Professional Development

What If Every Teacher Could Build an AI Tutor? David Wiley’s Generative Textbooks Idea Is Worth Your Attention

There’s a particular kind of idea that shows up in education technology every few years — one that sounds almost too obvious once you hear it, but that nobody had quite put together that way before. David Wiley‘s work on generative textbooks is one such idea.

I’ve been following Wiley for a long time. If you’ve ever used an open textbook in a course or benefited from freely available educational materials online, there’s a good chance his fingerprints are on the infrastructure that made that possible. He’s one of the founders of the open educational resources movement — the effort to create, share, and freely adapt teaching and learning materials under open licenses. It’s unglamorous, important work that has saved students billions of dollars in textbook costs and given teachers genuine tools they can actually modify.

So when Wiley started applying that same philosophy to AI, I paid attention.

The Problem He’s Solving

The standard AI-in-education conversation goes like this: here are some tools (ChatGPT, Gemini, Claude, take your pick), and here are some ways teachers can use them. The tools belong to the companies. The teachers are users. If the company changes pricing, changes policy, or shuts down, the teacher starts over.

Wiley’s question is different: what if the instructional logic — the pedagogical intelligence built into an AI learning experience — belonged to the teacher? What if any educator could author an AI-powered learning tool without writing code, without a budget, and without surrendering control to a platform?

That’s what generative textbooks are attempting to answer.

How It Actually Works

The architecture is simpler than it sounds. A generative textbook isn’t a document — it’s a structured collection of inputs that, when assembled, tell an AI model exactly how to behave as a learning tool for a specific subject.

Here’s what an author creates:

A book-level prompt stub — the template that sets the AI’s voice, tone, format, and overall behavior. Think of this as the personality and ground rules of the learning experience.
Learning objectives — one per chapter or topic, short statements about what a learner should understand or be able to do.
Topic summaries — accurate, context-rich summaries written for the AI, not for students. These are what the model uses to stay grounded in accurate content rather than hallucinating.
Activity templates — the types of interactions available: flashcards, explanations, quiz questions, Socratic dialogue, whatever the author builds in.

When a student picks a topic and an activity type, the system assembles the relevant pieces into a single prompt and sends it to the language model, which generates a fresh, tailored learning experience — not retrieved from a database, but generated in the moment based on the author’s pedagogical structure.

As Wiley puts it: in this model, prompt engineering is instructional design. The authoring isn’t code — it’s curriculum work. That’s a meaningful distinction for teachers.

The Clever Pivot on Cost

The original prototype sent prompts through an API to open-weight language models hosted on Groq. Clean, seamless, technically elegant. Also not free — API calls cost money at scale, and Wiley found that most educators he consulted weren’t particularly concerned with whether the underlying model was “open” in the ideological sense. They were concerned with whether it was free for students.

So he made a pragmatic call: rather than routing prompts through a back-end service, the tool now assembles the prompt and copies it to the student’s clipboard. The student pastes it into whatever AI interface they already have access to — ChatGPT’s free tier, Gemini, a school-licensed model, whatever.

This is inelegant in the user-experience sense. There’s a copy-paste step that breaks the flow. Analytics become difficult. Student privacy depends on whatever tool they choose to use. Wiley is honest about all of this — he describes the project explicitly as a tech demonstration, not a finished product.

But there’s something worth noticing in the pragmatism. The decision prioritizes actual access over technical elegance. For students in districts that can’t afford platform licenses and teachers who don’t control their school’s technology budget, a tool that works with the free tier of a consumer AI product is more useful than a seamless experience behind a paywall.

Where Wiley Has Taken This Since

The generative textbook prototype was a starting point, and Wiley has kept building. His more recent thinking has evolved toward what he calls OELMs — Open Educational Language Models — a framework that combines open-licensed content with AI in a more sophisticated way.

The key addition is retrieval-augmented generation (RAG): rather than just grounding the AI’s behavior in a few paragraph-length topic summaries, an OELM includes a curated collection of OER content that the model actively retrieves from when generating responses. This makes the outputs more accurate, more traceable to specific source materials, and more trustworthy for educational use — one of the genuine limitations of relying on a general-purpose language model that might confabulate confidently.

The broader argument Wiley is making — that generative AI is the logical successor to OER — is worth sitting with. His claim isn’t that AI replaces open textbooks, but that the principles that made OER valuable (open licensing, participatory creation, the ability to adapt and remix) need to be extended into the AI space. As the educational materials market shifts toward AI-powered products, the question of who owns the instructional logic matters enormously for equity and access.

