By Sarah Zerwin, CCIRA Conference Featured Speaker
“What do you notice?’
This is where my instruction starts, with a simple invitation to my students to point out the small things they notice in any kind of text. From this low-stakes starting place, students build their own meaning out of complexity following a three step meaning making process.
Step one is to Start Small with what you notice.
Step two is to Seek Connections to grow your thinking.
Step three is to Take Action by deciding what you’ve figured out and do something with it.
The Original Thought Annotation (OTA) is the most frequent Step One strategy in my classroom. On a humble sticky note, students jot down a specific text detail that grabbed their attention and then a sentence or two about what they think about it.
To Seek Connections, my students use rambling, rough writing to explore connections across a few separate OTAs, and they also use conversation with their classmates to explore and build their ideas.
Step Three looks different depending on the class. My IB English juniors take all the ideas they’ve built about our shared texts in Steps One and Two and use that thinking as the content of their official IB assessments. My sophomores take the thinking they’ve built to help them decide what they want to write about in informal weekly timed writings and in process papers toward the end of each unit.
We loop through these three steps again and again and again, offering students repeated practice in a meaning making process that shows them how to make sense of anything complex. (See my book, Step Aside: Strategies for Student-Driven Learning with Secondary Readers and Writers, for many more details about the Three Step Meaning Making Process.)
My Gmail inbox now asks if I want it to summarize an email thread for me. I have a teaching-focused AI tool at school I can use to generate instructional plans, emails to parents, and multiple choice reading comprehension questions. I can put a sizable collection of student responses into a chatbot and ask it to discern the top five themes in my students’ thinking, instantly completing a qualitative data analysis task that would take me much longer than the chatbot’s few seconds. In short, we have new tools that can save us significant time if we choose to use them, and so do our students. We and they may choose to use those tools even when we really should do the thinking on our own. It’s more critical than ever that we teach our students concrete strategies for figuring things out, using their own words to navigate and explore their thinking.
The temptation to offload thinking work to the robot brains in AI chatbots is real. Our students are hungry for guidance to help think through it. I want to create reasons in my students’ minds that will combat the temptation. After reading this open letter from a high school student to ChatGPT, my students now might think, using the chatbot might make me less creative. From reading this op-ed from a college professor, my students might stop and think, using the chatbot might get in the way of me developing some really important foundational thinking skills.
But even with these reasons floating around in their thinking, they still might opt to offload the hard thinking work to a chatbot, especially if they’re not sure where to start. That’s the impact of a simple strategy that yields rich, student-generated thinking. A strategy they can use when they’re trying to make sense of any complexity, like a conversation they have with someone or a news report they read or see. This meaning making work is not just for poems and novels in classrooms. The reading and writing work we do in ELA classrooms is skill building for life.
A simple three step meaning making process teaches students what to do on their own, without the AI crutch.
The challenge is convincing students that they can make sense of complexity and that what seems like extra work up against the lightning speed of a chatbot is worth their time.
Our students are hungry for our guidance. Let’s offer it to them. Not just guidance about new and evolving AI tools, but also what to do instead of asking the chatbot to make sense of things for them.
It’s simple. Start here: What do you notice?
Sarah M. Zerwin teaches language arts at Fairview High School in Boulder, Colorado. She is the author of Point-Less: An English Teacher’s Guide to More Meaningful Grading and Step Aside: Strategies for Student-Driven Learning with Secondary Readers and Writers. See more at sarahmzerwin.com.








