This guide grew out of real conversations with teachers. Many of you have shared stories about experimenting with AI tools in your classrooms, trying to make lesson planning easier, or looking for ways to spark student engagement. What stood out most from these conversations was a common challenge: teachers wanted guidance that made sense for real classrooms, not just theoretical overviews or tech marketing talk.
That’s what inspired me to write Teaching with AI, a practical, research-backed guide written from the perspective of an educator who understands what teaching looks like day to day.
The book begins with the foundations of AI literacy, unpacking what it truly means for teachers and students to understand and use AI responsibly. It also connects AI literacy with critical thinking, helping teachers design lessons that push students to question, analyze, and reflect on how AI systems generate information.
The next section explores the major instructional frameworks: SAMR, Bloom’s Revised Taxonomy, TPACK, and Webb’s Depth of Knowledge, and shows how each can anchor meaningful AI integration. I used familiar classroom examples to help teachers see what AI use might look like at different levels of depth and complexity.
From there, the focus turns to practice: lesson planning with AI, evaluating tools, and creating prompts that lead to better results. I also included a large section on AI tools for teachers, featuring platforms and applications that support everything from differentiation and assessment to creative content generation.
The final chapters invite reflection. They explore how AI can support teacher professional development, including ways to use AI as a personal learning partner, a research assistant, and a tool for reflective practice. I also shared a wide variety of trusted resources and online tools that teachers can start using right away.
I concluded the book with a chapter on AI ethics, where I discussed the key concerns teachers face (e.g., data privacy, academic integrity, bias, equity, and student wellbeing) and suggested practical approaches for handling them with transparency and care.
Throughout the book, I kept the language accessible and classroom-friendly. I stayed away from technical jargon and dense theoretical explanations. I also avoided long detours into the history of AI or generative AI. My focus was on practicality: ideas, tools, and examples teachers can apply immediately.
Teaching with AI is the product of collaboration, curiosity, and shared learning. It’s built for teachers who want to understand AI, not just use it. I hope it serves as both a companion and a catalyst as we all continue exploring what AI can mean for teaching and learning.