What This Means for Teachers

I want to be careful not to oversell where this project currently is. The generative textbooks site is live and explorable, but this is genuinely early-stage work. The copy-paste workflow has real friction. The quality of the learning experience depends heavily on the quality of the inputs a teacher creates, which means the authoring itself requires genuine pedagogical thought — garbage in, garbage out applies acutely here.

But the underlying question Wiley is raising is one I think about a lot as an instructional coach: who gets to design the learning experience, and on whose terms?

The dominant model in AI-powered education right now is platform-centric. A company builds an AI tool, schools license it, teachers become users. This mirrors exactly what happened with traditional educational technology — districts buy the LMS, teachers work inside it, the pedagogical architecture belongs to the vendor. We know how that story tends to go: cost escalation, lock-in, tools that don’t quite fit what teachers actually need because they were designed generically.

Wiley’s generative textbooks project is asking whether there’s another path — one where educators are architects rather than users. Where the instructional intelligence lives in open, adaptable, teacher-created structures rather than in proprietary platforms. Where a teacher in a school with limited resources can build a learning tool that’s as good as anything a well-funded district is paying for.

That’s not a modest ambition. And it’s not finished yet. But it’s the kind of work that tends to matter more than it seems to when it starts.

Go explore:

generativetextbooks.org — the live tool, free to explore
Wiley’s original post on the idea — where this started
His thinking on OELMs — where it’s going
His blog at opencontent.org — ongoing thinking on OER, AI, and the intersection

Related reading: my AI books post covers Ethan Mollick’s Co-Intelligence, which has useful framing for educators thinking about AI as a co-teacher rather than a replacement — a theme that runs directly through Wiley’s work.

From Counting Blocks to Bias: Rethinking How We Teach Young Children Math

brown numbers cutout decors — Photo by Magda Ehlers on Pexels.com

Math is supposed to be the most “objective” subject in school. Two plus two equals four, no matter who you are, right? But research shows the way we teach early math is full of bias—and those inequities start shaping kids’ identities before they even reach third grade.

That’s the focus of the Racial Justice in Early Math project, a collaboration between the Erikson Institute and the University of Illinois Chicago. The team is developing resources—books, classroom activities, teacher trainings—to help educators confront racial bias in how young children experience math.

As project director Priscila Pereira points out, bias isn’t just an individual teacher problem; it’s baked into structures like scripted curricula, under-resourced schools, and practices like ability grouping. Danny Bernard Martin, a professor at UIC, highlights how stereotypes like “Asians are good at math” and deficit narratives about Black children filter into classrooms, shaping expectations in damaging ways. Even the smallest teacher choices—who gets called on, whose creative solutions are validated—can reinforce or disrupt those narratives.

The initiative is working to equip educators with not just strategies but reflective spaces: webinars, fellowships, and immersive experiences where teachers and researchers can rethink what it means to create racial justice in early math classrooms. As Pereira puts it, “We just have to keep doing the work, because we know what’s right.”

It’s a reminder that math isn’t just about numbers—it’s about identity, power, and whose ideas we choose to value.

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Beyond Policing AI: Rethinking Assessment Through Authentic Learning and Connectivism

Leon Furze makes an important case: if the best we can do in the age of AI is to tighten surveillance, we’ve already lost.

In all corners of education, we need to stop policing artificial intelligence and focus instead on designing better assessments. GenAI gives us an excuse to have these conversations. AI needs to prompt us to reflect on what matters most: validity, fairness, transparency and of course, learning.

Instead of treating generative AI as a threat to assessment, we should see it as a provocation—an opportunity to reimagine how we measure and value learning. His five principles (validity, reality, transparency, process, and professional judgement) are solid on their own, but when refracted through authentic learning and connectivism, they take on even sharper meaning.

1. Validity becomes authenticity.
Assessment validity isn’t just about matching standards to outcomes—it’s about ensuring that what students are asked to do actually matters. Authentic learning demands that assessments reflect the messy, interconnected problems students will face beyond school. A lab report, a policy pitch, or a podcast that connects with a real audience provides validity in a way a locked-down multiple-choice exam never will. AI doesn’t threaten that kind of assessment; it strengthens it, because students must decide how and when to use the tool responsibly within authentic contexts.

