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.