# Progression between two exams under three conditions

I want to test if three types of learning mehods have different effects on the progression between two exams.

The data was collected like this:

• A first exam was done with all participants. They had various level of knowledge of the subject, ranging from expert to novice.

• The participants were randomly separated into three groups which were given a lecture based on text, pictures or animations.

• They all passed a second exam (the same for everyone, but not the same as the first one) on the same subject.

I would like to know which learning method was the best one in that case. I was thinking of calculating the "progression" like this: $$\text{score on the second test} - \text{score on the first test}$$ And to run an ANOVA on this. However I realized that participants with very good previous knowledge had a low progression because they scored high on both tests while participant with very low previous knowledge had a much better progression even if the score at the second test was below average.

I thought of removing the participants with high scores on the first test, but I am not sure it is a very good solution. I also thought of doing something with the ranking: average the ranking of the user under each condition before and after the lecture and see if one condition allowed a greater increase in average ranking.

What do you think?