2. Designing for reality means designing for networks.
Furze’s “design for reality” principle resonates strongly with connectivism. The reality is that knowledge no longer lives solely inside a student’s head—it’s distributed across networks of people, resources, and technologies. An assessment that ignores that fact is already outdated. When we allow students to bring AI into the process (declared openly, as Furze suggests), we invite them to practice navigating networks of information, filtering noise from signal, and building connections that mirror the way knowledge flows in the real world.

3. Transparency and trust are relational, not transactional.
Authentic learning environments thrive on trust: teachers trust students to take risks, and students trust teachers to guide without over-policing. Connectivism reminds us that learning happens in community, and that means shared norms around how tools like AI are used. Instead of “thou shalt not” rules, we need open conversations: Why might you use AI here? When might it short-circuit your learning? Transparency becomes less about compliance and more about cultivating reflective practitioners who can articulate their choices.

4. Assessment as process = learning as ongoing connection.
If assessment is a process, not a point in time, then it looks less like a final judgment and more like a portfolio of evolving connections. Students don’t just demonstrate what they know; they show how they know, who they connect with, and how their thinking shifts over time. This is connectivism in action: learning is the ability to make and traverse connections, not the ability to store facts in isolation. AI can become part of that process—as a collaborator, a draft partner, or even a provocateur that challenges their assumptions.

5. Respecting professional judgement = empowering educators as designers.
Authentic learning doesn’t happen in lockstep with rigid policies; it requires teachers to design experiences that matter in their contexts. Connectivism reminds us that teachers are nodes in the network too, bringing their expertise, relationships, and creativity. Respecting professional judgement means trusting teachers to balance the affordances of AI with the human dimensions of belonging, curiosity, and care.

The big takeaway?
AI doesn’t invalidate assessment. It invalidates bad assessment. If the only way an assignment “works” is by pretending students live in a vacuum, disconnected from tools, networks, and communities, then it was never truly authentic to begin with.

For those of us who see learning as both deeply human and deeply networked, Furze’s five principles are a call to action: design assessments that honor authenticity, embrace connections, and prepare students for a world where knowledge is always evolving—and never isolated.

Here are a few ideas to get your creative mind going as you think about redesigning your assessments:

1. Color Mapping Across Disciplines (Art + Science)

Task: Students design a digital exhibit that compares different historical models of color (Newton’s circle, Munsell’s system, RGB cubes). They use AI tools to generate visualizations, then critique the limitations of each.

Authenticity: Color mapping is both a scientific and artistic problem. Students engage in real-world disciplinary practices.
Connectivism: Students link to a network of thinkers (Newton to Roussel), and share their exhibits with peers online.
AI Role: Visualization generator, comparison tool, but students must justify why a model matters for perception or art.

2. Community Podcast: Local Environmental Issues (ELA + Science + Civics)

Task: Students research a local environmental challenge (e.g., water quality, urban green space), create a podcast episode featuring expert interviews, and use AI to help with transcription, sound editing, and draft questions.

Authenticity: Students contribute to civic discourse in their community.
Connectivism: They learn from and connect with real experts and share publicly.
AI Role: Drafting interview questions, transcribing recordings, generating promotional materials—but students remain responsible for the core knowledge and ethical framing.

3. History “What If” Simulation (Social Studies)

Task: Students use AI to model counterfactual scenarios (e.g., “What if the printing press had been invented 200 years earlier?”). They must critique the AI’s reasoning, identify inaccuracies, and build their own historically valid narrative in response.

Authenticity: Historians often test counterfactuals to sharpen their understanding of cause and effect.
Connectivism: Students cross-reference scholarly works, archives, and even online history communities.
AI Role: Idea generator and foil—the flawed AI answers become a catalyst for deeper historical reasoning.

4. Entrepreneurial Pitch for a School Problem (Business + Math + Design)

Task: Students identify a real issue in their school (e.g., cafeteria waste, lack of study space), design a product/service solution, and pitch it to administrators or community members. AI is used for market research summaries, prototype visuals, or cost projections.

Authenticity: Mirrors real entrepreneurial problem-solving.
Connectivism: Students collaborate with community stakeholders and pitch to an authentic audience.
AI Role: Research and prototyping assistant, not a substitute for problem-finding or decision-making.

5. Literature in the Age of Machines (ELA)

Task: Students select a literary theme (identity, power, justice) and compare how a human-authored poem and an AI-generated poem tackle it. They publish a critical essay or multimedia piece reflecting on authorship, creativity, and meaning.

