Physics Internal Assessment

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Hello everyone,

In the Physics class today, we just got the news that we had to do an experiment to find out the relation between the length of a pendulum and the time period for the oscillation. And the big bomb was that it would go to IB for grading.

It was an Internal Assessment.

We just got this question and an equation. Now we have to make a DCP CE experiment...what the hell is that?!

I am being honest, I don't know much about practicals.

In my entire life, I have never done a practical before coming to IB. Now suddenly I am being bombarded with these DCP CE and IA stuff which I have never even heard about!
But I did do the experiment and I have a bunch of readings.

But what do I do now?

I have two weeks to submit this experiment and I have no idea how do I write it?

So could you please tell me how does one write a DCP CE experiment and what the hell does it stand for?

And what are the uncertainties or errors of the stop watch, the pendulum, the ruler (scale) and my own brain?

'Cause as it turns out, we have to write all that too.

And I have three summatives and three formatives this week!

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DCP stands for Data Collection and Processing. It's where you show all the data you've collected and present it in tables and graphs.

CE stands for Conclusion and Evaluation. It's where you draw a conclusion about your results (ie what do they show), discuss your results including any outliers or anomalies on your graph, and finally you evaluate your method and how you would improve it.

Here's what you need to include in short.

DCP

Raw data tables

A table of all the data you collected, including all trials, completely unchanged (if you included the average make sure you have all the trials too and don't write that the table is of 'raw data' because averaging is technically processing). Also include uncertainties and units in the table, and justify why you have used those uncertainties.

Processed Data Tables

A table or tables of all your processed data, so anything you've calculated. Include uncertainties and units too. You also need to include example calculations to show what you've done and if you've had to calculate you're uncertainties include examples for them too.

Graph

A graph of your data-use excel or any other graphing program, don't draw it yourself, the examiners don't like that. You need to include: headings, units, uncertainties, error bars, line of best fit and the equation of line of best fit, I usually write a 1-3 sentence graph analysis under my graphs stating the trend, any intercepts and any outliers.

CE

Conclusion

conclude by stating the trend, the gradient and the uncertainty in the gradient. If you can calculate a certain value from the gradient (eg. acceleration of g, specific heat capacity of water) do that here. Discuss any odd things on your graph (eg. outliers, position of X/Y intercepts). Give an overall evaluation of the accuracy of your results.

Evaluation

I usually make this a table with three columns: Uncertainty-where you list any systematic or random errors, Description -where you write a brief description of each error, state whether it was random or systemation and how much and in what way it would affect the trend, and Improvement -how you could realistically fix/reduce that error in the future. Try to include about 4-7 errors.

The uncertainty of the stopwatch is just plus or minus 1 in the last decimal place. (for example if your stopwatch reads to the nearest milisecond, your uncertainty would be 0.001?

Same thing for the ruler except plus or minus 5 because you are reading it (it is not being digitally shown)

I can't tell you any errors in the pendulum because you get marked on it but a hint is to look at things like how you attatched the pendulum to whatever it was swinging off, where the centre of mass of the pendulum was and whether the string length might of changed somehow as the pendulum swung.

And your brain can't be an uncertainty

Also, look up example IAs on the internet, the IB website actually has some examples that have been 'marked' by examiners.

Good Luck!

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Thank you so much!
You don't know how much you have helped me!

Thanks, again!

Ps - I understood the hint.

PPs - You are awesome.

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Well, considering I wont we able to top the other poster, I will just contribute one small thing.

http://xmltwo.ibo.org/publications/DP/Group4/d_4_physi_tsm_0711_1/design_en.html, this website many of the IB's key requirements, and examples, with marks of many IA's, both good and bad.

It is also fantastic for taking you through errors, graphs, etc. If you follow those suggestions you should do quite well.

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here is a marking grid i use with my students, you should be able to follow what parts of the items need to be included

Design D

[1] Defines the problem and selects variables: - Clearly states a Research Question.

- Clearly states the Input and Output Variables.

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[2] Controlling variables:

- Clearly states the variables controlled.
- Designs a
realistic method which clearly controls ALL such variables (Fair Test).

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[3] Designing a Method:

- The method allows for the collection of sufficient relevant data.

- The method clearly states a suitable range for the input variable.

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Data Collection & Processing

DCP

[1] Recording the RAW data:

- Records an appropriate amount of RAW data.
- Presents raw data clearly
allowing for easy interpretation (eg., data in ascending or descending order).

- Units MUST be included.
-
Sensible uncertainties MUST be given.
-
Consistent AND Appropriate Sig Figs MUST be given. - Uncertainties MUST be consistent with Sig. Figs.

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[2] Processing the RAW data:

- Processes the RAW data correctly.
- Plots an Input-Output graph if appropriate. -
Uncertainties/Error Bars are included.
-
Best Curve or Straight Line is included.

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[3] Presenting the PROCESSED data:

- Presents processed data appropriately.
- Uncertainties are correctly calculated.
- Uncertainties are clearly shown.
- Graphs have
error bars, max-min lines and

Slope ± slope (with UNITS) calculated.

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Conclusion & Evaluation

CE

[1] Concluding:

- States a valid conclusion.
- Conclusion is based on
correct interpretation of results.
- Clearly states how the conclusion is
justified by the data. - When numerical, the conclusion MUST include the

uncertainty.
- Where appropriate, the results are compared to values in the literature and a comparison includes the uncertainty.

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[2] Evaluating procedure(s):

- States the limitations of the procedure.

e.g., what you did that was not ideal; were the uncertainties BIG if so why?

- States the weaknesses of the procedure(s)

e.g., what you wanted to do but could not.

- States how the limitations and/or weaknesses may affect the results.

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[3] Improving the investigation:

- States Improvements on the methodology. - Improvements which address the identified

limitations.
- Improvements

weaknesses.

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