Closing Thoughts
Taken together, the message for skill assessors considering the use of motion capture data for generating metrics of performance efficiency is that they must work to ensure a high degree of consistency between data processing techniques and assessment contexts; and given that acceptable ranges for movement efficiency can be established for particular clinical skills, progressions of efficiency should be evaluated specifically within the constraints posed on the task by the individual performer. In presenting this commentary, the hope is to convey that an incomplete knowledge of the tenets of objective movement capture can yield inaccurate results. It is my position, then, that a solid understanding of motion capture and human motor control is essential to the effective implementation of objective computerized competency-based assessment in medical education contexts. Beyond concerns about the way movements are defined and counted, this also includes consideration for the nature of learning progressions and challenges the assumption that number of movement measures will reflect greater efficiency as a learner progresses from novice to expert. In this regard, it is essential that educators and assessors are careful to reflect any efficiency data through the lens of task success.
Conflict of Interest : Lawrence Grierson has no conflict of interest to declare.
Ethical Approval : Ethical approval was not required for this work.
Acknowledgements : Lawrence wishes to acknowledge Dr. Daniel Garcia, Dr. Simran Ohson, Dr. Jim Lyons, and the Department of Kinesiology at McMaster University for making possible the data collection associated with the small controlled experiment described in this commentary. Lawrence also wishes to acknowledge Dr. David Rojas, who provided critical insight and input to the conversation regarding setting data processing parameters.