Authenticity: Engages with contemporary debates about art and authorship.
Connectivism: Students link across traditions—classic texts, modern scholarship, AI-driven art.
AI Role: Source of creative “texts” to analyze, not a replacement for analysis.

Why These Work

Each task:

Builds validity by aligning with standards and real-world practices.
Designs for reality, where AI is part of the workflow.
Encourages transparency—students must declare and justify how they used AI.
Emphasizes process, not just a single product.
Relies on teacher judgment to guide reflection and assess growth.

Book Review: Tomorrow, and Tomorrow, and Tomorrow by Gabrielle Zevin

I read this book over the summer, in that particular state of rest that July occasionally allows — the one that educators know well, when the school year is genuinely far enough away that you can read for pleasure without it feeling like time you should be spending on something else.

Tomorrow, and Tomorrow, and Tomorrow by Gabrielle Zevin sat on my TBR for a while because I was skeptical. A literary novel about video game designers. The hype was enormous. The overlap between “prestige literary fiction” and “video game culture” felt like it might produce something condescending to both.

It didn’t.

What It’s About

Sam Masur and Sadie Green first meet as children in a hospital, bonding over video games while Sam is recovering from a car accident that has shattered his foot. The friendship deepens, fractures, and then reforms years later when they encounter each other again in college — and discover they can make something together that neither could make alone.

The book spans thirty years and three coasts, following Sam and Sadie as they build a series of video games, a company, a complicated creative partnership, and a relationship that is one of the most fully realized portrayals of deep friendship I’ve read in recent fiction. Marx, Sam’s roommate who becomes their producer and eventually Sadie’s partner, is the third point of the triangle — generous, perceptive, and ultimately the character whose absence reshapes everything.

Zevin structures the novel partly around the games Sam and Sadie create, which mirror their emotional states and the health of their relationship. It’s a formal choice that shouldn’t work as well as it does. The games are real in the way fictional technology rarely feels real — specific, idiosyncratic, built with apparent care rather than gestured at.

The Macbeth Problem (or Gift)

The title comes from the “tomorrow, and tomorrow, and tomorrow” speech in Macbeth — one of the most despairing passages in Shakespeare. Macbeth, after his wife’s death, catalogs the emptiness of time, the way tomorrow keeps arriving and delivering nothing but more of the same meaninglessness.

Here’s Patrick Stewart’s take from a modern interpretation of Macbeth:

Zevin takes this and inverts it. The “tomorrows” in her novel are not nihilistic. They are the respawns — the new game, the fresh start, the decision to keep playing after failure. The book is in conversation with the speech in a way that isn’t heavy-handed: the reference illuminates without dominating.

For educators, and I’m thinking here specifically about what it means to start a new school year, this inversion lands differently than it might for other readers. Every August is a tomorrow in exactly Zevin’s sense. Not the Macbeth sense — not emptiness recycling — but the choice to come back to something you believe in, again, after whatever last year held. That’s not a small thing to name.

What the Book Gets Right

Zevin is excellent on the texture of creative partnership — the way collaboration requires vulnerability, the way credit becomes a site of injury, the way people who make things together can genuinely love each other and also genuinely damage each other through the work. The professional and the personal don’t separate cleanly in Sam and Sadie’s relationship, and Zevin doesn’t pretend they should.

The treatment of disability is careful and specific. Sam’s foot injury — which eventually leads to amputation — is present throughout the book not as a symbol but as a lived reality that shapes his movement, his endurance, his relationship to physical space and physical pain. It’s not the defining fact of his character, but it’s not invisible either.

The friendship itself, which Zevin consistently describes as love without romance, is the novel’s real subject and greatest achievement. Sam and Sadie are “often in love, but never lovers” — and Zevin makes that distinction feel earned rather than coy. The question the book refuses to answer is whether their relationship would have been better or worse if it had become romantic, and the refusal feels honest rather than evasive.

What Doesn’t Quite Land

The novel is long and sometimes diffuse. Zevin covers thirty years of characters’ lives across multiple coasts and collaborations, and the middle section loses momentum in ways the beginning and end don’t. Some readers will find this immersive; others will find it baggy.

Some of the secondary characters — particularly the antagonists — function more as plot machinery than people. The novel’s sympathies are clearly with Sam and Sadie, and the characters who create obstacles for them occasionally feel as though they exist solely for that purpose rather than as full human beings.

The tech industry milieu is well-rendered but could have pushed harder on the structural inequities of creative industries. Sadie’s experience as a woman in gaming is addressed but somewhat lightly — a few scenes of credit being stolen, a few moments of being underestimated — in ways that feel like acknowledgment rather than full engagement.

