In many classrooms, Ed Tech like generative AI has quietly altered the emotional climate. Conversations that once centered on learning now carry an undercurrent of suspicion—Who used AI? How much? Was this allowed? The effort to catch students in the act, however well-intentioned, can introduce tensions more disruptive than the technology itself. EdTech Essentials: 12 Strategies for Every Classroom in the Age of AI (2nd Edition) does not dwell in a policing mindset. Instead, Burns focuses on the literacies that make those tensions less central: helping students become capable, discerning participants in digital spaces. While the original edition was not written with AI in mind, the revised edition treats AI as a defining pressure of the moment—using it to reframe enduring questions about teaching rather than allowing it to overshadow them.
At its core, this book is not about tools. It is about judgment. Burns positions educational technology not as a solution in search of a problem, but as a set of skills, habits, and dispositions students must develop if they are to navigate an increasingly complex world with discernment. The twelve “essentials” read less like a checklist and more like a practical philosophy—pedagogy in the foreground, technology in a supporting role. That ordering matters, especially at a moment when AI threatens to dominate instructional conversations. While the revision foregrounds AI, most of the book is devoted to foundational digital learning practices that long predate generative models—and supersede them.
What struck me most is how calmly Burns handles the presence of AI. There is no breathless futurism here, and no reactionary moral panic. AI is treated as another literacy demand—powerful, imperfect, and worthy of scrutiny. The chapters on generating ideas with AI and evaluating digital content with an “AI mindset” stand out not because they offer restrictions, but because they encourage educators to slow down and ask better questions. What does this tool do well? Where does it mislead? How do students learn to notice the difference?
This is where the book quietly—but distinctly—shines. Burns’ emphasis on transfer is grounded in the lived reality of students moving across search engines, shared documents, media platforms, and AI tools that rarely announce their assumptions or limitations. Skills such as navigating online spaces, curating resources, and collaborating digitally are framed not as isolated competencies but as habits of judgment that must hold across contexts. Her use of modeling, think-alouds, and scaffolded exploration is about making invisible decision-making visible—how to choose sources, ignore distractions, question generated content, and organize thinking when access and prior experience vary widely. In a field where digital fluency is often assumed rather than taught, Burns insists that these skills are learned, not inherited.
The book is also grounded in classroom reality. Burns does not assume one-to-one devices, flawless bandwidth, or unlimited planning time. Her examples span grade levels and subject areas, making it easy to imagine these strategies living inside real lessons rather than hovering above them. Paired with consistent connections to ISTE standards, this practicality makes EdTech Essentials useful not only for classroom teachers, but also for instructional coaches and school leaders seeking coherence between vision and practice.
The design strengthens the message. The second edition integrates AI not by overhauling the text, but by extending it—adding focused chapters while keeping the broader framework intact. The appendices reinforce this restraint: planning tools, chapter summaries, a study guide for collective learning, and a carefully framed set of chatbot prompts that emphasizes review and judgment. Even the tool lists are organized by instructional purpose rather than novelty. This is a book built to be revisited.
What distinguishes EdTech Essentials from many recent books on AI and teaching is that same steadiness. After a wave of titles that catalog tools, debate detection, or speculate about the future of assessment, Burns’ approach feels intentionally stable. Rather than asking educators to redesign coursework with every new model release, she grounds her guidance in enduring practices—navigation, evaluation, collaboration, creation, and transfer. AI enters the conversation not as a disruption to outpace, but as one more context in which these skills must be taught.
One implication of Burns’ approach is that it treats trust as a design problem rather than a behavioral one. When students are explicitly taught how to navigate, evaluate, and create responsibly in digital spaces, the need for constant suspicion diminishes. Education works best when we stop trying to catch students doing the wrong thing and start teaching them how to do the right thing well. In an era shaped by AI, that reframing may be the most essential strategy of all.
