

So I built an app instead.

Build What You Need

Using Claude Code, I built a small interactive simulation that scaffolds the action potential process for students. It is tailored specifically to my class, my sequence, my learning goals. No extra features, no unnecessary information, no generic PhET simulation that shows too much too soon. Just the right amount of discovery at the right moment.

Here is the thing that surprised me: the app took less time to build than the video would have taken to record and edit. And it does something a video never could. It lets students interact, explore, and arrive at understanding on their own terms.

The shift: I was not looking for a tool. I was not shopping for a simulation. I was building exactly what my students needed, and the act of building it forced me to think more carefully about the learning experience than any lesson plan ever would.

I shared both apps with my colleagues this week. The Action Potential App and the Demyelination App are live. They are simple, purposeful, and built for inquiry. If you want to see what "build the tool" looks like in practice, start there.

Is Software Dead?

This experience pushed me into a bigger question that I have been turning over for weeks: is traditional educational software dead?

Think about it. We used to search for the right app, the right simulation, the right platform. We evaluated SaaS products, compared features, sat through demos. And most of the time, the tool was close but not quite right. Too broad, too narrow, too cluttered, too rigid.

Now students can build their own. A student struggling with organic chemistry can use Claude to generate a tailored study app. A student mapping historical events can create a custom timeline tool. A student learning Arduino can build a simulation specific to their project. The combination of Claude and NotebookLM has quietly made one-size-fits-all software feel like a relic.

The question I keep coming back to: should we be teaching students how to dynamically create tools in response to their own learning needs? Not coding for coding's sake, but building as a form of thinking. The app is not the product. The app is the process.

Rigor and Creativity in the Same Breath

There is a tension I feel every week between wanting rigorous, measurable learning and wanting students to create freely. Grading makes it harder. Standards make it harder. The instinct to control the outcome makes it harder.

But here is what I am learning: when students build something, the rigor is embedded in the building. You cannot build an action potential simulation without understanding action potentials. You cannot create a study tool without deeply engaging with the content. The creative act and the rigorous thinking are not in tension. They are the same thing.

The challenge is designing assessment structures that honor this. Standard grade formats were not built for student-created software. They were built for essays and exams. I do not have a clean answer yet, but I think the answer lives somewhere in the process documentation, in the iteration, in the visible thinking that building requires.

The real question: How do we build classrooms where rigor and creativity are not competing values but inseparable ones? Where the standard and the project are the same thing?

I am still working on this. But the action potential app taught me something I did not expect: sometimes the best lesson plan is not a plan at all. It is a tool that did not exist until you needed it.

Resources

  • Action Potential Interactive App
  • Demyelination Interactive App

Build the Tool, Don't Find the Tool

4/9/2026

 

A student in my neuroscience class blinked. A lot. That's not remarkable in itself — we all blink. What was remarkable was the question that followed: How many times do we blink in a minute? And does it change when we're focused?

In the past, I would have Googled "blink counter app," scrolled through the App Store, found something close, settled for something mediocre, and moved on. Instead, I built one. Right there. During class. An app that counts blinks, times them, and gives students real data to analyze.

This is the shift I can't stop thinking about.

The Problem-Solver's Instinct

We've spent years training ourselves — and our students — to be tool finders. Need a timer? Find one. Need a quiz platform? Compare five. Need a simulation? Hope someone built one. The entire edtech ecosystem is built on the assumption that teachers are consumers of tools built by someone else.

But what happens when you can build the tool yourself? When the distance between "I have a problem" and "I have a solution" collapses to minutes instead of months?

Building apps to solve problems rather than looking for tools to solve problems is very metal. Solving your own problems through invention just might be the next AI-powered critical thinking.

My own app, Spark Learning Inquiry Studio, is an example of this. I had a problem: inquiry-based lesson design is powerful but hard to structure, hard to present, hard to share. No tool existed that thought the way I think about the 5E learning cycle. So I built one. And it continues to evolve because it's mine — it solves my problems.

Students as Builders

Here's where it gets exciting: students can do this too. Not hypothetically. Right now.

Jacob, a student in my Design for Social Good class, needed a way to test assistive technology connections for the Xbox Adaptive Controller. There's no app for that. So he built one: an Arduino-based testing interface that solves a real problem for real users. He didn't find a tool. He became the toolmaker.