Why I Kept Thinking About It

The reason this book stayed with me into August and into the start of the school year is the question at its center: what does it mean to keep making things together, across setbacks, failures, and the wreckage of what didn’t work?

The games Sam and Sadie build aren’t perfect. Some are failures. Some succeed in ways that create new problems. The process is recursive, sometimes painful, and never finished. And they keep doing it because the alternative — not making anything, not collaborating, not returning to the relationship even when it’s been damaged — is worse.

That’s not a bad frame for teaching. Or for any work that asks you to keep showing up to something that matters, in partnership with other people, over the years.

Rating: 4.5 out of 5 stars.

Get Tomorrow, and Tomorrow, and Tomorrow

If You Liked This, Read Next

A Little Life by Hanya Yanagihara — The other major literary novel of the last decade about a decades-spanning friendship between creative people. Significantly darker and more harrowing than Zevin’s novel. If you can handle it, it’s extraordinary.

The Midnight Library by Matt Haig — The most direct overlap on the “what if you could respawn, what lives might you have lived” question. Lighter than Zevin, more explicitly hopeful, and a genuinely affecting read.

Piranesi by Susanna Clarke — Another novel about navigating an invented world with its own strange rules, and what it means to find meaning and connection inside a reality that isn’t quite the ordinary one. Very different in tone from Zevin, but shares something with the game-as-parallel-world structure.

Klara and the Sun by Kazuo Ishiguro — A novel about observation, loyalty, and the limits of understanding the people you care most about. Quieter than Zevin but similarly interested in the question of what we owe to the people we love.

I also wrote a newsletter piece that blends this book with Shakespeare’s Macbeth and Jane McGonigal’s Reality is Broken, reflecting on what the “respawn” metaphor means for educators heading into a new school year. Read it here →

Sharpen Your Collective Spears: How to Write SMART Goals That Actually Move a PLC

Photo by Polina Zimmerman on Pexels.com

“In a world of infinite meetings, the scarcest resource is a goal people still remember after the coffee goes cold.”—my inner monologue every Tuesday at 7:45 a.m.

The bell hasn’t even rung when the dread kicks in. Our math PLC shuffles into a windowless room, walls plastered with mission statements no one can quite quote. The agenda glows on the projector—review data → craft SMART goal → adjourn—and someone opens last year’s spreadsheet. The cursor blinks like a taunting metronome:

Specific? “Raise Algebra II mastery five percent.”
Measurable? “Benchmarks track that.”
Achievable? “If the moon aligns with spring break.”
Relevant? “District said so.”
Time-bound? “May 15—graduation is May 16.”

Click Save. Google Drive adopts another orphan destined to be rediscovered—unfed and unloved—during next August’s in-service.

SMART ≠ Smart Enough

George T. Doran’s 1981 article introduced SMART as a managerial life-hack for middle managers drowning in vague memos. It worked because clarity beats wish-craft, so the acronym stuck. But teaching isn’t widget manufacturing, and a Professional Learning Community (PLC) is not middle management. Drop the vanilla acronym into a PLC and you often get tidy compliance—polite, forgettable, and incapable of nudging practice. (community.mis.temple.edu)

I’m not here to bury SMART; I’m here to jailbreak it. A goal that’s merely Specific and Measurable can still be pedagogically hollow. “Cover Unit 9 by Friday” is S-M-A-R-T and about as inspiring as a DMV form.

To make SMART sparkle inside a PLC, we have to graft it onto four live wires:

The Science of Learning & Development (SoLD)—brains toggle between threat and reward;
Connectivism—knowledge flows through networks, not warehouses;
Authentic learning anchored in your district’s Portrait of a Learner;
and the 4 Shifts Protocol, an instructional OSHA for deeper learning.

Flash these firmware updates onto the SMART scaffold, and the goal begins to breathe.

SoLD: Wiring the Goal to the Brain

Why does vanilla SMART sputter? Because it’s silent on how humans learn. SoLD research shows brains remain plastic when three conditions coexist: high challenge, high belonging, and obvious relevance. Stress without support drowns the prefrontal cortex in cortisol; stress with support sparks focus and growth. (soldalliance.org)

SoLD’s three non-negotiables translate into PLC design questions:

Do learners feel seen?
Is the work just beyond current mastery?
Can every brain tag the task as useful outside class?

