Learning abstract concepts is difficult because our students are beginners in many cases. This means they primarily understand new ideas in the context of what they already know, which is usually concrete. To build a robust “schema” (a mental structure of organized knowledge), students need more than a definition; they need to see the concept in action through examples vs. non examples. With this said, it is now ever been easier to create examples vs. non examples using Gemini’s Nano Banana Pro image generator that is associated with Gemini 3. In this post, you’ll see how to do this to support your instruction.
Tag Archives: instruction
From the Sidelines to the Shoulder: Using Co-Teaching as the Engine for Instructional Coaching
The Gradual Release of Responsibility (“I do, We do, You do”) is a powerful framework for instructional coaching, and it can be delivered directly through co-teaching strategies. Instead of a coach modeling and then simply observing, the crucial “We do” phase becomes a hands-on, collaborative partnership. This post explores how to use specific co-teaching models as the bridge from “I do” to “You do.” I share a single-session example of supporting a teacher with multilingual learners, moving from my “I do” (model) to our “We do” (“Team Teaching”) and finally to their “You do” (with me in a “One Teach, One Support” role), all within a single lesson.
From Digital Consumers to Digital Pedagogues: A Framework for Moving Teachers from Digital Consumers to Tech-Enabled Pedagogues
In my work with teachers, I’ve seen firsthand a significant challenge that has only accelerated in our tech-saturated world: the gap between how pre-service teachers use technology and their capacity to teach with it. This is the Consumer-to-Pedagogue Gap, and it is one of the most critical hurdles we must overcome in modern teacher preparation and on-going professional development and coaching as they progress forward in their careers.
This post outlines a framework to bridge this gap, moving teacher candidates from passive digital consumers to active, tech-enabled pedagogues. The central thesis is straightforward: we must replace passive observation with a system of structured, low-stakes rehearsal. This over time will improve instruction as well as the use of technology when integrated together.
This system is not built on intuition; it is grounded in established learning science, specifically the Technological Pedagogical Content Knowledge (TPACK) framework and Cognitive Load Theory (CLT). These are the foundational lenses I advocate for in all effective instructional design.
AI Agent Advancements: Google Lens (aka Homework Helper) and Comet Browser
As educators, we’ve navigated the shift from chalkboards to smartboards, from calculators to laptops. But the change barreling towards us now is different. It’s not just a new tool; it’s a new kind of actor in the learning process. I’m talking about AI-powered tools like Google Lens and the emerging class of AI-agent browsers, such as Perplexity’s Comet Browser. These technologies are fundamentally reshaping what it means to “do work” and forcing us to confront a critical reality: we can no longer guarantee the authenticity of any work done outside our direct supervision. As a result, what does this mean for asynchronous online learning and completing graded work outside of traditional in-person classes?
Webinar – Innovative Co-Teaching: Strategies and Tools for the Modern Classroom
Last week, my co-author Dr. Karge and I had the opportunity to share ideas from our book Co-Teaching Evolved in an edWebinar with educators from around the world. It was exciting to dive into the 11 research-backed co-teaching strategies, from One Teach, One Support to Team Teaching, and show how they can flex across grade levels and content areas. This is a fantastic webinar that provides an overarching themes of co-teaching and how to implement some of its strategies across classrooms and schools.
Using AI to Support Interleaving & Spaced Practice and Retrieval in Unit Planning
As teachers, we are constantly seeking ways to make learning more durable and meaningful for our students. We want them to not just memorize facts for a test, but to fully understand and retain what they’ve learned over the long haul. Cognitive science offers a powerful toolkit of strategies to achieve this, and with theContinueContinue reading “Using AI to Support Interleaving & Spaced Practice and Retrieval in Unit Planning”
EdTech Leadership in the Age of AI: What Matters Most When Everything is Changing
My coffee is still warm when the first alert comes in. A teacher cannot access Canvas, and their students are stuck at the login screen. I walk the teacher through the SSO steps, confirm access, and move on. By midmorning, I have visited classrooms, supported teachers with technology integration, and observed lessons to plan follow-up coaching. After that, I sit with our engineers to review system performance, troubleshoot issues, and test several EdTech tools and updates planned for release.
At two o’clock, there are three messages on LinkedIn about a new AI tool that promises to transform learning. I scan one, note the potential and the hype, and return to the work I already committed to do. The afternoon goes to email, planning professional learning, and reviewing the week ahead.
Sound familiar?
For many of us in EdTech and instructional leadership, this mix of strategic and immediate work is the norm. Some hours go to multi-year plans, budgets, and compliance. Others are dedicated to making sure one specific app works for one teacher so students can keep learning. The pace makes it easy to lose focus when the day is packed and many things are going on simultaneously. I return to a single question: how do people learn, and how can instruction and technology work together to support that? If we cannot answer that question, systems, budgets, and tools will have little impact.
