In a previous lesson students conducted a reaction rate experiment they designed. Today, students will analyze data they gathered from that reaction rate experiment in order to draw a conclusion. To do this, they calculate averages and percent yield, and they compare their data with one other group and to the trend their hypothesis predicted. They then use this data analysis to draw a conclusion.
This lesson aligns to the NGSS Disciplinary Core Idea of HS-PS1-5: Apply scientific principles and evidence to provide an explanation about the effects of changing the temperature or concentration of the reacting particles on the rate at which a reaction occurs because in this lesson they will take the raw data they gathered and turn it into manageable pieces of information that will be the evidence they use to describe how one of these variables affects reaction rate.
It aligns to the NGSS Practice of the Scientist of Analyzing and interpreting data by giving students the chance to do what scientists do with large amounts of data—they synthesize their data and interpret it. Students will do this with their experimental data. It also aligns to the Practice of Engaging in argument from evidence by supporting students with the task of making an argument about how reaction rate was affected, and how confident they should feel about their conclusion.
It aligns to the NGSS Crosscutting Concept of Stability and change because this lesson highlights the fact that rates of change can be quantified over very periods of time.
In terms of prior knowledge or skills, students will benefit most from this exact lesson if they have conducted the experiment and gathered data. However, it would be possible to replicate this lesson using other data.
There are no special materials needed for this lesson.
Do Now: Students start class by finding the amount of CO2 that each of the reactions yielded in the sample data. They do this by subtracting the mass at time 0 from the mass at 180 s.
I reason that this is a good way to start class because today students will be crunching their numbers, and this is a good first step in the process.
Activator: After I take attendance I walk around the class room to find a student who has completed this task. I then ask that student to project her work so that students can compare answers. Having the correct answers is important because making sense of the rest of the work depends on these answers being correct. I have sense of what the data analysis for the sample data looks like with this sample data answer key.
Mini-lesson: I begin my lesson by noting that the work we will do today is the work that scientists do. After collecting large amounts of data, they must make sense of it by using statistics and by summarizing large amounts of data into manageable pieces of information and draw data-based conclusions.
I then explain how to make sense of the larger data set by using the table on the second page, which corresponds to the data section of their Reaction Rates Experiment Graphic Organizer. For the “Average CO2 output for whole time” column students will need to calculate that average by adding up the three values they have for the first variation of their variable (for example, the same temperatures) and divide by 3. For the “Average CO2 output for first minute” column, they will focus on the differences for the first minute following a similar procedure. For the “Average Percent Yield” column, students will need to divide their total amount of CO2 they produced by the theoretical yield they gathered from their stoichiometry calculations.
I note that they will get this same data from a group that conducted an experiment with the same independent variable (temperature, concentration, or surface area.
Finally, I note that now students have a number of pieces of evidence to evaluate going into the conclusion and discussion section of their lab report. These include the average total CO2 they and another group produced, the amount of CO2 they and another group’s reactions produced in the first minute, and the percent yields from each group. They can use this information in their conclusion to evaluate how their independent variable affected the reaction rate of the experiment they conducted.
This instructional choice reflects my desire to help students analyze and draw conclusions from data they generate. By giving students 3 pieces of evidence, my expectation is that all students should be able to evaluate their data.
Student Activity: Once I have answered questions students have I let them get to work on crunching the numbers. I walk around the room answering questions and observing student work. Once most students have had a chance to process their own data and get data from another lab group, I bring everyone together for a catch and release.
Catch and Release Opportunities: This is a good time to review the conclusion questions with students to see if they have any questions. I note that the first question can only be answered effectively if the data clearly shows a relationship. We look at the sample data, and I ask students how they feel about the data.
Does it show a pattern? Students should notice that more gas was evolved from the higher molarities. I ask them to also look at the data after one minute. Again, there seems to be a pattern. Does the pattern agree with the hypothesis? Yes it does. Finally, I remind students to compare their data with another group’s data. If that too is a match, then there is pretty strong evidence of the trend. If not, there is still strong evidence if the other two pieces match up. The other group may have made a measurement error or some other error when they generated their data. I note that this analysis covers the first 3 conclusion questions.
Finally, I draw their attention to a special question that relates to their research topic to see if they can apply what they learned about their variable to a related scenario.
Stopping class to discuss all of this is important because it further contextualizes what they have been doing and the discussion will allow them to finish their project.
In this first video, a student is looking at data. I love this video because it shows a student struggling to make sense out of his data. His experiment looked at surface area’s effect on reaction rate. He has some data that shows an increase in mass when the reaction should show a decrease; this is likely due to measurement error. While I wish I had caught this error sooner so they would have time to do additional trial, the way he handles the problem by owning it and noting that it is problematic is exactly what practicing scientists do.
In the second video, I try to help the student to see that while there was very little reaction with the pebbles, there actually was a significant decrease in mass associated with the reaction that used powder relative to the pebbles, and that this is in keeping with the hypothesis that larger surface areas lead to higher reaction rates.
To wrap this lesson up I entertain any questions students have and then I ask a few students to share what they are thinking with regards to how well they are able to answer their experimental question about reaction rate.
Ending class this way allows me one more chance to check in with students before they finish the assignment for homework, and it gives everyone a chance to listen to or be part of a conversation about what makes for a strong or weak conclusion in science.
Next year I plan to spend more time in helping students assess the results of their experiments so that they can make better arguments about how confident they are in their data. However, many students were able to do fairly well with this task. I used the LT 2 Reaction Rates Experiment Grading Sheet to evaluate student work. This student's student lab report and completed rubric are a good sample of how this unit ends.