Compare two drafts:

Vanilla — Increase correct factoring of polynomials by five percent.
SoLD-Tuned — By March 1, our Algebra II PLC will co-design three community-based modeling tasks—housing prices, local wage growth, skateboard trajectories—to lift correct use of multiple representations from 52 % to 75 %, measured by a shared rubric at a public expo.

The rewrite injects authenticity (local data), public exhibition (belonging + accountability), and the sort of demanding lift brains find exhilarating instead of paralyzing.

Connectivism: Goals as Network Packets

George Siemens argued that learning is less about what you know and more about how quickly knowledge flows through your network. In PLC terms, the nodes are you, your colleagues, that teacher on Instagram who posts slick Desmos hacks, and the treasure trove of lesson plans fermenting in Google Drive. A goal that stops at student data is a half-closed circuit—knowledge stagnates; momentum dies. (jotamac.typepad.com)

A network-savvy SMART goal spells out connection rituals:

a shared Drive folder where every lesson artifact lives;
a standing five-minute “What I tried this week” round-robin at each PLC;
a Friday Google Classroom prompt where teachers asynchronously swap feedback clips.

Bandwidth is a pedagogy. If the SMART statement doesn’t declare how the signal moves—from teacher to teacher and from student back to teacher—the circuit stays dark.

Authentic Learning & the Portrait of a Learner

Your district likely brandishes a glossy “Portrait of a Graduate”—creative problem-solver, compassionate collaborator, civic-minded innovator. Trouble is, many goals never leave the gated community of state standards; they measure skill fragments in lab conditions and call it progress. Authentic learning demands the opposite: skills unleashed in messy, consequential contexts, judged by audiences who care. Real-world stakes super-charge motivation and memory. (Edutopia)

That shows up in the Relevant clause. Instead of “aligns with KY Standard A2.Q.E,” try:

Students will design statistical dashboards for the city’s housing task force and defend their recommendations at a public forum.

Now the graduate-profile competencies are mission requirements, not hallway décor.

The 4 Shifts Protocol: Deeper-Learning Guardrails

Scott McLeod and Julie Graber’s 4 Shifts—deeper thinking, authentic work, student agency, technology infusion—work like a four-question crash test. Ask them of every draft goal: Does the task demand real cognitive wrestling? Will the product matter outside class? Do learners steer key decisions? Does tech amplify learning rather than merely digitize worksheets? If you answer “no” to any, keep writing. (dangerouslyirrelevant.org)

Most beige goals die on question 2: they yield products destined for the recycling bin, not the community or the Web.

Crafting Goals for PLCs, Not in PLCs

Here’s how our team writes without turning the meeting into a TED-style slog:

We walk in with evidence, not impressions—photos, student reflections, screenshots. We verb-hack mushy words like improve into verbs that signal complexity: design, simulate, defend. Every first-person singular becomes we—collective efficacy is grammatically plural. Before anyone clicks Save, we schedule two mid-cycle check-ins and agree on which artifacts (videos, drafts, rubric snapshots) will anchor them. Finally, we script a diffusion ritual—maybe a 60-second TikTok recap or a slide deck for the next faculty meeting. When sharing is baked into the goal, it doesn’t depend on hero-level willpower later.

A Full-Stack Example

Here’s a possible Algebra II goal :

By April 30, our Grade 10 math PLC will co-create, peer-review, and teach two interdisciplinary projects where students build interactive dashboards using local housing and wage data. At least 80 % of students will accurately interpret variability and propose actionable recommendations, judged by a shared rubric and showcased during a public “Data Night.” The team will meet every other Wednesday to iterate, store artifacts in a shared Drive folder, and survey students’ sense of belonging before and after the unit.

Break-down:

SoLD — belonging survey + public showcase.
Connectivism — Drive folder, peer-review rhythm, community data partnership.
Authentic Learning — city-council-relevant dashboards.
4 Shifts — deeper thinking (stats modeling), authentic work (public policy), agency (students choose variables), tech infusion (interactive dashboards).

The acronym didn’t change, but the genome inside is worlds away from “raise scores five percent by May.”

Dumpster Fires I’ve Authored (So You Don’t Have To)

I’ve written SMART goals that cratered spectacularly. Patterns emerge:

Input worship—“cover all twelve units” tracks what teachers do, not what kids learn.
Equity blindness—averages hide who’s drowning.
Ankle-high ambition—easy feels achievable, but starves growth.
Write-once, read-never—static goals in dynamic systems rot.