This is what I mean by "app slop" used for good — quick, purpose-built applications that solve specific problems. They don't need to be polished. They don't need to scale. They need to work.

The Classroom as Laboratory

This week I used a Slinky to get my neuroscience students thinking about perception and time delay. A simple warm-up in Spark Learning — watch the Slinky drop, notice the delay between what you see and what you feel, and wrestle with why. In chemistry, we used Jenga blocks to model the molecular instability of nitrogen triiodide. The tower wobbles. You hold your breath. Then it collapses — just like the compound.

These aren't tech moments. They're inquiry moments. The Slinky and the Jenga tower are tools I built into a learning cycle using the same app I built to solve my own problem. The technology isn't the point. The thinking is the point. The technology just makes the thinking visible, shareable, and structured.

The Question

Here's what I keep coming back to: What's a problem you have? Not a tool you need — a problem. And what would happen if you — or your students — just... built the solution?

I think we're entering an era where the ability to identify a problem and invent a solution is more valuable than the ability to find and evaluate existing tools. That's a different kind of critical thinking. And AI makes it accessible to everyone — not just developers.

Something to sit with this weekend.

— Ramsey

Resources

  • Spark Learning Inquiry Studio — Inquiry-based instructional design
  • Jacob's Arduino Assistive Tech App — Student-built problem solving

Cycles of Learning — Ramsey Musallam
cyclesoflearning.com

AI and Media Literacy Lessons

11/4/2025

 
When most people hear I’m teaching a new class called AI and Media Literacy, they assume it’s a sharp turn from chemistry. In some ways, they’re right. My TED Talk, 3 Rules to Spark Learning focused on curiosity and inquiry in science classrooms, and chemistry has long been my home base. But this new course grows from that same philosophy: it’s about giving students safe, hands-on ways to play, question, and create with the unknown. In this case, the “unknown” is artificial intelligence.

The class centers on two big ideas: Predictive AI and Generative AI. Rather than treating AI as a mysterious black box, students learn to work inside it—to build, test, and critique it. I want them to experience the useful side of AI right alongside the problematic side, building the kind of fluency that can only come from making things.

Project 1: Predictive AI: Our first project explores Predictive AI, which powers tools that classify, sort, and detect patterns based on trained data. Students use Teachable Machine to build simple but meaningful predictive models—image, sound, or pose classifiers—that serve a purpose in their community. Students start by comparing how different AI models (ChatGPT, Gemini, Claude) define predictive versus generative AI, then move into hands-on modeling.

From there, they train AI to do something useful: maybe detect hand signals for accessibility, identify safe vs. unsafe environmental conditions, or recognize actions that can help others. The final challenge is to turn that model into a functioning web app, using a mix of Claude, ChatGPT, and Netlify. The results are surprisingly creative. You can browse their finished apps here on Padlet. If you’re curious about the full structure and rubric, you can view the Predictive AI Project.

Project 2: Generative AI: The second project flips the perspective. Instead of using AI to predict something about the world, students use Generative AI tools—Gemini, NotebookLM, Teachable Machine, and Google AI Studio—to analyze the world. Specifically, they build a web app that determines whether an image was created or altered by AI.

The process starts with research. Students prompt Gemini to curate ten recent YouTube videos explaining how to identify AI-generated imagery, then feed those into NotebookLM to digest and summarize the key ideas as a mind map and audio overview. From there, they design a rubric in NotebookLM listing 10–12 signs of AI manipulation.

They train a Teachable Machine model using real and AI-generated examples, then combine that model with their rubric inside Google AI Studio to produce a working app that analyzes uploaded images and explains why it thinks an image is or isn’t AI-made. The full project guide is available here: Generative AI Project.

The real goal of the course isn’t to turn students into coders. It’s to make them critical and confident participants in the age of AI. They learn how predictive systems make judgments, how generative systems can deceive or inform, and how both can be used for creativity and good.

For teachers interested in exploring AI in the classroom, I am hopeful that these projects strike a balance between creation and critique. They show students that AI isn’t magic—it’s math, data, and design choices made by humans. And like any good chemistry experiment, the best learning happens when they roll up their sleeves and see what reacts.
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    Ramsey Musallam is a full-time science teacher in Santa Rosa California.
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