Over the past year, I’ve led professional development sessions with computer science teachers across the country. Regardless of the session’s focus, teachers consistently voice concerns about AI in their classrooms. I’ve found myself balancing a conversation that acknowledges these fears while encouraging teachers to embrace this new era, ensuring that neither they nor their students are left behind.
Initially, I wasn’t sure how to approach these discussions. But then, I had a pivotal experience that changed my perspective.
When I first left the classroom, it was for an assessment-writing role at a K-12 science curriculum company. I was creating multiple-choice questions for subjects ranging from kindergarten science to high school physics. And I like to think I was good at it. But writing effective questions is time-consuming, and crafting high-quality assessments can be a daunting task.
With my background in this area, I have often revisited those skills to shape and develop computer science assessments at Ellipsis. I still have a knack for multiple-choice questions, but I recognized that it wasn’t the best use of my time. So, with AI making its way into education, I decided to give it a try. I uploaded the relevant standards to an AI tool and prompted it to generate 25 multiple-choice questions at a 4th-grade reading level.
And that’s when I had what can only be described as a moment of existential crisis. Generative AI accomplished in five seconds what would have taken me two days. I let out a deep sigh, questioned my existence, and called an old assessment-writing colleague. He asked, “Well, were the questions any good?” I had to admit that about half met our criteria for quality. The others needed to be tossed or significantly reworked. Then he reminded me, “You are still the expert in assessment; AI cannot take that away from you.”
That conversation was a turning point. It’s a story I now share with teachers when we discuss AI in the classroom.
Before AI, I balanced the roles of content creator and content evaluator. The time and energy spent on creating content often left me with little bandwidth for careful critique. But with AI, I found a shift—AI took over some of the laborious creation tasks, leaving me more space to critically evaluate its output. This shift has proven to be surprisingly empowering.
The lesson I share with teachers is this: AI invites us to focus on higher-order thinking. It allows us to move beyond the time-consuming tasks and instead channel our expertise into being evaluators, critics, and synthesizers. It shifts our energy from creating to improving, from producing to refining.
To illustrate this, I often use a generative AI tool in workshops to create a simple HTML code outline for a website about a storybook character. Within seconds, the AI generates a basic template. I then ask teachers to review the code, identify areas for improvement, and make edits. Together, we become the critics, refining and enhancing the AI’s work.
As educators, we can choose to see AI as either a challenge or an opportunity. Rather than fearing that AI will replace our skills, we can embrace its potential to elevate our roles as critical thinkers and expert evaluators. By leveraging AI in the computer science classroom, we can move beyond the grind of content creation and focus on deeper analysis, creativity, and mentorship. It’s not about relinquishing our expertise; it’s about using AI to sharpen it and inspire our students to do the same. Together, we can shape a future where both teachers and students thrive alongside the very tools that once seemed daunting.
Explore free resources from Ellipsis Education, including computer science lesson plans and pre-recorded professional development webinars covering a range of computer science topics.