The fix is unglamorous: reopen the document, ask where belonging, relevance, or cognitive demand evaporated, and then rewrite.

Why This Matters More Than Benchmarks

A well-coded SMART goal has just two outcomes: teacher practice shifts and student cognition blooms. Everything else—acronyms, rubrics, meeting norms—is scaffolding. When a goal hits all four live wires, classrooms feel weird in the best sense. Students argue over data visualizations. Parents cheer on their children in Instagram stories from public showcases. Teachers trade spreadsheet formulas like favorite playlists. One morning, you realize no one’s counting ceiling tiles; everyone’s too busy debugging and learning in real time.

If that sounds utopian, remember: it’s biology plus bandwidth plus sentences you’ll actually reread. The brain loves hard problems in safe rooms. Networks love traffic. A SMART goal that guarantees both is no longer paperwork—it’s propulsion.

Your Turn

Open last year’s PLC folder, find the stalest goal, and run it through SoLD, Connectivism, authentic relevance, and the 4 Shifts. Rewrite until it hums like good sci-fi—plausible, provocative, people-centric. Then ship it. Invite your students, your admin, and your Instagram teacher circle to poke holes. Iterate. Repeat.

If this dive hit home, subscribe to The Eclectic Educator—my Friday dispatch where pedagogy meets punk rock—and forward this post to your PLC before the next calendar-driven time heist. Let’s make SMART stand for something again.

Oh, and you might want to pick up a copy of Read This Before Our Next Meeting, because most PLCs are 45-minute time vampires and this 90-minute read shows you how to turn them into fast, decision-driven sprints.

Slow Light: When Yesterday Hijacks Today

Ever wondered what life would feel like if your eyes buffered reality the way old dial-up modems buffered videos? Slow Light, the stop-motion stunner from Warsaw animation duo Kijek/Adamski, answers that question with style. It’s nameless hero sees everything on a seven-year delay—kindergarten birthday candles flare up during his first kiss, a forgotten snowball fight snows over a job interview, and so on. Yesterday isn’t lurking in the background; it’s live-streaming right on top of today.

The filmmakers crank up the disorientation to eleven with hand-cut paper sets awash in neon paint. Every frame feels like a pop-up book crossed with a fever dream. Their mini behind-the-scenes reel on Vimeo is a crash course in low-tech wizardry; it’s a reminder that big ideas don’t need Hollywood budgets, just relentless creativity (and a mountain of X-Acto blades).

Turning Slow Light into Authentic Learning

Below are four ways to let this short brain-bender spark real-world, student-centered work. Mix and match, or allow students to design their path.

Lens	Authentic Task	Real-World Connection	Graduate Profile Tie-In
Physics & Neuroscience	Remix the film’s handmade aesthetic in 3D: scan paper sets into Blender and add interactive hotspots that reveal “past vs. present” layers when clicked.	Partner with a local optometrist or university lab for feedback; publish explainer videos debunking vision myths.	Innovative Problem Solver, Effective Communicator
Media Literacy & Storytelling	Analyze how stop-motion’s frame-by-frame illusion mimics the film’s time-lag theme. Teams storyboard their own short that visualizes a cognitive quirk (e.g., déjà vu, false memories).	Submit films to a youth animation festival or stream them during a community movie night.	Creative Producer, Productive Collaborator
SEL & Psychology	Use the protagonist’s delayed perception as a metaphor: How do past experiences color present choices? Students craft personal “slow light” journals, then design advisory lessons to help younger peers understand trauma and resilience.	Collaborate with school counselors to run peer-led workshops on growth mindset and coping strategies.	Empathetic Citizen, Reflective Learner
Design Thinking & Tech	Remix the film’s handmade aesthetic in 3-D: scan paper sets into Blender, add interactive hotspots that reveal “past vs. present” layers when clicked.	Publish the interactive scene on the class website; invite feedback from professional animators via Zoom.	Digitally Fluent Innovator, Self-Directed Navigator

Ready-Made Reflection Prompt

If your own vision carried a seven-year delay, which past moments would you be doomed (or delighted) to relive—and how might that reshape who you are today?

Let students answer in whatever medium they choose—audio diary, comic strip, data viz—then host a gallery walk to surface common themes of perception, bias, and memory.

