Flipped Labs? Yes!
During our research interviews while developing Pivot Interactives, many high school teachers told us that labs -- especially inquiry-based labs -- take a lot of classroom instructional time. For AP Physics teachers, the instructional time to conduct inquiry labs competes with other needed instruction, like problem-solving and practicing written solutions.
We’re developing a method using Pivot Interactives that retains the open-ended discovery aspects of inquiry-based labs, and focuses instructional time on the parts students find most challenging: experimental design and data analysis/model discovery.
When doing traditional apparatus-based inquiry labs in our classes, we’ve tried to speed the process by having students work on parts of the lab outside of class. Students work on experimental design before the lab, collect data in class on the day of the lab, and then work at home on data analysis and interpretation outside of class after the lab. But we’ve noticed that experimental design and data analysis are often the most challenging for students, and are where students benefit most from classroom discussions.
With flipped labs, we reverse which parts of the lab are done in class and which parts are done outside of class. Students use classroom discourse and collaboration to develop an experimental design. They make measurements and graphs individually outside of class using Pivot Interactives. The next day in class, students have a data set and graph that they are ready to compare with their peers', looking for similarities and differences, and discovering the underlying model. This approach lets students work together on the most difficult parts of the lab, but use their own data in the process.
An example of a Pivot Interactives Flipped Lab is our new Newton's Second Law lab: Exploring the Cause of Acceleration -- Flipped Lab version, written by Pivot Interactives content developer Colleen Nyeggen @ColleenNyeggen. This is a complex lab, where students discover two relationships: acceleration vs force, and acceleration vs mass, and then combine them into one model that relates all three quantities. The Pivot Interactives version allows students to use videos of an air-track glider driven by a battery-powered turbine (like a fancy fan cart). Students can independently vary the turbine force, and glider mass. They measure the turbine force with a spring scale, and make displacement and time measurements to calculate the resulting acceleration.
On the first day of the lab, we begin with a kinesthetic learning experience that allows students to understand the model we are seeking. For this lab, students do a version of Frank Noschese's Bowling Ball Activity (we use billiard balls and coffee stirrer sticks), and use carts, spring scales, and weights to qualitatively explore the relationship between forces and acceleration. Students explore the parameters at play: force, mass, and acceleration, and experience how increasing the force or increasing the mass seem to affect the acceleration of a cart.
Next, they begin to explore the videos in the Pivot Interactives activity that allows them to precisely vary the force and mass on a turbine glider, and measure the resulting acceleration. One advantage to the turbine glider compared to the modified Atwood's machine is that students can directly measure the force exerted by the turbine. Students work in collaboration to plan the experiment, discussing what and how to measure, deciding what relationships they seek, choosing independent and dependent variables, and setting up their data table. When students leave class, they have an experimental design completed and a plan for how they'll collect their data.
That night for homework, every student uses the Pivot Interactives videos and data table to collect their data, and create their graph(s). In addition, we often have students submit key aspects of the data, such as the slope of a linearized graph, via a google form so the class can look for trends and patterns among aggregated student data. For this lab, students submit the slope of their a vs F graph, as well as the glider mass they used. As teachers, we can evaluate student work within each student's Pivot Interactive assignment and provide feedback at any point during the process. We've noticed that when students work individually making measurements and filling in a data tables, they gain a sense of ownership of their data.
The next day in class, students are ready to analyze their data with the goal of developing a mathematical model that underlies their data. Through white-boarding and class discourse, students compare their data with their peers' data to look for similarities, differences, and patterns. A key moment in this process comes when students discuss the aggregated class data which clearly shows the relationship between the slope of the a vs Fgraph and the mass of the glider students selected: students who selected a higher glider mass have a vs F graphs with lower slope values. This allows students to hypothesize that the constant of proportionality for the a vs F relationship is the inverse of the glider mass. To verify this, students design a second experiment where they hold the turbine force constant and vary the glider mass. With this experimental design in hand, students collect another data set as homework.
On the final day of the lab, students compare their new results that confirm the inverse relationship between acceleration and mass. Looking at aggregated class data, they quickly see that the proportionality constant for the linearized a vs mgraph is the turbine force. Now they have two data sets that confirm the same relationship: a=F/m.
We like to ask students to explore the limitations of the model they discovered. For example, students will notice that the proportionality constants they got for the a vs Frelationship, and linearized the a vs mrelationship are not exactly the same as 1/massand F, respectively. Rather than attributing this to poor measurement or [shudder] human error, students will see that every student has the same kind of deviation. The proportionality constant for the linearized a vs mrelationship for all students' data will show a value slightly lessthan the measured force. Similarly, the mass value students get from the inverse of the proportionality constant on their a vs Frelationship is slightly morethan the actual glider mass. In both cases this is consistent with the low, but clearly noticeable, friction on the air track.
Finally, students can use other Pivot Interactives activities, like the Rocket Cart or Turbine Glider Teststo test their results. In both cases, students can verify the effectiveness of Newton's Second Law.
We're seeing that Pivot Interactives allows added flexibility and a new mode of instruction that offers different strengths than traditional apparatus based labs. We'll update this post as we learn more.