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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David Wiley is experimenting with what he calls “generative textbooks” — a mashup of OER (open educational resources) and generative AI. His core idea is:
What if anyone who can create an open textbook could also create an AI-powered, interactive learning tool without writing code?
From Open Content to Open AI-Driven Learning
For decades, Wiley has championed open education resources (OER)—teaching and learning materials freely available to adapt and share under open licenses like Creative Commons. With generative AI now in the mix, Wiley sees a unique opportunity to merge the participatory spirit of OER with the dynamic adaptability of language models.
The result? A new kind of learning tool that feels less like a dusty PDF and more like a responsive learning app—crafted by educators, powered by AI, and free for students to use.
The Anatomy of a Generative Textbook
Wiley’s prototype isn’t just a fancy textbook—it’s a modular, no-code authoring system for AI-powered learning. Here’s how it works:
Learning Objectives: Short, focused statements about what learners should master.
Topic Summaries: Context-rich summaries intended for the AI—not students—to ground the model’s responses in accuracy.
Activities: Learning interactions like flashcards, quizzes, or explanations.
Book-Level Prompt Stub: A template that sets tone, personality, response format (e.g., Markdown), and overall voice.
To build a generative textbook with ten chapters, an author creates:
One book-level prompt stub
Ten learning objectives (one per chapter)
Ten concise topic summaries
Various activity templates aligned with each chapter
A student then picks a topic and an activity. The system stitches together the right bits into a prompt and feeds it to a language model—generating a live, tailored learning activity.
Open Source, Open Models, Open Access
True to his roots, Wiley made the tool open source and prioritized support for open-weight models—AI models whose architectures and weights are freely available. His prototype initially sent prompts to a model hosted via the Groq API, making it easy to swap in different open models—or even ones students host locally.
Yet here’s the catch: even open models cost money to operate via API. And according to Wiley, most educators he consulted were less concerned with “open” and more with “free for students.”
A Clever—and Simple—Solution
Wiley’s creative workaround: instead of pushing the AI prompt through the API, the tool now simply copies the student’s prompt to their clipboard and directs them to whatever AI interface they prefer (e.g., ChatGPT, Gemini, a school-supported model). Students just paste and run it themselves.
There’s elegance in that simplicity:
No cost per token—students use models they already have access to.
Quality-first—they can choose the best proprietary models, not just open ones.
Flexibility—works with institution-licensed models or free-tier access.
Of course, there are trade-offs:
The experience feels disjointed (copy/paste instead of seamless).
Analytics and usage data are much harder to capture.
Learners’ privacy depends on the model they pick—schools and developers can’t guarantee it.
A Prototype, Not a Finished Product
Wiley is clear: this is a tech demonstration, not a polished learning platform. The real magic comes from well-crafted inputs—clear objectives, accurate summaries, and effective activities. Garbage in, garbage out, especially with generative AI.
As it stands, generative textbooks aren’t ready to replace traditional textbooks—but they can serve as innovative supplements, offering dynamic learning experiences beyond static content.
The Bigger Picture: Where OER Meets GenAI
Wiley’s vision reflects a deeper shift in education: blending open pedagogy with responsive AI-driven learning. It’s not just about access; it’s about giving educators and learners the ability to co-create, remix, and personalize knowledge in real time.
Broader research echoes this trend: scholars explore how generative AI can support the co-creation, updating, and customizing of learning materials while urging care around authenticity and synthesis.
Related Innovations in Open AI for Education
VTutor: An open-source SDK that brings animated AI agents to life with real-time feedback and expressive avatars—promising deeper human-AI interaction.
AI-University (AI‑U): A framework that fine-tunes open-source LLMs using lecture videos, notes, and textbooks, offering tailored course alignment and traceable output to learning materials.
GAIDE: A toolkit that empowers educators to use generative AI for curriculum development, grounded in pedagogical theory and aimed at improving content quality and educator efficiency.
Final Thoughts
David Wiley’s generative textbooks project is less about launching a product and more about launching possibilities. It’s a thought experiment turned demonstration: what if creating powerful, AI-powered learning experiences were as easy as drafting a few sentences?
In this vision:
Educators become prompt architects.
Students become active participants, selecting how they engage.
Learning becomes dynamic, authorable, and—critically—free to access.
That’s the open promise of generative textbooks. It may be rough around the edges now, but the implication is bold: a future where learning tools evolve with educators and learners—rather than being fixed in print.
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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.
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This summer, I did something radical for me: I rested. Fewer obligations, slower mornings, and a little more space to think. Somewhere in that quiet, I read Gabrielle Zevin’s Tomorrow, and Tomorrow, and Tomorrow—a story of friendship, creativity, and the belief that no loss is permanent if you just keep playing.
That idea stuck with me.
As educators, every August is our respawn point. A fresh save file. We reset the level, rebuild the world, and invite our students to play again. Some days will be victories, others spectacular defeats, and plenty will be somewhere in between. But if we keep showing up—together—we can win.
In my first newsletter of the year, I’m blending lessons from Zevin’s novel, Shakespeare’s Macbeth, and Jane McGonigal’s Reality is Broken into a hopeful reminder that “tomorrow” is always coming, and the game is worth playing.
The Eclectic Educator is a free resource for everyone passionate about education and creativity. If you enjoy the content and want to support the newsletter, consider becoming a paid subscriber. Your support helps keep the insights and inspiration coming!
“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.
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.
The Eclectic Educator is a free resource for everyone passionate about education and creativity. If you enjoy the content and want to support the newsletter, consider becoming a paid subscriber. Your support helps keep the insights and inspiration coming!
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.
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.
The Eclectic Educator is a free resource for everyone passionate about education and creativity. If you enjoy the content and want to support the newsletter, consider becoming a paid subscriber. Your support helps keep the insights and inspiration coming!
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.
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
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
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!
The Eclectic Educator is a free resource for everyone passionate about education and creativity. If you enjoy the content and want to support the newsletter, consider becoming a paid subscriber. Your support helps keep the insights and inspiration coming!