Bottom line: Slow Light isn’t just artsy eye candy. In the right hands (read: your classroom), it becomes a launchpad for interdisciplinary inquiry, hands-on making, and soul-searching reflection—all hallmarks of authentic learning that sticks long after the credits roll.

h/t to kottke.org

The Top 7 Professional Development Books for Teachers

In the ever-evolving education landscape, continuous professional development is crucial for teachers striving to enhance their skills and improve student outcomes. As educators, we are always seeking resources that can inspire and guide us through the challenges of modern teaching. Professional development books are an invaluable asset, offering insights, strategies, and perspectives that can transform our teaching practices and reinvigorate our passion for education.

In this blog post, we highlight seven must-read professional development books that every teacher should consider adding to their reading list. From understanding the power of vulnerability to implementing equitable grading practices, these books cover various topics designed to support and empower educators. Whether you are looking to foster a more inclusive classroom, engage students through culturally responsive teaching, or explore innovative educational practices, these books provide practical advice and inspiration.

Each book in this list has been carefully selected for its relevance, impact, and ability to address current educational challenges. We delve into the key takeaways and reasons why these books are essential reads for teachers committed to professional growth and student success. So, grab a cup of coffee, find a comfortable spot, and get ready to explore some transformative reads that will enrich your teaching journey.

Professional Development Books for Teachers — Photo by fauxels on Pexels.com

1. “Daring Greatly” by Brené Brown

Overview: Brené Brown explores the concept of vulnerability, challenging the idea that it is a weakness. She argues that vulnerability is a path to courage, engagement, and meaningful connections.
Key Takeaways: Understanding and embracing vulnerability can transform teaching practices and classroom management, fostering a more engaging and empathetic learning environment.
Reasons to Read: This book helps teachers develop stronger relationships with their students and colleagues by promoting authenticity and courage in the classroom

2. “Street Data” by Shane Safir and Jamil Dugan

Overview: Shane Safir and Jamil Dugan propose a new approach to data usage in education, focusing on qualitative data that captures student experiences and voices.
Key Takeaways: The authors provide a framework for using “street data” to create more equitable and responsive educational practices.
Reasons to Read: This book is valuable for educators and administrators seeking to transform their schools by centering student voices and experiences in their data practices

3. “The Art of Coaching: Effective Strategies for School Transformation” by Elena Aguilar

Overview: Targeting instructional coaches and leaders, this professional development book offers insights into emotional intelligence and collaboration.
Why Buy: If you’re in a leadership role, this book will equip you with the tools for transformative education.

4. “The Power of Place: Authentic Learning Through Place-Based Education” by Tom Vander Ark, Emily Liebtag, and Nate McClennen

Overview: This book explores place-based education, where learning is deeply connected to the local environment and community.
Key Takeaways: The authors provide examples and strategies for integrating place-based learning into the curriculum, making education more relevant and engaging.
Reasons to Read: Teachers interested in making learning more meaningful and connected to students’ lives will find this book a valuable resource for implementing place-based education

5. “For White Folks Who Teach in the Hood… and the Rest of Y’all Too” by Christopher Emdin

Overview: Christopher Emdin shares his experiences and insights on teaching in urban schools, offering practical advice for educators working in diverse settings.
Key Takeaways: The book emphasizes the importance of cultural competence and reality pedagogy in engaging and supporting all students.
Reasons to Read: Educators will benefit from Emdin’s strategies for creating more inclusive and effective learning environments in urban schools

6. “Culturally Responsive Teaching and the Brain” by Zaretta Hammond

Overview: Zaretta Hammond combines neuroscience and culturally responsive teaching to offer strategies that enhance student engagement and achievement.
Key Takeaways: The book includes ten key moves for teachers to make in diverse classrooms, helping students connect and thrive.
Reasons to Read: This book is essential for educators who want to understand and implement culturally responsive teaching practices, improving educational outcomes for all students

7.“Grading for Equity” by Joe Feldman

Overview: Joe Feldman addresses the inconsistencies and biases in traditional grading systems and offers strategies for more equitable assessment practices.
Key Takeaways: The book provides practical ideas for creating grading systems that promote fairness and support student learning and growth.
Reasons to Read: Educators looking to reform their grading practices will find valuable insights on how to implement equitable assessments that benefit all students

Conclusion

The world of education is ever-changing, and professional development books for teachers are essential tools to navigate this dynamic landscape. These top 7 professional development books for teachers offer diverse insights and strategies to cater to different needs and teaching styles. Whether you’re looking to inspire, innovate, or introspect, there’s a book on this list for you. Invest in your professional growth today with these exceptional reads. Happy teaching!