Teaching Sequence

Work through this resource material in the following sequence:

10 minutes – Part A: Preparation Phase
20 minutes – Part B: Experimentation Phase
20 minutes – Part C: Analysis Phase
5 minutes – Reflection

Lesson preparation: The first clip in this lesson is on Enhance TV. Enhance TV is a subscription service. Some teachers will have access through their school or employer membership. Please check with your school librarian, principal or IT department to see if you already have access to Enhance TV, or to request to join.

Part A: Preparation Phase

Step 1.

Play the DIY skipping challenge to get students thinking about the different variables impacting their skipping.

DIY Skipping Challenge (https://www.enhancetv.com.au/index.php/t/aa0fccd471/scope-diy-skipping-challenge)

Step 2.

Explain to students that a dependent variable is something that changes due to the independent variable. It 'depends' on other factors. This is the thing we are trying to figure out, or measure, in our experiment. In this case, it is how ‘successfully’ we can skip.

Ask students to define what ‘successful’ skipping actually looks like. Be specific. Success has to be quantifiable so that it can be measured during the experiment, otherwise there is no way to compare data at the end. Is success the number of jumps: the more the better? Is it the number of mistakes, with fewer mistakes indicating ‘better’ skipping?

Step 3.

Explain to students that an independent variable is the thing that we change during an experiment, to see how it impacts the dependent variable. This is the thing we think will make a difference to our skipping success. In this case, the independent variables are rope length, surface type and different skipping techniques.

Only one variable should change between tests, otherwise we won’t be able to be certain which independent variable is impacting the result (dependent variable). For example, if you are testing the length of rope, always skip on the same surface each time.

Step 4.

Explain to students that confounding variables are things besides the independent variable that can impact the result. We want to eliminate these as much as possible so that we are only testing one independent variable at a time, but often these confounding variables get in the way despite our best efforts, hence they ‘confound’ or muddy the result. In this case, it could be things like the wind changing between tests, or the different skipping action individuals have, or how tired they are.

Lead students to the understanding that it is almost impossible to run experiments in total isolation so that the conditions are exactly the same every time. One way this can be counteracted is to find the average of many experiments. Lead students to the idea that collating data from the whole class might give you better insight into the impact of the specific variables you are trying to measure.

Step 5.

Independently, using the Experiment Record Sheet, invite students to hypothesise which variables will yield the most successful results.

Part B: Experimentation Phase

Step 1.

Split students into pairs or invite students to choose their own partner.

Step 2.

Students collect a single short rope between them and find a space outside to skip.

Step 3.

Students independently conduct the experiments as listed on the Student Worksheet. One student skips for 60 seconds under the condition of a variable. The other student manages the stopwatch and records the number of skips.

Step 4.

The student who was skipping rates out of 10 how easy or difficult it was to skip under the conditions of that variable.

Step 5.

Students swap roles and repeat the experiment and data collection. This allows students a short rest between skipping sessions as they record data for their partner.

Step 6.

Students continue until they have tested their skipping under the conditions of all the different variables.
Remember: Only one variable should change between tests. Otherwise, something other than the variable being tested might influence the results.

For example: if you are testing how the different lengths of rope impact your skipping, always skip on the same surface each time.

Step 7.

As a class, you might agree upon some additional variables you want to test. Add these to the bottom of the Experiment Record Sheet. Make sure there are at least three different conditions or levels to test so that you get an appropriate range of data.

Step 8.

Towards the end of the session, students will need to join up with another pair to conduct the experiments that require the use of the long rope.

Part C: Analysis Phase

Step 1.

Ask students to add their data to a collated table on the board or projector. You can use a large version of the Experiment Record Sheet to help organise your results.

Step 2.

To find the averages for each test, add all of the results together, then divide by the number of students in the class.

For example, three students record their number of jumps as 45, 50 and 55.

(45 + 50 + 55) / 3 = 50

Therefore, the average number of jumps under this variable is 50.

Finding the average mitigates many of the confounding variables which might negatively impact your results.

Step 3.

As a class, facilitate a discussion about the data. Do the experiments reveal any conclusive results? That is, can we conclusively say which variables lead to more successful skipping? Or does there not appear to be much difference between the variables?

Step 4.

Discuss whether there are any reasons to doubt your findings. Lead students to the idea that there may have been slight differences in the way each pair conducted the experiment. For example, some students may have swung the rope differently, or been jumping higher, making their rotations slower. There may also have been some confounding variables that could have impacted the results, such as the wind.

Step 5.

Draw students' attention to the ‘Ease of Skipping’ score column. Discuss whether this is a useful piece of data for supporting your conclusion about the most successful variable? Why or why not?

Step 6.

Explain the difference between quantitative and qualitative data. Some things can be measured in hard numbers, such as the number of jumps made. That is, this value is a quantity of something. Other things rely more on individual experience and a subjective viewpoint, such as how good or bad an experience someone had. That is, this value is trying to judge the quality of something. But can we really do this in a fair way? Everyone has their own unique perspective, even when reacting to exactly the same thing, which makes a comparison of this kind of data difficult.

Step 7.

Students choose one set of variables. Independently, they plot the averages for this variable on a column graph. The X-axis should show the variable. The Y-axis should be a numerical scale. Use a blue column for the number of jumps and a red column for the number of mistakes.

Reflection

Invite students to consider what they would change about the Experimentation Phase if they were to conduct it again in the future? For example, maybe it was too windy outside and they think working in an enclosed space would give different results. Or maybe the experiments were run straight after a PE lesson and their legs were tired.

On their worksheets, students can work in pairs to write down one thing that went well, one challenge they faced and one thing they would do differently.

Differentiated Learning

Extension - Fatigue is a variable that has a massive impact on these kinds of experiments and is worth investigating all on its own. After discussing results (or as another lesson) conduct another experiment where students skip for 30 seconds, with a 10-second break in-between. Use these questions as a prompt for a discussion about the validity of your other test results.

What trend occurred after three attempts?
Could there actually be an increase in skill level after students have warmed up a bit?
What trend occurred after ten attempts?
How does this impact our thinking on the results data we have produced? Are the experiments conducted towards the end of the session any more or less valid?

Provisions for Learning Support - Be aware that not all of your students will be confident or capable skippers. Try to alter the experiments to involve students as much as possible, rather than relegating some students to the role of data collectors.

For example, how quickly can you do a 10m sprint on concrete, asphalt and grass surfaces? Or, how many times can you bounce a basketball, tennis ball and football in 30 seconds?

Teacher Reflection

Take this opportunity to reflect on your own teaching:

What did you learn about your teaching practice today?
What worked well?
What didn't work so well?
What would you share?
Where to next?
How are you going to get there?

Jump Rope For Heart - Skipping Experiments

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