Flipping the ‘I Do, We Do, You Do’ Model in Science Class

“When will I ever use this?”

The rest of the class nodded in agreement. We were midway through a traditional lecture on Newton’s laws, and the student’s question, along with their classmates’ collective response, made me pause. I realized my students weren’t disengaged because they didn’t care about science; they were struggling to understand the lesson at hand. They hadn’t been invited to do science.

I’m a consultant and a former educator dedicated to transforming education through student-centered practices. My colleagues and I often observe science classrooms that follow a predictable structure: warm-up, lecture, guided practice, and an assignment. This “I Do, We Do, You Do” model assumes that students must be told what to think first before they apply what they’ve been told. What if we flipped that? In other words, start with a phenomenon or prompt, explore student reasoning, and then offer structured support.

Moving away from lecture-heavy instruction takes time, and it requires teachers to rethink traditional structures, but the payoff is immense. Students are able to better retain knowledge, develop stronger problem-solving skills, and, most important, see themselves as capable scientific thinkers who embrace inquiry and discourse.

Below, I explain how to envision and rethink the science classroom.

Let Students Lead

Imagine stepping into a science classroom where students aren’t passively waiting for information to be delivered. Instead, small groups are gathered around a puzzling image of an astronaut’s glove floating outside the International Space Station. “Why doesn’t it fall to Earth?” one student asks. Another student sketches an idea, while a third student searches through evidence from a previous lesson on forces and motion.

In this science classroom, the teacher activates student thinking before instruction; the teacher doesn’t rush in with answers but instead facilitates a discussion. They ask probing questions so that students grapple with ideas, articulate their thoughts, and explore a variety of possibilities. The lesson unfolds like a scientific investigation, where students build and revise their understanding along the way. This shift, from teacher-centered delivery to student-driven learning, is at the heart of effective science instruction.

Flip the ‘I Do, We Do, You Do’ Model

Many science educators have adopted the gradual release model, where the teacher models first, guides second, and then allows students to practice. There’s a time and place for I Do, We Do, You Do, especially around skill-based science lessons such as using a graduated cylinder for the first time. But in science classrooms, I believe the I Do, We Do, You Do approach can lead to mimicking, rather than thinking. Students may memorize explanations but then struggle to apply them in new situations.

A more student-centered approach is as follows:

• Launch: Introduce a real-world phenomenon or question that sparks curiosity and thinking.
• Explore: Allow students to investigate, discuss, and generate ideas before instruction.
• Discuss: Facilitate conversations that refine students’ thinking and deepen understanding.

When students explore before receiving formal instruction, they connect new information to their existing ideas and experiences. This fosters a sense of ownership over learning.

Try These Science Classroom Scaffolds and Strategies

How do we create classrooms where students take the lead in their learning, as opposed to teachers jumping straight into content delivery? The answer lies in structured strategies like thinking routines, which promote curiosity, collaboration, discourse, and sensemaking.

Thinking routines provide science classroom scaffolds that guide students as they construct and refine their ideas, ultimately ensuring that students meaningfully participate in the learning process in a way that’s observable to both peers and teachers.

Here are some thinking routine examples:

• See, Think, Wonder: Students analyze an image, graph, or model and discuss their observations, interpretations, and questions.
• Quick Draw and Pair-Share: Students sketch their initial understanding of a concept before discussing it with a partner.
• Alike and Different: Students compare and contrast two scientific models, processes, or datasets to identify key patterns.

These routines engage students in science and give them a voice, rather than asking them to be passive observers. For instance, instead of telling students how a plant gains mass through photosynthesis, a teacher might ask, “Where does the mass of a tree come from?” Students sketch their ideas, discuss in small groups, and refine their models as they gather new evidence. The iterative process mirrors how scientists develop theories, which is something teachers can always remind students about if and when they get stuck during a thinking routine.

I also like to remind students that science is more than knowing facts. It’s about making claims, analyzing evidence, and engaging in reasoned argumentation. In fact, discourse and argumentation play a critical role in science.

That said, structured discourse doesn’t unfold automatically. It requires intentional scaffolding. One way to support argumentation is through the Claim, Evidence, Reasoning framework. Students make a claim, support it with data, and justify their reasoning. This structure helps them move beyond gut feelings and toward evidence-based explanations.

To make argumentation more interactive, teachers can employ activities like gallery walks, where students present their scientific arguments on posters and provide feedback on each other’s ideas. As they talk with one another, students begin to see how knowledge in science is constructed: It really requires discussion, critique, and revision.

Though analyzing and interpreting data is often reduced to a simple procedural task, it’s much more than that. In real-world science, data is messy and requires critical thinking. Teachers can engage students in data analysis with the following:

• Slow-Release Graphs: Present data incrementally so that students make predictions and adjust their interpretations as more information becomes available.
• Data Stations: Rotate students through different visual representations (graphs, tables, models) to analyze and compare data in multiple ways.
• Consensus Placemats: Groups of students (up to four at a time) jot down their interpretations of data on the edges of a placement, then collaborate and agree on key takeaways, which they write in the center of the placemat.

These approaches move data analysis from rote calculation to an active, inquiry-driven process.