Mixed observation favors motor learning through better estimation of the model's performance

Observation contributes to motor learning. It was recently demonstrated that the observation of both a novice and an expert model (mixed observation) resulted in better learning of a complex spatio-temporal task than the observation of either a novice or an expert model alone. In the present study, we sought to determine whether the advantage of mixed observation resulted from the development of a better error detection mechanism. The results revealed that mixed observation resulted in a better estimation of the model's performance than that with other regimens of observation. The results also suggest that observational learning is improved when observation with knowledge of the results (KR) is followed by an observation phase without KR.