This post shares how I connect what we know about learning with the daily realities of leading technology and instructional change in schools. I will describe several major themes and then provide a summary of the next steps to help you further reflect upon your leadership and programs.
Creating AI Agent Safeguards (for now) through Pragmatic Instructional Design to Deliver Assignments and Assessments
As you prepare your syllabus for the upcoming semester, a question I’ve explored before looms large. In a previous post, “The Death of the LMS in Higher Ed,” I argued that its role as a simple repository for assignments is becoming obsolete. With AI agents now ubiquitous, how do we prevent the LMS from becoming a mere drop-box for bot-generated work from an autonomous AI Agent?
The solution isn’t to fully abandon the LMS (for now), but to evolve its purpose and create humanizing instructional barriers in the tasks and assessments we deliver to our students. This post presents a few practical strategies (I am implementing this term in my own graduate-level course) to revitalize our courses by shifting the focus from the final product, which AI can generate in seconds, to the learning process, which it cannot. This is going to my attempt to defend against students utilizing AI Agents. While I know this may not be one-hundred percent effective, I do have a hunch it will mitigate AI Agents to a degree, at least for the time being, this semester.
Using AI to Build Powerful Retrieval Practice Activities to Supercharge Student Learning Opportunities
The “testing effect,” a term championed by researchers like Roediger and Karpicke, demonstrates that every time a student actively recalls information, they strengthen the neural pathways associated with it. This effortful retrieval tells the brain that the information is important and makes it easier to access in the future. Ultimately, over time, if students are able to actively recall correctly, this means they likelihood of them learning the content, is much higher. Although the challenge for teachers has always been the time it takes to create a rich variety of material, such as flashcards, practice tests, and quizzes, that facilitate this process.
With powerful AI tools, we can now create engaging, interactive retrieval practice activities in minutes. Tools like Gemini, Claude, and ChatGPT have built-in “Canvas” features that can generate the code for these resources, and you don’t need to be a coding expert to use them.
Instructional Coaches Need to Know How Memory Works – And It’s Not a Muscle
I often hear memory described as a muscle—something that gets stronger the more you “work it out.” While the sentiment is well-intentioned, it’s a misleading metaphor. Our memory isn’t a single entity that we can simply beef up through brute force. It’s a complex system, and for instructional coaches, understanding its nuances is a game-changer for helping teachers truly embed new and refined strategies into their practice as well as teach the teachers we are coaching how learning happens.
5 Ways Agentic AI Can Transform Your Teaching Workflow
What if you had a personalized assistant who knew your school’s handbook, understood your instructional philosophy, and could help you design lessons tailored to your students’ needs? This isn’t a glimpse into a far-off future; it’s the reality of what AI agents can offer teachers today.
Boost Student Learning with Interactive Worked Examples: Thanks to the Canvas Feature in Gemini, ChatGPT, and Claude
Picture this: you can provide interactive, step-by-step worked examples for just about anything – math problems, ELA sentence structures, science processes, you name it. And here’s the best part: you absolutely do not need to be a coding expert to pull this off.
Scaling Instructional Coaching: Overcoming Key Challenges
While the evidence for instructional coaching’s effectiveness is compelling, translating this potential into widespread impact presents significant challenges, particularly when attempting to scale programs across schools or districts. A primary concern, identified by Kraft et al. (2018), is the potential dilution of quality as coaching programs expand. The personalization and strong relationships that underpin effectiveContinueContinue reading “Scaling Instructional Coaching: Overcoming Key Challenges”
Aspire to Lead Podcast Appearance: Revolutionizing Collaboration in Schools Through Inclusion
About a month ago, I had the pleasure of joining the Aspire to Lead podcast to discuss co-teaching and instructional coaching. Episode Description: In this episode of Aspire to Lead, Dr. Matthew Rhoads, author of Co-Teaching Evolved and Crush It from the Start: 25 Tips for Instructional Coaches and Leaders, joins me to explore how artificial intelligence is reshapingContinueContinue reading “Aspire to Lead Podcast Appearance: Revolutionizing Collaboration in Schools Through Inclusion”
Digital Learning Today Podcast Appearance: Episode 66 – Crush it From the Start – Top Tips for Instructional Coaches
This podcast episode emphasizes the significance of understanding cognitive science, effective coaching strategies, and the integration of technology in education. The conversation also touches on the challenges faced by coaches and the need for reflection and balance in their professional lives.
Navigating the Present and Future of Education 