Tips for doing well on your evaluation

Tip 1: Discuss what your results mean with regard to the theory.

The focus of the evaluation should be on how your research supports the theory.  If you managed to get the same results as the original study, you have supported the theory. So, you should explain how your study supports the theory. For example, if your study investigates the role of schema theory on recall, to what extent do your findings support the theory?

The problem is - what do I do if I don't get the same results as the original?  It is highly unlikely that an IB candidate has just disproven a key theory in psychology in their IA with a sample size of less than 20. In this case, it is helpful to compare your results with the results of the original study. Start by discussing what the theory predicts should be your results vs what your results actually were. Then discuss why you think your results might be different from the original study.  What might account for differences? How might differences in the samples that were used potentially have affected the results?

Tip 2: Discuss the limitations of the design, sample, materials, and procedure.

You must write about the strengths and limitations of ALL of these components of your study.  Forgetting to include even one lowers your marks significantly.

Tip 3: Strategies for evaluation:

Design: what are the disadvantages of using the chosen design (independent samples, repeated measures); how could a matched pairs design potentially have improved the validity of the findings? Was counter-balancing done? How would this have helped?

Sample: How might specific characteristics of the sample have influenced the results (e.g. age or native language)? What are the strengths and limitations of the sampling technique that you used?

Materials: How were the materials put together? Did this influence the outcome of the experiment? How could they be designed differently in order to improve the validity or reliability of the study?

Procedure: Was there enough/too much time for the participants to do the task? Were the standardized directions clear enough? Could you add something / change something in order to make the procedure more effective in testing the DV? Was the DV appropriately operationalized and measured? Was there something that you could have done better when running the experiment?

Tip 4: Do not write about researcher error.

The bottom line is that if there is a mistake, redo the experiment. It is not acceptable to write in the report limitations such as, "We forgot to read the standardized directions", "we didn't carefully time the second group", or "the audio was difficult to hear." These are researcher errors and this means that the students have to do it again - just as they would in their science classes. Writing such comments earns no credit.

Tip 5: Do not write about sample size.

The sample size is always an issue.  It could always be bigger. Therefore, it is not a valid limitation.  It is also not a valid limitation that the two groups in your sample were not the same size.  This is fine; inferential statistics deal with differences in sample size.

Tip 6: Justify your modifications.

You have to make suggestions for improvement based on the limitations you have identified.  You have to justify those suggestions.  If you suggest that it would be better to do your experiment in the native language of the participants, then you need to explain why you think that this would make a difference.

Tip 7: End the evaluation with a statement of the conclusion that reflects the hypothesis.

Finally, the report should end with a conclusion. The conclusion should clearly state what was found. A typical conclusion might look like this:

As a result of our study, we can conclude at a p ≤ 0.01 level of significance that playing music while trying to rehearse a list of 40 words has a negative effect on international teenagers' recall.