  The work in this paper focuses on the role of machine learning in assessing
the correctness of a human motion or action. This task proves to be more
challenging than the gesture and action recognition ones. We will demonstrate,
through a set of experiments on a recent dataset, that machine learning
algorithms can produce good results for certain actions, but can also fall into
the trap of classifying an incorrect execution of an action as a correct
execution of another action.
