I would look for response clusters. Each participant could have a different counting method rendering different results (e.g. - estimate volumes/ count radius & height/ estimate there’s an empty cone at the top which you don’t see), and some methods could be common pitfalls. Therefore, some results—those obtained by a wrong way of counting, should be discarded, otherwise the median result would lead away from the right result. In order to decide which is the right response cluster, trying to figure out each method/mistake and determining the correct one would be useful. Of course, your method is not necessarily the right one, just because it’s yours.
I would look for response clusters. Each participant could have a different counting method rendering different results (e.g. - estimate volumes/ count radius & height/ estimate there’s an empty cone at the top which you don’t see), and some methods could be common pitfalls. Therefore, some results—those obtained by a wrong way of counting, should be discarded, otherwise the median result would lead away from the right result. In order to decide which is the right response cluster, trying to figure out each method/mistake and determining the correct one would be useful. Of course, your method is not necessarily the right one, just because it’s yours.