Observational learning of motor skills : Looking for optimal models

Observation of a model practicing a motor skill has been shown to promote the learning of that skill. However, relatively little is known regarding the attributes of a good model and the conditions of observation that can optimize learning. In the three studies reported in this thesis, we investigated the effects of the model’s skill level, the model’s handedness, the observation perspective, and the medium of presentation on the learning of a sequential, four-segmented timing task. In the first experiment of the first study, we had participants observe a novice, an expert, or a combination of both novice and expert models (i.e., mixed model). The results of the retention/transfer tests revealed that observation of the novice model was not as effective for the learning of the task as observation of the expert and mixed models. Importantly, a mixed schedule of novice and expert observation resulted in more stable movement time and better generalization of the imposed relative timing pattern than observation of either a novice or an expert model. In the second experiment, we wanted to determine whether a certain type of novice performance (highly variable, with or without performance improvement) in a mixed observation schedule results in better learning of the task. No significant differences were revealed with respect to the type of novice model used in a mixed schedule of observation. These results suggest that mixed observation provides an accurate template of what to do (expert observation), which is enhanced when it can be contrasted with the performance of less successful models.   In our second study, right-handed participants were asked to observe, from a first-person or a third-person perspective, a right-handed (i.e., same-handed) or left-handed (i.e., opposite-handed) model performing the experimental task. Observation of the same-handed model resulted in better learning of the task than did observation of the opposite-handed model, regardless of the observation perspective. This suggests that the action observation network (AON) is more sensitive to the model’s handedness than to the observer’s viewpoint. Thus, the AON seems to be linked to sensorimotor regions of the brain that simulate motor programming as though the observed movement was performed with one’s own dominant hand.  Finally, in the third study, we were interested to determine whether the medium of presentation (live vs. video) affects observational learning and whether this effect would be mediated by the observer’s viewpoint (1st vs. 3rd person). In that regard, participants observed a live model or a video presentation of the model from a first- or third-person perspective. Our results revealed that observation did not differ significantly as a function of the media or the perspective of observation. These results are inconsistent with the predictions of brain imaging studies that show a larger activation of the sensorimotor cortex during live observation compared with video observation and from a first-person compared with the third-person perspective. Taken together, our results indicate that the model’s skill level and handedness are important determinants of observational learning, whereas the observer’s viewpoint and the medium of observation had no significant impact on motor task learning. In addition, our results suggest that the larger activation of AON revealed in brain imaging studies during action observation does not necessarily result in or indicate better learning of the task.

Keyphrases: Observational learning, Motor learning, Timing task, Motor skill, Relative timing, Action observation network, Model handedness, Live observation, Video observation, Observation perspective