Planning an "Intro to lab work" lab?

[nashed]

O.K. here's the deal, a friend and I are taking a physics teaching methods course as an elective, as a part of the requirement we were asked to plan and execute (teach) a one hour lab on kinematics ( specifically ballistic movement), the Tracker program and error estimation.

We decided on taking a differing route to the standard and to use this lab to teach about experiment integrity, that is we want to teach about possible factors for errors/inaccuracy in experiments such as analyzing a video but having the reference object and the tracked object in different planes (different distances from the camera), or using an object which is severely affected by air friction to measure the acceleration due to gravity without taking the air friction into account, basically we want to teach about robust experimental setups and how to check for factors to hinder this robustness.

After preparing the lesson plan and preparing some experimental setups in which we included some of the above mentioned factors as examples we found out that our criteria for a bad experiment is deviation from the accepted value ( i.e. g =14 while the accepted value is g = 9.8 give or take), now this is a bad criterion because in this lesson we don't really care about the numerical result, we care about the experiment's robustness and if we can't find a better criterion our lesson will fall apart, so her I am asking for help after a long time of inactivity, can someone point me in the right direction?

 

[ZapperZ]

I don't understand.

Without having a "benchmark", in this case, getting the value of g out of your experiment, how are you to know that you have either a robust or a poorly-designed experiment? What other benchmark is there?

Zz.

 

[TeethWhitener]

I don't understand.

Without having a "benchmark", in this case, getting the value of g out of your experiment, how are you to know that you have either a robust or a poorly-designed experiment? What other benchmark is there?

Zz.

Maybe "robust" is the key here. If two students do the experiment and get wildly different values for g, then it is likely that there is a difference in their experimental setups. You could (as a very simple example) have different groups of students measure g using lead weights, ping pong balls, and feathers, and then have them compare their results at the end and brainstorm on how their experiments can be brought into agreement. The advantage of an approach like this is that that this actually happens in scientific research. Different groups come to different conclusions based on their own data, and through presenting and discussing their results they often find that their experiments are different in subtle ways that they hadn't considered. This leads them to a richer picture of what science is actually going on.

 

[ZapperZ]

Maybe "robust" is the key here. If two students do the experiment and get wildly different values for g, then it is likely that there is a difference in their experimental setups. You could (as a very simple example) have different groups of students measure g using lead weights, ping pong balls, and feathers, and then have them compare their results at the end and brainstorm on how their experiments can be brought into agreement. The advantage of an approach like this is that that this actually happens in scientific research. Different groups come to different conclusions based on their own data, and through presenting and discussing their results they often find that their experiments are different in subtle ways that they hadn't considered. This leads them to a richer picture of what science is actually going on.

But you still have to measure g and compare. From what I understood, the OP did not want to go all the way to do that.

Zz.

 

[Andy Resnick]

we were asked to plan and execute (teach) a one hour lab on kinematics ( specifically ballistic movement), the Tracker program and error estimation.

We decided on taking a differing route to the standard and to use this lab to teach about experiment integrity <snip>, basically we want to teach about robust experimental setups and how to check for factors to hinder this robustness.

First, I applaud your willingness to try something different, hopefully you'll end up with a compelling lab.

I don't know who your audience is (the putative students, as opposed to your instructor) I think part of the problem is that 'experiment integrity' or 'robust results' takes longer to teach than 1 hour. Certainly 'repeatability' or 'reliability' is part of what you are considering, and having that tighter focus may help you set up a plan- @TeethWhitener 's response was good in this respect.

So, one approach could be to give different groups different objects, the objects may differ in obvious or non-obvious ways (size, density, shape, etc.), and then devote some time for a guided discussion about everyone's results- do they differ in a statistically significant way or not? If they do (for example, one group has a feather while the other has a ball bearing), can the students understand why and propose a follow-on experiment to explore this?

Another approach would be to guide a (post-experiment) discussion about what experimental requirements are needed in order to obtain a precise value of 'g' to say, 3 or 4 digits of accuracy. "User error" is a poor excuse for bad data- let the students start to understand how difficult it is to measure anything with a precision of 0.01%.

Good luck!